Market research methods and sampling: primary and secondary research, quantitative and qualitative data, the main methods and their costs and reliability, and sampling methods including random, quota and stratified sampling.

What this dot point is asking

WJEC Unit 1 wants you to know how a business finds out about its market: the difference between primary and secondary research and between quantitative and qualitative data, the main methods with their costs and reliability, and how a firm chooses a sample that represents its customers. Strong answers match the method to the firm's budget and purpose, and they explain why a poor sample produces misleading results.

The answer

Primary and secondary research

The trade-off is straightforward. Primary research is relevant and up to date because it answers the firm's exact question, but it is expensive and slow. Secondary research is cheap and quick because the data already exists, but it is general and may be out of date or not quite fit the firm's needs. Most firms use both: secondary research to size the market and primary research to test their specific idea.

Quantitative and qualitative data

• Quantitative data is numerical - how many people would buy, at what price, how often. It is easy to compare and put into charts, and it suits large samples.
• Qualitative data is descriptive - customers' opinions, motives and feelings, the "why" behind their choices. It gives depth and insight but is harder to measure and easy to interpret subjectively.

The main methods

The choice depends on the budget, the time available and whether the firm needs numbers (quantitative) or reasons (qualitative). A start-up with little cash leans on free secondary data and low-cost online surveys.

Sampling

A firm cannot ask every potential customer, so it surveys a sample and treats the result as representative of the whole population (all the people of interest). The method of choosing the sample matters:

• Random sampling - every member of the population has an equal chance of selection; it removes bias but can be expensive and may by chance miss key groups.
• Quota sampling - the sample is filled to match set proportions (for example 50% female, 30% under 25); it is cheaper and ensures key groups appear, but the within-quota choice can be biased.
• Stratified sampling - the population is split into strata (groups) and sampled in proportion to each stratum's size; it is representative but needs accurate information about the population first.

A larger, more representative sample gives more reliable results, but it also costs more, so firms balance accuracy against budget.

Examples in context

Example 1. A cash-strapped start-up. A person launching a food-truck business in Cardiff has almost no research budget. They use free secondary data (council footfall figures, competitors' menus and prices online) to size the market, then run a free social-media poll and chat to potential customers at events for primary feedback. The approach shows how a small firm gets useful research cheaply, accepting that small, self-selecting samples are less reliable than a funded survey.

Example 2. An established firm using stratified sampling. A larger Welsh food producer testing a new product splits its customer base into strata by region and age and samples each in proportion, so the results genuinely reflect its whole market rather than one area. Because it knows its customer profile from sales records, stratified sampling is feasible and produces representative data. The contrast with the food truck shows how budget and existing data widen a firm's research options.

Try this

Q1. Define the term primary research. [2 marks]

• Cue. The collection of new, first-hand data for a specific purpose, for example through questionnaires, interviews, focus groups or observation.

Q2. Explain one advantage of using quota sampling. [3 marks]

• Cue. It is cheaper than random sampling and ensures that key groups (for example by age or gender) appear in the sample in set proportions, so important segments are not missed.