quantitative research methods marketing

"For example, we did a large voluntary survey of email subscribers and top readers a few years back."

While these readers gave us a long list of topics, formats, or content types they wanted to see, they sometimes engaged more with content types they didn’t select or favor as much on the surveys when we ran follow-up ‘in the wild’ tests, like A/B testing.”  

Pepsi saw similar results when it ran its iconic field experiment, “The Pepsi Challenge” for the first time in 1975.

The beverage brand set up tables at malls, beaches, and other public locations and ran a blindfolded taste test. Shoppers were given two cups of soda, one containing Pepsi, the other Coca-Cola (Pepsi’s biggest competitor). They were then asked to taste both and report which they preferred.

People overwhelmingly preferred Pepsi, and the brand has repeated the experiment multiple times over the years to the same results.

What I like: It yields qualitative and quantitative data and can make for engaging marketing content, especially in the digital age.

What I dislike: It can be very time-consuming. And, if you’re not careful, there is a high risk for scientific error.

Best for: Product testing and competitive analysis

Pro tip:  " Don’t make critical business decisions off of just one data set," advises Pamela Bump. "Use the survey, competitive intelligence, external data, or even a focus group to give you one layer of ideas or a short-list for improvements or solutions to test. Then gather your own fresh data to test in an experiment or trial and better refine your data-backed strategy."

Secondary Research

8. public domain or third-party research.

While original data is always a plus, there are plenty of external resources you can access online and even at a library when you’re limited on time or resources.

Some reputable resources you can use include:

• Pew Research Center
• McKinley Global Institute
• Relevant Global or Government Organizations (i.e United Nations or NASA)

It’s also smart to turn to reputable organizations that are specific to your industry or field. For instance, if you’re a gardening or landscaping company, you may want to pull statistics from the Environmental Protection Agency (EPA).

If you’re a digital marketing agency, you could look to Google Research or HubSpot Research . (Hey, I know them!)

What I like: You can save time on gathering data and spend more time on analyzing. You can also rest assured the data is from a source you trust.

What I dislike: You may not find data specific to your needs.

Best for: Companies under a time or resource crunch, adding factual support to content

Pro tip: Fellow HubSpotter Iskiev suggests using third-party data to inspire your original research. “Sometimes, I use public third-party data for ideas and inspiration. Once I have written my survey and gotten all my ideas out, I read similar reports from other sources and usually end up with useful additions for my own research.”

9. Buy Research

If the data you need isn’t available publicly and you can’t do your own market research, you can also buy some. There are many reputable analytics companies that offer subscriptions to access their data. Statista is one of my favorites, but there’s also Euromonitor , Mintel , and BCC Research .

What I like: Same as public domain research

What I dislike: You may not find data specific to your needs. It also adds to your expenses.

Best for: Companies under a time or resource crunch or adding factual support to content

Which marketing research method should you use?

You’re not going to like my answer, but “it depends.” The best marketing research method for you will depend on your objective and data needs, but also your budget and timeline.

My advice? Aim for a mix of quantitative and qualitative data. If you can do your own original research, awesome. But if not, don’t beat yourself up. Lean into free or low-cost tools . You could do primary research for qualitative data, then tap public sources for quantitative data. Or perhaps the reverse is best for you.

Whatever your marketing research method mix, take the time to think it through and ensure you’re left with information that will truly help you achieve your goals.

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Qualitative and Quantitative Marketing Research Methods

Some researchers take a hard approach to data, either falling squarely on the side of the numbers (quantitative data) or on the other side, one of focus groups and individual consumer feedback (qualitative data).

But the richest insights come from a paired approach to research, one that seeks both statistically significant findings to define our product’s place in the market as well as a deep understanding of how our product fits into a single consumer’s life.

Why do you need either of these types of research? Learning about your customers means that you can more efficiently answer their needs. A crystal-clear picture of who your consumer is and why they need your product allows you to not only refine your product but ideate even better solutions to your consumers’ problems.

Quantitative Methods

What Is Quantitative Research?

The most common quantitative research methods are customer surveys and questionnaires. If you have questions that drill down into specifics about your company, your market, or your target customer population, you’re looking for quantitative research. It answers questions like who, when, where, how many, how frequently? These are not general, exploratory questions; they’re questions looking for transactional, numerical data.

Why Do You Need Quantitative Research?

It will tell you:

• Whether customers are looking for or need a product like yours
• Who your target population should be and what convinces them to buy
• What, if anything, your target population knows about your market or your product
• If your target market’s attitude or perception is changing, which can give insights into how you should respond

How Do You Conduct Quantitative Research?

While the big two methods of gathering data are surveys and questionnaires, there are plenty of ways to conduct these methods.

When you only need a few questions answered and can’t justify the cost of rolling out a full-scale survey, an omnibus is a good solution. This style groups questions from multiple businesses into one survey so that the time and effort spent recruiting and compensating participants can be spread across several companies who have only a few questions.

Email or Snail Mail Surveys

Digital or printed surveys are the most common for a reason: They are extremely cost-effective because they are automated. Results roll in without needing a person to make a phone call or interact with every individual respondent. These are most effective when the questions are straightforward, like choosing A vs. B. They’re not so effective in nuanced preference questions, like describing how A vs B makes a participant feel.

Telephone Surveys

The human interaction of phone surveys can make a participant feel more engaged than a digital or printed survey, leading them to give more considered answers – this creates better data. Telephone surveys also allow the researcher to understand a participant’s answer more clearly based on their voice and tone. The statistical reliability of a survey over an interview also remains intact because the questions are consistent across participants. Telephone surveys are best:

• If the survey questions end with a “Why?” or “Can you explain?”
• If the survey questions are longer or slightly complicated and require better participant concentration than normal
• If you are pilot (or metric) testing your online survey questions before they are deployed widely online. “Why?” and “Can you explain?” phone questions can capture the most common answers, which can then be listed as checkbox options A, B, C, and D in the widely distributed online survey. This will discourage write-in answers, making your data easier to analyze.

Face-To-Face Surveys

A criticism of surveys, in general, is that they don’t allow for conversation or elaboration. While this is a benefit in keeping data consistent, it also leaves findings on the table that a researcher could have used to better understand the participant’s feedback. In face-to-face surveys, a researcher still can’t go off script, but they can make note of a scrunched nose when a product is mentioned or a disengaged stance. Face-to-face surveys are best when the survey questions delve into emotions. An example might be survey questions for emotionally charged products or campaigns , like Dove’s Campaign for Real Beauty. “How does marketing around women’s beauty products today make you feel?”

It’s easy for face-to-face surveys to become interviews, but keep in mind the difference is that surveys do not go off script. The survey researcher must stick to the order of the questions and the exact wording to keep statistical reliability, and in an interview, the researcher has control over the order, pacing, and structure of all questions.

Analyzing quantitative results is easier now with survey tools like SurveyMonkey, SurveyGizmo, and Qualtrics. But those tools won’t be able to remove outliers or include questions that will weed out people who didn’t understand the question and people who rushed through without reading. Those tools still require human manipulation to produce clean, statistically reliable data. This data can be analyzed through various different lenses, including segmentation and personas, to better understand the population who answered the survey and predict their behavior.

Quantitative findings can lead to the following findings and deliverables:

• Market segmentation
• Pricing projections
• Net promoter scores
• Customer satisfaction ratings
• Recommendations about a product launch, pricing, messaging
• Changes in sales efforts to increase customer satisfaction and target market segments

Qualitative Methods

What Is Qualitative Research?

Qualitative research is interested in finding the opinions, beliefs, and values of a target population. The most common forms of qualitative research are focus groups and interviews. While not usually statistically significant, qualitative research is valuable in putting a face to a number and answering questions like, “How?” “Why?” and “Would?” This style of research humanizes your consumer base, allowing more accurate predictions of customer behavior. Qualitative research can also identify problems and opportunities that a survey or questionnaire never would have identified. In qualitative research, we pose probing questions that aim to understand consumers as people. A few drawbacks of qualitative research are (A) results are always open to concern about researcher subjectivity, as results are not numerical and are based on conversations and (B) qualitative research can be time-consuming and expensive.

Why Do You Need Qualitative Research?

It will help you:

• Make human-centered decisions across the entire business, not just in the marketing department, leading to a better customer experience overall
• Understand context around quantitative data – like why bounce rates are so high off of one page on your site
• Predict how your product or service would fit in and impact the consumer’s life
• Understand the emotions your target population feels in relation to your product or market
• How do you conduct qualitative research?

Focus Groups

In focus groups, 6-10 people with something in common (like looking to buy a luxury car or having a baby) have a discussion moderated by a researcher. This style is best for exploring “what if”s, researching new concepts, and testing new product ideas. It helps let participants bounce ideas off of each other, spurring memories but also giving individuals time to think while others are talking. There’s less pressure on each participant to answer spontaneously, as in an interview. The drawback is that it’s very easy for a focus group to become derailed by one or two overpowering or disengaged participants.

