Quantitative research—practical and to the point
Quantitative market research measures people’s opinions, preferences, and behaviour in numbers and percentages on a representative sample. It’s the right fit when you need to decide based on data: compare options, measure satisfaction, test a concept, or track change over time. At NMS, we primarily collect data via CAWI, CATI, and CAPI—and we put strong emphasis on quality (control mechanisms, ESOMAR/SIMAR standards).
Quick summary:
- results in numbers: how many people, how often, what matters more
- representative sample and the ability to generalise to the population
- data collection methods: CAWI / CATI / CAPI based on the target group and topic
- competitor comparison and measuring change over time (tracking)
- statistical analyses to uncover relationships and key drivers
- deliverables: data file + interpretation + recommendations (report / dashboard)
- suitable for CX, brand, product, and public opinion (depending on the brief)
- can be combined with qualitative research to explain the “why” (mixed-method)
Benefits you’ll see in practice
- Confidence in your decision—compare options and see what truly matters to your audience (not just “gut feel”).
- Competitive benchmarking—measure where you’re strong/weak and where investment makes sense.
- Measuring change over time—set up repeated measurement (tracking) and monitor shifts after changes in product, communication, or service.
- Driver prioritisation—we statistically isolate the factors that genuinely drive satisfaction, choice, or loyalty.
- Representative results—with the right sampling and methodology, you can generalise outcomes to the target population.
- Clear outputs—instead of a “pile of tables”, you get interpretation and recommendations you can defend internally.
When quantitative research makes sense
Quantitative research is the right choice when you need to measure the scale of a phenomenon and make a data-based decision—typically when you:
- want to find what most affects satisfaction and where customers drop off (builds on customer satisfaction and customer journey mapping)
- need to quickly test a concept / product / price / logo (see price testing and logo testing)
- are working on segmentation and need to validate segment sizes and behaviour (see customer segmentation)
- want to measure brand awareness and brand perception (see brand awareness research and brand perception & evaluation)
- need representative output for public opinion research
Deliverables you can actually use
So the result doesn’t stay “just in research”, we deliver outputs that work across teams:
- Key findings summary (what matters, what differs by segment, what the drivers are)
- Interpretation and recommendations (what to do and why)—not just numbers in a table
- Data output for further work (aggregations + option for follow-up analyses)
- Clear visualisations and reports—including interactive outputs in our online app
- If it makes sense, we can also help translate findings into CX management customer experience management
Data quality and credibility: the foundation of the whole study
Quantitative research only has value if you can rely on data quality. That’s why we:
- develop our own data-collection interfaces and quality control mechanisms
- follow standards and are members of ESOMAR and SIMAR
- work with an experienced analytics team and advanced statistical approaches
- run an online panel footprint in Central Europe (with respondent verification)
Questions and answers
What is quantitative research and when is it used?
Quantitative research answers “how many” and “how much”. Qualitative research explains “why”. In many cases, the best approach is to combine both.
What’s the difference between quantitative and qualitative research?
CAWI is an online questionnaire, CATI is phone interviewing, and CAPI is face-to-face interviewing with a tablet. We choose the method based on the target group, topic, and the level of representativeness required.
How many respondents do I need for the research to be representative?
It depends on the population, target groups, and the required precision. The key is correct quota/sampling design and methodology—not just “as many people as possible”.
Will I get only tables, or also interpretation?
It’s not just about numbers—the goal is interpretation and recommendations so the results can be used in decision-making.
Can we benchmark against competitors or track development over time?
Yes—quantitative research is a natural fit for benchmarking and tracking (comparison and change over time are typical advantages).
When does it make sense to add qualitative research as well?
When you need to understand motivations and explain the “why” behind the numbers—for example before designing a questionnaire, or after surprising findings.
