Quantitative Market Research: A Guide + Examples

Quantitative Market Research: A Guide + Examples

Quantitative market research is a numbers game.

It’s one of the four types of traditional market research; and a tried, trusted, and proven way to get answers to strategically important questions. 

Whether you’re already familiar with quantitative research, looking for practical examples, or considering using it in your business, I will cover everything you need to know.

Peter Druker quote

What is quantitative market research?

Quantitative market research collects numerical data to help answer a research question or objective. Popular forms of quantitative research include surveys, polls, questionnaires, and demographical data from primary and secondary sources. The data can be easily quantified, compared, and analyzed to establish patterns, trends, and insights that disprove or prove a research question. It’s used by large and small organizations, thanks to modern market research tools like Similarweb.

quantitative market research definition

What questions can quantitative market research answer?

Quantitative data can help a company find answers to strategic questions. It can help organizations find patterns, spot trends, make predictions, and establish averages. Most questions that can be answered by quantitative research help determine the: how, when, what, and where. Some of these include:

  • What is the market size ?
  • How have the needs of a market changed?
  • What is the number of people that make up your target audience?
  • How many people are interested in buying your product?
  • Is there a market for your products?
  • Where does my target audience spend most of their time online?
  • The frequency that people buy your product or service?
  • How many people are aware of your brand, product, or service?
  • What type of people are your best customers?
  • How long do people spend on your website?
  • What percentage of customers are happy with your product or service?

Read More: 98 Quantitative Market Research Questions & Examples

Types of quantitative market research design

Quantitative market research deals with secondary and primary data–as long as it’s presented in numerical form. There are five key techniques of quantitative research design to know.

Experimental research

Experimental research design

Experimental research (AKA true experimental research) is a research technique that analyzes to prove a theory. In most cases, it will involve several theories yet to be proved or disproved.

This type of design creates a controlled environment where multiple variables are examined and observed to establish the cause and effect they each have. Various data types of manipulated in the process and each impact is assessed. The study aims to determine the precise conditions in which the different variables affect each other.

A few examples of experimental quantitative research design include

  • The effect of Black Friday Marketing on the success of a business.
  • Impact of service delivery issues on the perceived reliability of a brand.
  • The effect of a gift with purchase on customer satisfaction levels.

Choosing a suitable quantitative research method is vital, as data collection can be utilized for different effects. For instance, statistics can be correlational (which helps infer conclusions about differences) or descriptive (which help to summarize data).

Descriptive research

Descriptive research method

This type of quantitative research is used to learn more about a specific topic, for instance:

Through observation, it measures different variables and investigates each in detail. It aims to describe characteristics– and is focused more on the ‘what’ of a research problem than the ‘why’ behind it. Aptly named, it describes a research subject without investigating why it happens.

A few examples of descriptive research include:

  • A company’s Black Friday marketing campaign description.
  • The description of service delivery issues a company or its customers face.
  • An outline of what companies offer a gift with online purchases.

Quasi-experimental research

quasi experimental research

This is similar to experimental research (aka casual comparative research), which seeks to evaluate cause-and-effect relations among variables. However, in the case of quasi-experimental research, the key difference is that it’s an independent and dependent variable that is used.

This type of quantitative research design takes at least two types of data, analyzing each together to examine the differences–using a typical cause-and-effect methodology. Research is usually undertaken in a near-natural setting, with information being gathered from two groups.

  • A naturally occurring group that’s closely matched with the original environment.
  • A group that is not naturally present.

In doing this, causal links can be made. However, not all casual links will be correct due to other variables impacting results.

Examples of descriptive quantitative design include:

  • The effect of the Black Friday campaign’s success on employee productivity.
  • Service delivery issues effect on the public perception of a brand.
  • The effect of free gifts on customer loyalty.

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Correlational research

Experimental research design

Correlational research is usually conducted to determine the relationship between two closely related entities. It looks at how each impacts the other and details the changes that occur.

This type of quantitative research design examines relationships between multiple data types. It will examine the extent to which they align with one another or where they differ. It will not delve into casual links any deeper than this.

Examples of quantitative correlational design include:

  • The relationship between Black Friday campaign success and annual revenues.
  • Correlations between delivery issues and brand reputation.
  • The relationship between free gifts and their perceived loyalty.

Quantitative market research data collection methods

You have a few options when considering which type of quantitative research is best. The first thing you’ll need to do is choose the data collection method. Below, I’ve summarized three of the most common quantitative research data collection methods.

This applies to telephone, video conference, or face-to-face interviews. While it’s an ideal way to connect with individuals to collect data, it’s a method that utilizes resources due to the time it takes to set up and conduct them.

A market research survey is a cost-effective way to collect quantitative data. Information can be obtained from large groups of people quickly, and the survey itself is relatively easy to set up. Your survey questions must be carefully considered for the results to provide meaningful data . When creating any form of survey for this type of market research , the questions should remain close-ended, giving participants a yes/no answer or one that requests a numerical result.

A few examples of quantitative market research survey questions include:

  • Would you recommend Similarweb to a colleague?

2. On a scale of 1-10, with one being the lowest and ten being the highest, how would you rate your experience with the Similarweb customer support team today?

3. Could you find the information you were looking for on our site today?

4. On a scale of 1-10, with one being the lowest and ten being the highest, how easy could you find the information you were looking for on our site today?

5. Was your query resolved in full by our support representative?

While similar, a poll is a shorter survey version. It’s often used to give researchers a point-in-time perspective of a large group of people. Data can be collected in person, over the phone, or online. The costs for polls can vary, depending on whether you buy questions on an existing poll, such as YouGov, or if you opt for a more bespoke survey that you create from scratch.

Fun fact: The origins of polls date back to the 19th century. They were first used in America to predict the outcome of the presidential elections.

Quantitative market research advantages and disadvantages

As with all market research, there are pros and cons to consider. While there are many benefits of using quantitative market research, it’s important to weigh these up with the drawbacks to ensure you make the best choice for your project.

Benefits of quantitative market research

The information you obtain directly results from the questions asked and the audience you choose. Get these two factors right, and you’ll reap the rewards in your research. Here’s a quick summary of the advantages doing quantitative research offers.

  • Collect a vast volume of data efficiently with a larger sample pool.
  • Get a generalized view of a target audience and demographic.
  • Results can be processed quickly as they are highly structured.
  • Easy comparison of results from different groups of participants.
  • Its objective–relying on solid numbers with fewer variables.
  • Number-based research is ideal for analysis.

Disadvantages of quantitative market research

While all quantitative market research collection methods can generate insightful data showing a wider opinion, there are limitations to consider.

  • If respondents are not representative of your target audience, this could potentially impact the accuracy of results–it’s also known as a sampling error.
  • The wording of questions can impact the findings–consider this carefully when designing interviews, polls, or surveys.
  • Quantitative research is close-ended, with no ability to receive data about the ‘why’ or ‘how’ behind the numbers. Findings can only provide a small part of the story without two-way dialogue.
  • You’ll need a hypothesis and an appropriate model to avoid invalid results or bias to collect and analyze the data.

What strategies are used to ensure the accuracy of quantitative market research?

Researchers employ several strategies to ensure the accuracy of their quantitative market research. This includes using various data sources to ensure that no single source is unduly influencing the results. Additionally, researchers may use advanced statistical techniques such as regression analysis and factor analysis to ensure that their results are accurate and valid. Lastly, researchers may employ survey design principles such as random and stratified sampling to ensure that the results represent the studied population.

Using Similarweb for quantitative market research

For all the advantages that quantitative market research offers, it’s hard to ignore the limitations. Things like timeliness, bias, and the close-ended nature of this method all matter when you need to make important decisions and don’t have time to take on a lengthy research project.

That’s where we come in.

Depending on your market research questions, there’s usually a faster way to achieve your goals with insights gained from digital research intelligence software like Similarweb. Whether you want to learn more about a target audience, market, industry, or competitors, you can get up-to-date intel that’s on point, easy to understand, and accurate.

Consider your research question, and see what insights and information are available to you right now. With a world of data at your fingertips, you can harness Similarweb Digital Research Intelligence to uncover telling facts, that inform research and strengthen your position. Use it for:

Market Research


Audience Insights

Company Research

Consumer Journey Tracking

Use it to uncover the insights you need to make decisions and develop strategies that help you win. 

Wrapping up

With all types of market research, it’s important to take a balanced approach. Organizations that use quantitative market research to get numerical data must balance this with qualitative data to understand the sentiment behind the numbers. So, while quantitative research has its advantages, it must be done in tandem with other research types to provide a complete picture that tells you what, when, how, and why.

Similarweb’s suite of digital intelligence solutions offers unbiased, accurate, honest insights you can trust. Take it for a trial run today, and see how it can power up  your research and save you time. 

What are the four types of market research?

The four main types of market research include primary, secondary, quantitative, and qualitative. While there are subcategories, most research falls into one of these four key categories.

What is the difference between quantitative and qualitative market research?

Quantitative market research is focused on numbers. It collects numerical data to inform a research question or develop a theory. On the other hand, qualitative research is more about consumer sentiment, looking at how and why people feel a certain way about a product, service, or brand.

What are the benefits of quantitative market research?

As it deals with numerical data, quantitative research data can be analyzed quickly and consistently. Future replication is an easy and effective way to conduct a broad study across a large sample size. There are also fewer variables as data is close-ended. Both collection and analysis can be automated and costs less than qualitative research.

What types of questions can quantitative market research answer?

Quantitative research can help answer questions that explain what, how much, when, and where. It seeks to quantify attitudes, behaviors, and opinions but can also be used for establishing averages, making future predictions, and trendspotting.

Who is quantitative market research for?

Quantitative research data delivers information that can help shed light on a market or business. This makes it valuable to both established firms and start-ups of any size. Practically, it can help with market sizing, forecasting, market validation , and more.

What advancements have been made in quantitative market research?

In the past decade, technological advances have enabled quantitative market research to become even more precise and comprehensive. AI and machine learning have allowed researchers to collect and analyze large amounts of data faster and more accurately.

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Home Market Research

Quantitative Research: What It Is, Practices & Methods

Quantitative research

Quantitative research involves analyzing and gathering numerical data to uncover trends, calculate averages, evaluate relationships, and derive overarching insights. It’s used in various fields, including the natural and social sciences. Quantitative data analysis employs statistical techniques for processing and interpreting numeric data.

Research designs in the quantitative realm outline how data will be collected and analyzed with methods like experiments and surveys. Qualitative methods complement quantitative research by focusing on non-numerical data, adding depth to understanding. Data collection methods can be qualitative or quantitative, depending on research goals. Researchers often use a combination of both approaches to gain a comprehensive understanding of phenomena.

What is Quantitative Research?

Quantitative research is a systematic investigation of phenomena by gathering quantifiable data and performing statistical, mathematical, or computational techniques. Quantitative research collects statistically significant information from existing and potential customers using sampling methods and sending out online surveys , online polls , and questionnaires , for example.

One of the main characteristics of this type of research is that the results can be depicted in numerical form. After carefully collecting structured observations and understanding these numbers, it’s possible to predict the future of a product or service, establish causal relationships or Causal Research , and make changes accordingly. Quantitative research primarily centers on the analysis of numerical data and utilizes inferential statistics to derive conclusions that can be extrapolated to the broader population.

An example of a quantitative research study is the survey conducted to understand how long a doctor takes to tend to a patient when the patient walks into the hospital. A patient satisfaction survey can be administered to ask questions like how long a doctor takes to see a patient, how often a patient walks into a hospital, and other such questions, which are dependent variables in the research. This kind of research method is often employed in the social sciences, and it involves using mathematical frameworks and theories to effectively present data, ensuring that the results are logical, statistically sound, and unbiased.

Data collection in quantitative research uses a structured method and is typically conducted on larger samples representing the entire population. Researchers use quantitative methods to collect numerical data, which is then subjected to statistical analysis to determine statistically significant findings. This approach is valuable in both experimental research and social research, as it helps in making informed decisions and drawing reliable conclusions based on quantitative data.

Quantitative Research Characteristics

Quantitative research has several unique characteristics that make it well-suited for specific projects. Let’s explore the most crucial of these characteristics so that you can consider them when planning your next research project:

purpose of quantitative research marketing

  • Structured tools: Quantitative research relies on structured tools such as surveys, polls, or questionnaires to gather quantitative data . Using such structured methods helps collect in-depth and actionable numerical data from the survey respondents, making it easier to perform data analysis.
  • Sample size: Quantitative research is conducted on a significant sample size  representing the target market . Appropriate Survey Sampling methods, a fundamental aspect of quantitative research methods, must be employed when deriving the sample to fortify the research objective and ensure the reliability of the results.
  • Close-ended questions: Closed-ended questions , specifically designed to align with the research objectives, are a cornerstone of quantitative research. These questions facilitate the collection of quantitative data and are extensively used in data collection processes.
  • Prior studies: Before collecting feedback from respondents, researchers often delve into previous studies related to the research topic. This preliminary research helps frame the study effectively and ensures the data collection process is well-informed.
  • Quantitative data: Typically, quantitative data is represented using tables, charts, graphs, or other numerical forms. This visual representation aids in understanding the collected data and is essential for rigorous data analysis, a key component of quantitative research methods.
  • Generalization of results: One of the strengths of quantitative research is its ability to generalize results to the entire population. It means that the findings derived from a sample can be extrapolated to make informed decisions and take appropriate actions for improvement based on numerical data analysis.