Customer & Prospect Interviews

Interviews can come in many forms, but the base form is a one-on-one conversation. An interview is meant to find underlying beliefs from a key, representative consumer about some facet of your product or service. A skilled interviewer can recognize when a topic is unproductive versus when a tangent is worthwhile to understand the participant’s perspective.

Contextual Inquiry

In a contextual inquiry, a researcher trails the participant in the participant’s normal activities. Contextual inquiries happen “in the wild.” For example, a lunchbox company might observe a customer all day, from packing lunch in the morning to bringing home the empty box at night, to understand the lunchbox’s deficits, what products the participant uses in conjunction with the lunchbox (like Tupperware, silverware, etc), and ask questions.

One of the best ways to fully understand your audience and what’s important to them is through social listening. A social listening tool allows you to monitor and analyze online posts and comments based on an established keyword criterion. By doing this, a brand can analyze the demographics or their online audience, their purchase intent, what they see as the key product attributes, their feelings on your brand versus the competition, as well as category-level conversations.

An article in Harvard Business Review tells this useful story that came out of social listening “A large pharmaceutical company, for example, learned about an unsuspected customer challenge through a single photo on Flickr. The image showed a man wrapping a part of his leg in foil after applying a pain relief ointment. It turned out that the medication left untreatable stains on certain fabrics, hence the protective foil. Executives had been unaware of the problem despite years of conventional consumer research.”

Customer Experience Research

Interviews are common in customer experience research, from usability studies (analyzing how easy it is to use a product, usually a website) to customer journey research (asking a customer to describe their entire relationship with a product, from learning about it to purchase), and more. The basic idea always comes down to asking a consumer about their relationship with a company’s product or service, though.

Qualitative and Quantitative Research Working Together

Qualitative and quantitative research are not at odds; in fact, they inform and enrich one another. One doesn’t come before the other, either. Personal, individualized insights of qualitative research can help us understand the questions we should be asking of our mass market in quantitative research, but wider quantitative research can also help us understand where we need to drill down and ask more questions from just a few consumers. Actually, the best research comes from a cyclical application of both techniques, allowing us to regularly turn from a wide-lens view of our product and its value to a mass market, to a more narrowed scope, focusing on understanding the unique perspectives of just a few people who we impact.

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Home • Knowledge hub • Choosing the Right Approach: Qualitative vs. Quantitative Market Research.

Choosing the Right Approach: Qualitative vs. Quantitative Market Research.

Imagine this scenario: you’re the Product Marketing Manager at Stellar Sneakers, a thriving company known for its innovative and stylish footwear. Your team is poised to launch a new line of eco-friendly shoes, but before you do, you want to gather valuable insights to ensure the product’s success. There’s a budget set aside for market research, but you’re faced with a crucial decision: should you go for a qualitative approach, diving into the deep and nuanced attitudes of your target audience? Or should you lean on quantitative research , capturing broad trends and measurable consumer preferences?

These choices are commonplace for marketing professionals. Market research is instrumental in developing successful products and campaigns, helping you understand your target audience, gauge customer preferences, and assess market trends. However, deciding between qualitative and quantitative methodologies can often seem like a labyrinth.

In this article, we will navigate this maze together. We’ll delve into the strengths and weaknesses of both qualitative and quantitative research, providing a practical guide for marketing executives like yourself wrestling with this choice. Our goal is to equip you with a more profound understanding, enabling you to select the most effective research methodology for your marketing objectives. 

Understanding Qualitative Research

Qualitative research can be likened to a deep, exploratory dive. Instead of skimming the ocean’s surface to understand what lies beneath, qualitative research immerses itself in the depths to explore the unseen. In other words, it involves gathering subjective, non-numerical data to uncover your target audience’s thoughts, feelings, and motivations.

Imagine conducting in-depth interviews or focus groups with your prospective customers. You might ask them open-ended questions like, “How important is sustainability in your footwear choices?” or “What would make you choose our new eco-friendly shoes over traditional options?” Such questions do not restrict respondents to choosing from pre-determined answers; instead, they allow them to express their unique thoughts and emotions.

Similarly, other qualitative methods, like observations or ethnography, enable researchers to study people in their natural settings. For instance, observing customers in a retail store can offer valuable insights into shopping habits and behaviors that would be difficult to capture through structured surveys.

In a nutshell, qualitative research is all about understanding the “why” behind consumer behavior. It delves into the intricacies of consumer attitudes, beliefs, and experiences, providing a rich, nuanced understanding of your target audience. But like all methodologies, qualitative research has its strengths and drawbacks.

Pros of Qualitative Research

Now that we understand what qualitative research entails let’s dive into its advantages. For you, as the Product Marketing Manager of Stellar Sneakers, these pros can guide your understanding of what consumers feel and why they behave the way they do.

In-depth Understanding: The primary strength of qualitative research lies in its depth of understanding. By allowing consumers to express their thoughts and feelings in their own words, you can gain a holistic and nuanced understanding of their attitudes, beliefs, and experiences. You might discover, for example, that your target audience highly values sustainable practices not just because of environmental concerns but due to an underlying desire to contribute positively to society. This insight goes beyond basic preferences and can help guide your product development and marketing strategies.

Flexibility: Qualitative research is adaptable, allowing exploring unexpected avenues that emerge during the research process. Let’s say during your focus group discussions, a participant brings up an unanticipated point about the aesthetics of eco-friendly shoes. This can lead the conversation down a new path, offering insights you hadn’t considered initially. This adaptability makes qualitative research a powerful tool for discovery.

Contextual Understanding: This research method provides context to your findings. Instead of just knowing that a certain percentage of your audience prefers eco-friendly shoes, you get to understand why they prefer them. Are they driven by concerns about climate change, peer influence, or simply a desire for unique, innovative products? This contextual understanding can help you craft more effective marketing messages.

Cons of Qualitative Research

While the strengths of qualitative research are many, it has limitations. Understanding these drawbacks is crucial for a balanced approach to your market research.

Limited Generalizability: Qualitative research typically involves smaller, more targeted sample sizes due to the time and resources required for in-depth interviews, focus groups, or observations. This means that while the insights you gather will be rich and detailed, they may not represent the views and experiences of your entire target population. For instance, the customers who participate in your focus groups might have particularly strong feelings about sustainability, which might not be as prevalent in the broader customer base.

Subjectivity: Unlike its quantitative counterpart, qualitative research relies heavily on interpretation and analysis. The findings are often expressed in words and narratives, making them susceptible to researcher bias. For example, two researchers might interpret a participant’s responses in a focus group differently, leading to different conclusions. Therefore, ensuring rigor and objectivity during the analysis phase is critical.

Time and Resource-Intensive: Conducting and analyzing qualitative research can be quite labor-intensive. Transcribing interviews, analyzing focus group discussions, and reviewing observational data require skilled moderators, transcription services, and a significant amount of time. Additionally, the need for specially trained researchers to conduct interviews or focus groups can add to the cost of the research.

These cons do not diminish the value of qualitative research; instead, they highlight the need for careful planning and thoughtful interpretation of the data gathered. By understanding this approach’s strengths and limitations, you can maximize its benefits and make informed decisions. 

Understanding Quantitative Research

As we leave the deep-diving world of qualitative research, we surface to the realm of quantitative research, where the breadth of understanding is the key. Think of it as casting a wide net into the sea, gathering as many fish (or, in our case, data points) as possible to analyze and identify patterns or trends.

In contrast to qualitative research, quantitative research involves gathering measurable, numerical data. This can be accomplished through various methods, such as online surveys , questionnaires, or structured observations. The questions in this type of research are often closed-ended, offering a set of predefined responses for the participants to choose from. For instance, you might ask your customers to rate on a scale of 1-5 how likely they are to buy your new eco-friendly shoes or to select from a list of options their primary reason for purchasing such shoes.

The essence of quantitative research is the ability to quantify consumer behavior and attitudes. Rather than focusing on individual narratives, it provides a statistical representation of a large group’s feelings or behaviors. For instance, it might tell you that 65% of your target market is willing to pay a premium for eco-friendly footwear.

Quantitative research, like its qualitative counterpart, has a unique set of pros and cons, which can significantly impact your research results and, consequently, your business decisions. 

Pros of Quantitative Research

Quantitative research provides a measurable, objective lens to view your market. Here are some of the key advantages it offers:

Generalizability: With its focus on large sample sizes, quantitative research enables you to gather data statistically representative of your target population. For instance, if your survey reveals that a significant percentage of respondents are willing to pay more for eco-friendly shoes, you can confidently infer this trend extends to your broader target market.

Measurable and Objective: Quantitative data can be precisely measured and easily analyzed using statistical methods. The responses you gather can be quantified, compared, and tracked over time, offering you valuable insights. For example, you can measure changes in consumer attitudes toward eco-friendly products over several years.

Efficiency: Given that quantitative research often employs online or paper surveys, you can collect data from a large number of respondents simultaneously. This method can be cost-effective and time-efficient, especially when compared to conducting numerous in-depth interviews or focus groups.

Cons of Quantitative Research

Despite the significant advantages of quantitative research, it’s essential to be mindful of its limitations to ensure a balanced approach to your market research.

