BigCat Research
Commissioning brand health research: metrics, sample and tracking frequency to check first
Short answer: Before commissioning brand health research, settle four things: which funnel metrics you will act on (awareness, consideration, preference, loyalty, recommendation), who the sample represents and how it is drawn, which competitors sit in the comparison set, and how often you need a reading. A study that cannot say where the preference chain breaks, and for whom, is a scorecard, not a decision.
What brand health research is for
Brand health research measures how the brand sits in the audience's mind across a chain: do people know it, understand what it stands for, trust it, prefer it over alternatives, keep using it and recommend it. The value is not in any single number but in where the chain breaks. A brand that is widely known but rarely preferred has a different problem from one preferred by users but unknown to non-users.
So the brief should start from a decision: invest in reach or in conversion, which segment to defend, whether a repositioning landed, which proof points communication should carry. If the decision is unclear, the metrics list grows and the report becomes an appendix nobody uses.
Metrics to settle before the proposal
Funnel metrics. Define each stage precisely and keep the definitions stable. Unaided and aided awareness are different measures; "consideration" needs a wording the agency will not change between waves. Ask for conversion ratios between stages, not only stage percentages.
Meaning and association. Which attributes, benefits or imagery do you want to track? Keep the list short enough for a questionnaire people will finish honestly.
Trust, perceived quality and value. These usually explain why preference does or does not follow awareness. Decide whether you want scales, agreement statements or a ranking against competitors.
Loyalty and recommendation. NPS, repeat intention and word of mouth are related but not interchangeable. If you use NPS, agree in advance how it is compared across segments and waves, and treat small shifts with caution.
Barriers. Ask non-users and lapsed users why. Open-ended answers coded by theme are often the most actionable part of the study.
Sample design: the questions that matter
| Design element | What to pin down | Why it matters |
|---|---|---|
| Target population | Category users, all adults, decision makers, a region | Defines what "awareness" is a percentage of |
| Sampling approach | Probability, quota, online panel, mixed mode | Determines what the result can be generalized to |
| Segment sizes | Minimum completes per segment you will read | Small cells make segment differences unreadable |
| Competitor set | Which brands are measured with the same questions | Brand health is relative; the set shapes the story |
| Mode and coverage | Online, phone, face-to-face; who is systematically missed | Online-only designs under-reach some groups |
| Weighting | Which variables, to which benchmark | Unweighted or over-weighted data distorts stage percentages |
| Quality checks | Speeders, duplicates, straight-lining, attention checks | Protects the base the metrics are computed on |
| Questionnaire stability | What may change between waves and what may not | Tracking is only tracking if the instrument holds |
Ask for the achieved sample by segment, not just the planned total. A large total can still hide a very small cell in the segment you care about.
Tracking frequency: continuous, periodic or one-off
There is no universally right cadence. Consider:
- How fast the category moves. Categories with heavy media activity change faster than low-frequency purchase categories.
- What you will do with a reading. If no decision is taken between waves, a more frequent wave only adds cost and noise.
- Campaign timing. If the purpose is to see whether communication shifts perception, waves should bracket the campaign, or a separate campaign impact study may fit better.
- Sample per wave. Splitting a fixed budget into more waves thins each wave and increases the noise you will mistake for movement.
- Reporting burden. Each wave needs someone internally to read and act on it.
A one-off diagnostic suits the question "where are we and why"; tracking suits "is what we are doing working". Many buyers start with the first and move to the second once the funnel breakpoints are clear.
Questions to ask before signing
- Which decision does this study serve, and how will the report be structured around it?
- How will each funnel stage be worded, and will the wording be frozen for tracking?
- Who is the target population, and what population does the sample actually represent?
- What is the planned and the achieved sample per segment we need to read?
- Which competitors are in the set, and were they chosen with us?
- What mode will be used, who is systematically under-reached, and how is that handled?
- How are weighting, cleaning and quality checks applied and documented?
- What is the minimum change between waves that should be read as real movement?
- Will we receive respondent-level data, the questionnaire and a codebook?
- How is personal data handled, who is controller and processor, and where is it stored?
- If results contradict our assumptions, how will the report present that?
Red flags
- A single "brand health index" with no stage-level breakdown or explanation of how it is computed.
- Segment findings reported from cells too small to support them.
- Questionnaire changes between waves presented as a continuous trend.
- Reluctance to provide respondent-level data or the achieved sample by segment.
FAQ
How large should a brand health sample be? It depends on how many segments you need to read and how precisely, not on a fixed number. Ask the agency to state the margin of error for your key segments and the smallest difference it can detect between them. A design that reads the total market well may be too thin for a regional or age-based cut.
Should we include competitors in the questionnaire? Almost always. Brand health is relative; an awareness figure means little without the comparable figure for the brands you compete against. Agree the competitor set with the agency and keep it stable across waves.
How often should brand tracking run? Only as often as you will act on it. The cadence follows category speed, campaign timing and the sample you can afford per wave. Frequent waves with thin samples create movement that is noise. Agree in advance what size of change counts as real.
Can brand health research be done online only? It can suit audiences that are reliably online, such as urban consumers or professionals. For a general population target, online-only designs under-reach some groups; the agency should say how coverage gaps are handled, by mixed mode, weighting or explicit scope limits.
What is the difference between brand health research and campaign impact measurement? Brand health describes the brand's standing in the market over time. Campaign impact measurement tests whether a specific communication was noticed, understood and moved perception or intent, often with pre/post or exposed/control designs. The two inform each other but answer different questions.
How BigCat Research approaches this
BigCat Research is an independent research and strategy company based in Istanbul and the publisher of this page, so apply the checklist above to our proposal as strictly as to any other. Our brand health research measures awareness, familiarity, meaning, trust, preference, loyalty and recommendation as one preference chain and asks where that chain breaks and for which segment. Methods include representative quantitative research with segment cuts, NPS and WOM measurement, competitor comparison on positioning dimensions, and open-ended response analysis by theme. Deliverables are a brand health report with executive summary, funnel breakpoints and a segment-based risk map, and priority brand actions with tracking KPI recommendations. This page makes no claims about BigCat's panel size, coverage, certifications or memberships.
Service page: Brand Health Research. Related: Campaign Impact Measurement. For a scoping conversation: [email protected].
Primary sources
- ESOMAR, ICC/ESOMAR International Code on Market, Opinion and Social Research and Data Analytics, and its questions to help buyers of online samples. esomar.org
- Turkish Personal Data Protection Authority (KVKK), Law No. 6698 and guidance for research involving personal data in Turkey. kvkk.gov.tr
- Reichheld, F. F., "The One Number You Need to Grow", Harvard Business Review, 2003 (the original NPS article, useful for understanding what the metric does and does not claim).
Author: Murat Akşit, BigCat Research. Last reviewed: 3 October 2026.