Market Research (Edexcel 9BS0 1.1.2)
Topic 1.1.2 examines how businesses gather and use information to identify and anticipate customer needs. Examiners like it because every product decision in a case study can be traced back to the quality of the research behind it.
Primary and secondary research
Primary research is first-hand data collected for a specific purpose: surveys, focus groups, interviews, observation and test marketing. It is up to date and tailored to the firm's exact question, but slow and expensive to collect. Secondary research uses existing data such as government statistics, Kantar grocery share reports, Mintel industry studies and a firm's own sales records. It is fast and cheap but may be out of date or gathered for a different purpose.
Large retailers combine both. Tesco's Clubcard scheme, analysed by its data business Dunnhumby, records the actual purchases of millions of households, giving Tesco continuous primary data on buying habits that it uses to set promotions and ranges. A start-up, by contrast, may rely on free secondary sources plus a small survey. The right mix depends on cost, the money at stake in the decision, and how fast the market is moving — product development usually justifies primary research, while an initial market-size estimate rarely does.
Quantitative and qualitative data, and sampling
Quantitative data is numerical — how many, how often, at what price — and is easy to analyse and compare. Qualitative data explores reasons, attitudes and feelings through focus groups and open interviews; it explains the why behind the numbers but is harder to generalise. Strong exam answers show the two working together: a survey might show that 40% of customers rejected a product, while a focus group reveals it was the packaging, not the price.
Because firms cannot ask everyone, they use sampling — collecting data from a group intended to represent the target population. Edexcel expects you to weigh sample size against cost: a bigger, better-designed sample cuts the chance of unrepresentative results but raises expense and delay. A gym-wear brand surveying only its own Instagram followers gets fast, cheap responses, yet the sample is biased towards existing fans and will overstate enthusiasm for new releases. Sample design matters as much as sample size.
Bias, limitations and the role of ICT
Research can mislead. Bias arises from leading questions, unrepresentative samples, or respondents saying what they think the interviewer wants to hear. Secondary data carries its own limits: a 2023 industry report may miss a shift that happened in 2025. This is why test marketing — launching in a limited area first — remains popular: real purchases are more honest than stated intentions.
ICT has changed how research is done:
- Loyalty and app data — the Greggs App and Tesco Clubcard record real transactions continuously.
- Social media monitoring — brands track mentions, reviews and engagement to spot trends early; Gymshark grew by reading and responding to its online community.
- Website analytics — abandoned baskets and click paths show where an online store loses customers.
These sources are cheap and vast, but they only describe existing customers, so firms entering new segments still need conventional research.
Key terms
Practice questions
Explain one benefit to a start-up of using secondary market research before launch. [4 marks]
Model answer guidance: Identify a benefit such as low cost and speed, then build the chain: a start-up has limited finance, secondary sources such as free industry reports give an immediate estimate of market size, which reduces spending before revenue exists and lowers the risk of entering a shrinking market. Keep it to one developed benefit — two shallow points score less than one deep one.
Explain one limitation of using social media followers as a research sample. [4 marks]
Model answer guidance: State the limitation: followers are existing fans, so the sample is unrepresentative. Develop: their responses will be more positive than the wider market, leading the firm to overestimate demand, which could cause overproduction or a failed wider launch. An application point, such as a clothing brand polling its Instagram audience, completes the answer.
Discuss the value of qualitative research to a food retailer developing a new product range. [8 marks]
Model answer guidance: Analyse the value: focus groups reveal why customers choose or reject flavours and packaging, insight a sales figure cannot give, guiding design before costly launch. Counter-analyse: small groups may be unrepresentative, results are hard to compare, and skilled moderation costs money. Use a retailer such as Greggs trialling menu items as context and reach a brief judgement, for example that qualitative research works best alongside sales data from test stores.
Assess whether loyalty-card data is more useful than traditional surveys for a supermarket planning promotions. [10 marks]
Model answer guidance: For loyalty data: it records real behaviour from millions of shoppers continuously, avoids the honesty problem in surveys, and is cheap once systems exist — Tesco's Clubcard analysis via Dunnhumby is the standard example. Against: it says nothing about non-customers or reasons behind behaviour, and privacy rules limit its use. Judgement: strongest for targeting existing shoppers; surveys still needed to understand rivals' customers.
Assess the importance of market research to a business entering a dynamic market. [12 marks]
Model answer guidance: For: in fast-changing markets, current data reduces the risk of launching the wrong product, and continuous digital research spots trends early. Against: research describes the past and present, can be outdated by launch day, and speed of entry may matter more than perfect information — some firms succeed by launching quickly and adapting. A top answer weighs cost, speed and accuracy, and concludes that the value depends on how much is at stake and how fast the market moves.
Examiner tips
- Link the research method to the decision being made — examiners penalise generic lists of methods that ignore the case context.
- If data in the case comes from a small or biased sample, say so explicitly and explain how it weakens the conclusion being drawn.
- Use the phrase 'identify and anticipate customer needs' — it mirrors the specification wording and signals accurate knowledge.
In The Business School simulation your students make these exact decisions in a live market against rival firms — every choice mapped to the specification. Free teacher demo, no installs, students join with a PIN.