Quantitative Research Methods

Quantitative research methods are systematic approaches used to gather and analyze numerical data to understand and draw conclusions about a phenomenon or population. Here are the quantitative research methods:

  • Primary quantitative research methods
  • Secondary quantitative research methods

Primary Quantitative Research Methods

Primary quantitative research is the most widely used method of conducting market research. The distinct feature of primary research is that the researcher focuses on collecting data directly rather than depending on data collected from previously done research. Primary quantitative research design can be broken down into three further distinctive tracks and the process flow. They are:

A. Techniques and Types of Studies

There are multiple types of primary quantitative research. They can be distinguished into the four following distinctive methods, which are:

01. Survey Research

Survey Research is fundamental for all quantitative outcome research methodologies and studies. Surveys are used to ask questions to a sample of respondents, using various types such as online polls, online surveys, paper questionnaires, web-intercept surveys , etc. Every small and big organization intends to understand what their customers think about their products and services, how well new features are faring in the market, and other such details.

By conducting survey research, an organization can ask multiple survey questions , collect data from a pool of customers, and analyze this collected data to produce numerical results. It is the first step towards collecting data for any research. You can use single ease questions . A single-ease question is a straightforward query that elicits a concise and uncomplicated response.

This type of research can be conducted with a specific target audience group and also can be conducted across multiple groups along with comparative analysis . A prerequisite for this type of research is that the sample of respondents must have randomly selected members. This way, a researcher can easily maintain the accuracy of the obtained results as a huge variety of respondents will be addressed using random selection. 

Traditionally, survey research was conducted face-to-face or via phone calls. Still, with the progress made by online mediums such as email or social media, survey research has also spread to online mediums.There are two types of surveys , either of which can be chosen based on the time in hand and the kind of data required:

Cross-sectional surveys: Cross-sectional surveys are observational surveys conducted in situations where the researcher intends to collect data from a sample of the target population at a given point in time. Researchers can evaluate various variables at a particular time. Data gathered using this type of survey is from people who depict similarity in all variables except the variables which are considered for research . Throughout the survey, this one variable will stay constant.

  • Cross-sectional surveys are popular with retail, SMEs, and healthcare industries. Information is garnered without modifying any parameters in the variable ecosystem.
  • Multiple samples can be analyzed and compared using a cross-sectional survey research method.
  • Multiple variables can be evaluated using this type of survey research.
  • The only disadvantage of cross-sectional surveys is that the cause-effect relationship of variables cannot be established as it usually evaluates variables at a particular time and not across a continuous time frame.

Longitudinal surveys: Longitudinal surveys are also observational surveys , but unlike cross-sectional surveys, longitudinal surveys are conducted across various time durations to observe a change in respondent behavior and thought processes. This time can be days, months, years, or even decades. For instance, a researcher planning to analyze the change in buying habits of teenagers over 5 years will conduct longitudinal surveys.

  • In cross-sectional surveys, the same variables were evaluated at a given time, and in longitudinal surveys, different variables can be analyzed at different intervals.
  • Longitudinal surveys are extensively used in the field of medicine and applied sciences. Apart from these two fields, they are also used to observe a change in the market trend analysis , analyze customer satisfaction, or gain feedback on products/services.
  • In situations where the sequence of events is highly essential, longitudinal surveys are used.
  • Researchers say that when research subjects need to be thoroughly inspected before concluding, they rely on longitudinal surveys.

02. Correlational Research

A comparison between two entities is invariable. Correlation research is conducted to establish a relationship between two closely-knit entities and how one impacts the other, and what changes are eventually observed. This research method is carried out to give value to naturally occurring relationships, and a minimum of two different groups are required to conduct this quantitative research method successfully. Without assuming various aspects, a relationship between two groups or entities must be established.

Researchers use this quantitative research design to correlate two or more variables using mathematical analysis methods. Patterns, relationships, and trends between variables are concluded as they exist in their original setup. The impact of one of these variables on the other is observed, along with how it changes the relationship between the two variables. Researchers tend to manipulate one of the variables to attain the desired results.

Ideally, it is advised not to make conclusions merely based on correlational research. This is because it is not mandatory that if two variables are in sync that they are interrelated.

Example of Correlational Research Questions :

  • The relationship between stress and depression.
  • The equation between fame and money.
  • The relation between activities in a third-grade class and its students.

03. Causal-comparative Research

This research method mainly depends on the factor of comparison. Also called quasi-experimental research , this quantitative research method is used by researchers to conclude the cause-effect equation between two or more variables, where one variable is dependent on the other independent variable. The independent variable is established but not manipulated, and its impact on the dependent variable is observed. These variables or groups must be formed as they exist in the natural setup. As the dependent and independent variables will always exist in a group, it is advised that the conclusions are carefully established by keeping all the factors in mind.

Causal-comparative research is not restricted to the statistical analysis of two variables but extends to analyzing how various variables or groups change under the influence of the same changes. This research is conducted irrespective of the type of relationship that exists between two or more variables. Statistical analysis plan is used to present the outcome using this quantitative research method.

Example of Causal-Comparative Research Questions:

  • The impact of drugs on a teenager. The effect of good education on a freshman. The effect of substantial food provision in the villages of Africa.

04. Experimental Research

Also known as true experimentation, this research method relies on a theory. As the name suggests, experimental research is usually based on one or more theories. This theory has yet to be proven before and is merely a supposition. In experimental research, an analysis is done around proving or disproving the statement. This research method is used in natural sciences. Traditional research methods are more effective than modern techniques.

There can be multiple theories in experimental research. A theory is a statement that can be verified or refuted.

After establishing the statement, efforts are made to understand whether it is valid or invalid. This quantitative research method is mainly used in natural or social sciences as various statements must be proved right or wrong.

  • Traditional research methods are more effective than modern techniques.
  • Systematic teaching schedules help children who struggle to cope with the course.
  • It is a boon to have responsible nursing staff for ailing parents.

B. Data Collection Methodologies

The second major step in primary quantitative research is data collection. Data collection can be divided into sampling methods and data collection using surveys and polls.

01. Data Collection Methodologies: Sampling Methods

There are two main sampling methods for quantitative research: Probability and Non-probability sampling .

Probability sampling: A theory of probability is used to filter individuals from a population and create samples in probability sampling . Participants of a sample are chosen by random selection processes. Each target audience member has an equal opportunity to be selected in the sample.

There are four main types of probability sampling:

  • Simple random sampling: As the name indicates, simple random sampling is nothing but a random selection of elements for a sample. This sampling technique is implemented where the target population is considerably large.
  • Stratified random sampling: In the stratified random sampling method , a large population is divided into groups (strata), and members of a sample are chosen randomly from these strata. The various segregated strata should ideally not overlap one another.
  • Cluster sampling: Cluster sampling is a probability sampling method using which the main segment is divided into clusters, usually using geographic segmentation and demographic segmentation parameters.
  • Systematic sampling: Systematic sampling is a technique where the starting point of the sample is chosen randomly, and all the other elements are chosen using a fixed interval. This interval is calculated by dividing the population size by the target sample size.

Non-probability sampling: Non-probability sampling is where the researcher’s knowledge and experience are used to create samples. Because of the researcher’s involvement, not all the target population members have an equal probability of being selected to be a part of a sample.

There are five non-probability sampling models:

  • Convenience sampling: In convenience sampling , elements of a sample are chosen only due to one prime reason: their proximity to the researcher. These samples are quick and easy to implement as there is no other parameter of selection involved.
  • Consecutive sampling: Consecutive sampling is quite similar to convenience sampling, except for the fact that researchers can choose a single element or a group of samples and conduct research consecutively over a significant period and then perform the same process with other samples.
  • Quota sampling: Using quota sampling , researchers can select elements using their knowledge of target traits and personalities to form strata. Members of various strata can then be chosen to be a part of the sample as per the researcher’s understanding.
  • Snowball sampling: Snowball sampling is conducted with target audiences who are difficult to contact and get information. It is popular in cases where the target audience for analysis research is rare to put together.
  • Judgmental sampling: Judgmental sampling is a non-probability sampling method where samples are created only based on the researcher’s experience and research skill .

02. Data collection methodologies: Using surveys & polls

Once the sample is determined, then either surveys or polls can be distributed to collect the data for quantitative research.

Using surveys for primary quantitative research

A survey is defined as a research method used for collecting data from a pre-defined group of respondents to gain information and insights on various topics of interest. The ease of survey distribution and the wide number of people it can reach depending on the research time and objective makes it one of the most important aspects of conducting quantitative research.

Fundamental levels of measurement – nominal, ordinal, interval, and ratio scales

Four measurement scales are fundamental to creating a multiple-choice question in a survey. They are nominal, ordinal, interval, and ratio measurement scales without the fundamentals of which no multiple-choice questions can be created. Hence, it is crucial to understand these measurement levels to develop a robust survey.

Use of different question types

To conduct quantitative research, close-ended questions must be used in a survey. They can be a mix of multiple question types, including multiple-choice questions like semantic differential scale questions , rating scale questions , etc.

Survey Distribution and Survey Data Collection

In the above, we have seen the process of building a survey along with the research design to conduct primary quantitative research. Survey distribution to collect data is the other important aspect of the survey process. There are different ways of survey distribution. Some of the most commonly used methods are:

  • Email: Sending a survey via email is the most widely used and effective survey distribution method. This method’s response rate is high because the respondents know your brand. You can use the QuestionPro email management feature to send out and collect survey responses.
  • Buy respondents: Another effective way to distribute a survey and conduct primary quantitative research is to use a sample. Since the respondents are knowledgeable and are on the panel by their own will, responses are much higher.
  • Embed survey on a website: Embedding a survey on a website increases a high number of responses as the respondent is already in close proximity to the brand when the survey pops up.
  • Social distribution: Using social media to distribute the survey aids in collecting a higher number of responses from the people that are aware of the brand.
  • QR code: QuestionPro QR codes store the URL for the survey. You can print/publish this code in magazines, signs, business cards, or on just about any object/medium.
  • SMS survey: The SMS survey is a quick and time-effective way to collect a high number of responses.
  • Offline Survey App: The QuestionPro App allows users to circulate surveys quickly, and the responses can be collected both online and offline.

Survey example

An example of a survey is a short customer satisfaction (CSAT) survey that can quickly be built and deployed to collect feedback about what the customer thinks about a brand and how satisfied and referenceable the brand is.

Using polls for primary quantitative research

Polls are a method to collect feedback using close-ended questions from a sample. The most commonly used types of polls are election polls and exit polls . Both of these are used to collect data from a large sample size but using basic question types like multiple-choice questions.

C. Data Analysis Techniques

The third aspect of primary quantitative research design is data analysis . After collecting raw data, there must be an analysis of this data to derive statistical inferences from this research. It is important to relate the results to the research objective and establish the statistical relevance of the results.

Remember to consider aspects of research that were not considered for the data collection process and report the difference between what was planned vs. what was actually executed.

It is then required to select precise Statistical Analysis Methods , such as SWOT, Conjoint, Cross-tabulation, etc., to analyze the quantitative data.

  • SWOT analysis: SWOT Analysis stands for the acronym of Strengths, Weaknesses, Opportunities, and Threat analysis. Organizations use this statistical analysis technique to evaluate their performance internally and externally to develop effective strategies for improvement.
  • Conjoint Analysis: Conjoint Analysis is a market analysis method to learn how individuals make complicated purchasing decisions. Trade-offs are involved in an individual’s daily activities, and these reflect their ability to decide from a complex list of product/service options.
  • Cross-tabulation: Cross-tabulation is one of the preliminary statistical market analysis methods which establishes relationships, patterns, and trends within the various parameters of the research study.
  • TURF Analysis: TURF Analysis , an acronym for Totally Unduplicated Reach and Frequency Analysis, is executed in situations where the reach of a favorable communication source is to be analyzed along with the frequency of this communication. It is used for understanding the potential of a target market.

Inferential statistics methods such as confidence interval, the margin of error, etc., can then be used to provide results.

Secondary Quantitative Research Methods

Secondary quantitative research or desk research is a research method that involves using already existing data or secondary data. Existing data is summarized and collated to increase the overall effectiveness of the research.

This research method involves collecting quantitative data from existing data sources like the internet, government resources, libraries, research reports, etc. Secondary quantitative research helps to validate the data collected from primary quantitative research and aid in strengthening or proving, or disproving previously collected data.

The following are five popularly used secondary quantitative research methods:

  • Data available on the internet: With the high penetration of the internet and mobile devices, it has become increasingly easy to conduct quantitative research using the internet. Information about most research topics is available online, and this aids in boosting the validity of primary quantitative data.
  • Government and non-government sources: Secondary quantitative research can also be conducted with the help of government and non-government sources that deal with market research reports. This data is highly reliable and in-depth and hence, can be used to increase the validity of quantitative research design.
  • Public libraries: Now a sparingly used method of conducting quantitative research, it is still a reliable source of information, though. Public libraries have copies of important research that was conducted earlier. They are a storehouse of valuable information and documents from which information can be extracted.
  • Educational institutions: Educational institutions conduct in-depth research on multiple topics, and hence, the reports that they publish are an important source of validation in quantitative research.
  • Commercial information sources: Local newspapers, journals, magazines, radio, and TV stations are great sources to obtain data for secondary quantitative research. These commercial information sources have in-depth, first-hand information on market research, demographic segmentation, and similar subjects.

Quantitative Research Examples

Some examples of quantitative research are:

  • A customer satisfaction template can be used if any organization would like to conduct a customer satisfaction (CSAT) survey . Through this kind of survey, an organization can collect quantitative data and metrics on the goodwill of the brand or organization in the customer’s mind based on multiple parameters such as product quality, pricing, customer experience, etc. This data can be collected by asking a net promoter score (NPS) question , matrix table questions, etc. that provide data in the form of numbers that can be analyzed and worked upon.
  • Another example of quantitative research is an organization that conducts an event, collecting feedback from attendees about the value they see from the event. By using an event survey , the organization can collect actionable feedback about the satisfaction levels of customers during various phases of the event such as the sales, pre and post-event, the likelihood of recommending the organization to their friends and colleagues, hotel preferences for the future events and other such questions.

What are the Advantages of Quantitative Research?

