Market research is the process of collecting and analysing information about a market, to help a business understand its customers, competitors and the wider market.
Why businesses carry it out:
To identify customer needs and wants before developing or launching a product
To spot gaps in the market
To monitor competitor activity
Why it's valuable: it reduces uncertainty and supports better-informed decisions, improves targeting, identifies trends and market changes, and supports business planning.
Primary Research
Primary research involves collecting new data that did not exist before — the business designs the research to answer a specific question. It's tailored to the business's needs, so it's usually more relevant, but also more expensive and time-consuming than secondary research.
Methods: surveys and questionnaires, interviews, focus groups, observation.
Secondary Research
Secondary research uses data that already exists, collected by someone else. It's quicker and cheaper to access than primary research, but it may not be specific enough to answer the business's exact question.
Sources: government statistics, trade publications and industry reports (e.g. Mintel), competitor analysis, internal data and accounts, internet searches, books and journals.
Businesses choose between primary and secondary research (or use both) based on timescale, purpose, reliability needed, and budget available.
Qualitative vs Quantitative Data
Quantitative data is information you can measure — statistical data, such as "how many units do you buy each week?" It's easy to compare and analyse, and quicker and cheaper to scale up (an online survey can reach thousands of people), but it can miss the context behind the numbers — a 15% sales decline tells you there's a problem, not what caused it.
Qualitative data is information about people's attitudes, beliefs, feelings and opinions — such as "what do you think of this product?" It gives rich insight into customer motivations, but is harder to analyse, can't easily be turned into statistics, takes longer to collect per person, and is more prone to researcher bias in how questions are asked and responses interpreted.
Confidence Levels & Confidence Intervals
When a business conducts quantitative research using a sample rather than the whole population, it needs to know how reliable the results are.
Confidence level tells you how sure you can be that the results are accurate. A 95% confidence level is standard — it means that if you repeated the research 100 times, you'd get a similar result 95 times.
Confidence interval is the margin of error. If a survey finds 60% of customers prefer Product A, with a confidence interval of ±3%, the true figure is likely between 57% and 63%.
Larger sample sizes produce narrower confidence intervals (more precise results), but cost more to collect — businesses must weigh the cost of a larger sample against the value of more precise data.
Real-World Case Studies
Greggs — using customer data to guide new products
Greggs has increasingly used customer insight to shape its menu, rather than guessing what will sell. The Greggs app and loyalty scheme now generate detailed data on customer purchase behaviour, which the business uses alongside sales trend data to decide what to launch — recent menu additions have included a chicken sausage roll, an enhanced salad range and iced matcha lattes, all aimed at broadening the brand's appeal across more dining occasions. This shows secondary/internal data (its own sales and loyalty figures) being used directly to steer new product development, rather than relying on guesswork.
Source: verified via search, September 2026 — Insider Media and Marketing Week coverage of Greggs' 2025/26 results and menu strategy.
Political opinion polls — confidence intervals in practice
UK opinion polls are a familiar real-world example of confidence intervals at work. Pollsters survey a sample of a few thousand voters rather than the whole electorate, and responsibly-reported polls state a margin of error (typically around ±3 percentage points) alongside the headline figures. This is exactly the concept covered above: the poll result is an estimate, not a certainty, and a candidate on "38%, ±3%" could genuinely be anywhere between 35% and 41% in the full population. It's a useful everyday example of why a business (or a pollster) reporting research results should always be transparent about how confident they are in those numbers.
Source: this describes standard, widely-documented UK polling methodology (sampling with a stated margin of error), not a single named study.
Sort It: Primary or Secondary Research?
Tap a research method below, then tap whether it's primary or secondary research.
Primary Research
Secondary Research
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Quick Knowledge Check
Short, snappy recall questions — tap to reveal the answer.
Give one method of primary research. (1 mark)
Any one of: surveys/questionnaires, interviews, focus groups, observation.
What is quantitative data? (1 mark)
Information/data that can be measured — statistical data.
What does a 95% confidence level mean? (2 marks)
If the research was repeated 100 times, a similar result would be found 95 times — it's a measure of how sure you can be the results are accurate.
Key Term Flashcards
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Tap a card to flip it, then rate yourself.
Primary Research
Collecting new data that didn't exist before, designed to answer a specific question — e.g. surveys, interviews, focus groups, observation.
Secondary Research
Using data that already exists, collected by someone else — e.g. government stats, trade reports, competitor accounts.
Qualitative Data
Information about attitudes, beliefs, feelings and opinions. Rich but harder to analyse and more prone to bias.
Quantitative Data
Measurable, statistical data. Easy to compare and scale up, but can miss the context behind the numbers.
Confidence Level
How sure you can be the results are accurate — 95% is the standard used.
Confidence Interval
The margin of error around a result — e.g. 60% ±3% means the true figure is likely between 57% and 63%.
A*/A Stretch
Examiner's eye
Don't just say a business "did market research" — top-band answers name the specific type (e.g. "conducted a customer focus group, a form of primary, qualitative research") and link it explicitly to a decision the business needs to make. Vague references to "research" without specifying primary/secondary or qualitative/quantitative rarely reach the top mark band.
Common misconception
A bigger sample doesn't automatically mean "more accurate" in every sense — it narrows the confidence interval (more precise), but the confidence level and precision are only meaningful if the sample is also representative of the target population. A huge but biased sample can still give misleading results.
Try This With AI
Before using this: AI tools can get facts or mark scheme details wrong, and quality varies by tool. Always check anything factual against your notes or ask your teacher.
Give me a short business scenario, then ask me to recommend one primary and one secondary research method the business could use, and to explain one advantage and one drawback of each. Mark my answer and tell me if I've clearly distinguished primary from secondary and qualitative from quantitative.