Lack of Depth: While quantitative research excels in measuring and quantifying consumer behaviors and attitudes, it often doesn’t capture the nuances and underlying reasons for those behaviors. For example, although you might know from a survey that a substantial percentage of your target market prefers eco-friendly shoes, you won’t necessarily understand the specific motivations, emotions, or experiences behind this preference.

Limited Context: Quantitative research provides statistical data but often lacks the rich, detailed context of qualitative research. It tells you “what” the trends are but often falls short of explaining “why” those trends exist. For instance, your survey might reveal that younger customers are more likely to buy eco-friendly shoes, but without further qualitative investigation, the reasons for this demographic preference may remain unclear.

Potential for Survey Bias: The design of your quantitative surveys can significantly influence the accuracy of your results. Poorly constructed questions, leading prompts, or a lack of diverse response options can introduce bias, resulting in skewed data. For example, if your survey questions are biased towards positive responses about eco-friendly products, you may end up with an inflated perception of your target market’s interest in such products.

By recognizing these limitations, you can take steps to mitigate them, such as supplementing your quantitative data with qualitative insights or ensuring your survey design is as unbiased and inclusive as possible. 

Choosing the Right Approach

At this point, you might wonder: Should I dive deep with qualitative research or cast a wide net with quantitative research? The truth is, there’s no one-size-fits-all answer. The most effective approach depends on several factors, including your research objectives, the representativeness and size of your sample, and the resources available to you.

Research Objectives: Your first consideration should be the purpose of your research. If you are at an exploratory stage, wanting to understand your target audience’s nuanced perspectives and motivations, qualitative research could be your best bet. On the other hand, quantitative research might be the way to go if you’re looking to test a hypothesis, measure the impact of a previous campaign, or collect data on a large scale.

Sample Size and Representativeness: If generalizability is a priority, and you want your research findings to represent your entire target market, then quantitative research, with its larger sample sizes, is generally more suitable. However, if your focus is on a smaller, more targeted group, qualitative research can offer the in-depth insights you need.

Time and Resource Constraints: Budget, time, and human resources are practical considerations that can impact your research choice. If you’re working within a tight budget or timeframe or have limited access to skilled qualitative researchers, a quantitative approach may be more efficient. Conversely, if you have the resources to conduct thorough interviews, focus groups, or ethnographic studies, qualitative research can yield rich, nuanced data.

Complementary Research: Remember that qualitative and quantitative research aren’t mutually exclusive. They can be effectively combined to offer a comprehensive view of your market. For instance, you could start with a qualitative study to explore consumer attitudes and behaviors and then design a quantitative survey based on those insights to gather data from a larger sample size. Alternatively, you might supplement quantitative data with qualitative research to add depth and context to your findings.

The right research methodology can make a significant difference in your understanding of your market and, consequently, the success of your marketing efforts. By carefully considering the above factors, you can select the most effective approach for your specific needs.

Navigating the world of market research and making these decisions can seem daunting. That’s where expert help can make a real difference. Consider partnering with a seasoned market research agency like Kadence International. With a wealth of experience across various industries and markets, we at Kadence can guide you in selecting the best research methodology tailored to your unique needs, ensuring you gain the insights needed to propel your business forward.

Ready to unlock the power of market research? Reach out to us, and let us guide you toward a better understanding your market and achieving business success.

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What is quantitative research?

Last updated

20 February 2023

Reviewed by

Quantitative methods and data are used by some business owners, for example, to evaluate their business, diagnose issues, and identify opportunities.

Quantitative research is used throughout the natural and social sciences, including economics, sociology, chemistry, biology, psychology, and marketing. 

Researchers use quantitative research to get objective, robust, and representative answers from individuals. Researchers gather quantitative data from sample groups of people and generalize it to a larger population. This is to, in some instances, explain a given phenomenon and answer questions about the population, such as product preferences, political persuasion, or demography.

For example, a hotel owner in the US can conduct quantitative research, perhaps via a questionnaire, on a small sample of their customers to understand their opinions about their products and services. The analyzed quantitative data from this questionnaire can be generalized to the larger population of their customers. The hotel can use these opinions to maintain or improve its service provision.

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• Quantitative research methods

Researchers employ various quantitative research methods to determine certain phenomena.

Observation

This method involves gathering information by simply observing behaviors or counting subjects relevant to a study. For example, a researcher could sit in a classroom and observe students when a teacher is teaching, recording those who are and are not paying attention.

Survey is one of the most popular and well-known quantitative methods. It involves asking individuals questions either physically or, most typically nowadays, online. These questions are usually in the form of a questionnaire that individuals can respond to, using a mix of single, multichoice, ranking, rating, and occasionally open-ended questions .

For example, a researcher could administer a questionnaire to first-year international college students about their college experiences using various question formats.

Experimental

This scientific approach is conducted with two sets of data, i.e., independent and dependent variables . Usually, researchers approach experimental studies with specific hypotheses to test. They may use two groups of participants: one who would receive the “treatment” and one who would not.

For example, a researcher might wish to test a short-term mindfulness treatment for individuals with depression. In this case, the independent or manipulated variable would be the mindfulness treatment group. One group would receive the mindfulness treatment, and another would not. In this case, the “experiment” would be to see if the individuals who received the mindfulness treatment experienced fewer depressive symptoms than those who did not.

• What is quantitative analysis?

Quantitative analysis is a process that involves manipulating and evaluating collected, measurable data. The goal is to understand the behavior of a given phenomenon and answer a research question (and, in a scientific setting, prove or disprove a hypothesis).

A business owner, for example, may analyze quantitative sales data and consumer quantitative data using a questionnaire. By doing this, the owner can figure out if their business is doing well or if they need to make changes to improve.

If you are a business owner, you could consider quantitative analysis to better understand your business's past, present, and potential future.

• What do quantitative analysts do?

A quantitative analyst is an expert in designing, developing, and implementing algorithms to answer research questions. They use quantitative research methods to help companies make appropriate business and financial decisions.

The primary responsibility of a quantitative analyst is to apply quantitative methods to identify opportunities and evaluate risks.

Quantitative analysts are important to staff in any business because:

They manage portfolio risks

They test a new trading strategy

They program and implement a new trading strategy

They improve signals used to evaluate trade ideas

• Understanding quantitative analysis

Analysts use quantitative analysis to analyze a business's past, present, and future. You can also use quantitative analysis to determine the progress of your business.

State governments also use quantitative analysis to make monetary and other economic policy decisions. It is used in the financial services industry to analyze investment opportunities. For example, a business owner can use quantitative analysis to determine when to sell or purchase securities based on macroeconomic conditions.

Quantitative analysis versus qualitative analysis

If you are pursuing a career in research or business analysis, it is essential to understand the two concepts—quantitative and qualitative analysis.

Quantitative analysis, at a very basic level, relies on using numbers and discrete values collected from the research. In contrast, qualitative analysis relies on content (e.g., language or text data) that either can’t be expressed in numbers or doesn’t have sufficient scale to be counted or coded.

A business owner wanting to better understand their business might use a representative quantitative sample of customers to generate insight by completing a questionnaire. A website owner could analyze quantitative metrics associated with their website to understand which aspects of the site are working well and which elements need to be optimized. These include the length of visit, number of links clicked, and areas of the site visited.

Various measures could be correlated by sales (or other outcomes) to determine the UX and marketing strategy linked to the site.

Businesses might use qualitative analysis to get a greater depth of understanding or look at the ‘why’ behind the ‘what.’ For example, they might ask customers, who gave a low quantitative score for a provided product, why they gave that rating and how they might improve the said product.

• Advantages of quantitative research

Quantitative research, done right, can help drive a business's success and generate a general understanding of key business metrics and customer behavior, wants, and needs. Quantitative research should be considered for the following reasons: 

It is efficient and fast

An experienced quantitative researcher can complete the reporting and analysis phase efficiently and quickly with a defined reporting structure and outputs while taking some time to define and structure questions (versus unstructured qualitative data ).

It is objective and requires limited interpretation

Quantitative research relies on standardized statistical processes and rules to answer research questions. If performed correctly, data generated from small sample groups can be extrapolated to represent the views of larger populations.

It is focused

Owing to its structure, the goals of quantitative research are determined at the beginning of the study, forcing researchers to clearly understand and define the objectives of their studies.

• Disadvantages of quantitative research

It’s only appropriate in certain cases

This method is only relevant when data can be captured and reflected in numbers. It cannot be used in situations where data is non-numerical, e.g., long-form verbal or textual responses that are not easily coded down into numerical responses.

It’s challenging to analyze the data collected

When quantitative research is collected, it can be difficult to make sense of the numbers without knowing statistical methods. Knowledge of research methods and data analytic techniques is essential for drawing conclusions about the study questions. These programs and methods take time to learn and can be time-consuming and complicated.

• What are the limitations of quantitative research?

Requires vast resources

This method requires a considerable investment of time, energy, and finance. One needs to prepare and structure questions, test their understanding and relevance, and determine how to distribute them to the respondents. Some respondents may expect payment or incentives to respond to the questions (this may be in the form of entry into a prize draw.)