There are many advantages to quantitative research. Some of the major advantages of why researchers use this method in market research are:


Collect Reliable and Accurate Data:

Quantitative research is a powerful method for collecting reliable and accurate quantitative data. Since data is collected, analyzed, and presented in numbers, the results obtained are incredibly reliable and objective. Numbers do not lie and offer an honest and precise picture of the conducted research without discrepancies. In situations where a researcher aims to eliminate bias and predict potential conflicts, quantitative research is the method of choice.

Quick Data Collection:

Quantitative research involves studying a group of people representing a larger population. Researchers use a survey or another quantitative research method to efficiently gather information from these participants, making the process of analyzing the data and identifying patterns faster and more manageable through the use of statistical analysis. This advantage makes quantitative research an attractive option for projects with time constraints.

Wider Scope of Data Analysis:

Quantitative research, thanks to its utilization of statistical methods, offers an extensive range of data collection and analysis. Researchers can delve into a broader spectrum of variables and relationships within the data, enabling a more thorough comprehension of the subject under investigation. This expanded scope is precious when dealing with complex research questions that require in-depth numerical analysis.

Eliminate Bias:

One of the significant advantages of quantitative research is its ability to eliminate bias. This research method leaves no room for personal comments or the biasing of results, as the findings are presented in numerical form. This objectivity makes the results fair and reliable in most cases, reducing the potential for researcher bias or subjectivity.

In summary, quantitative research involves collecting, analyzing, and presenting quantitative data using statistical analysis. It offers numerous advantages, including the collection of reliable and accurate data, quick data collection, a broader scope of data analysis, and the elimination of bias, making it a valuable approach in the field of research. When considering the benefits of quantitative research, it’s essential to recognize its strengths in contrast to qualitative methods and its role in collecting and analyzing numerical data for a more comprehensive understanding of research topics.

Best Practices to Conduct Quantitative Research

Here are some best practices for conducting quantitative research:

Tips to conduct quantitative research

  • Differentiate between quantitative and qualitative: Understand the difference between the two methodologies and apply the one that suits your needs best.
  • Choose a suitable sample size: Ensure that you have a sample representative of your population and large enough to be statistically weighty.
  • Keep your research goals clear and concise: Know your research goals before you begin data collection to ensure you collect the right amount and the right quantity of data.
  • Keep the questions simple: Remember that you will be reaching out to a demographically wide audience. Pose simple questions for your respondents to understand easily.

Quantitative Research vs Qualitative Research

Quantitative research and qualitative research are two distinct approaches to conducting research, each with its own set of methods and objectives. Here’s a comparison of the two:

purpose of quantitative research marketing

Quantitative Research

  • Objective: The primary goal of quantitative research is to quantify and measure phenomena by collecting numerical data. It aims to test hypotheses, establish patterns, and generalize findings to a larger population.
  • Data Collection: Quantitative research employs systematic and standardized approaches for data collection, including techniques like surveys, experiments, and observations that involve predefined variables. It is often collected from a large and representative sample.
  • Data Analysis: Data is analyzed using statistical techniques, such as descriptive statistics, inferential statistics, and mathematical modeling. Researchers use statistical tests to draw conclusions and make generalizations based on numerical data.
  • Sample Size: Quantitative research often involves larger sample sizes to ensure statistical significance and generalizability.
  • Results: The results are typically presented in tables, charts, and statistical summaries, making them highly structured and objective.
  • Generalizability: Researchers intentionally structure quantitative research to generate outcomes that can be helpful to a larger population, and they frequently seek to establish causative connections.
  • Emphasis on Objectivity: Researchers aim to minimize bias and subjectivity, focusing on replicable and objective findings.

Qualitative Research

  • Objective: Qualitative research seeks to gain a deeper understanding of the underlying motivations, behaviors, and experiences of individuals or groups. It explores the context and meaning of phenomena.
  • Data Collection: Qualitative research employs adaptable and open-ended techniques for data collection, including methods like interviews, focus groups, observations, and content analysis. It allows participants to express their perspectives in their own words.
  • Data Analysis: Data is analyzed through thematic analysis, content analysis, or grounded theory. Researchers focus on identifying patterns, themes, and insights in the data.
  • Sample Size: Qualitative research typically involves smaller sample sizes due to the in-depth nature of data collection and analysis.
  • Results: Findings are presented in narrative form, often in the participants’ own words. Results are subjective, context-dependent, and provide rich, detailed descriptions.
  • Generalizability: Qualitative research does not aim for broad generalizability but focuses on in-depth exploration within a specific context. It provides a detailed understanding of a particular group or situation.
  • Emphasis on Subjectivity: Researchers acknowledge the role of subjectivity and the researcher’s influence on the Research Process . Participant perspectives and experiences are central to the findings.

Researchers choose between quantitative and qualitative research methods based on their research objectives and the nature of the research question. Each approach has its advantages and drawbacks, and the decision between them hinges on the particular research objectives and the data needed to address research inquiries effectively.

Quantitative research is a structured way of collecting and analyzing data from various sources. Its purpose is to quantify the problem and understand its extent, seeking results that someone can project to a larger population.

Companies that use quantitative rather than qualitative research typically aim to measure magnitudes and seek objectively interpreted statistical results. So if you want to obtain quantitative data that helps you define the structured cause-and-effect relationship between the research problem and the factors, you should opt for this type of research.

At QuestionPro , we have various Best Data Collection Tools and features to conduct investigations of this type. You can create questionnaires and distribute them through our various methods. We also have sample services or various questions to guarantee the success of your study and the quality of the collected data.

Quantitative research is a systematic and structured approach to studying phenomena that involves the collection of measurable data and the application of statistical, mathematical, or computational techniques for analysis.

Quantitative research is characterized by structured tools like surveys, substantial sample sizes, closed-ended questions, reliance on prior studies, data presented numerically, and the ability to generalize findings to the broader population.

The two main methods of quantitative research are Primary quantitative research methods, involving data collection directly from sources, and Secondary quantitative research methods, which utilize existing data for analysis.

1.Surveying to measure employee engagement with numerical rating scales. 2.Analyzing sales data to identify trends in product demand and market share. 4.Examining test scores to assess the impact of a new teaching method on student performance. 4.Using website analytics to track user behavior and conversion rates for an online store.

1.Differentiate between quantitative and qualitative approaches. 2.Choose a representative sample size. 3.Define clear research goals before data collection. 4.Use simple and easily understandable survey questions.


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The Complete Guide to Quantitative Market Research

purpose of quantitative research marketing

Quantitative research is a chief category in the research sphere, along with qualitative research. An encompassing aspect of market research , it can include both primary and secondary methods of extracting data. 

Although used interchangeably with qualitative research, quantitative research is a distinct process that should not be confused with its counterpart. In fact, it is the opposite of qualitative research.

Let’s navigate through the waters of quantitative research in this complete guide.

What Defines & Makes Up Quantitative Research?

As its name suggests, quantitative research is the process of aggregating quantitative, or numerical data for research purposes. This data is used for a number of applications. These include:

  • Quantifying opinions, behaviors, attitudes and problems
  • Making generalizations
  • Forming predictions
  • Discovering patterns
  • Determining averages
  • Testing relationships

Quantitative research generally relies on a larger sample size in order to quantify any issue or variable. In order to achieve this, this research method involves using mathematical and statistical means. 

This type of research answers the “what” and the “how much” of a subject within a research endeavor. As it forms generalizations, this type of method involves surveying a larger population, using measurable data and processing all the data first and then analyzing it from a statistical standpoint.

The Four Main Types of Quantitative Research

There are four main ways to perform quantitative research. Aside from their methodology, these sub-categories also seek different types of answers and conclusions.

purpose of quantitative research marketing

1. Descriptive Research

This is used to determine the state of variables. It describes the situation and environment surrounding a variable or topic. As such, it is used for arranging comparisons, outlining sample characteristics, overlooking emerging trends and confirming existing phenomena.

The data is collected by way of observation. Descriptive Research is used to form a hypothesis, but only after having aggregated all the necessary data.

2. Correlational Research

This research method is used to examine the relationships between different subjects and variables. Analyzing relationships is necessary to either test a hypothesis or a prediction. Because this research focuses on relationships between fixed variables, other outlying variables are not part of the investigation.

Correlational research is in direct opposition to experimental research, as none of the studied variables are manipulated. Correlations can be either positive or negative, with different degrees of the relationship’s strength.

3. Experimental Research

This method is used for finding whether there is a cause and effect relationship among variables. This kind of research relies on the scientific method. Unlike correlational research, experimental research involves manipulating variables.

Researchers would manipulate a variable to uncover its effect on another one. This method is frequently referred to as true experimentation, as no experimental undertaking leaves all variables unchanged; at least one must be influenced in some way. 

This includes manipulating, randomizing or reverting back a variable. The variables are then measured, calculated and compared.

4. Survey Research

The final research method is crucial to understanding behavior. In market research, it is often used to acclimate a brand with its target market’s desires, needs, points of contention and behaviors.

Surveys allow researchers to ask pointed questions to either discover their target audience or get a granular sense of their opinions. As such, they can be conducted within one group or many, for the sake of comparison.

Instead of turning to survey panels , which are likely to have skewed or biased results, researchers should use a random sample of people. A non-panel-based survey will garner more respondents that aren’t motivated by professional compensation.

Surveys can be administered by mail,  in-person, on the phone, or digitally. The latter has even more options: online surveys, third-party surveys, emails and in-app.

Examples of Questions for Quantitative Research

Survey research has a far larger scope of questions than do the other three types, as researchers can ask practically anything to conduct their studies. However, there are some best practices in survey questionnaires, such as focusing on your industry, your product and the desires of customers.

Learn more about asking insightful market research questions . Here are a few examples of quantitative research questions in the three other categories.

  • Is working from home the best option to improve productivity for employees with long commutes? Variable: Working from home and in-office Demographic: Employees with long commutes Quantitative Research Type : Experimental
  • How has the coronavirus changed employment for white-collar workers? Variable: Employment types and statuses Demographic: White-collar workers Quantitative Research Type : Experimental
  • How often do working people travel for a holiday? Variable: Amount of times respondents travel during a holiday Demographic: working people Quantitative Research Type : Descriptive
  • How much would you pay for a subscription to an entertainment magazine? Variable: payments for a magazine subscription Demographic: women aged 14-44, those interested in celebrities Quantitative Research Type : Descriptive
  • What is the difference in smartphone usage between Millennials and senior citizens? Variable: Time spent on using a smartphone Demographic: Millennials and seniors Quantitative Research Type: Correlational
  • Does the leadership style of car shop owners predict the job satisfaction of car salespeople? Variable: Leadership style and job satisfaction Demographic: Car shop employers and salespeople Quantitative Research Type: Correlational 

When to Use Quantitative Research and How to Analyze It

purpose of quantitative research marketing

The quantitative research method has specific use cases. You ought to consider which is best for your particular business, which includes your strategy, your marketing and other facets.

The core of quantitative research is to quantify a phenomenon (a problem, an inadequacy, and a slew of other occurrences) and understand its prevalence. Researchers do this by observing large portions of a population.

You should use this form of research whenever you need to be presented with the state of things at a higher level, or from a bird’s eye view. This Is because this type of research can identify links between various factors, look for correlations and discover cause and effect relationships.

Researchers can then use the results of their findings to form predictions. This is useful in market research when launching a new product, brainstorming product ideas or innovations or growing a customer base.

To analyze this research, it should first be made quantifiable and objective. Researchers should pin down the scales and units of measurements in their various studies. Then, they should organize them into easily interpretable formats.

For example, once you gather the numerical data, you can enter it into a spreadsheet. Thereafter, you can organize it by desegregating it into graphs, charts and tables. Finally, you should draw data-based conclusions from your study. You can also do further sleuthing via advanced analytics.

The Benefits and Drawbacks of Quantitative Research

Quantitative research has a bevy of benefits; it also has some hindrances. You should peruse both the positive and negative qualities of this research type before setting out on any major research project. The following may help you choose one form of research over the other, or use aspects of both.

  • Larger sample pools: the larger the group of respondents, the more accurate are the results.
  • Highly structured: Surveys, questionnaires, and other tools for recording numerical data
  • Focused: The design of the study is determined before it begins
  • Theory-based: Research tests a theory to provide support/proof
  • Designed to Be Analyzed: Numbers/statistics exist as tables, charts, figures and other non-textual forms for easy analysis.
  • Objective: Steering clear of bias as the research is separated from the data & only objective responses are sought.
  • Direct comparisons of results: The study can be set in different cultural environments, times or different groups of participants with a statistical comparison of results.
  • Focuses solely on numbers: This can be limiting as researchers may overlook other data and larger themes.
  • Superficial Representations: It cannot adequately describe complex concepts (ex: feelings, opinions) it only shows the numbers behind them. 
  • Several factors can invalidate results: A hypothesis and a model for collecting/ analyzing required; any mistake can lead to bias and inaccurate illustrations.
  • Erred Structure: If any data is missing or if measurements are not clear, biases easily take precedence.

The Final Word on Quantitative Research

Market research is far too encompassing to fully complete, especially in a limited amount of time. To tackle market research, begin with a research method. Quantitative research is often a good starting point, as it shows you the existence of a problem by way of quantifying it.

Aside from confirming the existence, it can help confirm a hypothesis, find correlations and prove cause and effect relationships. A hard set of data can also help you make educated predictions.

While the three types of quantitative research methods are useful, they do have several disadvantages. The fourth one, ie, survey research helps fill in the gaps and inadequacies of numerical limitations. Interestingly enough, they too can be a source of hard data and numbers. 

Either way, market research is sure to benefit from incorporating surveys as part of the processes.

Frequently asked questions

What is quantitative market research.

Quantitative market research utilizes the techniques of quantitative research in order to better understand the target market. In quantitative research, the information gathered from surveys and questionnaires is converted into numerical values so it can be easily analyzed.

What types of questions do quantitative research answer?

Quantitative research seeks to define “what” and “how much.” It is used for identifying patterns, making predictions, establishing averages, and quantifying opinions, attitudes or behaviors.

