Quantitative research
Quantitative research is a research methodology that collects numerical data from large samples to measure, compare, and statistically validate consumer attitudes, preferences, and behaviors. Common methods include surveys, polls, MaxDiff exercises, and conjoint analysis — producing statistically reliable findings that can guide decisions at scale and be generalized to a broader population.
Why it matters
Quantitative research answers the questions that require scale and statistical confidence: How many customers feel this way? Which concept scores highest? Is this difference real or random variation? Because it collects structured data from large samples, quantitative research is repeatable, comparable, and trackable over time — making it the backbone of brand tracking, concept validation, pricing research, and segmentation.
Common quantitative methods
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SurveysStructured questionnaires with closed-ended questions (rating scales, multiple choice, ranking) delivered to a defined sample. The most widely used research method in consumer insights.
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PollsShort, single-question (or very short) surveys designed for rapid feedback — used for pulse-checking or real-time decisions where speed matters more than depth.
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MaxDiffA forced-choice exercise that identifies which features, messages, or attributes consumers value most and least — more discriminating than a standard rating scale.
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Conjoint analysisA technique that simulates real trade-off decisions by presenting respondents with combinations of attributes (price, features, packaging) to identify what drives preference.
Use cases
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Concept testing — scoring multiple product or message concepts with a large sample to identify a clear winner
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Brand tracking — measuring awareness, consideration, and NPS at regular intervals to monitor brand health
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Pricing research — using conjoint or van Westendorp methods to identify optimal price points
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Segmentation — identifying distinct audience groups based on attitudes, behaviors, or needs
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Campaign measurement — pre/post studies that measure the impact of a marketing campaign
A technology company is considering three pricing tiers for a new product. They run a MaxDiff study with 500 target users to identify which feature bundles drive the most perceived value at each tier — giving the product team data-driven guidance on packaging that a subjective internal debate could never produce.
Run quantitative research with your own audience on Fuel Cycle
Surveys, polls, MaxDiff, conjoint — all running against your owned research audience, with AI-powered analysis that compresses results into insight.