Requires many respondents

Quantitative research generally requires access to (relative to other methods) large samples to ensure inferences made from the research are robust and reliable. Finding this audience, especially where the incidence is low can be both time-consuming and expensive.

Research is limited in its scope

What quantitative research can explore is limited due to the need to agree on the specific questions to be asked and analyzed versus qualitative research. The latter doesn’t define specific numbers and forms of questions in advance.

Why is it called quantitative research?

It is called quantitative research because it involves the use of ‘quantities’ of things—things that can be expressed in numbers or measured.

What does quantitative research answer?

Quantitative research answers questions measuring value or size, which can be expressed in numbers. It answers questions such as how many, how much, and how often.

For example, you can study the number of individuals who wish to study at American universities and their traits. Questions can include how many come from low, medium, or high socio-economic brackets, how many want to study law versus humanities, and what proportion feel excited versus anxious about the prospect of undertaking higher education.

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Research Methodologies

August 14, 2024

Qualitative vs. Quantitative Market Research: Why Not Both?

Discover the benefits of qualitative and quantitative methods. Learn how to leverage both approaches for insights into consumer behavior and industry trends.

by Ashley Shedlock

Content Coordinator at Greenbook

Market research is vital for understanding target markets, consumer behavior, and industry trends. Qualitative and quantitative methods offer distinct advantages. Qualitative research explores concepts, opinions, and motivations, uncovering rich insights into consumer preferences through techniques like interviews and focus groups.

Quantitative market research involves gathering numerical data through surveys and questionnaires for statistical analysis to identify trends in a target market. It offers measurable results from a large sample size for generalization and prediction. On the other hand, qualitative research explores subjective experiences and motivations, aiming to provide deeper insights into consumer behavior through non-statistical analysis.

Selecting the appropriate research approach is vital for successful studies. Qualitative dives into intricate matters, while quantitative gauges broader market trends. The choice between qualitative and quantitative methods depends on research objectives and results. Both offer valuable insights for strategic decisions in competitive markets. Knowing the distinctions between the methods aids in picking the optimal approach for meaningful data and a competitive advantage.

What is Qualitative Market Research?

Qualitative research methodologies, such as in-depth interviews and focus groups, play a crucial role in providing a deeper understanding of consumer behavior. These methodologies delve into the intricacies of individual attitudes and motivations, allowing researchers to uncover rich insights that quantitative data alone cannot reveal.

One of the key advantages of qualitative research lies in its ability to explore the underlying reasons behind consumer behaviors. By allowing researchers to engage directly with participants, qualitative methods offer a more holistic view of consumer attitudes, preferences, and decision-making processes. This approach can uncover nuanced insights that quantitative surveys may overlook.

However, it is important to acknowledge the limitations of qualitative research, particularly in its subjective nature. The reliance on human interpretation in qualitative analysis introduces the potential for biases to influence outcomes. Researchers must be vigilant in managing subjectivity and potential biases throughout the research process to ensure the credibility and reliability of their findings.

In real-world applications, qualitative research proves invaluable in various contexts, from product development to marketing strategies. By gaining a deep understanding of consumer perspectives and behaviors, businesses can tailor their offerings to meet customer needs more effectively. Qualitative research also plays a crucial role in shaping communication strategies and enhancing customer engagement by tapping into the emotional and psychological drivers behind consumer decisions.

While qualitative research may come with its challenges in terms of subjectivity and potential biases, its ability to provide rich, nuanced insights into consumer behavior makes it a valuable tool for any market researcher looking to gain a deeper understanding of their target audience.

Types of Qualitative Research 

When it comes to qualitative research, there are various types that provide unique insights into consumer behavior and preferences. 

Ethnographic Research: Involves immersing researchers in the environment or context of the subjects to observe their behaviors in real-life settings. This approach goes beyond simply asking questions, allowing researchers to uncover deeper insights into how consumers interact with products or services on a day-to-day basis.

In-depth Interviews: Enable researchers to explore participants' thoughts and motivations thoroughly by asking open-ended questions. Focus groups, another qualitative method, involve a small group discussing a topic, allowing researchers to observe group dynamics and shared perspectives.

Observational Research: the direct observation and recording of participant behavior in natural settings. This approach is particularly valuable for capturing nonverbal cues and subconscious behaviors that might not surface during standard interview formats. By focusing on body language, gestures, and interactions, researchers can gain profound insights into consumer preferences and the intricacies of decision-making processes.

Advantages of Qualitative Research

Qualitative research offers valuable insights into the emotional and psychological aspects of consumer decision-making, uncovering the reasons behind consumer behaviors.

Qualitative research offers flexibility and adaptability, allowing researchers to adjust approaches based on emerging insights. By directly engaging with participants, it uncovers hidden motivations and attitudes that may not be easily quantified, fostering a human connection for authentic data collection.

Qualitative data delves into intricate consumer emotions, brand perceptions, and societal influences on purchasing choices. It forms hypotheses tested later via quantitative research , enhancing insights into consumer behavior. Utilizing the qualitative aspect provides a profound grasp of intricacies determining consumer preferences and market trends.

What is Quantitative Market Research?

Quantitative methods play a vital role in market research by using surveys and questionnaires to gather structured data systematically. This approach provides measurable insights into consumer behavior, trends, and preferences, offering a comprehensive view of the market. A key benefit is the statistical analysis capability, allowing researchers to identify correlations and predictive patterns within large datasets. This analytical depth enables data-driven decision-making and strategic planning based on empirical evidence.

However, like any methodological approach, quantitative research does have its limitations. One notable constraint is the potential difficulty in capturing nuanced or complex phenomena that may be better understood through qualitative means. While quantitative research excels in quantifying data and providing statistical significance, it may sometimes overlook the underlying reasons or motivations driving consumer behavior. This limitation underscores the complementary role that qualitative research plays in offering deeper insights into the 'whys' behind the 'whats' uncovered through quantitative analysis.

Quantitative research is widely used in different industries for tasks like market segmentation , customer profiling, and product testing. It helps businesses evaluate market share, consumer preferences, and marketing campaign effectiveness with credibility and objectivity. Stakeholders can rely on the empirical evidence from quantitative research to make informed decisions for business growth and innovation.

Types of Quantitative Research

Quantitative research involves the collection and analysis of numerical data to understand patterns, correlations, and trends in a target audience or market. This method utilizes structured questionnaires, surveys, and experiments to gather information that can be statistically analyzed for meaningful insights. 

One common type of quantitative research is surveys, which provide a snapshot of the opinions, behaviors, and preferences of a large group of people. Another approach is experiments, where variables are manipulated to study cause-and-effect relationships within a controlled environment. These quantitative methods offer the advantage of producing numerical data that can be easily quantified and compared across different groups or time periods.

Advantages of Quantitative Research

Quantitative research offers a plethora of advantages that make it an indispensable tool in the realm of market analysis. 

Quantitative research excels in offering numerical data for statistical analysis, ensuring objective insights into market trends and consumer behavior through structured surveys and experiments.

Quantitative data is ideal for large sample sizes, providing generalizable insights applicable to broader populations. The scalability enhances reliability, revealing trends not obvious in smaller studies. In fast-paced markets, the quick data collection, analysis, and interpretation of quantitative research are advantageous for swift decision-making.

Quantitative research is crucial for marketers to measure variables and determine causal relationships, aiding in understanding consumer behavior and strategic decision-making. Techniques like regression analysis or correlation studies unveil hidden patterns, offering valuable market insights and ensuring businesses remain competitive.

Quantitative research not only provides analytical rigor and scalability but also allows for easy comparability and benchmarking. It quantifies data in numerical terms, facilitating comparisons of variables, tracking changes over time, and benchmarking against industry standards or competitors. This comparative nature empowers businesses to identify best practices, evaluate market positioning, and optimize strategies effectively.

Comparing Qualitative and Quantitative Approaches

Combining qualitative and quantitative research methods provides a comprehensive understanding of market dynamics. Triangulating data from both sources offers a well-rounded perspective. Qualitative methods like interviews reveal consumer motivations, while surveys give broader trends. Selecting between qualitative and quantitative research hinges on research objectives and the nature of questions. Qualitative research delves into complex phenomena, while quantitative uncovers patterns at scale. The choice depends on study goals and required information for decision-making.

Common misconceptions about qualitative research often revolve around its perceived subjectivity and lack of generalizability. However, when conducted rigorously, qualitative research can provide valuable insights into the underlying reasons behind consumer behaviors and preferences. On the other hand, quantitative research is sometimes criticized for being too rigid and detached from the human experience. In reality, quantitative methods can yield actionable data that reveal trends and correlations with a high degree of reliability.

Market research methodologies are evolving to prioritize a balance between qualitative depth and quantitative breadth. Combining qualitative richness with quantitative rigor provides a holistic view of consumer behavior, uncovering patterns and underlying motivations effectively. Emerging trends in market research incorporate advanced analytics such as predictive modeling and machine learning for faster, more precise decision-making. The future of market research lies in integrating qualitative and quantitative approaches, emphasizing innovation to navigate complexities and derive valuable strategic insights.