What are the four main types of quantitative research?

The four main types of quantitative research are survey research, correlational research, descriptive research, and experimental research.

What type of surveys are used for quantitative research?

Quantitative surveys are best suited for quantitative research. In this type of survey, there are no open-ended questions, and all responses can be assigned a numerical value. In most cases, a quantitative survey is distributed to a large and random sample of individuals.

Why are large sample sizes important when conducting quantitative research?

A small sample size can lead to inaccurate results. The larger the sample size (i.e. the group of individuals who receive the survey), the more likely it is that the results will be statistically significant and accurate.

Do you want to distribute your survey? Pollfish offers you access to millions of targeted consumers to get survey responses from $0.95 per complete. Launch your survey today.

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Home » Quantitative Research – Methods, Types and Analysis

Quantitative Research – Methods, Types and Analysis

Table of Contents

What is Quantitative Research

Quantitative Research

Quantitative research is a type of research that collects and analyzes numerical data to test hypotheses and answer research questions . This research typically involves a large sample size and uses statistical analysis to make inferences about a population based on the data collected. It often involves the use of surveys, experiments, or other structured data collection methods to gather quantitative data.

Quantitative Research Methods

Quantitative Research Methods

Quantitative Research Methods are as follows:

Descriptive Research Design

Descriptive research design is used to describe the characteristics of a population or phenomenon being studied. This research method is used to answer the questions of what, where, when, and how. Descriptive research designs use a variety of methods such as observation, case studies, and surveys to collect data. The data is then analyzed using statistical tools to identify patterns and relationships.

Correlational Research Design

Correlational research design is used to investigate the relationship between two or more variables. Researchers use correlational research to determine whether a relationship exists between variables and to what extent they are related. This research method involves collecting data from a sample and analyzing it using statistical tools such as correlation coefficients.

Quasi-experimental Research Design

Quasi-experimental research design is used to investigate cause-and-effect relationships between variables. This research method is similar to experimental research design, but it lacks full control over the independent variable. Researchers use quasi-experimental research designs when it is not feasible or ethical to manipulate the independent variable.

Experimental Research Design

Experimental research design is used to investigate cause-and-effect relationships between variables. This research method involves manipulating the independent variable and observing the effects on the dependent variable. Researchers use experimental research designs to test hypotheses and establish cause-and-effect relationships.

Survey Research

Survey research involves collecting data from a sample of individuals using a standardized questionnaire. This research method is used to gather information on attitudes, beliefs, and behaviors of individuals. Researchers use survey research to collect data quickly and efficiently from a large sample size. Survey research can be conducted through various methods such as online, phone, mail, or in-person interviews.

Quantitative Research Analysis Methods

Here are some commonly used quantitative research analysis methods:

Statistical Analysis

Statistical analysis is the most common quantitative research analysis method. It involves using statistical tools and techniques to analyze the numerical data collected during the research process. Statistical analysis can be used to identify patterns, trends, and relationships between variables, and to test hypotheses and theories.

Regression Analysis

Regression analysis is a statistical technique used to analyze the relationship between one dependent variable and one or more independent variables. Researchers use regression analysis to identify and quantify the impact of independent variables on the dependent variable.

Factor Analysis

Factor analysis is a statistical technique used to identify underlying factors that explain the correlations among a set of variables. Researchers use factor analysis to reduce a large number of variables to a smaller set of factors that capture the most important information.

Structural Equation Modeling

Structural equation modeling is a statistical technique used to test complex relationships between variables. It involves specifying a model that includes both observed and unobserved variables, and then using statistical methods to test the fit of the model to the data.

Time Series Analysis

Time series analysis is a statistical technique used to analyze data that is collected over time. It involves identifying patterns and trends in the data, as well as any seasonal or cyclical variations.

Multilevel Modeling

Multilevel modeling is a statistical technique used to analyze data that is nested within multiple levels. For example, researchers might use multilevel modeling to analyze data that is collected from individuals who are nested within groups, such as students nested within schools.

Applications of Quantitative Research

Quantitative research has many applications across a wide range of fields. Here are some common examples:

  • Market Research : Quantitative research is used extensively in market research to understand consumer behavior, preferences, and trends. Researchers use surveys, experiments, and other quantitative methods to collect data that can inform marketing strategies, product development, and pricing decisions.
  • Health Research: Quantitative research is used in health research to study the effectiveness of medical treatments, identify risk factors for diseases, and track health outcomes over time. Researchers use statistical methods to analyze data from clinical trials, surveys, and other sources to inform medical practice and policy.
  • Social Science Research: Quantitative research is used in social science research to study human behavior, attitudes, and social structures. Researchers use surveys, experiments, and other quantitative methods to collect data that can inform social policies, educational programs, and community interventions.
  • Education Research: Quantitative research is used in education research to study the effectiveness of teaching methods, assess student learning outcomes, and identify factors that influence student success. Researchers use experimental and quasi-experimental designs, as well as surveys and other quantitative methods, to collect and analyze data.
  • Environmental Research: Quantitative research is used in environmental research to study the impact of human activities on the environment, assess the effectiveness of conservation strategies, and identify ways to reduce environmental risks. Researchers use statistical methods to analyze data from field studies, experiments, and other sources.

Characteristics of Quantitative Research

Here are some key characteristics of quantitative research:

  • Numerical data : Quantitative research involves collecting numerical data through standardized methods such as surveys, experiments, and observational studies. This data is analyzed using statistical methods to identify patterns and relationships.
  • Large sample size: Quantitative research often involves collecting data from a large sample of individuals or groups in order to increase the reliability and generalizability of the findings.
  • Objective approach: Quantitative research aims to be objective and impartial in its approach, focusing on the collection and analysis of data rather than personal beliefs, opinions, or experiences.
  • Control over variables: Quantitative research often involves manipulating variables to test hypotheses and establish cause-and-effect relationships. Researchers aim to control for extraneous variables that may impact the results.
  • Replicable : Quantitative research aims to be replicable, meaning that other researchers should be able to conduct similar studies and obtain similar results using the same methods.
  • Statistical analysis: Quantitative research involves using statistical tools and techniques to analyze the numerical data collected during the research process. Statistical analysis allows researchers to identify patterns, trends, and relationships between variables, and to test hypotheses and theories.
  • Generalizability: Quantitative research aims to produce findings that can be generalized to larger populations beyond the specific sample studied. This is achieved through the use of random sampling methods and statistical inference.

Examples of Quantitative Research

Here are some examples of quantitative research in different fields:

  • Market Research: A company conducts a survey of 1000 consumers to determine their brand awareness and preferences. The data is analyzed using statistical methods to identify trends and patterns that can inform marketing strategies.
  • Health Research : A researcher conducts a randomized controlled trial to test the effectiveness of a new drug for treating a particular medical condition. The study involves collecting data from a large sample of patients and analyzing the results using statistical methods.
  • Social Science Research : A sociologist conducts a survey of 500 people to study attitudes toward immigration in a particular country. The data is analyzed using statistical methods to identify factors that influence these attitudes.
  • Education Research: A researcher conducts an experiment to compare the effectiveness of two different teaching methods for improving student learning outcomes. The study involves randomly assigning students to different groups and collecting data on their performance on standardized tests.
  • Environmental Research : A team of researchers conduct a study to investigate the impact of climate change on the distribution and abundance of a particular species of plant or animal. The study involves collecting data on environmental factors and population sizes over time and analyzing the results using statistical methods.
  • Psychology : A researcher conducts a survey of 500 college students to investigate the relationship between social media use and mental health. The data is analyzed using statistical methods to identify correlations and potential causal relationships.
  • Political Science: A team of researchers conducts a study to investigate voter behavior during an election. They use survey methods to collect data on voting patterns, demographics, and political attitudes, and analyze the results using statistical methods.

How to Conduct Quantitative Research

Here is a general overview of how to conduct quantitative research:

  • Develop a research question: The first step in conducting quantitative research is to develop a clear and specific research question. This question should be based on a gap in existing knowledge, and should be answerable using quantitative methods.
  • Develop a research design: Once you have a research question, you will need to develop a research design. This involves deciding on the appropriate methods to collect data, such as surveys, experiments, or observational studies. You will also need to determine the appropriate sample size, data collection instruments, and data analysis techniques.
  • Collect data: The next step is to collect data. This may involve administering surveys or questionnaires, conducting experiments, or gathering data from existing sources. It is important to use standardized methods to ensure that the data is reliable and valid.
  • Analyze data : Once the data has been collected, it is time to analyze it. This involves using statistical methods to identify patterns, trends, and relationships between variables. Common statistical techniques include correlation analysis, regression analysis, and hypothesis testing.
  • Interpret results: After analyzing the data, you will need to interpret the results. This involves identifying the key findings, determining their significance, and drawing conclusions based on the data.
  • Communicate findings: Finally, you will need to communicate your findings. This may involve writing a research report, presenting at a conference, or publishing in a peer-reviewed journal. It is important to clearly communicate the research question, methods, results, and conclusions to ensure that others can understand and replicate your research.

When to use Quantitative Research

Here are some situations when quantitative research can be appropriate:

  • To test a hypothesis: Quantitative research is often used to test a hypothesis or a theory. It involves collecting numerical data and using statistical analysis to determine if the data supports or refutes the hypothesis.
  • To generalize findings: If you want to generalize the findings of your study to a larger population, quantitative research can be useful. This is because it allows you to collect numerical data from a representative sample of the population and use statistical analysis to make inferences about the population as a whole.
  • To measure relationships between variables: If you want to measure the relationship between two or more variables, such as the relationship between age and income, or between education level and job satisfaction, quantitative research can be useful. It allows you to collect numerical data on both variables and use statistical analysis to determine the strength and direction of the relationship.
  • To identify patterns or trends: Quantitative research can be useful for identifying patterns or trends in data. For example, you can use quantitative research to identify trends in consumer behavior or to identify patterns in stock market data.
  • To quantify attitudes or opinions : If you want to measure attitudes or opinions on a particular topic, quantitative research can be useful. It allows you to collect numerical data using surveys or questionnaires and analyze the data using statistical methods to determine the prevalence of certain attitudes or opinions.

Purpose of Quantitative Research

The purpose of quantitative research is to systematically investigate and measure the relationships between variables or phenomena using numerical data and statistical analysis. The main objectives of quantitative research include:

  • Description : To provide a detailed and accurate description of a particular phenomenon or population.
  • Explanation : To explain the reasons for the occurrence of a particular phenomenon, such as identifying the factors that influence a behavior or attitude.
  • Prediction : To predict future trends or behaviors based on past patterns and relationships between variables.
  • Control : To identify the best strategies for controlling or influencing a particular outcome or behavior.

Quantitative research is used in many different fields, including social sciences, business, engineering, and health sciences. It can be used to investigate a wide range of phenomena, from human behavior and attitudes to physical and biological processes. The purpose of quantitative research is to provide reliable and valid data that can be used to inform decision-making and improve understanding of the world around us.

Advantages of Quantitative Research

There are several advantages of quantitative research, including:

  • Objectivity : Quantitative research is based on objective data and statistical analysis, which reduces the potential for bias or subjectivity in the research process.
  • Reproducibility : Because quantitative research involves standardized methods and measurements, it is more likely to be reproducible and reliable.
  • Generalizability : Quantitative research allows for generalizations to be made about a population based on a representative sample, which can inform decision-making and policy development.
  • Precision : Quantitative research allows for precise measurement and analysis of data, which can provide a more accurate understanding of phenomena and relationships between variables.
  • Efficiency : Quantitative research can be conducted relatively quickly and efficiently, especially when compared to qualitative research, which may involve lengthy data collection and analysis.
  • Large sample sizes : Quantitative research can accommodate large sample sizes, which can increase the representativeness and generalizability of the results.

Limitations of Quantitative Research

There are several limitations of quantitative research, including:

  • Limited understanding of context: Quantitative research typically focuses on numerical data and statistical analysis, which may not provide a comprehensive understanding of the context or underlying factors that influence a phenomenon.
  • Simplification of complex phenomena: Quantitative research often involves simplifying complex phenomena into measurable variables, which may not capture the full complexity of the phenomenon being studied.
  • Potential for researcher bias: Although quantitative research aims to be objective, there is still the potential for researcher bias in areas such as sampling, data collection, and data analysis.
  • Limited ability to explore new ideas: Quantitative research is often based on pre-determined research questions and hypotheses, which may limit the ability to explore new ideas or unexpected findings.
  • Limited ability to capture subjective experiences : Quantitative research is typically focused on objective data and may not capture the subjective experiences of individuals or groups being studied.
  • Ethical concerns : Quantitative research may raise ethical concerns, such as invasion of privacy or the potential for harm to participants.

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Quantitative market research- everything you need to know, table of contents, introduction.

Did you ever wonder how companies like Amazon or Google seem to predict your preferences with uncanny accuracy? The answer often lies in the realm of quantitative market research. But what precisely does this entail, and how does it enable businesses to comprehend consumer behavior with such finesse?

According to recent studies, over 75% of businesses worldwide rely on market research to guide their decision-making processes, highlighting its pivotal role in today’s competitive landscape. By quantifying consumer opinions and behaviors, companies can make informed strategic choices, tailor products and services to meet specific needs, and stay ahead of market trends.

What is Quantitative Market Research?

Quantitative market research is a systematic approach to gathering and analyzing data from a target market. It relies on numerical data and statistical analysis to understand consumer behavior, preferences, and trends. This method involves collecting data through structured surveys, questionnaires, and experiments conducted with a large sample size representative of the target population. The objective is to obtain measurable insights into consumer opinions, attitudes, and purchasing habits.

One of the key advantages of quantitative marketing research is its ability to provide precise and quantifiable data. By using statistical techniques such as regression analysis, correlation, and hypothesis testing, researchers can identify patterns and relationships within the data, allowing for informed decision-making. This data-driven approach enables businesses to make strategic decisions regarding product development, pricing strategies, and marketing campaigns.

