Quantitative research is the systematic collection and analysis of numerical data to measure attitudes, behaviours, preferences, market trends or relationships between variables. Quantitative market research helps organisations move from anecdote to evidence by answering questions such as how many people think something, how often something happens, how strongly customers feel, and whether different groups behave in meaningfully different ways.
At its best, quantitative research gives decision-makers a clear view of scale. A business may know from customer conversations that people are frustrated by a service process, interested in a new product idea, or confused by a brand message. Quantitative research helps determine whether that issue is isolated, widespread, commercially significant or different across customer segments.
This is why quantitative research is a core tool in market and social research. It helps organisations measure demand, test ideas, prioritise opportunities and make decisions with more confidence. It does not replace judgment, creativity or strategy. It gives them stronger evidence base.
| Definition
Quantitative research is a research approach that collects and analyses numerical data to measure attitudes, behaviours, preferences, trends and relationships with a defined population or sample. |
What are the types of quantitative research?
When designing a study, there are three broad types of quantitative research that relate to goals. These broad types of quantitative research are descriptive, correlational and causal. While a study may include more than one type, it will focus on one.
Another type of research is exploratory research. This type of research focuses on identifying who, what, when, where, and why, and mostly uses qualitative methods.
Descriptive
Descriptive research describes the who, what, when, where, and how. Quantitative research that uses descriptive measures assesses the frequency and incidence of things but does not examine how these changes relate to one another.
Examples of descriptive quantitative research include customer satisfaction surveys and opinion polls. These studies describe opinions, including opinions within different groups, such as between females and males, and over time.
Correlational
Correlational research focuses on determining relationships between variables, specifically how changes in one variable affect another. In correlational studies, different levels of one variable or event are manipulated to assess their impact on other variables. This includes testing communication, interventions, and strategies on outcomes.
Examples of correlational quantitative research include A/B testing and field experiments.
Causal
Causal research is like correlational research, but uses stronger controls to rule out other factors that might explain change and the relationship.
This type of research requires strong controls and is mostly done using randomised trials and experiments. In some cases, quasi-experiments and natural experiments are used. An example of casual quantitative research in marketing is pricing tests and feature testing.
| Type | Purpose | Key Features | Methods |
| Descriptive | Define status | Observational and explanatory with no variables manipulated | Surveys, Data analytics, observation, case studies |
| Correlational | Identify relationships | Predicts results and change, but does not prove causation | Surveys, Data analytics, A/B testing, natural and quasi-experiments, |
| Causal | Determine causation | Manipulates variables to find cause-and-effect | Randomised trials and experiments. |
Why quantitative research matters in market research
Business decisions are not made in isolation. They are made in live markets, with imperfect information, changing customer expectations and competing internal priorities. Quantitative market research helps reduce that uncertainty.
It is particularly useful when organisations need to estimate the size of an issue, compare options, track change over time or understand which factors are most strongly associated with customer behaviour. It can support decisions about brands, products, services, pricing, communications, customer experience and market entry.
How do quantitative and qualitative research methods differ?
Quantitative and qualitative research are both essential to strong market research, but they serve different purposes. Quantitative research measures. Qualitative research explores. Quantitative research is used when an organisation needs robust evidence about frequency, strength or difference. Qualitative research is used when an organisation needs depth, context and explanation.
You can learn more about qualitative research in our article “Qualitative Market Research: What It Is, How It Works and When to Use It”.
A simple way to understand the distinction is this: qualitative research helps identify what matters and why; quantitative research helps measure how much it matters, how widespread it is and whether it differs across groups, time and place.
Quantitative vs qualitative research
| Area | Quantitative research | Qualitative research |
| Main purpose | Measures attitudes, behaviours and trends | Explores motivations, meanings and experiences |
| Typical questions | How many? How often? How much? To what extent? | Why? How? What does it mean? |
| Data type | Numbers | Words, stories, observations and images |
| Common methods | Surveys, polls, tracking studies, experiments and analytics | Focus groups, interviews, ethnography and online communities |
| Sample size | Larger | Smaller |
| Analysis | Statistical analysis | Thematic or interpretive analysis |
| Output | Metrics, trends, segments and models | Themes, insights, stories and hypotheses |
| Best used for | Determining the size, relationship and trends | Exploring and understanding |
The two approaches often work best together. Qualitative research can uncover the language, motivations and decision drivers that matter to customers. Quantitative research can then test those findings at scale, showing which issues are most common, which segments are most affected and which opportunities are most commercially important.
What are the benefits of quantitative research?
Quantitative research is valuable because it turns questions into measurable evidence. It provides structure, comparison, and statistical confidence when the research is well designed.