How to Choose the Right Method? Quantitative vs Qualitative Research 

When choosing between quantitative and qualitative market research, align the method with your research goals. Quantitative research gathers numerical data for statistical analysis, while qualitative research explores underlying reasons and opinions through interviews or observation.

The decision depends on research objectives. Quantitative research quantifies data for testing hypotheses and generalizing results, ideal for customer satisfaction or A/B testing . Conversely, qualitative research offers insights into behavior and preferences through open-ended questions and exploratory techniques like content analysis or ethnographic studies.

Consider timing and resources: quantitative research needs larger samples for statistical significance, while qualitative research is flexible with smaller samples. For quick feedback, opt for quantitative surveys or experimental studies.

Balancing detailed insights with ample data is crucial in research. A mixed-method approach often provides the most complete understanding. The key is to align your research method with your goals, resources, and desired insights to make informed decisions that enhance your marketing strategies and business outcomes.

Ashley Shedlock

10 articles

The views, opinions, data, and methodologies expressed above are those of the contributor(s) and do not necessarily reflect or represent the official policies, positions, or beliefs of Greenbook.

Comments are moderated to ensure respect towards the author and to prevent spam or self-promotion. Your comment may be edited, rejected, or approved based on these criteria. By commenting, you accept these terms and take responsibility for your contributions.

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9 Quantitative Research Methods With Real Client Examples

• June 21, 2021
• Tallwave Team

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Quantitative research is essential to developing a clear understanding of consumer engagement and how to increase satisfaction.

Primary Quantitative Research Methods

When it comes to quantitative research, many people often confuse this type of research with the methodology. The research type refers to style of research while the data collection method can be different.

Research types

These are the primary types of quantitative research used by businesses today.

• Survey research: Ideally when conducting survey research businesses will use a statistically relevant sample to understand the sentiments and actions of a large group of people. This could be their current customers or consumers who fit into their ideal demographic.
• Correlational research: Correlational research compares two variables to come to a conclusion about whether there is a relationship between the two. Keep in mind that correlation does not always imply causation, which is to say you need to account for external variables that could cause an apparent relationship.
• Experimental research: This form of research takes a scientific approach, testing a hypothesis by manipulating certain variables to understand what changes this could cause. In these experiments, there is a control group and a manipulated group.

Also read:  6 Factors Influencing Customer Behaviors in 2021

Data collection methods

Launching the above research requires creating a plan to collect data. After all, quantitative research relies on data. Here are the common primary data collection methods for quantitative research.

• Surveys: A common approach to collecting data is using a survey. This is ideal especially if the business can obtain a statistically relevant sample from their responses. Surveys are often conducted through web or email questionnaires.
• Interviews: Yes, interviews can be used to obtain quantitative data. While this form of data collection is typically associated with qualitative research, interviewers can ask a standard set of questions to collate formal, quantitative data.
• Documentation review: With an increasing amount of business occurring digitally, there is more documentation now than ever before to help inform quantitative conclusions. Businesses can assess website metrics such as return visits, time on page or even use a pixel to track customer movement across websites. They can also view how many times their app has been opened and actions users have taken on their platform to determine customer engagement.

Secondary research can be helpful when formulating a plan for obtaining primary quantitative data. It can help narrow areas of focus or illuminate key challenges.

Secondary Quantitative Research Methods

Secondary data is information that is already collected and not necessarily exclusive to the company but still relevant when understanding overall industry and marketplace trends. Here are a few examples of secondary data:

• Government reports: Government research can indicate potential regulatory roadblocks, customer pain points and future opportunities. For example, a fitness company might use government data that shows an increase in use of outdoor running trials to develop a new product used to meet that specific use case.
• Survey-based secondary data: Polls or surveys that have been conducted for a primary use could be reused for secondary purposes. This could include survey data obtained by other companies or governments.
• Academic research: Research that has been previously conducted and published in peer-reviewed journals can help inform trends and consumer behavior, even if it doesn’t apply to a company’s specific customers.

Secondary research can be helpful when formulating a plan for obtaining primary quantitative data. It can help narrow areas of focus or illuminate key challenges. It can also help when it comes to interpreting primary data, especially when trying to understand the relationship between two variables of correlated data.

Also read:  The What, Why, & How of Customer Behavior Analysis

Real Examples of Quantitative Research

We regularly use quantitative research to help our clients understand where they can best add value to increase customer engagement. Here are three examples of quantitative research in motion.

Example 1: Leading food distribution company

We helped a leading food distribution company identify changes in the needs and values of their restaurant clients as a result of COVID-19. This helped inform opportunities to become more valuable partners.

The research plan involved creating a survey that was emailed to clients. The questions were specific and numeric. For example, respondents were asked what percentage of their weekly spend was used with the food distribution company. They were also asked to assign a percentage to the way their food ordering had changed during COVID-19 and to rate their satisfaction with the food distribution company.

The results showed changes that had occurred for clients of the food distribution company as a result of the unique stressors of the pandemic. We were able to determine changes in weekly food supply and customer count as well as menu adaptations and purchase behavior.

Example 2: Leading credit card company

Our work with a leading credit card company required us to understand what current travel card members valued about the rewards program and their preferred communication method for booking travel in order to create an omnichannel servicing strategy and ideal customer journey.

Through an online survey of younger cardholders, the target demographic for this project, we asked questions such as length of card membership, total spend and the number of annual leisure trips in addition to more specific questions that showed how members get inspiration for trip planning and where they research.

The results highlighted ways to overcome resistance to pricing by proving more value. It also illuminated ways to make the benefits of membership more tangible to card holders and how to influence travelers in the early stages of planning their journey.

Example 3: Internal research report

We’re in the business of drinking our own champagne, so to speak, which is why we conducted our own quantitative research aimed at understanding the consumer trends that were spurred by the pandemic and how these will transform behaviors in the future.

There’s no question that new customer experiences emerged from the pandemic. Think of offerings such as “buy online, pickup in store (BOPIS),” or blended restaurant meals that are cooked at home. We wanted to understand how consumers truly felt about these new experiences and which they were likely to continue using even after restrictions were lifted. We also wanted to know more about the changing expectations for branded communication and how all of these pieces of the puzzle fit together to create consumer engagement. Our method of data collection was a survey.

Our research led us to develop insights we could use to inform our customers in their decision making. For example, we found convenience is paramount for consumers who are seeking out hybrid experiences such as BOPIS to take the best of both worlds. We also found many of these changes are permanent as consumers embraced new experiences that made their lives easier.

We regularly use quantitative research to help our clients understand where they can best add value to increase customer engagement.

The Bottom Line

Quantitative research is essential to developing a clear understanding of consumer engagement and how to increase satisfaction. Though online surveys are one of the most common methods for obtaining data, research isn’t limited to this strategy. It’s important to use whatever strategies are within your scope to constantly evaluate new trends and consumer behaviors that could significantly impact your offerings. The results can show you how to re-engage customers and drive loyalty.

Interested in partnering with us to learn more about your customers needs, wants, and behaviors to inform future experience design? Contact us today !

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Home Market Research

Quantitative Research: What It Is, Practices & Methods

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:

• 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:

• 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:

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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• Qualitative vs. Quantitative Research | Differences, Examples & Methods

Qualitative vs. Quantitative Research | Differences, Examples & Methods

Published on April 12, 2019 by Raimo Streefkerk . Revised on June 22, 2023.

When collecting and analyzing data, quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings. Both are important for gaining different kinds of knowledge.

Common quantitative methods include experiments, observations recorded as numbers, and surveys with closed-ended questions.

Quantitative research is at risk for research biases including information bias , omitted variable bias , sampling bias , or selection bias . Qualitative research Qualitative research is expressed in words . It is used to understand concepts, thoughts or experiences. This type of research enables you to gather in-depth insights on topics that are not well understood.

Common qualitative methods include interviews with open-ended questions, observations described in words, and literature reviews that explore concepts and theories.

Table of contents

The differences between quantitative and qualitative research, data collection methods, when to use qualitative vs. quantitative research, how to analyze qualitative and quantitative data, other interesting articles, frequently asked questions about qualitative and quantitative research.

Quantitative and qualitative research use different research methods to collect and analyze data, and they allow you to answer different kinds of research questions.

Quantitative and qualitative data can be collected using various methods. It is important to use a data collection method that will help answer your research question(s).

Many data collection methods can be either qualitative or quantitative. For example, in surveys, observational studies or case studies , your data can be represented as numbers (e.g., using rating scales or counting frequencies) or as words (e.g., with open-ended questions or descriptions of what you observe).

However, some methods are more commonly used in one type or the other.

Quantitative data collection methods

• Surveys :  List of closed or multiple choice questions that is distributed to a sample (online, in person, or over the phone).
• Experiments : Situation in which different types of variables are controlled and manipulated to establish cause-and-effect relationships.
• Observations : Observing subjects in a natural environment where variables can’t be controlled.