Furthermore, quantitative research allows for generalization of findings to a larger population. With a sizable and diverse sample, researchers can draw conclusions that are applicable beyond the study group. This scalability enhances the reliability and validity of the research findings, providing businesses with confidence in their market strategies. Overall, quantitative market research serves as a powerful tool for businesses seeking to understand market dynamics and make data-driven decisions in an increasingly competitive landscape.

Common Types Of Quantitative Market Research

Quantitative market research encompasses various methods tailored to gather numerical data for analysis. Some common types include surveys, experiments, and observational studies.

Surveys are one of the most widely used methods in quantitative market research. They involve structured questionnaires administered to a representative sample of the target population. Surveys can be conducted through various channels such as online platforms, telephone interviews, or in-person interactions. By asking specific questions and collecting responses in a standardized format, researchers can quantify consumer opinions, preferences, and behaviors.

2. Experiments

Experiments are another essential type of quantitative marketing research. In experiments, researchers manipulate one or more variables to observe their effect on consumer behavior. This method allows for causal inference, helping businesses understand the impact of changes in product features, pricing strategies, or marketing tactics. Through controlled experiments, researchers can measure and analyze quantitative data to identify trends and patterns.

3. Observational studies

Observational studies involve systematically observing and recording consumer behavior in real-life settings. Researchers may use techniques such as tracking consumer purchases, monitoring website traffic, or analyzing social media interactions. By quantifying observational data, businesses can gain insights into consumer habits, trends, and preferences without direct intervention. Observational studies provide valuable quantitative data that complement findings from surveys and experiments, offering a comprehensive understanding of the market landscape.

Overall, these common types of quantitative market research enable businesses to gather, analyze, and interpret numerical data to make informed decisions and drive success in the marketplace. Each method offers unique advantages and insights, contributing to a robust understanding of consumer behavior and market dynamics.

Quantitative vs. Qualitative Market Research

Quantitative market research and qualitative market research are two distinct approaches used to gather and analyze data about consumer behavior and preferences. Here’s a breakdown of their key differences:

Data Collection Methods

  • Quantitative Research: Utilizes structured methods such as surveys, experiments, and observational studies to gather numerical data from a large sample size. The focus is on quantifiable information, allowing for statistical analysis and measurement of trends and patterns.
  • Qualitative Research: Relies on unstructured or semi-structured techniques like interviews, focus groups, and observations to gather in-depth insights into consumer attitudes, motivations, and perceptions. It emphasizes open-ended questions and discussions to explore nuances and uncover underlying reasons behind behaviors.

Data Analysis Techniques

  • Quantitative Research: Involves the use of statistical tools and techniques to analyze numerical data systematically. Researchers employ methods such as regression analysis, correlation, and hypothesis testing to identify relationships, trends, and statistical significance.
  • Qualitative Research: Focuses on interpreting non-numerical data through thematic analysis, content analysis, or grounded theory. Researchers analyze textual or visual data to identify themes, patterns, and emerging concepts, providing rich, descriptive insights into consumer experiences and perspectives.

3. Scope and Generalizability

  • Quantitative Research: Offers the advantage of scalability and generalizability, allowing findings to be applied to a broader population. With a large and representative sample size, researchers can draw statistically valid conclusions and make predictions about market trends and consumer behavior.
  • Qualitative Research: Emphasizes depth over breadth, providing detailed insights into specific contexts or segments of the target market. While findings may not be statistically generalizable, qualitative research offers rich, contextual understanding that can inform product development, marketing strategies, and decision-making.

4. Objective and Purpose

  • Quantitative Research: Often used to quantify phenomena, measure market trends, evaluate product performance, or assess customer satisfaction through numerical metrics. It aims to provide precise, quantifiable data to support strategic decision-making and hypothesis testing.
  • Qualitative Research: Focuses on exploring perceptions, attitudes, and motivations behind consumer behavior, uncovering underlying emotions and motivations. It is valuable for generating hypotheses, uncovering emerging trends, and gaining deeper insights into consumer needs and preferences.

In summary, quantitative market research focuses on numerical data collection and statistical analysis to quantify market phenomena and trends, while qualitative market research delves into the subjective experiences and perceptions of consumers through in-depth exploration and interpretation of non-numerical data. Both approaches offer valuable insights and have unique strengths, often complementing each other in comprehensive market research strategies.

Top Advantages of Quantitative Market Research

Quantitative market research offers numerous advantages for businesses seeking to understand their target market, make informed decisions, and stay ahead of the competition. Here are some of the top advantages:

1. Statistical Validity

Quantitative research allows for the collection of numerical data that can be analyzed statistically. This statistical analysis provides a level of validity and reliability to the findings, enabling businesses to make confident decisions based on concrete evidence rather than intuition or anecdotal evidence.

2. Large Sample Sizes

One of the key strengths of quantitative research is its ability to gather data from large sample sizes. This ensures that the findings are representative of the broader population, providing a comprehensive understanding of market trends, preferences, and behaviors.

3. Generalizability

With its focus on numerical data and large sample sizes, Quantitative market research results are often generalizable to a larger population. This means that insights drawn from the research can be applied to a wider audience, helping businesses make strategic decisions that resonate with their target market.

4. Measurable Insights

Quantitative research allows businesses to measure various aspects of consumer behavior, such as purchasing habits, brand loyalty, and product preferences. These measurable insights provide actionable data points that can inform marketing strategies, product development, and overall business planning.

5. Comparative Analysis

Quantitative market research enables businesses to conduct comparative analysis across different demographic groups, geographic regions, or time periods. By comparing data sets, businesses can identify trends, patterns, and correlations, helping them understand how various factors impact consumer behavior and market dynamics.

6. Predictive Modeling

Quantitative research often involves the use of advanced statistical techniques and predictive modeling. By analyzing historical data and identifying patterns, businesses can forecast future market trends, anticipate consumer demands, and proactively adjust their strategies to stay ahead of the competition.

7. Cost-Effective Data Collection

While quantitative research may require initial investment in survey development and data analysis tools, it is generally more cost-effective than qualitative research methods such as focus groups or in-depth interviews. Online surveys and data collection platforms make it easier and more affordable to gather large volumes of data from diverse respondents.

8. Data-driven Decision Making

In today’s data-driven business landscape, Quantitative market research plays a crucial role in informed decision-making. By leveraging data analytics and empirical evidence, businesses can make strategic decisions based on real-world data rather than gut feelings or assumptions, leading to more successful outcomes and sustainable growth.

Disadvantages of Quantitative Marketing Research

While quantitative market research offers numerous advantages, it’s also important to recognize its limitations and potential drawbacks. Here are some disadvantages of quantitative marketing research:

1. Limited Depth of Understanding

Quantitative research often focuses on numerical data and standardized survey instruments, which may limit the depth of understanding compared to qualitative research methods such as interviews or focus groups. It may not capture the richness of consumer experiences, emotions, or underlying motivations behind their behavior.

Quantitative research often involves surveying a large number of respondents, which provides a representative sample of the target population. The large sample size enhances the reliability and generalizability of the findings, allowing businesses to make informed decisions with confidence.  

3. Inability to Explore Complex Issues

Quantitative market research research is well-suited for exploring straightforward questions and measuring predefined variables. However, it may struggle to address complex or nuanced issues that require in-depth exploration and qualitative insights. Complex phenomena often cannot be fully captured or understood through quantitative measures alone.

4. Lack of Contextual Understanding

Quantitative market research provides numerical data without always providing context or meaning behind the numbers. Without a deeper understanding of the context in which data was collected, businesses may misinterpret findings or overlook important insights. Contextual understanding is essential for making informed decisions based on quantitative research findings.

5. Difficulty in Capturing Unforeseen Variables

Quantitative research relies on predetermined survey questions and predefined variables, which may overlook unforeseen variables or emerging trends that could influence consumer behavior. This limitation can result in incomplete or outdated insights, particularly in fast-changing industries or markets.

Key Steps for Quantitative Marketing Research

Conducting quantitative market research involves several key steps to ensure the collection of reliable data and the generation of actionable insights. Here are the steps for conducting quantitative marketing research:

Define Research Objectives

Clearly define the research objectives and goals. Determine what specific information you want to gather, what questions you need to answer, and how you plan to use the research findings to inform business decisions.

Identify Target Population

Identify the target population or the group of individuals you want to survey. Define the characteristics of your target audience, such as demographics (age, gender, income), geographic location, behavior patterns, or other relevant criteria.

Develop Research Instrument

Design the survey instrument or questionnaire to collect quantitative data. Craft clear, concise, and unbiased questions that address your research objectives. Consider using a mix of closed-ended (e.g., multiple-choice, rating scales) and open-ended questions to gather both quantitative and qualitative insights.

Select Sampling Method

Choose an appropriate sampling method to select participants from the target population. Common sampling methods include random sampling, stratified sampling, cluster sampling, or convenience sampling. Ensure that your sample size is sufficient to achieve statistical significance and representativeness.

Data Collection

Administer the survey to the selected participants using appropriate data collection methods. This may include online surveys, telephone interviews, face-to-face interviews, or mail surveys, depending on the characteristics of your target population and the research objectives.

Ensure Data Quality

Implement measures to ensure the quality and validity of the collected data. This includes pretesting the survey instrument to identify any issues or ambiguities, monitoring data collection procedures to minimize errors, and verifying the accuracy of responses through data validation techniques.

Data Analysis

Analyze the collected data using statistical analysis techniques. This may involve descriptive statistics to summarize the data (e.g., mean, median, mode), inferential statistics to test hypotheses and make predictions (e.g., t-tests, regression analysis), and data visualization techniques to present findings effectively (e.g., charts, graphs, tables).

Interpret Findings

Interpret the findings of the data analysis in relation to the research objectives. Identify key trends, patterns, correlations, and insights that emerge from the data. Consider how the findings align with the research objectives and what implications they have for decision-making.

Draw Conclusions

Draw conclusions based on the interpreted findings and assess their implications for the business. Determine whether the research objectives have been met and what actionable insights can be derived from the findings. Consider any limitations or caveats associated with the research findings.

Report and Present Findings

Prepare a comprehensive research report that summarizes the methodology, findings, conclusions, and recommendations of the quantitative market research. Present the findings to relevant stakeholders in a clear and engaging manner, using visual aids and storytelling techniques to enhance understanding and facilitate decision-making.

By following these steps, businesses can conduct effective quantitative marketing research to gain valuable insights into their target market, make informed decisions, and achieve strategic objectives.

10 Best Practices for Quantitative Market Research

Quantitative research finds wide-ranging applications across various domains and industries due to its ability to provide systematic, numerical insights into market dynamics, consumer behavior, and business performance. Some key applications of quantitative research include:  

1. Clearly Define Objectives

Start by clearly defining the research objectives and goals. Understand what specific information you need to gather and how you plan to use the research findings to inform decision-making.

2. Use Validated Measures

Utilize validated measurement tools and standardized survey instruments to ensure the reliability and validity of your data. Choose established scales and question formats that have been tested and proven to produce accurate results.

3. Pretest Survey Instrument

Before launching the survey, pretest the survey instrument with a small sample of respondents to identify any issues or ambiguities. This allows you to refine the questionnaire, improve question clarity, and ensure that respondents interpret questions as intended.

4. Ensure Representative Sampling

For quantitative market research, use appropriate sampling methods to ensure that your sample is representative of the target population. Consider factors such as demographics, geographic location, and behavior patterns when selecting participants to minimize sampling bias.

5. Maximize Response Rate

Implement strategies to maximize the response rate and minimize non-response bias. This may include personalized invitations, clear instructions, incentives for participation, and multiple reminders to encourage survey completion.

6. Maintain Data Quality

Implement measures to maintain data quality throughout the research process. This includes monitoring data collection procedures, verifying the accuracy of responses, and conducting data validation checks to identify and address errors.

7. Analyze Data Rigorously

Conduct rigorous data analysis using appropriate statistical techniques. Ensure that the analysis is conducted accurately and transparently, and interpret the findings in relation to the research objectives.

8. Consider Contextual Factors

Consider contextual factors that may influence the interpretation of research findings, such as market trends, competitive landscape, and consumer preferences. Contextual understanding helps provide a deeper understanding of the data and its implications.

9. Provide Actionable Insights

Focus on providing actionable insights that can inform decision-making and drive business outcomes. Present the findings in a clear, concise manner, and highlight key trends, patterns, and recommendations that stakeholders can act upon.

10. Continuously Improve

Continuously evaluate and improve your quantitative research processes based on feedback and learnings from each study. Incorporate lessons learned into future research initiatives to enhance the effectiveness and reliability of your market research efforts.

Quantitative Data Collection Methods for Marketing Research

Quantitative market research relies on various data collection methods to gather numerical data and statistical insights about consumer behavior, preferences, and trends. Here are some commonly used quantitative data collection methods for marketing research:

Online Surveys

Online surveys are one of the most popular methods for quantitative data collection in marketing research. Surveys are distributed electronically via email, websites, or social media platforms, allowing respondents to provide feedback on their preferences, purchasing habits, brand perceptions, and more. Online surveys offer the advantages of cost-effectiveness, wide reach, and the ability to collect large volumes of data quickly.

Telephone Surveys

Telephone surveys involve conducting interviews with respondents over the phone to gather quantitative data. Trained interviewers follow a standardized script and ask respondents a series of structured questions. Telephone surveys are useful for reaching diverse populations, including those without internet access, and can provide immediate feedback from respondents.

Face-to-Face Interviews

Face-to-face interviews involve direct interaction between interviewers and respondents in person. Interviewers use structured questionnaires to collect quantitative data on topics such as product preferences, satisfaction levels, and brand perceptions. Face-to-face interviews allow for deeper probing and clarification of responses but can be more time-consuming and expensive compared to other methods.

