In every market research project, the difference between meaningful insight and wasted effort lies in one critical decision: what exactly should be measured. Businesses often fall into the trap of collecting a flood of data without direction. The result is reports filled with numbers that look impressive but fail to guide real business actions. To avoid this pitfall, researchers must begin with a clear, systematic process of determining what to measure, ensuring the data collected aligns with business needs, consumer realities, and decision-making priorities.
The process is not about measuring everything but about measuring the right things. Below, we’ll explore how to make these choices effectively.
The foundation of every market research study is its objective. Objectives define the purpose of the study and should directly guide measurement choices. For instance, if the goal is to understand consumer satisfaction, then metrics like Net Promoter Score (NPS), satisfaction ratings, and service quality perceptions are crucial. But if the objective is to test product-market fit, then willingness to pay, feature importance, and purchase intent become far more relevant.
A simple but powerful question to ask is: What decision will this research help us make? If a metric does not contribute to that decision, it probably does not need to be measured.
Once the objective is clear, the next step is to break it into specific business questions. These questions turn broad goals into measurable targets.
For example, consider a company exploring entry into Vietnam’s healthy snack market. Its objective might be: Assess consumer acceptance of new snack products. That can be broken down into business questions such as:
What are consumers’ current snacking habits?
Which product attributes (taste, packaging, health claims) matter most?
How price-sensitive is the target audience?
Each of these questions points directly to variables that must be included in the research.
Business questions naturally lead to measurable variables. These usually fall into four categories:
Demographic and Profiling Variables – Basic information such as age, gender, income, location, and occupation. These are essential for understanding who the respondents are and segmenting the results.
Behavioral Variables – Data on what respondents do, including frequency of purchase, preferred channels, brand switching, or trial of new products.
Attitudinal Variables – Insights into how respondents feel, such as perceptions of value, satisfaction, trust, and brand loyalty.
Market Environment Variables – External context such as competitor performance, distribution availability, and category trends.
By organizing variables this way, researchers can ensure that no essential dimension of the market is missed.
Not all variables carry equal weight. A strong market research design emphasizes metrics that lead to action. For instance, while it may be interesting to know whether respondents recognize a brand’s advertising colors, that knowledge rarely drives business decisions. On the other hand, understanding why customers churn, which features they prefer, or how much they are willing to pay provides actionable intelligence.
A guiding principle here is: If you cannot act on it, do not measure it.
Determining what to measure also depends on the research design. Qualitative research explores attitudes, motivations, and the “why” behind behaviors. It measures depth—what people say, feel, and mean. Quantitative research, by contrast, measures scale—how many people share a behavior or attitude.
For example:
In the early stage of testing a new app, qualitative focus groups might reveal pain points in the user experience.
In the next stage, quantitative surveys might measure how widespread those pain points are among a larger population.
Both are valuable, and choosing the right balance ensures that research is both rich in insight and statistically reliable.
Another critical step is ensuring that stakeholders—marketing teams, product managers, senior leadership—are aligned on what needs to be measured. Different teams may have different priorities, and early alignment ensures that the chosen metrics serve multiple needs. This also increases the likelihood that research findings will be used, not shelved.
When stakeholders are engaged in defining what to measure, the research gains both relevance and organizational buy-in.
Even with careful planning, some measurements may not perform as expected. For example, a survey question might confuse respondents or fail to capture the intended meaning. That’s why pilot testing is essential. Testing on a small sample ensures clarity, validity, and efficiency before the main research is conducted.
This step may reveal the need to add, remove, or refine certain measures, making the final study stronger and more precise.
A common mistake in market research is to overload questionnaires or discussion guides with too many questions. While it may seem efficient to collect “as much as possible,” it often leads to respondent fatigue, poor-quality data, and bloated reports.
The best research instruments are lean, purposeful, and focused. Every question should earn its place by directly tying back to the objectives.
Ultimately, the value of research is not in the data itself but in the actions the data enables. Deciding what to measure is about clarity, discipline, and alignment. Done well, it ensures that research delivers real insight—insight that helps businesses make smarter decisions, anticipate customer needs, and compete effectively in the marketplace.