Qualitative data collection methods

• Interviews : Asking open-ended questions verbally to respondents.
• Focus groups : Discussion among a group of people about a topic to gather opinions that can be used for further research.
• Ethnography : Participating in a community or organization for an extended period of time to closely observe culture and behavior.
• Literature review : Survey of published works by other authors.

A rule of thumb for deciding whether to use qualitative or quantitative data is:

• Use quantitative research if you want to confirm or test something (a theory or hypothesis )
• Use qualitative research if you want to understand something (concepts, thoughts, experiences)

For most research topics you can choose a qualitative, quantitative or mixed methods approach . Which type you choose depends on, among other things, whether you’re taking an inductive vs. deductive research approach ; your research question(s) ; whether you’re doing experimental , correlational , or descriptive research ; and practical considerations such as time, money, availability of data, and access to respondents.

Quantitative research approach

You survey 300 students at your university and ask them questions such as: “on a scale from 1-5, how satisfied are your with your professors?”

You can perform statistical analysis on the data and draw conclusions such as: “on average students rated their professors 4.4”.

Qualitative research approach

You conduct in-depth interviews with 15 students and ask them open-ended questions such as: “How satisfied are you with your studies?”, “What is the most positive aspect of your study program?” and “What can be done to improve the study program?”

Based on the answers you get you can ask follow-up questions to clarify things. You transcribe all interviews using transcription software and try to find commonalities and patterns.

Mixed methods approach

You conduct interviews to find out how satisfied students are with their studies. Through open-ended questions you learn things you never thought about before and gain new insights. Later, you use a survey to test these insights on a larger scale.

It’s also possible to start with a survey to find out the overall trends, followed by interviews to better understand the reasons behind the trends.

Qualitative or quantitative data by itself can’t prove or demonstrate anything, but has to be analyzed to show its meaning in relation to the research questions. The method of analysis differs for each type of data.

Analyzing quantitative data

Quantitative data is based on numbers. Simple math or more advanced statistical analysis is used to discover commonalities or patterns in the data. The results are often reported in graphs and tables.

Applications such as Excel, SPSS, or R can be used to calculate things like:

• Average scores ( means )
• The number of times a particular answer was given
• The correlation or causation between two or more variables
• The reliability and validity of the results

Analyzing qualitative data

Qualitative data is more difficult to analyze than quantitative data. It consists of text, images or videos instead of numbers.

Some common approaches to analyzing qualitative data include:

• Qualitative content analysis : Tracking the occurrence, position and meaning of words or phrases
• Thematic analysis : Closely examining the data to identify the main themes and patterns
• Discourse analysis : Studying how communication works in social contexts

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Chi square goodness of fit test
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Inclusion and exclusion criteria

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
• If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

There are various approaches to qualitative data analysis , but they all share five steps in common:

• Prepare and organize your data.
• Review and explore your data.
• Develop a data coding system.
• Assign codes to the data.
• Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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Marketing Research Methods: Quantitative and Qualitative Approaches

• ISBN-10 1108834981
• ISBN-13 978-1108834988
• Publisher Cambridge University Press
• Publication date March 11, 2021
• Language English
• Dimensions 7.5 x 1.75 x 9.75 inches
• Print length 882 pages
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• Publisher ‏ : ‎ Cambridge University Press (March 11, 2021)
• Language ‏ : ‎ English
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• Item Weight ‏ : ‎ 4.4 pounds
• Dimensions ‏ : ‎ 7.5 x 1.75 x 9.75 inches
• #3,324 in Market Research Business (Books)
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LIFE EXPERIENCES OF YOUNG MINNESOTANS WITH MARGINALIZED IDENTITIES

Intersectionality study iii, quantitative research report.

7 AUGUST 2024

Research conducted by,MarketResponse International Project #2526 For the Minnesota Governor's Councilon Developmental Disabilities

Table of Contents

• Research Overview

Research Method

• Respondent Profile
• Executive Summary
• Detailed Findings
• Measures of Discrimination
• Feelings Out In The Community
• Intersectionality Impacts
• Discrimination Experiences

Multi-phased Intersectionality Studies are focused on the intersection of developmental disabilities with race and ethnicity and other marginalized communities, which leads to social discrimination and disparities in areas such as:

• Health Care
• Social Services (home and community-based services)

Phase I: Qualitative research completed in August 2022

• Literature review
• Internal Qualitative Interviews
• Narrative Research Focus Groups and 1:1 Interviews (n=49)
• Was designed to gain insights regarding:
• The nature of discrimination and all its forms
• How it is experienced by various groups with intersecting profiles
• Impacts and results, both short-term and long-term

Phase II: Benchmark Quantitative survey completed in September 2023 was designed to gain comparative measures of various forms of discrimination among four populations (n=593):

• White people with disabilities
• Black, indigenous, (and other) people of color (BIPOC*) with disabilities
• White people without disabilities
• BIPOC without disabilities

* We are using the term BIPOC to represent all non-white racial and ethnic communities included in this study

Phase III: Quantitative and Qualitative research completed in July 2024 is focused on young Minnesotans (ages 13-22), to better understand their life experiences and the extent to which those with marginalized identities feel included in the One Minnesota promise of diversity, equity and inclusion. This pilot study provides preliminary measures (n=261), which can help inform the design and fielding of a future potential statewide survey of young Minnesotans.

Quantitative Survey of Young Minnesotans

Included 9-12th grades and transition program students, ages 13-22

Two groups were identified, based on disability status:

1. No Disability (control sample) n=176

2. Have a disability n=57 or Parent (assisting child respondent with a disability n=28 Total Disability Sample: n=85 (55% reported as a developmental disability)

TOTAL n=261

The quantitative survey was administered through two methods:

1) Commercial opt-in online panel, used primarily to recruit young persons without disabilities from all around the State of Minnesota.

2) Young Minnesotans with developmental and other disabilities were included in the survey with help from state agencies

A qualitative Online Community was conducted among a sampling of respondents with disabilities who participated in the online survey

n=7 around the state of Minnesota, 2 weeks duration

YOUTH RESPONDENT PROFILE

With 70% White, Caucasian, and 30% BIPOC, the survey sample closely matched the diversity of the general population of young Minnesotans.*

* SOURCE: Exploring Age Groups in the 2020 Census, learn about age, sex, and racial and ethnic diversity for states, counties, and census tracts

We are using the term BIPOC to represent all nonwhite communities included in this study.

Our sample of young Minnesotans had good representation by age and gender:**

Age and Gender (n=256)

Age Age 13-17, 44% Age 18-22, 54%

Gender 47% Male 52% Female

Age and Gender Female 13-17 18% Male 13-17 26% Female 18-22 33% Male 18-22 21%

**Data does not add up to 100% due to rounding and 2% self reporting as non-binary.

Race, Ethnicity (n=261)

White, Caucasian 70% BIPOC See below breakdown - Total 30% Black, African American, Born in the US 9% Other Asian or Pacific Islander 5% Hispanic or Latino 5% Two or more (non-white) races 3% American Indian or Alaska Native 3% Southeast Asian - Hmong 3% Other 1% Black, Immigrant, Born outside the US 1%

RESPONDENT PROFILE - DISABILITY STATUS

Disability Status (n=261)

Parent advocate 11% Have a disability 22% No disability 67%

Type of Disability (n=85) of those with a disability 55% were developmental disabilities

Developmental Disability 55% Other Disability 28% Don't know 16%

Nature of Disability

Autism 38% Cognitive or Intellectual disability 36% Mental Health 34% A condition that limits one or more physical activities 14% Epilepsy 8% Down syndrome 8% Blindness or low vision 8% Hard of hearing 6% Deaf 1% DeafBlind 0 Other 24% Unsure, I really don't know 4%

EXECUTIVE SUMMARY

A DIFFERENT REALITY FOR YOUNG PEOPLE WITH DISABILITIES - Twice as many incidences of discrimination were experienced by Minnesota teens and young adults with disabilities, as compared to youth without disabilities.

The young respondents selected words that best describe the way they typically feel when they are out and about and interacting with other people in their community. Words selected most often reveal very different perceptions among young people with disabilities, as compared to those without disabilities.

The TOP 5 WORDS selected by . . .

Young people WITHOUT disabilities:

Friendly Anxious At Ease Confident Accepted

Young people WITH disabilities:

Friendly Anxious Misunderstood Excluded Frustrated

EXECUTIVE SUMMARY - Intersectionality Impacts

Impact of the intersection between disability and race and ethnicity:

BIPOC teens and young adults WITHOUT disabilities experience twice as many incidences of discrimination, as compared to white youth without disabilities.

For both white and BIPOC teens and young adults, having a disability greatly increases the likelihood of experiencing discrimination.

The relative amounts of reported discrimination experiences were highest among young white Minnesotans with disabilities, as compared to the BIPOC youth with disabilities.

There was a similar finding from The One Minnesota Baseline Quantitative Survey among Minnesota adults, completed in September 2023. (Our project #2508)

We believe these similar findings from both studies are indications of a loss of privilege impact that is possibly more noticed and experienced by white people with disabilities, as compared to BIPOC with disabilities.