Mail Surveys

Mail surveys involve sending questionnaires to respondents via postal mail and asking them to complete and return the surveys by mail. While less common in the digital age, mail surveys can still be effective for reaching certain demographic groups, particularly older or rural populations. However, they tend to have lower response rates and longer turnaround times compared to online or telephone surveys.

Mobile Surveys

With the widespread use of smartphones and mobile devices, mobile surveys have become increasingly popular for quantitative data collection. Mobile surveys are designed to be mobile-friendly, allowing respondents to complete surveys on their smartphones or tablets at their convenience. Mobile surveys offer the advantages of accessibility, real-time data collection, and the ability to capture location-based information.

Point-of-Sale (POS) Data Collection

POS data collection involves capturing transactional data from point-of-sale systems used in retail stores, e-commerce platforms, and other sales channels. POS data provides quantitative insights into consumer purchasing behavior, including sales volumes, product preferences, pricing strategies, and seasonal trends. POS data collection is valuable for analyzing market trends, monitoring sales performance, and optimizing marketing strategies.

Website Analytics

Website analytics tools track and analyze quantitative data about website visitors’ behavior, interactions, and engagement metrics. These tools provide insights into website traffic, user demographics, conversion rates, bounce rates, and other key performance indicators (KPIs). Website analytics help marketers understand how visitors navigate their websites, identify areas for improvement, and optimize digital marketing efforts.

Social Media Monitoring

Social media monitoring tools collect quantitative data from social media platforms, such as Facebook, Twitter, Instagram, and LinkedIn. These tools track metrics such as follower counts, likes, shares, comments, and sentiment analysis to gauge brand awareness, customer engagement, and social media ROI. Social media monitoring provides valuable insights into consumer conversations, trends, and competitive intelligence in real-time.

In conclusion, quantitative market research is like a reliable guidebook for understanding how consumers behave and what’s happening in the market. It uses numbers and straightforward analysis to uncover insights that help businesses make smart decisions and plan for the future. By carefully collecting and studying data, companies can get a clear picture of who their customers are and what they want, which guides everything from product development to marketing strategies. Essentially, quantitative research helps businesses stay on track and ahead of the competition by giving them the knowledge they need to navigate the twists and turns of the market.

In today’s fast-paced business world, quantitative marketing research is essential for companies looking to understand what’s going on with their customers and in their industry. It’s like having a map that shows you where to go and how to get there. By using simple tools and techniques to analyze data, businesses can spot trends, predict what’s coming next, and make decisions with confidence.


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B2B Market Research Services: A Comprehensive Overview

1. What is quantitative markeing research?

Quantitative marketing research involves collecting and analyzing numerical data to understand market trends, consumer behavior, and preferences. It employs structured surveys, polls, and statistical methods to quantify insights, providing measurable data for making informed business decisions and assessing market opportunities.

2. Is market research qualitative or quantitative?

Market research can be both qualitative and quantitative, depending on the type of data collected and analyzed. Quantitative research uses numerical data and statistical methods, while qualitative research uses non-numerical data and interpretive methods.

3.What are examples of the most common quantitative marketing research

Examples of common quantitative marketing research include surveys, experiments, observational studies, and data analysis techniques such as regression analysis and factor analysis.

4. How qualitative research can be useful in marketing?

Qualitative research can be useful in marketing for various purposes, such as exploring new product ideas, testing concepts, understanding customer satisfaction and loyalty, identifying market segments and personas, developing brand positioning and messaging, and generating creative solutions.

5. How to analyze quanitative data for marketing research?

To analyze qualitative data for marketing research, start by transcribing or summarizing the data. Then, use thematic analysis or coding techniques to identify recurring themes, patterns, and insights. Interpret these findings within the context of the research objectives to inform marketing strategies effectively.

6. How to conduct qualitative market research?

Qualitative market research can be conducted by using different methods and techniques, such as focus groups, in-depth interviews, observation, ethnography, case studies, and online communities. The choice of method depends on the research objectives, questions, budget, and time constraints.

7. What are some common quantitative market research techniques?

Common techniques include online surveys, telephone interviews, face-to-face interviews, mail surveys, and statistical analysis using software. These methods help gather numerical data and analyze consumer behavior and market trends.

8. How can businesses benefit from quantitative market research services?

Businesses gain expertise in designing robust methodologies, collecting high-quality data, and gaining insights into consumer preferences and market trends. This enables data-driven decision-making and staying competitive.

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purpose of quantitative research marketing

The Importance of Quantitative Research in Marketing Decision Making

  • January 30, 2024

Sales and Marketing Management

In the dynamic realm of marketing, where every trend is a shifting landscape and consumer preferences resemble a kaleidoscope of ever-changing patterns, the role of quantitative research emerges as the compass guiding decision-makers through this vibrant maze. 

Picture this: a symphony of data, a dance of numbers, and a canvas painted with statistical insights. Welcome to the world where the alchemy of numbers not only deciphers market trends but also unveils the secrets hidden within the labyrinth of consumer behavior. 

As we embark on this journey into the heart of data-driven decision-making , the spotlight falls on the unsung hero – quantitative research. In this exploration, we unravel the significance, the power, and the transformative impact that harnessing the quantitative can have on steering the ship of marketing strategies toward success. 

So, buckle up as we delve into the captivating narrative of why, in the grand tapestry of marketing, numbers aren't just digits; they are the pulsating heartbeat of informed choices and strategic triumphs.

Overview of Decision-Making Process

Let's take a quick pit stop to understand the decision-making process. Picture this: you're at a crossroads, faced with choices that could make or break your marketing strategy. How do you navigate through this maze of possibilities? Data-driven insights are the compass that guides you.

Role of Data in Decision-Making

Data is the backbone of decision-making. Whether you're deciding on your next data-driven marketing campaign or fine-tuning your target audience, having solid data at your fingertips is like having a secret weapon. It minimizes the risk of guesswork and transforms your decisions from shots in the dark to well-calculated moves.

How to use quantitative research to make better marketing decisions?

Now, let's shine a spotlight on the star of our show – quantitative research. What is it, you ask? In simple terms, it's the method of collecting and analyzing numerical data to understand patterns, trends, and correlations. 

Quantitative research plays a vital role in market research, utilizing concrete facts and numerical data to achieve an objective understanding of people's opinions. Think surveys, experiments, and statistical analyses – the kind of stuff that turns raw numbers into actionable insights.

What are the benefits of Quantitative Research in Marketing?

Quantitative research isn't just a fancy term; it's a marketing superhero. 

Here are some of its key benefits:

  • Precision in Decision-Making: Numbers don't lie. With quantitative research, you get precise data that forms a solid foundation for your marketing decisions.
  • Measurable Results: Ever heard the phrase "what gets measured gets managed"? Quantitative research allows you to measure the impact of your marketing efforts with tangible metrics. 
  • Risk Mitigation: In the dynamic world of marketing, risks are inevitable. However, with quantitative data, you can identify potential pitfalls early on and navigate your strategy accordingly.

Applications of Quantitative Research

Now that we're singing the praises of quantitative research, let's see it in action. From market segmentation to product testing, this method wears many hats.

  • Market Segmentation: Want to tailor your message to a specific audience? Quantitative research helps you understand the demographics, behaviors, and preferences of your target market.
  • Product Development: Before launching a new product, test the waters with quantitative research. Get insights on potential demand, pricing strategies, and consumer preferences.
  • Campaign Effectiveness: Ever wondered if your latest marketing campaign actually resonated with your audience? Quantitative research can measure its success through metrics like conversion rates and customer feedback.

Challenges in Quantitative Decision-Making

Of course, no superhero is without its challenges. Quantitative research, too, faces a few hurdles, such as:

  • Limited Context : Numbers tell a story, but sometimes the context is lost. Quantitative research may only capture part of the picture, especially when it comes to understanding the 'why' behind certain trends.
  • Inflexibility: Unlike qualitative research, which allows for flexibility and exploration, quantitative methods can be rigid. This can be a limitation when dealing with complex, multifaceted issues.

Considerations in Quantitative Decision-Making

Now, before you go all-in on quantitative research, there are a few considerations to keep in mind:

  • Sample Size : Ensure your sample size is representative of your target audience. Small samples may lead to skewed results.
  • Data Quality : Garbage in, garbage out. The accuracy of your findings depends on the quality of your data. Ensure it's reliable and relevant.
  • Ethical Considerations: Respect privacy and ethical standards when collecting and using data. It's not just about numbers; it's about people.

Steps to Conduct Quantitative Research

Alright, you're convinced and ready to embark on your market research journey. Here's a roadmap to guide you:

  • Define Your Objective: Clearly outline what you want to achieve through your research.
  • Design Your Study: Choose the right methodology – surveys, experiments, or statistical analyses – based on your objectives.
  • Collect Data: Implement your study and gather the numerical data needed for analysis .
  • Analysis and Interpretation: Crunch the numbers and derive meaningful insights.
  • Draw Conclusions : Use your findings to make informed decisions for your marketing strategy.

The Final Thoughts

In a nutshell, quantitative research isn't just a tool; it's a mindset. It transforms the way we approach decision-making in the dynamic landscape of marketing. By embracing the power of numbers, you're not just making decisions – you're making informed, strategic moves that can propel your brand to new heights.

Summary of Key Points

  • Data is the compass in decision-making.
  • Quantitative research offers precision and measurable results.
  • Applications include market segmentation, product development, and campaign effectiveness.
  • Challenges include limited context and inflexibility.
  • Considerations involve sample size, data quality, and ethical standards.
  • Steps include defining objectives, designing studies, collecting data, analyzing, and drawing conclusions.

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The NextGen Business Leadership Program focuses on developing a high degree of sales and marketing acumen, strategic thinking, people leadership, and execution skills. These are the essential skills that business leaders need to succeed in today's competitive landscape.

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Ready to supercharge your marketing decisions with quantitative research? Dive into the numbers, explore the possibilities, and watch your strategies soar. If you want to learn more insights, join our sales and marketing management program and take your skills to the next level. Let's not just make decisions; let's make data-driven, game-changing decisions together. Are you in?

Remember, in the world of marketing, numbers aren't just numbers – they're the keys to unlocking success.

 Happy researching!

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What is Marketing Research? Examples and Best Practices

12 min read

What is Marketing Research? Examples and Best Practices

Marketing research is essentially a method utilized by companies to collect valuable information regarding their target market. Through the common practice of conducting market research, companies gather essential information that enables them to make informed decisions and develop products that resonate with consumers. It encompasses the gathering, analysis, and interpretation of data, which aids in identifying consumer demands, anticipating market trends, and staying ahead of the competition.

Exploratory research is one of the initial steps in the marketing research process. It helps businesses gain broad insights when specific information is unknown. If you are seeking insight into how marketing research can influence the trajectory of your SaaS, then you have come to the right place!

  • Market research is a systematic and objective process crucial for understanding target markets, refining business strategies, and informing decisions, which includes collecting, analyzing, and interpreting data on customers, competitors, and the industry.
  • Primary market research gathers specific data directly from the target audience using tools like surveys and focus groups, while secondary market research utilizes existing data from various sources to provide broader market insights.
  • Effective market research combines both qualitative methods, which explore consumer motivations, and quantitative methods, which provide measurable statistics, to create comprehensive insights that guide business strategy and decision-making.

purpose of quantitative research marketing

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purpose of quantitative research marketing

Defining marketing research

market research definition

Launching a product without knowing what your target audience wants is like walking in the dark. Market research lights the way, helping you collect, analyze, and understand information about your target market. This allows you to refine your business strategies and make decisions based on solid evidence.

Gone are the days when just intuition or subjective judgment was enough. Objective insights from market research help avoid costly mistakes and meet consumer needs by identifying trends and changes in the market. This is crucial for assessing a product’s potential success, optimizing marketing strategies, and preparing for market shifts.

Market research is a systematic approach that provides essential information, helping businesses navigate the complexities of the commercial world. Partnering with market research companies can offer additional benefits, leveraging their expertise in understanding market demands, trends, market size, economic indicators, location, market saturation, and pricing. Whether starting a new business, developing products, or updating marketing plans, understanding how to conduct effective market research is key to success.

To conduct market research effectively, businesses must determine study goals, identify target consumers, collect and analyze data, and use the findings to make informed decisions. This process is vital for evaluating past performance, measuring changes over time, and addressing specific business needs. It guides businesses in product development, marketing strategies, and overall decision-making, ensuring a better ROI and providing an eye-opening view of the market through various research methods, whether conducted in-house or outsourced.

The purpose of marketing research

Conducting marketing research is more than just gathering data; it’s about turning that data into actionable insights to refine your business strategies. This process helps you understand what motivates your customers, enabling you to tailor your products and services to minimize risks from the start. Importantly, market research plays a pivotal role in measuring and enhancing customer satisfaction and loyalty, which are critical for understanding key demographics, improving user experience, designing better products, and driving customer retention. Customer satisfaction is measured as a key outcome, directly linked to the success of marketing strategies and business activities.

For SaaS product managers, market research, including competitive analysis, is crucial. It evaluates past strategies and gauges the potential success of new offerings. This research provides essential insights into brand strength, consumer behavior, and market position, which are vital for teams focused on sales, marketing, and product development.

A key aspect of market research is analyzing customer attitudes and usage. This analysis offers detailed insights into what customers want, the choices they make, and the challenges they face. It helps identify opportunities in the market and aids in formulating effective strategies for market entry.

Overall, market research equips SaaS entrepreneurs with the knowledge to meet their target audience’s needs effectively, guiding product adjustments and innovations based on informed decisions.

Key components of market research

Conducting market research is analogous to preparing a cake, requiring precise ingredients in specific quantities to achieve the intended outcome. Within this realm, necessary components consist of primary and secondary data gathering, thorough analysis, and insightful interpretation.

Primary research techniques such as exploratory studies, product evolution inquiries, estimations of market dimensions and shares, and consumer behavior examinations play a crucial role in collecting targeted information that can be directly applied. These methods afford a deeper understanding of your target demographic, allowing for customized strategy development.