1. It measures the size of an issue
Quantitative research helps organisations understand whether an issue affects a small niche or a large proportion of the market. A handful of customer complaints may suggest a problem; a robust survey can show whether the problem affects 5% or 45% of customers.
2. It supports evidence-based decision-making
Quantitative research gives leaders a stronger basis for decisions about the right level of investment and prioritisation.
3. It allows comparison between groups
Results can be compared by customer segment, age, location, behaviour, usage level, life stage, market, product holding or other variables relevant to the decision.
4. It tracks change over time
Tracking studies can show whether brand awareness, customer satisfaction, trust, consideration or behaviour is improving, declining or remaining stable.
5. It tests ideas before launch
Concept testing, product testing and pricing research help organisations understand how customers are likely to respond before significant resources are committed.
6. It identifies patterns and relationships
Quantitative analysis can reveal associations between variables, such as the relationship between satisfaction and loyalty, or between brand awareness and purchase consideration.
What are the limitations of quantitative research?
Quantitative research is powerful, and it can clarify patterns and measure scale, but it still depends on good research design, good data and careful interpretation.
1. It may not explain why people think or behave a certain way
A survey may show that 60% of customers reject a product concept, but qualitative research may be needed to understand whether the issue is price, relevance, language, trust, design or perceived value.
2. Poor questionnaire design can produce misleading results
Leading questions, confusing wording, missing answer options and poorly structured scales can distort results and create false certainty.
3. Sample quality matters
If the sample is biased or poorly recruited, the results may not represent the target audience. The quality of a quantitative study depends heavily on the quality of the sample.
4. It can oversimplify complex behaviour
Human behaviour is emotional, contextual and sometimes inconsistent. Numbers can make patterns visible, but they can also flatten nuance if interpreted too mechanically.
5. It requires careful interpretation
A statistically significant result is not always strategically significant. Findings need to be interpreted in relation to the business problem, market context and decision at hand.
6. It can miss unexpected issues
Structured surveys are good at measuring known topics, but they may miss issues that people would raise in a more open-ended qualitative discussion.
| Important point
Quantitative research works best when the questions, sample and analysis are carefully designed around the decision the organisation needs to make. |
What are the main types of quantitative research methods?
There are two main types of quantitative research methods: primary and secondary. Primary research is research undertaken for the primary purpose of the research, while secondary research uses quantitative data collected for another purpose but is being used for research.
Primary quantitative research is done through surveys and observations, and secondary research uses data analytics.
Surveys
Surveys are the most common quantitative market research method. They use structured questions to collect data from a defined sample of respondents. Surveys can measure customer satisfaction, brand awareness, product interest, usage behaviour, purchase intent, customer needs and market attitudes.
There are many types of survey methods that require careful consideration of various factors to be effective. The article by Eris Strategy on choosing the right survey methodology outlines what you need to consider.
Observation
Quantitative observational research is any study that tracks behaviour by observing it rather than asking people to say what they did. This type of quantitative research includes counting participants at an event, measuring how many people perform a task, or measuring how often different types of people engage.
Examples of observation research are facility and infrastructure usage studies, tourist behaviour studies and retail behaviour studies. Observational research is done both online and in the physical world,
Data analytics and behavioural data
Quantitative research can also use existing data such as website analytics, CRM data, sales data, app usage, transaction data, search behaviour and customer service records. This can be especially powerful when combined with survey or qualitative research.
How is quantitative research used by businesses?
Quantitative research is used across many areas of business strategy, marketing and customer experience. The most common applications include the following.
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- Brand strategy. Quantitative research helps measure brand awareness, consideration, preference, trust, distinctiveness, reputation and market position. It can show whether a brand is strengthening, weakening or failing to convert awareness into consideration.
- Customer experience. Surveys and tracking studies can identify customer pain points to improve customer experience. While measuring satisfaction, and prioritise improvements most likely to influence loyalty, retention, or advocacy.
- Product and service development. Quantitative research can test concepts, features, packaging, pricing and likely demand before launch. This helps reduce risk and refine the offer before investment decisions are made.
- Marketing and communications. Research can evaluate advertising effectiveness, message clarity, creative appeal, channel performance and campaign impact.
- Market sizing and opportunity assessment. Quantitative research can estimate the size of a potential market, the level of demand, the likely uptake or the value of an opportunity.
- Segmentation and targeting. Quantitative analysis can identify different customer segments and help organisations tailor propositions, messages, channels and experiences.
- Public policy and social research. Quantitative methods can measure community attitudes, awareness, service usage, policy support, behaviour change and program outcomes.
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Why quantitative and qualitative research often work best together
Quantitative and qualitative research should not be treated as rivals. In many projects, the strongest insights come from combining the two.
