Table of contents
- Why use quantitative research?
- Quantitative vs qualitative methods
- What is quant marketing research good for?
- Quantitative marketing research methods and techniques
- Quantitative marketing research examples
- Quant research tactics & tooling
- Structured data and the AI revolution
- Food for thought
- More on qualitative marketing research
- About Growth Method
- Frequently asked questions
Quantitative marketing research is the collection and analysis of numerical data, such as survey responses, web analytics and experiment results, to measure what customers do and how many do it. Also called quantitative market research, it shows marketers the size and pattern of a behaviour, so they can make growth decisions with evidence rather than opinion.
Why use quantitative research?
Quantitative research (along with qualitative research) is often undertaken to reduce risk when making big decisions in growth. You can use research to learn more about your target audience, customer pains, onboarding friction and more.
Perhaps most important for growth marketers, user research is one of the best sources of test ideas.
Quantitative vs qualitative methods
As you likely know - quant gives you the what, qual gives you the why. Quant research will tell you that most users drop off at step 3. Qual research will help you to understand why.
| Qualitative | Quantitative | |
|---|---|---|
| Purpose | To explore ideas, concepts, or experiences | To quantify data and identify patterns |
| Nature of data | Non-numerical (words, images, observations) | Numerical (statistics, metrics, graphs) |
| Data collection methods | Interviews, focus groups, observations, open-ended surveys | Structured surveys, experiments, longitudinal studies |
| Analysis | Thematic analysis, narrative analysis, content analysis | Statistical analysis, mathematical models, computational techniques |
| Sample size | Smaller, non-representative samples | Larger, representative samples |
| Outcome | In-depth understanding of phenomena | Generalisable results, statistical significance |
| Flexibility | Flexible, can adapt during the research process | Structured, follows a fixed research design |
What is quant marketing research good for?
Quantitative market research is particularly good at observing trends over time, such as:
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Identifying and tracking market trends
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Segmenting customers based on measurable criteria (such as demographics, buying behaviours, and psychographics)
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Measuring the effectiveness of different marketing and advertising campaigns
Quantitative marketing research is typically performed at larger (potentially infinite) scale although the insights tend to be relatively thin and shallow compared with its quant research cousin.
Quantitative marketing research methods and techniques
Most growth teams rely on a handful of quantitative techniques. Each one answers a different question about your audience.
| Method | What it measures | Example |
|---|---|---|
| Surveys | Attitudes, preferences and awareness from structured, closed-ended questions | A brand awareness survey sent to a sample of your target accounts |
| Polls | A single quick question put to a large audience | An in-product poll asking which feature visitors want next |
| A/B and multivariate tests | The effect of a change on a metric. See A/B testing | Two landing page headlines tested against sign-up rate |
| Web and product analytics | What users do, at scale. See conversion funnels | Tracking drop-off at each step of the sign-up flow |
| Longitudinal studies | How a measure changes over time for the same group | Tracking one cohort’s retention and satisfaction across 12 months |
Teams that run tests continuously turn these techniques into a habit. Our guide to marketing experimentation covers how.
Quantitative marketing research examples
Here are four examples growth marketers use most often:
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Funnel drop-off analysis. Measure the share of visitors who complete each step from landing page to sign-up, then find the step that loses the most people.
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NPS survey. Ask customers how likely they are to recommend you on a 0 to 10 scale, then track the score by segment over time.
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Pricing survey. Ask a representative sample which price points feel too cheap, fair or too expensive, then use the spread to set a test range.
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Campaign attribution analysis. Compare how channels contribute to sign-ups using an attribution model, so budget follows evidence.
Quant research tactics & tooling
Modern tooling has made it easier to observe people in general now, and to gather both qual and quant data at infinite scale. The most reliable quant data is first-party data: numbers you collect yourself from your site, product and customers. Here are some popular tools and use cases.
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Web analytics: Track and observe people and events on your website - PostHog, Google Analytics, Amplitude, Mixpanel (see PostHog vs Google Analytics)
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Product analytics: Track and observe people and events in your product - PostHog, Mixpanel, Amplitude
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Data analytics: Visual analytics platform - Tableau
Structured data and the AI revolution
Similar to how AI is likely to revolutionise unstructured data, there are likely to be significant changes within structured data as well. We believe the most significant of these will be the ability to supplement real visitor data with synthetic audience data to solve a number of today’s challenges.
Using synthetic data is likely to transform the A/B testing playbook by offering a faster, more effective, privacy-conscious alternative for testing new features, marketing and brand messaging when granular data is difficult to obtain. Gartner estimated in 2022 that by 2030, synthetic data will completely overshadow real data in AI models.
Food for thought
Science does not bring absolutely certainty to ideas, but rather provides a systematic way of understanding the world through observation, experimentation, and theoretical explanation.
Similarly, in growth our goal is to gather both qualitative and quantitative insights at every opportunity in order that we can better meet the needs of our users and customers’ needs, which ultimately translates to business value.
More on qualitative marketing research
The UX Research reckoning is here | Judd Antin (Airbnb, Meta) https://www.lennyspodcast.com/the-ux-research-reckoning-is-here-judd-antin-airbnb-meta
Tools and tactics for modern user research | Noam Segal https://www.dive.club/deep-dives/noam-segal
About Growth Method
Quantitative research only pays off when it changes what you do next, and most marketing teams now have more numbers than they can act on.
Growth Method gives B2B marketing teams AI agents that run their campaigns: plan, launch and analyse, from live data, against one goal. The agents read your first-party data from tools such as PostHog, GA4 and Search Console, rank campaign ideas by their likely effect on your goal, record the before-metrics at launch, and analyse each finished campaign so you know what worked and why. That turns quantitative research into a repeating loop of evidence and action instead of a one-off report. 2,400+ campaigns have been planned, launched and analysed on Growth Method.
“We are on-track to deliver a 43% increase in inbound leads this year. There is no doubt the adoption of Growth Method is the primary driver behind these results.”
Laura Perrott, Colt Technology Services
Get started, connect your marketing stack, and the numbers you already collect start turning into campaign ideas within days.
Frequently asked questions
What is quantitative marketing research?
Quantitative marketing research is the collection and analysis of numerical data, such as surveys, web analytics and experiment results, to measure what customers do and how many do it. It is also called quantitative market research.
What is the difference between quantitative and qualitative marketing research?
Quantitative research gives you the what: numbers, patterns and trends at scale. Qualitative research gives you the why: motivations and context from smaller samples. Most growth teams use both, with quant to find where the problem is and qual to understand it.
What are examples of quantitative research methods?
Common methods include structured surveys, polls, A/B and multivariate tests, web and product analytics, and longitudinal studies that track the same measures over time.
What tools are used for quantitative marketing research?
Popular tools include PostHog, Google Analytics, Amplitude and Mixpanel for web and product analytics, and Tableau for visual analytics. Survey tools and A/B testing platforms cover the rest.