In contrast, secondary research enriches the specificity of primary findings by adding wider context. It taps into external resources encompassing works from other investigators, sector-specific reports, and demographics data, which provide an expansive yet less particularized landscape view of the marketplace.

The subsequent phase involves meticulous analysis of collated data offering unbiased perspectives critical for identifying deficiencies while recognizing emerging patterns. Technological progress now facilitates examination efforts on both structured and unstructured datasets effectively addressing large-scale analytical complexities.

Ultimately, it’s through expert-led interpretation that value transcends raw figures, yielding strategies grounded in deep comprehension. Akin to decoding recipes using selected ingredients—this interpretative step enables crafting optimal business maneuvers just as one would bake their ideal confectionery creation utilizing proper culinary guidance.

Types of market research: primary and secondary

Now that you know the importance of clear research objectives, let’s explore the different types of market research and the techniques available to achieve these goals. Market research methods can be divided into two main categories: primary research and secondary research . The choice between these depends on factors like your budget, time constraints, and whether you need exploratory data or definitive answers.

Primary research involves collecting new data directly from sources. This process is like mining for precious metals, as it requires using various methods to gather fresh insights.

  • Surveys (here – in-app survey templates from Userpilot ).

Userpilot surveys

  • Interviews.

user interview

  • Focus groups.
  • Product trials.

free trial

This approach gives you first-hand insight into your target audience.

Conversely, secondary research uses already established datasets of primary data – which can add depth and reinforcement to your firsthand findings.

Conducting your own market research using primary research tools can be a cost-effective strategy, allowing businesses to gather valuable insights directly and tailor their research to specific needs.

Let’s look a bit deeper into them now.

What is primary market research?

Market research uses primary market research as an essential tool. This involves collecting new data directly from your target audience using various methods, such as surveys , focus groups, and interviews.

userpilot surveys

Each method has its benefits. For example, observational studies allow you to see how consumers interact with your product.

userpilot paths

There are many ways to conduct primary research.

Focus Groups : Hold discussions with small groups of 5 to 10 people from your target audience. These discussions can provide valuable feedback on products, perceptions of your company’s brand name, or opinions on competitors. Additionally, these discussions can help understand the characteristics, challenges, and buying habits of target customers, optimizing brand strategy.

Interviews : Have one-on-one conversations to gather detailed information from individuals in your target audience.

userpilot analytics

Surveys : These are a common tool in primary market research and can be used instead of focus groups to understand consumer attitudes. Surveys use structured questions and can reach a broad audience efficiently.

userpilot surveys

Navigating secondary market research

While marketing research using primary methods is like discovering precious metals, secondary market research technique is like using a treasure map. This approach uses data collected by others from various sources, providing a broad industry view. These sources include market analyses from agencies like Statista, historical data such as census records, and academic studies.

Secondary research provides the basic knowledge necessary for conducting primary market research goals but may lack detail on specific business questions and could also be accessible to competitors.

To make the most of secondary market research, it’s important to analyze summarized data to identify trends, rely on reputable sources for accurate data, and remain unbiased in data collection methods.

The effectiveness of secondary research depends significantly on how well the data is interpreted, ensuring that this information complements the insights from primary research.

Qualitative vs quantitative research

Market research employs both qualitative and quantitative methods, offering distinct insights that complement each other. Qualitative research aims to understand consumer behaviors and motivations through detailed analysis, while quantitative research collects measurable data for statistical analysis.

The selection of qualitative or quantitative methods should align with your research goals. If you need to uncover initial insights or explore deep consumer motivations, qualitative techniques like surveys or interviews are ideal.

userpilot surveys

On the other hand, if you need data that can be measured and analyzed for reliability, quantitative methods are more suitable.

userpilot analytics

However, these approaches don’t have to be used separately. Combining qualitative and quantitative methods in mixed-method studies allows you to capture both detailed exploratory responses and concrete numerical data. This integration offers a comprehensive view of the market, leveraging the strengths of both approaches to provide a fuller understanding of market conditions.

Implementing market research tools: Userpilot’s role

Similar to how a compass is essential for navigation at sea, businesses need appropriate instruments to carry out effective market research. Userpilot’s suite of product analytics and in-app engagement tools are critical components for this purpose.

Acting as a Buyer Persona Research instrument, Userpilot’s product analytics provide key quantitative research capabilities. This helps clearly define and comprehend the attributes and behaviors of potential customers, providing you with insights into your ICP (Ideal Customer Persona), user preferences, and product-market fit.

Beyond product analytics, Userpilot offers robust in-app engagement features such as modals and surveys that support real time collection of market research information. These interactive features work synergistically with the analytical tools to enable companies to gather detailed data and feedback crucial for informed business decision-making.

Marketing research process: Step-by-step guide

smart goals

Marketing research conists of several critical stages:

  • Defining precise goals.
  • Delving into the knowledge of your target demographic.
  • Collecting and scrutinizing data.
  • Revealing insights that can be translated into tangible actions.

Following these steps allows you to gather critical information that guides business decisions.

An effective research strategy is crucial and involves:

  • Properly allocating funds.
  • Formulating testable hypotheses.
  • Choosing appropriate methods for the study.
  • Determining the number of study participants.
  • Considering external variables.

A well-planned strategy ensures that your market research is focused, efficient, and produces useful outcomes.

After collecting data, the next step is to analyze it. This involves comparing the data to your initial questions to draw conclusions relevant to your business strategies.

Userpilot makes your data analysis easier by providing handy analytics dashboards for key user metrics such as activation, engagement, core feature adoption, and retention out of the box:

purpose of quantitative research marketing

Finally, you report the findings and the process, providing recommendations based on the evidence. This is like solving a puzzle: each piece helps to complete the overall picture.

Challenges and best practices in market research

Delving into market research comes with its own set of hurdles. Those conducting the research must deliver more profound insights within increasingly shorter timespans, and they need to cultivate strategic, continuous research methods to stay abreast of an ever-changing business landscape.

Ensuring high-quality data can be demanding due to issues such as disjointed tools or insufficient analytical expertise. New solutions like Userpilot are surfacing that make these obstacles less daunting by offering accessible and user-friendly options. Maintaining clear lines of communication with your market research team is crucial for achieving both punctuality and quality in outcomes.

The advantages of engaging in marketing research cannot be overstated.

Real-life examples of successful market research

Real-life examples of market research in the SaaS industry often showcase innovative approaches to understanding customer needs and product-market fit.

For instance, Slack, the communication platform, utilized extensive market research to identify gaps in communication tools and understand the workflows of teams. This led to the development of features that seamlessly integrated with other tools and catered to the needs of various team sizes and structures.

Another example is HubSpot, which conducted market research to understand the pain points of small to medium-sized businesses in managing customer relationships. The insights gained helped shape their all-in-one inbound marketing, sales, and service platform, which has become integral to their users’ daily operations. These examples demonstrate how SaaS companies can employ market research to inform product development, improve user experience, and strategically position themselves in a competitive market.

Choosing the right market research tools

For B2B SaaS product managers aiming to do market research, having the right set of tools can make a significant difference. Here’s a list of valuable SaaS tools that can be leveraged for effective market research:

  • Userpilot : A comprehensive Product Growth Platform offering in-depth product analytics, a code-free in-app experience builder, bespoke in-app survey capabilities, and robust integration options with platforms like Salesforce and Hubspot. This tool is particularly useful for understanding user behavior, enhancing user engagement, and gathering targeted feedback.
  • Qualtrics : Known for its powerful survey tools, Qualtrics helps businesses gather and analyze customer feedback effectively. Its advanced analytics features are ideal for testing market hypotheses and understanding customer sentiments.
  • SurveyMonkey : A versatile tool that enables product managers to create, send, and analyze surveys quickly and easily. SurveyMonkey is suitable for gauging customer satisfaction and collecting feedback on potential new features.
  • Mixpanel : Specializes in user behavior analytics, offering detailed insights into how users interact with your product. This is essential for identifying patterns and optimizing product features.
  • Hotjar : Combines analytics and feedback tools to give teams insights into user behavior and preferences. Hotjar’s heatmaps and session recordings are invaluable for understanding the user experience on a deeper level.
  • Tableau : A leading platform for business intelligence and data visualization, Tableau allows product managers to create comprehensive visual reports that can inform strategic decisions based on user data analysis.

Each of these tools provides unique functionalities that can assist SaaS product managers in conducting thorough market research, thereby ensuring that their products are perfectly aligned with user needs and market demands.

Measuring the impact of market research

The pivotal challenge for market research lies in demonstrating its return on investment (ROI) and overall influence on corporate success sufficiently enough to justify regular financial commitment from company leaders. The worth attributed to a market research firm hinges not only on their ability to deliver relevant and high-caliber information, but also on their pricing structures and their contribution towards propelling organizational growth.

To gauge how effectively business choices made based on market research findings succeed, various metrics and key performance indicators (KPIs) are utilized. These numerical tools act as navigational aids directing enterprises toward achieving objectives while simultaneously verifying that efforts invested in conducting market analysis are yielding fruitful guidance.

Throughout our look at market research, we’ve seen its importance and impact. Our discussion covered the basics of market research, its key components, and different types, including both qualitative and quantitative methods, and the role of Userpilot’s tools. We’ve examined the details of the market research process, tackled challenges, identified best practices, and shared success stories. We also provided advice on choosing the right market research partner and how to measure the effectiveness of your market research.

In today’s data-driven world, comprehensive market research is crucial for companies that want to succeed. It acts like a guide, helping businesses navigate the complex market landscape. Start your own detailed research today, supported by insightful analytics to help you succeed.

Frequently asked questions

What is market research and why is it important.

Understanding your target market, honing business strategies, and making informed decisions are all essential components that depend heavily on effective market research. It offers objective insights to help avoid expensive errors and foresees the needs of customers .

What is the difference between primary and secondary market research?

Primary market research is characterized by the direct gathering of data, in contrast to secondary market research which leverages existing information from alternative sources for addressing research inquiries.

Such a distinction can guide you in selecting an approach that aligns with your precise needs for conducting specific research.

What are some examples of successful market research?

Examples of successful market research are evident in the operations of well-known companies such as Starbucks, Apple, and McDonald’s. They have harnessed this tool to fine-tune their business strategies and make decisions based on solid information.

By employing market research, these businesses have managed to gain insight into their customers’ desires and needs, which has contributed significantly to their success.

How can I choose the right market research partner?

Selecting an ideal market research ally involves identifying a firm that resonates with your project requirements, financial plan, and corporate goals while also verifying their track record of dependability and consistency via reviews from previous clients.

Best wishes on your endeavor!

How is the impact of market research measured?

The effectiveness of market research hinges on the precision, representativeness, and pertinence of its data, along with how successful business decisions are when they’re based on the findings from this research. These elements define the impact of the research conducted.

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What is quantitative research?

2020-06-30 Market Research

purpose of quantitative research marketing

Quantitative research is the most common research framework in the social sciences. While other research frameworks, such as qualitative research, can be subjective, quantitative research is more objective. It studies processes through numbers, and often, the goal of the research is to produce statistics. The information researchers collect using quantitative methods allows them to perform analyses that can be simple or complex, such as showing the connections made between data, calculating averages or percentages, or using inferential statistics to make generalizations about a large population. Researchers use specific methodologies, such as experiments, questionnaires, and structured observations, to collect the data they use for quantitative research.

Let’s take a closer look at quantitative research methods and data analysis to understand what quantitative research is and how you can use it.

What is the purpose of quantitative research?

Quantitative research aims to help scientists, marketers, and researchers better understand society and people. It often involves the exploration or examination of events or occurrences that affect individuals. An example of quantitative research could involve a hospital that conducts surveys after patients have been admitted and discharged. The surveys’ purpose could be to discover how much time doctors who work at the hospital actually spend with their patients.

Surveys could ask patients research questions about how long their visits with a doctor lasted and how long they spent waiting to be seen. The surveys could also ask patients to rank their overall satisfaction with the care they received on a rating scale from one to 10. The surveys’ goal might be to discover if doctors are spending enough time with patients and how that correlates with the patients’ overall care. Using the data collected in the surveys, the hospital can estimate how much time each physician spends with patients. The hospital may also see a connection between higher patient satisfaction — such as patients giving scores of eight, nine or 10 — and increased patient-physician interaction or shorter wait times.

purpose of quantitative research marketing

Types of quantitative research methods and techniques

Quantitative research design describes how a researcher arranges a study in an attempt to control the variables. At one end of the spectrum is a method to observe and describe data rather than control or manipulate variables. At the opposite end are methods that aim to control variables and establish clear connections between them. The method you might use depends on your overall goals and what you hope to get from your research.

1. Descriptive research

Descriptive research describes situations, circumstances, or variables. The focus of descriptive statistics is the “what” instead of “why.” Usually, descriptive research involves a fair amount of observation. A researcher might ask children to describe how they spent their summer vacation or watch a teacher during a class to see how they explain concepts to students.

When using descriptive research, a scientist isn’t likely to start from a hypothesis. If they develop one at all, it will be after they have collected data. They can then use the data to test the hypothesis through synthesis and analysis. As they collect data, they need to be careful about the variables they measure and the items they study. Descriptive research typically doesn’t end with an explanation of the cause and effect between variables.