Qualitative research uncovers the language, emotions, barriers and motivations that shape customer behaviour. Quantitative research can then measure the extent to which those factors are widespread and how strongly they relate to business outcomes. Alternatively, a quantitative study may reveal an unexpected pattern that requires qualitative research to explain.
For example, a business may begin with customer interviews to understand why people are leaving a service. Those interviews may reveal possible drivers of churn, including poor onboarding, unclear fees and lack of proactive communication. A quantitative survey can then identify which issues are most common and most strongly associated with churn. The result is not just more data, but better prioritisation.
How to design reliable quantitative research
Reliable quantitative research requires more than a large sample. It requires a clear purpose, disciplined design and careful interpretation. Several elements are especially important which are also important when writing a market research brief.
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- Clear objectives. The project should begin with a clear understanding of the business problem, the decisions to be made and the evidence required.
- Representative sampling. The sample should reflect the audience the organisation wants to understand, or be designed to support the intended analysis.
- Good questionnaire design. Questions should be clear, neutral and easy for respondents to answer. Scales should be consistent, and answer options should be complete.
- Adequate sample size. The sample must be large enough to support the level of analysis required, including any subgroup comparisons.
- Quality control. Responses should be checked for poor-quality data, including duplicates, speeders, straight-lining and inconsistent answers.
- Appropriate analysis. The analysis should match the research question. This may include descriptive statistics, cross-tabulations, significance testing, regression, segmentation or modelling.
- Strategic interpretation. The final output should translate data into implications, choices and recommended actions. A good chart shows what happened. A good insight explains why it matters.
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Understanding how many people to include in a survey is critical for ensuring reliability and power when used in an evaluation or for providing insights.
Example of quantitative research in practice
When a financial services client wanted to improve customer retention. An early qualitative research suggested several possible drivers of churn: poor onboarding, confusing fees, limited support and a lack of proactive communication.
We then conducted a quantitative survey with current and former customers. The results showed that poor onboarding and the lack of fee explanations were the strongest predictors of early account opening churn, while support mattered more for younger and multi-account customers. The analysis also showed that customers who receive proactive communication in the first 60 days were significantly more likely to stay.
This gave the business a clearer action plan. Instead of spreading investment thinly across every possible issue, it was able to prioritise onboarding, fee communication and targeted proactive support.
| For examples of quantitative research conducted by Eris Strategy, including mixed-method studies, see the case studies section. These are real case studies covering a broad range of industries and private and public-sector projects. |
Conclusion: quantitative research turns data into evidence for better decisions
Quantitative research is essential for organisations that need to understand their markets, customers, behaviours and trends. It helps answer questions about incidence, scale, frequency, difference and impact. It can show how many people think something, how strongly they feel, which groups differ and which factors are linked to important business outcomes.
Like all research methods, quantitative research has limitations. It may not fully explain the deeper reasons behind behaviour, and poor design can create misleading results. But when it is built around a clear business question, a strong sample and thoughtful analysis, it becomes a powerful tool for decision-making.
When combined with qualitative insight and strategic interpretation, quantitative research becomes even more powerful in helping to uncover issues and opportunities, understand the impact of strategies and determine prioritisation for investment.
| Eris Strategy has over 30 years of experience using quantitative research to help clients make clearer decisions, develop stronger strategies, and achieve better outcomes. Contact us to discuss how quantitative market research can support your next business decision. |
Frequently asked questions for quantitative research
What is quantitative research in simple terms?
Quantitative research is research that collects numerical data to measure attitudes, behaviours, preferences or trends. It is used to answer questions such as how many people think something, how often something happens or how strongly people feel about an issue.
How do quantitative and qualitative research methods differ?
Quantitative research measures patterns using numerical data, while qualitative research explores motivations, experiences and meanings. Quantitative research answers questions such as “how many” or “how much”. Qualitative research answers questions such as why or how.
What are the main types of quantitative research?
The main types of quantitative research include surveys, observation studies and data analysis. Surveys are often used for usage and attitude surveys, community needs, polls, tracking studies, concept testing, product and service concept testing, market uptake, pricing research, and segmentation research.
What are the benefits of quantitative research?
Quantitative research provides reliable evidence for decision-making that can show clear results between segments and markets and track changes over time.
What are the limitations of quantitative research?
Quantitative research may not fully explain why people behave in a certain way. It can also produce misleading results if the sample, questionnaire or analysis is poorly designed.
When should a business use quantitative research?
A business should use quantitative research when it needs to measure customer attitudes, market demand, brand performance, satisfaction, behaviour, price sensitivity, campaign effectiveness or differences between customer segments.