4.1 Market research
- Syllabus
- 2026
- Topic
- 4.1
- Level
- —
Market research is the systematic collection and analysis of information about customers and markets. It helps a business reduce uncertainty before committing resources; it cannot remove risk or guarantee demand.
| Purpose | Evidence sought | Decision it can inform |
|---|---|---|
| identify and understand customer needs | desired features, service expectations, price sensitivity and reasons for choice | product design, service, price and promotion |
| identify a market gap | needs not well served by current offers and competitors | whether and how to launch or position an offer |
| reduce risk | likely demand, objections and trial response before a large commitment | test, modify, delay or reject a launch/expansion |
| inform business decisions | relevant evidence on customers, competitors and market conditions | marketing mix, location, target segment and capacity |
Build the reasoning as uncertainty → evidence → changed decision → lower exposure. Example: research reveals that target customers value battery life more than an extra feature → the design budget shifts toward battery performance → the offer better matches the identified need and costly launch failure becomes less likely.
Research is most useful when it asks the right people a clear question at the right time. Tastes can change, respondents may not behave as stated, competitors can react and a small sample may not represent the market, so managers must weigh cost, time and decision importance.
Market research reduces uncertainty; it does not prove a product will succeed. A market gap is commercially useful only if enough reachable customers want the offer and the business can serve them profitably.
Primary research collects new data first-hand for the business's current question. Secondary research uses data already collected by another person or organisation. The best method depends on the decision, required detail, population, time, cost and reliability—not simply on whether it is primary or secondary.
| Method | Type | Best used for | Main limitation |
|---|---|---|---|
| survey/questionnaire | primary | standardised answers from many respondents; closed questions can quantify patterns | low response, misunderstood or leading questions, shallow answers |
| focus group | primary | exploring reasons, reactions and ideas through discussion | small group may be unrepresentative; dominant voices or moderator bias |
| observation | primary | recording what people actually do in a setting | behaviour is visible but motives may remain unknown; observer effects |
| test marketing | primary | trialling an offer in a limited market before full launch | costly/time-consuming; competitors see the offer and the test area may not generalise |
| internet | secondary | quick access to competitors, trends and published information | source quality, relevance and date vary widely |
| market report | secondary | organised industry size, trends, segments and forecasts | may be expensive, broad, methodologically unclear or dated |
| government report | secondary | official demographic, economic or industry data | may be aggregated, slow to update or not specific to the decision |
Select by fit. A questionnaire can estimate how many customers prefer an option; a focus group can probe why; observation can test actual behaviour; a test market can reveal trial purchase. Secondary evidence can first map the market, then targeted primary research can fill the decision-specific gap.
Primary data can be current and specific but usually costs more time and money. Secondary data is often faster and cheaper but may have been collected for another purpose. Combining methods can triangulate findings when the decision justifies the extra cost.
A method name alone is not a justification. Link the method's data to the named decision and population, then qualify sample, response, cost and time. Internet research is secondary when using existing online information; an online questionnaire is primary because it collects new responses.
Quantitative data is numerical, such as ratings, prices, counts and percentages. Qualitative data captures attitudes, beliefs, intentions and reasons. Numbers show the size or frequency of a pattern; explanations help reveal why it exists. Strong decisions often need both.
| Evidence | Processing | Decision use | Check |
|---|---|---|---|
| membership prices customers are willing to pay | frequency, percentage or average | set/test a price range | sample includes the intended customers; average is not hiding distinct segments |
| satisfaction ratings over time | mean/median and a line or bar chart | locate a service problem and monitor change | same question, scale, timing and population are used |
| open comments about a recipe | code recurring themes and retain important minority views | modify features or investigate objections | coding is consistent; vivid comments are not mistaken for majority opinion |
| social-media reactions | counts plus themes, compared across posts/platforms | detect rapid feedback and emerging issues | users are self-selecting; bots, duplicates, algorithms and sentiment ambiguity are considered |
Choose a display that matches the data: bars compare categories, a line shows change over time, and a pie chart shows parts of one whole when categories are mutually exclusive. Label axes, units, time period, sample size and source; truncated scales or missing denominators can exaggerate differences.
Audit evidence with five questions: Who was sampled and how? How large and representative was the sample? Were questions neutral and understood? Is the source current and transparent? Do another method or source produce a similar pattern? Reliability improves with representative sampling, consistent collection and triangulation.
More data is not automatically better. A precise average from a biased sample can mislead, social-media volume is not the same as population demand, and correlation in a chart does not by itself show cause. State what the evidence supports and what remains uncertain.