Some examples of descriptive research include:

  • A description of teenagers’ alcohol habits:  Researchers can issue surveys asking teens how much they drink, when they drink, and who they drink with. They can conduct the surveys over a period of years to see how teenage alcohol consumption changes with time.
  • A description of how people in assisted-living facilities spend their time:  Researchers can conduct surveys asking people who live or work at assisted-living facilities how much time they spend on certain activities. A researcher might also visit a facility to observe residents and workers, timing their activities.
  • A description of how the housing market in a particular city has changed over the years:  A researcher can collect data on housing prices, sales volume, and time-on-the-market to see how real estate in a city has changed over a defined period, such as the past 10 years. Since the researcher aims to describe the data, they aren’t looking for factors that could have affected homes’ prices, such as economic recessions or new amenities in the city.
  • A description of how opinions on a subject have changed over a period:  Researchers can describe how opinions on a subject, such as climate change or driving while intoxicated, have changed over time. They can collect data by conducting surveys that ask people to rank their feelings or beliefs on a subject on a scale from one to 10. They can follow up with the same people year after year to describe the evolution of opinions.

purpose of quantitative research marketing

2. Correlational research

The goal of correlational research is to examine and determine the relationship between multiple variables or data points. Like descriptive research, correlational research doesn’t attempt to identify a reason for the connection between variables or find a cause for the relationship. Instead, the intent is to discover patterns or trends between the variables by making comparisons. A researcher performing correlational research shouldn’t manipulate or adjust the data.

Examples of correlational research include:

  • An examination of the relationship between depression and diet:  A researcher might ask people to rate their depression on a scale from one to 10 and provide details about what types of food they eat and how much of each food. For example, a researcher might notice a correlation between eating less than one serving of vegetables or fruit each day and more severe depression. They might notice that people who rate their depression as a one or two tend to eat multiple servings of sweets during the day.
  • An examination of the relationship between SAT scores and grades during the first year of college:  A researcher might be curious to see if there is a connection between standardized test scores and grades once a student is in college. They might look at the grades of first-year college students who received scores of 2200 or higher on the SATs to see if there is a relationship.
  • An examination of people’s lifestyle habits and the prevalence of certain diseases:  Researchers can ask people about their lifestyle habits, such as how much alcohol they drink daily or weekly or how many cigarettes they smoke, to see if there is a connection between habits and the prevalence of diseases. People who smoke more might have higher lung cancer rates or more respiratory issues than people who don’t smoke.
  • An examination of types of classroom exercises and the grades students receive:  A researcher might be interested in discovering if there is a connection between the types of exercises a teacher leads in a classroom setting and the grades students earn on tests. The research might measure how much time students spend listening to lectures, performing group work, or working individually, then compare that information to the grades students receive.

purpose of quantitative research marketing

3. Causal-comparative research

Causal-comparative research is also called quasi-experimental research. It has aspects in common with experimentation but can’t be considered a true experiment. The goal of causal-comparative research is to create a cause-and-effect relationship among multiple variables. What sets this type of research apart from true experimentation is that the researchers cannot manipulate the independent variable. Researchers also need to use naturally occurring or pre-existing groups as part of the study and randomly assign individuals to particular groups. Unlike a true experiment, there is no control group during quasi-experimental research.

Examples of quasi-experimental research include:

  • Examining the effect taking vitamins has on children’s school attendance:  A researcher might examine the attendance record of a group of elementary school students who take a multi-vitamin each day to see if the students taking the vitamin are more likely to go to school regularly compared to a group of students who don’t take the vitamin.
  • Examining the connection between gender and scores on math tests:  A researcher might ask students in the same grade to take a math test, then examine the scores the students received to see if one gender scored higher than the other overall.
  • Examining the effect exercise habits have on heart health:  A researcher compares blood pressure levels, cholesterol levels, and resting heart rates of people who exercise daily and people who don’t exercise to see if there is a connection between exercise and heart health.
  • Examining the effect going to preschool has on high school graduation rates:  A researcher might look at preschool attendance rates and compare them to graduation rates later on to see if students who started their education earlier were more likely to finish high school.

One thing to keep in mind with quasi-experimental research is that many other variables, not just the ones studied, can impact the results. Students who take multivitamins might also have other things going on in their lives that cause them to go to school more often, for example. People who exercise and have lower cholesterol and blood pressure levels might have other factors, such as a healthier diet or family history, that make them more likely to have better heart health.

purpose of quantitative research marketing

4. Experimental research

An experimental research approach relies on the scientific method to manipulate and control variables to determine the cause-and-effect relationship. Experiments can take place in lab settings, but researchers can also conduct them in workshops or classrooms. To be considered a true experiment, research needs to have a control group and control over all possible variables except the independent variable, which the researchers manipulate. Participants in the experiment are assigned to a random group rather than self-selected, as they usually are in a quasi-experimental research method.

Examples of experimental research include:

  • Examining the effect of a new medication on chronic illness:  Researchers divide patients with the same illness into three groups. One group receives no treatment, one receives a placebo, and the third receives a new medication. At the end of the experiment, the researchers assess the patients to determine if the new medication was more effective than a placebo or no treatment at all.
  • Examining the effect of personalized instruction on students’ grades:  Researchers divide a class of students into two. Both groups receive in-class instruction. One group also gets an hour of one-on-one tutoring three times a week. At the end of the trial, the students take a test. The researchers examine the students’ grades to see if those who received tutoring performed better than those who didn’t.
  • Examining the effect of race or gender on crime:  Researchers hire actors to pretend to commit a crime in broad daylight, such as stealing a bike or breaking into a car. The experiment’s goal is to determine if bystanders react differently based on the gender or race of the actor.

purpose of quantitative research marketing

Data collection methodologies

Data collection is a critical part of any research study. When you perform quantitative research, you use one or more methods to gather your data.

1. Surveys or questionnaires

A survey or questionnaire asks participants questions to help researchers collect the data they need. Survey questions can be open-ended, such as, “How do you feel after drinking a cup of coffee?” or closed, such as, “How many cups of coffee do you drink daily?: 0-1, 2-3, 4 or more.” Quantitative research surveys usually use closed questions that provide a numerical value as an answer.

Your sampling methods, or how you choose the  people you will survey , are a key part of data collection. You might want to collect surveys from people who fit a certain demographic description or a wider subset of the population. How frequently you collect survey information is also essential. Two general methods of conducting surveys exist:

  • Cross-sectional surveys  gather data from multiple demographic groups at the same point in time. The method lets you compare answers across demographics and also lets you track multiple variables.
  • Longitudinal surveys  gather data from one demographic group at multiple periods. A longitudinal survey might follow up with participants one month later, one year later, and five years later. This type of survey aims to see how habits can change over time or what impact habits have on a particular group of people over the course of months or years.

2. Interviews

Interviews are similar to questionnaires. Instead of having a participant fill out a paper or digital form, the researcher asks the questions while sitting face-to-face with the participant or while they are on the phone. Interviews can be structured, meaning the researcher asks the same questions, in the same order, to everyone who participates. During an unstructured interview, the researcher might ask questions as they think of them or questions in response to what the participant says.

3. Observation

Observation involves watching people and taking note of their behaviors and habits. It’s commonly used to collect qualitative data but can be used to collect quantitative data. For example, a researcher might observe employees leaving work for the day and count those who leave right at 5 p.m., those who leave a bit early and those who stay late. The researcher might observe employees for several days to see if there are patterns or changes when people leave work.

purpose of quantitative research marketing

Advantages of quantitative research

Quantitative research has many advantages for researchers and companies that need to get information on their customers. Some of the benefits of quantitative research include:

  • Reliability:  Quantitative research is objective, meaning the variables and data you collect are reliable and accurate. When you ask someone how many cups of coffee they drink every day, you get a direct, objective answer.
  • Reproducibility:  Since you are collecting numerical or computational data when you perform quantitative research, it’s easy to reproduce the surveys or interviews when needed. Replication is a key component of a quantitative approach.
  • Impartiality:  Numbers and statistics don’t have a bias. There’s no way for a research team to influence the results or otherwise make the results biased when using a quantitative approach.
  • Scalability:  You can scale quantitative research up or down as needed without affecting the quality of the surveys or the data’s validity.

purpose of quantitative research marketing

Disadvantages of quantitative research

Quantitative research might not be the best option in all cases. Some possible drawbacks of the method include:

  • Might not tell the whole story:  The variables you collect through quantitative methods can be superficial or limited. For example, asking people how much coffee they drink doesn’t tell you very much. It can also be the case that other factors you are surveying affect the responses people give.
  • Sample sizes can be small:  Small sample sizes can limit the impact research has. Asking 10 people about their coffee drinking habits won’t give you a good idea of how coffee consumption plays out across the country, for example.
  • Data can be over-manipulated:  It’s possible for the setting of a research study to be manipulated and controlled to such an extent that it affects the accuracy of the results or for a range of other, unaccounted-for variables to affect the study.

Although there can be drawbacks to quantitative research, a well-designed study will account for those drawbacks and seek to eliminate them. For example, ensuring a large sample size and setting representational population parameters can help increase the accuracy of the results.

Secondary quantitative research methods

Secondary data is data someone else has already collected. Secondary research is sometimes called desk research since it involves collecting, summarizing, synthesizing and analyzing existing data rather than collecting data, often to strengthen the results from primary research. Secondary data is available from various sources, including:

  • Universities and colleges
  • Public and private libraries
  • Government institutions
  • Non-government organizations
  • Commercial information sources

What’s the difference between quantitative and qualitative research?

Quantitative research and qualitative research are often compared. While quantitative research focuses on objectivity and numerical values, qualitative research is subjective and values descriptions of feelings or situations. Quantitative research focuses more on establishing measurable (quantifiable) data, while qualitative research is more interpretive and focused on qualities or characteristics.

Some of the data collection methods used during qualitative research are the same as those used during quantitative research, but the end goal is different. A qualitative research study might involve observation and surveys. The survey questions will generally be open-ended. Observation will be to see and describe how people approach situations, rather than counting how frequently they do something.

Another way to look at the difference between quantitative and qualitative research is that one often informs the other — in fact,  they can be used together . Businesses typically perform qualitative research when they want to create a hypothesis. Asking people their opinions on a subject can help a business learn more about its customers’ concerns or the opportunities available to it. The company uses the information gathered to form a hypothesis, which it then tests using quantitative research.

purpose of quantitative research marketing

Learn More About Cint’s Quantitative Research Tools

Quantitative research can help you learn more about your company’s customers, potential customers, and the overall market. Cint connects brands and businesses to the right audience for quantitative research surveys. To learn more about our platform and what we do to ensure the data we collect is high-quality and accurate, contact us today.

purpose of quantitative research marketing

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Quantitative and Qualitative Research

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What is Quantitative Research?

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Quantitative methodology is the dominant research framework in the social sciences. It refers to a set of strategies, techniques and assumptions used to study psychological, social and economic processes through the exploration of numeric patterns . Quantitative research gathers a range of numeric data. Some of the numeric data is intrinsically quantitative (e.g. personal income), while in other cases the numeric structure is  imposed (e.g. ‘On a scale from 1 to 10, how depressed did you feel last week?’). The collection of quantitative information allows researchers to conduct simple to extremely sophisticated statistical analyses that aggregate the data (e.g. averages, percentages), show relationships among the data (e.g. ‘Students with lower grade point averages tend to score lower on a depression scale’) or compare across aggregated data (e.g. the USA has a higher gross domestic product than Spain). Quantitative research includes methodologies such as questionnaires, structured observations or experiments and stands in contrast to qualitative research. Qualitative research involves the collection and analysis of narratives and/or open-ended observations through methodologies such as interviews, focus groups or ethnographies.

Coghlan, D., Brydon-Miller, M. (2014).  The SAGE encyclopedia of action research  (Vols. 1-2). London, : SAGE Publications Ltd doi: 10.4135/9781446294406

What is the purpose of quantitative research?

The purpose of quantitative research is to generate knowledge and create understanding about the social world. Quantitative research is used by social scientists, including communication researchers, to observe phenomena or occurrences affecting individuals. Social scientists are concerned with the study of people. Quantitative research is a way to learn about a particular group of people, known as a sample population. Using scientific inquiry, quantitative research relies on data that are observed or measured to examine questions about the sample population.

Allen, M. (2017).  The SAGE encyclopedia of communication research methods  (Vols. 1-4). Thousand Oaks, CA: SAGE Publications, Inc doi: 10.4135/9781483381411

How do I know if the study is a quantitative design?  What type of quantitative study is it?

Quantitative Research Designs: Descriptive non-experimental, Quasi-experimental or Experimental?

Studies do not always explicitly state what kind of research design is being used.  You will need to know how to decipher which design type is used.  The following video will help you determine the quantitative design type.

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A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.


Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.


A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12


Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10


Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1


Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.


To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

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Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

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  • EXAMPLE 1. Descriptive research question (quantitative research)
  • - Presents research variables to be assessed (distinct phenotypes and subphenotypes)
  • “BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
  • RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
  • EXAMPLE 2. Relationship research question (quantitative research)
  • - Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
  • “Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
  • Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
  • EXAMPLE 3. Comparative research question (quantitative research)
  • - Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
  • “BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
  • RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
  • STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
  • EXAMPLE 4. Exploratory research question (qualitative research)
  • - Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
  • “Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
  • EXAMPLE 5. Relationship research question (quantitative research)
  • - Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
  • “Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23


  • EXAMPLE 1. Working hypothesis (quantitative research)
  • - A hypothesis that is initially accepted for further research to produce a feasible theory
  • “As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
  • “In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
  • EXAMPLE 2. Exploratory hypothesis (qualitative research)
  • - Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
  • “We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
  • “Conclusion
  • Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
  • EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
  • “We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
  • Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
  • EXAMPLE 4. Statistical hypothesis (quantitative research)
  • - An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
  • “Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
  • “Statistical Analysis
  • ( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27


  • EXAMPLE 1. Background, hypotheses, and aims are provided
  • “Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
  • “ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
  • “This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
  • EXAMPLE 2. Background, hypotheses, and aims are provided
  • “We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
  • “ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
  • EXAMPLE 3. Background, aim, and hypothesis are provided
  • “In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
  • “This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
  • “ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

  • Conceptualization: Barroga E, Matanguihan GJ.
  • Methodology: Barroga E, Matanguihan GJ.
  • Writing - original draft: Barroga E, Matanguihan GJ.
  • Writing - review & editing: Barroga E, Matanguihan GJ.


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