quantitative marketing research

Quantitative marketing research for growth marketers

Article written by

Stuart Brameld

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.

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 / Generalizable 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:

Identifying and tracking market trends
Segmenting customers based on measurable criteria (such as demographics, buying behaviours, and psychographics)
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.

Quant research tactics & tooling

Modern tooling has made it easier to observe people in general now, and to gather both qual an quant data at infinite scale. Here are some popular tools and use cases.

Web analytics: Track and observe people and events on your website - Google Analytics, PostHog, Amplitude, MixPanel
Product analytics: Track and observe people and events in your product - PostHog, MixPanel, Amplitude
Data analytics: Visual analytics platform - Tableau

Structure data & 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 predicts 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 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.