3.2 Market research

Market research collects and analyses information about customers, competitors and the wider market to reduce uncertainty about an idea or decision.

Research is valuable only when the question is clear, the sample and method fit the decision and the evidence is interpreted cautiously.

Before launching a snack, a firm might test flavour, price and purchase context with the target segment rather than ask a broad “do you like it?” question.

Research cannot guarantee demand; respondents may report intentions that differ from actual behaviour.

Primary research collects new information for the specific question; secondary research uses existing information collected for another purpose. Each can be qualitative or quantitative.

Primary data can be tailored but costs time and money. Secondary data is faster but may be outdated, biased, inaccessible or measured with a different definition.

A firm may combine official population data with its own interviews and a product trial; the sources answer different parts of the decision.

“Primary” does not mean accurate and “secondary” does not mean weak; judge method, relevance and credibility.

A sample is a subset of the target population. Random, systematic, quota, stratified and convenience methods trade representativeness, cost, access and control in different ways.

Define the population, sampling frame, sample size and selection rule before collecting data. Bias can arise when accessible people differ from the population.

A school survey taken only from volunteers may over-represent highly engaged pupils; stratifying by year group and using a consistent selection rule can improve coverage.

A large sample is not automatically representative, and a small purposive sample may be appropriate for exploratory interviews.

Research data may be quantitative or qualitative, primary or secondary, and structured or open-ended. Before using it, check definitions, missing values, timing, sample and collection method.

Percentages, averages and charts summarise evidence but can hide base size, wording effects or subgroup differences. Interpretation must stay within what the design supports.

“70% prefer option A” means little without the number surveyed, question wording and whether respondents represent the target market.

A precise-looking chart is not automatically reliable evidence; data quality precedes presentation.