Note: Privilege is a special right, advantage or immunity granted or available only to particular individuals or groups. (Oxford Languages) In the original intersectionality study completed August 2022, we surmised that discrimination happens in the absense of privelege.

EXECUTIVE SUMMARY - Satisfaction in the Community

White people with disabilities are more than twice as likely to be dissatisfied with how they are treated, included, and accepted in their communities, as compared to BIPOC youth, with or without disabilities.

Question asked: All things considered, how satisfied are you with the way you are treated, included, and accepted by your community as a whole?

White WITHOUT Disability (n=123)

Total Dissatisfied 6% (Somewhat dissatisfied 4% Very dissatisfied 2%) Total Satisfied 77% (Somewhat satisfied 53% Very satisfied 24%)

BIPOC WITHOUT Disability (n=53)

Total Dissatisfied 12% (Somewhat dissatisfied 8% Very dissatisfied 4%) Total Satisfied 64% (Somewhat satisfied 45% Very satisfied 1%)

White WITH Disability (n=58)

Total Dissatisfied 26% (Somewhat dissatisfied 17% Very dissatisfied 9%) Total Satisfied 48% (Somewhat satisfied 38% Very satisfied 10%)

BIPOC WITH Disability (n=26)

Total Dissatisfied 12% (Somewhat dissatisfied 4% Very dissatisfied 8%) Total Satisfied 66% (Somewhat satisfied 54% Very satisfied 12%)

EXECUTIVE SUMMARY - Discrimination Experiences

When describing their discrimination experiences, including unfair treatment, barriers to products or services, or restrictions from privileges, the following top six themes emerged.

White WITHOUT Disability (n=48) BIPOC WITHOUT Disability (n=33) White WITH Disability (n=46) BIPOC WITH Disability (n=17)

Social Exclusion, Favoritism, and Bullying

White WITHOUT Disability 17% BIPOC WITHOUT Disability 24% White WITH Disability 35% BIPOC WITH Disability 35%

Inadequate Support Services for People with Disabilities

White WITHOUT Disability 6% BIPOC WITHOUT Disability 6% White WITH Disability 46% BIPOC WITH Disability 18%

Disability Discrimination in Education

White WITHOUT Disability 4% BIPOC WITHOUT Disability 3% White WITH Disability 28% BIPOC WITH Disability 24%

Workplace Discrimination

White WITHOUT Disability 15% BIPOC WITHOUT Disability 15% White WITH Disability 9% BIPOC WITH Disability 18%

Racial Discrimination

White WITHOUT Disability 6% BIPOC WITHOUT Disability 33% White WITH Disability 0% BIPOC WITH Disability 6%

Healthcare Discrimination

White WITHOUT Disability 8% BIPOC WITHOUT Disability 3% White WITH Disability 11% BIPOC WITH Disability 12%

To improve the lives of young Minnesotans with disabilities, the State would need to better understand the issues - and provide solutions related to - support services for disabilities, discrimination in education, and workplace and healthcare discrimination.

Note: Differences of 20% or more, between groups with sample sizes greater than 30, are likely to be statistically significant at the 90% level or greater.

DETAILED FINDINGS

Achieving the One Minnesota promise is synonymous with eliminating discriminatory behaviors and barriers that limit the possibility for people to achieve their full potential.

Discrimination is the act of making unjustified distinctions between people based on the groups, classes, or other categories to which they belong or are perceived to belong.

Occurs when individuals or groups are unfairly treated in a way which is worse than other people are treated.

Or when barriers or obstacles to needed products or services exist for some people but not for others.

Or when members of one group are restricted from opportunities or privileges that are available to members of another group.

MEASURES OF DISCRIMINATION

The three questions used to measure incidences of discrimination are shown here. Adding up the YES percents from the three questions yields a total discrimination index for each group.

Within the past 12 months, do you believe you....

Were restricted from opportunities, privileges or activities Encountered barriers or obstacles to needed products or services Were unfairly treated, worse than others are treated

TOTAL WITHOUT Disability (n=176) Discrimination index 71

Were restricted from opportunities, privileges or activities - 19% Encountered barriers or obstacles to needed products or services - 20% Were unfairly treated, worse than others are treated - 32%

TOTAL WITH Disability (n=85) Discrimination index 154

Were restricted from opportunities, privileges or activities - 54% Encountered barriers or obstacles to needed products or services - 51% Were unfairly treated, worse than others are treated - 49%

As shown, twice as many incidences of discrimination were experienced by Minnesota teens and young adults with disabilities, as compared to youth without disabilities.

HOW THE YOUTH FEEL IN THEIR COMMUNITY

The young Minnesotans were asked to select the few words that best describe the way they typically feel when they are out and about and interacting with other people in their community.

Without a disability (n=176)

Four of the top 5 most selected words by those who do not have a disability were all positive. (The exception is the word Anxious.)

Friendly 44% Anxious 33% At ease 31% Confident 24% Accepted 19% Misunderstood 15% Invisible 14% Respected 13% Valued 13% Frustrated 10% Excluded 9% Fearful 4%

With a disability (n=85)

Four of the top 5 most selected words by the young Minnesotans with disabilities were negative: Anxious, Misunderstood, Excluded, Frustrated

Friendly 33% Anxious 39% At ease 13% Confident 12% Accepted 15% Misunderstood 34% Invisible 15% Respected 14% Valued 9% Frustrated 21% Excluded 27% Fearful 11%

INTERSECTIONALITY IMPACTS - Disability and Ethnicity

BIPOC teens and young adults WITHOUT disabilities experience twice as many incidences of discrimination, as compared to white youth WITHOUT disabilities.

White youth with disabilities experienced the highest number of discrimination incidences.

White WITHOUT Disability (n=123) Discrimination index 56

Were restricted from opportunities, privileges or activities - 15% Encountered barriers or obstacles to needed products or services - 15% Were unfairly treated, worse than others are treated - 26%

BIPOC WITHOUT Disability (n=53) Discrimination index 107

Were restricted from opportunities, privileges or activities - 28% Encountered barriers or obstacles to needed products or services - 32% Were unfairly treated, worse than others are treated - 47%

White WITH Disability (n=58) Discrimination index 158

Were restricted from opportunities, privileges or activities - 53% Encountered barriers or obstacles to needed products or services - 57% Were unfairly treated, worse than others are treated - 48%

BIPOC WITH Disability (n=26*) Discrimination index 142

Were restricted from opportunities, privileges or activities - 54% Encountered barriers or obstacles to needed products or services - 38% Were unfairly treated, worse than others are treated - 50%

* Given the relatively small sample size of n=26, caution is advised in making statistical inferences to the population of young BIPOC Minnesotans with disabilities.

INTERSECTIONALITY IMPACTS - How Youth Feel in their Communities

The teens and young adults from the four groups selected words that best describe the way they typically feel when they are out and about and interacting with other people in their community.

Positive Words

Friendly 45% At Ease 36% Confident 24% Accepted 22% Respected 15%

NEGATIVE Words

Anxious 29% Misunderstood 11% Frustrated 8% Excluded 8% Fearful 2%

Friendly 43% At Ease 21% Confident 25% Accepted 13% Respected 8%

Anxious 42% Misunderstood 23% Frustrated 13% Excluded 9% Fearful 8%

Friendly 34% At Ease 16% Confident 7% Accepted 16% Respected 10%

Anxious 41% Misunderstood 33% Frustrated 21% Excluded 29% Fearful 7%

BIPOC WITH Disability (n=26*)

* Given the relatively small sample size of n=26, caution is advised in making statistical inferences to the population of young BIPOC Minnesotans with disabilities. Positive Words

Friendly 31% At Ease 8% Confident 23% Accepted 15% Respected 23%

Anxious 35% Misunderstood 38% Frustrated 19% Excluded 23% Fearful 19%

BIPOC youth with disabilities appear to be least likely to feel at ease in their communities.

White youth with disabilities appear least likely to feel confident.

Fearful was selected by one of five BIPOC with disabilities, substantially more than any other group.

Note: Differences of 15% or more, between groups with sample sizes greater than 50, are likely to be statistically significant at the 90% level or greater.

