Introduction: What is quantitative research?
In today’s data driven world, quantitative research is the backbone of evidence based decision making. Whether launching a new product, refining a proposition, optimising pricing or profiling and segmenting audiences, organisations rely on quantitative methods to generate statistically robust, scalable and trackable insights.
As a leading market research agency, Bryter uses quantitative techniques to move beyond opinion and deliver measurable, actionable evidence. This article outlines what quantitative research is, the key methodologies used in market research, and when to apply each approach.
The strength of quantitative research lies in its ability to generalise findings to a wider population, typically through structured data collection methods such as surveys and experiments.
Advanced analytics turn quantitative research data into deeper, actionable insight. Methods including segmentation, regression, conjoint analysis and predictive modelling uncover the factors driving consumer choices, identify meaningful audience groups and quantify trade-offs. This enables businesses to predict behaviour, optimise propositions and make more confident, evidence-based decisions
Surveys: the foundation of quantitative research
Origins:
Surveys are the most widely used quantitative method, enabling researchers to collect structured data from large samples. How surveys are conducted has evolved over time.
Methodological developments:
Watch outs:
Designing effective market research surveys is deceptively difficul. Small errors in wording, structure or sampling can systematically distort results, often without being obvious until it’s too late. Key considerations and watch outs include
1. Sampling bias (who you ask): If your sample isn't representative, you risk skewing your results. Address this by ensuring you define your audience and structure your sample in a way that gives you a balanced view. Applying quotas to specific subgroups e.g by demographic profile, and weighting your data can both help to ensure that your sample accurately reflects the true state of the market you are researching
2. Response bias (how people answer): Even with the right sample, respondents don’t always tell the truth. This can happen for a number of reasons social desirability bias (giving what feel like the socially acceptable answer), acquiescence bias (tendency to agree with statements) or satisfying (rushing answers and defaulting to stock answers or consistent ratings). Key to minimising the negative affects of response boas is good survey design. Ensure surveys are not overly long and participants lose interest, avoid priming participants to give socially acceptable answers and ensure there is balance in terms of how attitudinal questions are structured with a mix of negative as well as positive statements. You can read more about the priming effect in the article 'What is the priming effect'
3. Survey design bias (how you ask): A poorly designed questionnaire will yield unreliable results. Leading questions, ambiguity, poorly balanced scales, missing or overlapping options and overly technical or complicated language can all cause issues. When designing a survey it is critical to keep language neutral and avoid priming the respondent as much as possible. To mitigate the risk of priming careful consideration needs to be given to the order questions are asked in e.g. asking participants to rate a product or service, before rating different aspects of their experience with it.
Before launching a survey, sanity check against:
✅ Is my sample representative?
✅ Are questions neutral, clear and single-minded?
✅ Are answer options balanced and exhaustive?
✅ Does the flow avoid priming or fatigue?
✅ Is every question essential to my objective?
✅ Has this been properly pilot tested?
Using surveys to quantify the size, shape, and dynamics of a market.
Typical applications:
They allow you to generalise findings to a wider population, answering questions like “how many” or “how often.”
Grouping customers into distinct segments based on behaviours, attitudes, or needs.
Typical applications:
Quantitative research is frequently used to evaluate new products, services and propositions. Respondents might be shown several concepts and asked to evaluate dimensions such as:
Price is another area where quantitative techniques can provide much more insight than simply asking customers what they would be prepared to pay.
Methods such as Van Westendorp price sensitivity analysis, Gabor-Granger and conjoint analysis can help investigate price perceptions, willingness to pay and the trade-offs consumers make between price and other product characteristics.
Why pricing research is used:
Pricing research can help organisations assess questions including:
Brand tracking is an ongoing quantitative research programme that measures how a brand’s position and consumer perceptions change over time. It typically surveys a consistent target audience at regular intervals, tracking metrics such as awareness, consideration, preference, usage, satisfaction, brand associations and advocacy.
Results are analysed over time and against key competitors to identify trends, assess the impact of marketing activity and understand changes in brand health. More advanced trackers can use techniques such as driver analysis, segmentation and statistical modelling to identify what is driving consideration, preference or purchase.
Why brand tracking and brand health research is used:
Repeating consistent measures regularly allows organisations to determine whether perceptions of the brand are changing and whether marketing activity is having the desired effect.
It can also provide competitive context by measuring the same indicators for rival brands.
Quantitative research becomes particularly powerful when sophisticated analysis is applied to the resulting dataset. Techniques can include:
These techniques allow researchers to move beyond simple percentages and averages.
For example, rather than reporting that satisfied customers are more likely to remain loyal, advanced analysis can investigate which aspects of the customer experience are most strongly associated with loyalty.
Similarly, segmentation can reveal hidden groups within a market, while conjoint analysis can quantify the trade-offs customers make when choosing between competing propositions.
In practice, the most effective research programmes often combine multiple methods leveraging their complementary strengths to build a holistic, insight driven understanding of audiences.
To read more about how market research services key sector like healthcare and pharmaceuticals, technology, gaming and B2B markets read our article ‘Bryter – market research company – an overview’
Get in touch with one of the insights team if you want to learn more about different approaches to market research and to understand which methodology may be most appropriate for your insight needs