DISCRIMINATION EXPERIENCES

The teens and young adults were asked to describe a time when they felt as though they were unfairly treated, or there were barriers to needed products or services, or they were restricted from privileges or activities. Their responses were coded as follows:The teens and young adults were asked to describe a time when they felt as though they were unfairly treated, or there were barriers to needed products or services, or they were restricted from privileges or activities. Their responses were coded as follows:

TOTAL (n=145)

Social Exclusion and Bullying 26% Inadequate Support Services for Disabilities 20% Disability Discrimination in Education 14% Workplace Discrimination 13% Racial Discrimination 10% Healthcare Discrimination 8% Inequality in Education Opportunities 6% Discrimination in Sports 6% Sexual Orientation Discrimination 3% Pregnancy Discrimination 1%

White WITHOUT Disability (n=48)

Social Exclusion and Bullying 17% Inadequate Support Services for Disabilities 6% Disability Discrimination in Education 4% Workplace Discrimination 15% Racial Discrimination 6% Healthcare Discrimination 8% Inequality in Education Opportunities 8% Discrimination in Sports 8% Sexual Orientation Discrimination 4% Pregnancy Discrimination 4%

BIPOC WITHOUT Disability (n=33)

Social Exclusion and Bullying 24% Inadequate Support Services for Disabilities 6% Disability Discrimination in Education 3% Workplace Discrimination 15% Racial Discrimination 33% Healthcare Discrimination 3% Inequality in Education Opportunities 3% Discrimination in Sports 3% Sexual Orientation Discrimination 3% Pregnancy Discrimination 0%

White WITH Disability (n=46)

Social Exclusion and Bullying 35% Inadequate Support Services for Disabilities 46% Disability Discrimination in Education 28% Workplace Discrimination 9% Racial Discrimination 0% Healthcare Discrimination 11% Inequality in Education Opportunities 7% Discrimination in Sports 7% Sexual Orientation Discrimination 2% Pregnancy Discrimination 0%

BIPOC WITH Disability (n=17)

Social Exclusion and Bullying 35% Inadequate Support Services for Disabilities 18% Disability Discrimination in Education 24% Workplace Discrimination 18% Racial Discrimination 6% Healthcare Discrimination 12% Inequality in Education Opportunities 0% Discrimination in Sports 0% Sexual Orientation Discrimination 0% Pregnancy Discrimination 0%

DISCRIMINATION EXPERIENCES: White Without Disabilities

Thirty-nine percent (39%) of young white Minnesotans without disabilities reported having any discrimination experiences. Some examples of those experiences are shown below under two general themes.

Our school only celebrates and encourages boys, not the girl athletes and smart kids. It makes me mad. I have a 4.0 GPA, but it doesn't matter if you're a girl: the school doesn't celebrate us. Just the boys. It's hurtful. In school I feel that they are not helpful for students that are at the bottom, and they didn't care if I succeed. I would go to them for extra help or support in certain classes and they didn't help in any way. Kids pick on me for wearing hand me downs. In baseball the coach plays favorites with kids that pay to go to his program outside of school & put them on teams above where they should play. Most cannot afford the outside program. It frustrates them & makes them want to quit the program.

At work, I was sexually harassed by another coworker and when I told HR, they did not care. This made me feel like I was treated very unfairly. It honestly made me feel like I was not respected because it was an ethical issue. I wanted to quit, and I still do. At work, I was more harshly judged because of my age and pregnancy. I was upset and I feel like I stopped trying as hard to be successful at my job. I feel that in my workplace, I am often looked down upon because I am young. I often am not able to lead in the same way my coworkers can even though they are only a few years older than me. It makes me feel frustrated. I feel that age does not define how hard one works. This affects my work because I become self-conscious in my decisions after not being able to participate in the same activities as my older coworkers.

DISCRIMINATION EXPERIENCES: BIPOC Without Disabilities

Sixty-two percent (62%) of BIPOC without disabilities have experienced discrimination. Various forms of racial discrimination were most often described.

My younger brother and I moved to a small town. Because we are part of a very small African American group, I feel things are harder, or people shun us because of our skin color, or maybe it's just the fact that we are young. I feel as though they see young gang members coming to cause trouble, when we are actually just young adults trying to survive. I was shopping for something, and no one came up to me. But then a white girl came in and the store workers were quick to greet and help her. Being Asian I couldn't hangout with my white friends because of their mom being mean to me and thinking I wasn't good enough. I was restricted from a group in my church because I was a black person. It made me feel sad, and very angry. I was at work, and they were being really racist and rude. They called me the N word.

I'm not considered part of the group or circle. I was treated with warmth in front of the public, but not behind the public, I'm nothing. My mom warned me about being careful trusting and hanging out with people. She is right. I don't get to walk with them. I can't sit with them. I was a new kid in school this year & after we moved it has been difficult for me to make friends and get involved in stuff. I suffer from anxiety, and it plays a big role in me making friends or doing normal kid stuff. I just don't want to be at school; there isn't anything to look forward to. I was bullied by my peers for cutting my hair short; kids teased me and called me trans.

DISCRIMINATION EXPERIENCES: White WITH Disabilities (n=46)

Among young white Minnesotans WITH disabilities, 79% reported experiences with discrimination, examples of which are shown below under four general themes.

Inadequate Support Services for Disabilities

Living in northwest Minnesota creates a barrier to needed services for an individual 18-22 with disabilities, because of the lack of availability. There are limited resources and opportunities for individuals with disabilities living in greater Minnesota. We lack supportive employment and meaningful transition programs. Individuals with disabilities lack community and leisure opportunities. At a minimum, our smaller schools struggle to provide level 3 settings for those students with higher needs. Within our region, our students do not have access to a Level IV facility. Currently, the nearest facility is over 100 miles away. That is not equity in education! I haven't been able to have PCA services due to not being recognized as disabled. It took almost 3 months to get a MN Choices assessment scheduled after a 3-year battle for SSDI certification. My disability wasn't recognized, I felt like I didn't matter. At my school, they told me my diagnosis wasn't "valid" because I got it from a Primary Care Physician not a specialist. I have been on the wait list to get my diagnosis confirmed by a specialist for 7 years. This loophole allowed them to not give me any accommodations at school. It made me feel like my education was not a priority and they wanted easy students and money rather than using resources to help people. I rely on services provided by waivers. Every year we have to answer the same questions about my disability just to access needed services, and it gets old. It is unfair because my condition and supports aren't going to change a lot from year to year. I need help with basic daily living activities. Each year it seems like I have to prove it over and over again just to maintain my current level of services.

Others in my education program were allowed to use video or remote learning option on days where I wasn't physically able to be present due to my disability, but I was denied that option despite meetings and advocating. Frustrated, hopeless, depressed, I felt there was lost opportunities and time to work on my growth, development, goals for my future. I have a processing speed deficit. There have been instances where I am not given the same respect when I need more time on an exam. Jokes are made towards me and a bit from teachers such as making snore noises, or jokes about how it takes me years to finish.

It is hard for me to pay attention for long periods of time, and it takes me longer to do bigger tasks. I do not get as good of marks as others in my class do. My peers get frustrated with me, and I feel like the teachers score me lower because of it. Due to mental health, I struggle with anxiety and have a hard time being around groups of people. The school wasn't always willing to help with accommodation that made it tolerable to attend school. I ended up missing several days of school for the year and the school secretary marked the days missed as unexcused and I ended up with truancy.

Wealth (or lack thereof) makes getting proper healthcare difficult. I can't afford it. There have been times when my son was overshadowed in the medical community because of his Down syndrome. There has been an institutional bias against some folks with Down syndrome. When physicians aren't sure what the person's diagnosis is, they say: "It's just part of Down syndrome." They do not look into the causes, nor do they do diagnostic testing to make an informed decision about the patient's symptoms.

DISCRIMINATION EXPERIENCES: BIPOC WITH Disabilities (n=17)

Among young BIPOC Minnesotans WITH disabilities, 65% reported experiences with discrimination. Some examples, in their own words, are provided below.

Social Exclusion, and Workplace Discrimination

At work I was not invited to activities because they thought my disabilities would make me not fun. It made me feel "less than," and made me look at my coworkers differently. Visiting any store and interacting with the cashier. I can't always understand what they are saying. Everyone around me gets irritated when I take too long. I get anxious and frustrated. I felt disrespected. I was treated unfairly due to my race at my old job. People assumed I didn't speak English and therefore ignored me. I was also treated unfairly by a customer due to my gender. I was threatened because I did not smile.

The education staff don't ask me relevant questions and are not providing me with transition services that address my needs and wishes for the future: to live independently in the community (with support) and be employed in the community (with appropriate supports as needed). The school has a "program" that I must "fit into." I have asked for assistive technology to support me in my transition plan. I have learned and use some assistive technology that my parents have shown me how to use, but I am not allowed or encouraged to use it at school or during my transition program. I am angry, I am supposed to be able to have the assistive technology I need to succeed, but because the school staff don't want to learn the technology, they don't provide it or even worse, they forbid me from using my phone with picture schedule app that I use at home. They say that other students can't use their phones so I can't use mine. I have always felt like I have ADHD. I expressed this to my mom, and she had countless meetings with my school and doctor, and no one would do anything or even test me. They don't want to listen or help, and I couldn't do it anymore. I dropped out my 10th grade year. Now I am a year behind in school. I started smoking weed to try to help. I was really good at track and football, and I gave it all up.

THANK YOU! From your MarketResponse team

TOM PEARSON, Managing [email protected] SUSAN McCULLOUGH, Sr. Research [email protected] LYNN SCHREIFELS, Sr. Research [email protected] DEREK PEARSON, Sr. Research [email protected]

The preparation of this document was financed in part by grant number 2301MNSCDD from the Administration for Community Living, U.S. Department of Health and Human Services, Washington, D.C. 20201. Grantees undertaking projects with government sponsorship are encouraged to express freely their findings and conclusions. Points of view or opinions do not, therefore, necessarily represent official ACL policy.