the distinction between primary research and secondary research and the main features of each

3.2 Market Research – Primary and Secondary Research

Learning Objective

By the end of this section students will be able to:

• Explain why market research is carried out and list its main purposes.
• Distinguish between primary and secondary research, describing the main features, advantages and limitations of each.
• Explain the need for sampling, recognise its limitations and calculate a basic sample size.
• Assess the reliability and validity of data sources.
• Apply basic quantitative and qualitative analysis techniques to interpret research findings.

3.2.1 Purpose of Market Research

Market research supplies the information a business needs to make informed decisions. The Cambridge syllabus lists six core purposes; each is illustrated with a real‑world example.

Purpose	What it means	Illustrative example
Estimate market size and growth rate	Determine how many potential customers exist and how fast the market is expanding.	A start‑up producing smart‑home devices uses Statista’s 2023 report to estimate a 12 % annual growth in the UK smart‑home market.
Identify and evaluate existing and potential competitors	Analyse who is already selling similar products and any new entrants.	A fashion retailer reviews competitors’ annual reports and social‑media activity to map the competitive landscape in fast‑fashion.
Develop a detailed customer profile (demographics, psychographics, buying behaviour)	Build a picture of the typical buyer – age, income, lifestyle, motivations.	A coffee chain creates a persona of “Urban Professionals, 25‑35, health‑conscious, willing to pay a premium for ethically sourced beans.”
Discover customers’ wants, needs and preferences for products or services	Find out what features, price points or services customers value most.	Before launching a new smartphone, a manufacturer runs focus groups to learn that battery life is the top priority for target users.
Assess the likely demand for a new product, service or market entry	Estimate how many units could be sold or how many customers would adopt the offering.	A grocery chain uses a test‑market in a single city to forecast national demand for a new plant‑based meat range.
Support strategic decision‑making (e.g., pricing, location, promotion)	Provide evidence for key business choices.	An online retailer analyses price elasticity from past sales data to set the optimal launch price for a new gadget.

Key Definitions

• Primary research: Data collected directly from original sources for a specific research purpose.
• Secondary research: Data that have already been collected, published or compiled by others and are used for a new purpose.

3.2.2 Primary vs. Secondary Research – Features, Advantages & Limitations

Primary Research

Fresh data gathered specifically for the research question at hand.

Aspect	Details
Typical sources	Customers, potential customers, suppliers, employees, industry experts.
Common methods	Surveys / questionnaires (online, face‑to‑face, telephone) Interviews (structured, semi‑structured, unstructured) Focus groups Observations (in‑store, online behaviour tracking) Experiments / test‑markets
Data types	Quantitative (numerical) and/or qualitative (opinions, attitudes).
Advantages	Highly specific to the research problem. Current and up‑to‑date. Full control over design, sampling and data‑collection.
Limitations	Generally more expensive and time‑consuming. Requires expertise in questionnaire design, sampling and administration. Risk of respondent bias, non‑response or social‑desirability bias.
Typical uses (examples)	Testing a new product concept with a focus group. Measuring customer satisfaction after a service change. Estimating demand for a product in a previously untapped market.

Secondary Research

Information that already exists and is repurposed for the current study.

Aspect	Details
Typical sources	Published market reports, government statistics, trade journals, company annual reports, internet databases, academic journals.
Common methods	Literature review, data mining, analysis of existing datasets.
Data types	Quantitative (e.g., sales figures, market share) and qualitative (e.g., industry commentary), often aggregated.
Advantages	Low cost and quick to obtain. Broad coverage – can provide industry‑wide context. Useful for background information, benchmarking and feasibility checks.
Limitations	May be outdated or not directly relevant to the specific problem. Quality and reliability can vary between sources. Researcher has limited control over how the data were originally collected.
Typical uses (examples)	Estimating total market size from government trade data. Conducting a competitor analysis using annual reports. Identifying macro‑economic trends that could affect demand.

Comparative Matrix – Which Method Fits Which Research Objective?

Research objective	Preferred approach	Why?
Rapid benchmarking of market size	Secondary research	Existing published figures give a quick, inexpensive overview.
Understanding why customers switch brands	Primary research (focus groups / interviews)	Requires in‑depth, current attitudes that are not captured in published data.
Testing price sensitivity for a new product	Primary research (structured survey or test‑market)	Specific price points must be evaluated with the target market.
Checking the feasibility of entering a foreign market	Secondary research (government statistics, trade journals) + limited primary research (expert interviews)	Secondary data provide macro‑environment; primary data fill gaps on local consumer preferences.
Monitoring competitor promotional activity over the last 12 months	Secondary research (company reports, media monitoring)	Historical data already recorded; primary research would be unnecessary.

3.2.3 Sampling – Need, Techniques & Basic Calculations

Why sampling is required

• Studying an entire population is usually impractical (cost, time, accessibility).
• A well‑designed sample allows statistical inference about the whole market.
• Sampling reduces the workload while still providing reliable insights.

Sampling techniques

• Probability sampling – each member of the population has a known chance of selection.
  • Simple random sample
  • Systematic sample
  • Stratified sample (e.g., by age, region)
  • Cluster sample
• Non‑probability sampling – selection is based on researcher judgment.
  • Convenience sample
  • Judgement / purposive sample
  • Quota sample

Sample‑size calculation (basic formula)

For a proportion‑type survey (e.g., “What % of customers would buy X?”) a common approximation is:

• n = required sample size
• Z = Z‑score for the desired confidence level (1.96 for 95 % confidence)
• p = estimated proportion (use 0.5 if unknown – gives the maximum sample size)
• e = acceptable margin of error (e.g., 0.05 for ±5 %)

Example: For 95 % confidence, margin of error ±5 % and p = 0.5, n ≈ 384. Adjust upward if the population is small or if a higher confidence level is required.

Sampling error, confidence intervals & limitations

• Sampling error – the difference between the sample result and the true population value, caused purely by chance.
• Confidence interval – a range that is likely to contain the true population value (e.g., 95 % confidence that the true proportion lies between 48 % and 52 %).
• Limitations
  • Sampling bias – the sample does not represent the whole market (e.g., only online respondents).
  • Non‑response bias – certain groups fail to answer, skewing results.
  • Too small a sample reduces reliability and widens confidence intervals.

3.2.4 Reliability & Validity of Data

Assessing source credibility (especially for secondary data)

• Author’s expertise and reputation.
• Publication date – ensure data are recent enough for the research purpose.
• Publisher’s authority (government agency, recognised market‑research firm, peer‑reviewed journal).
• Methodology disclosed – sample size, sampling method, data‑collection technique.

Triangulation

Use at least two independent sources or methods to confirm a finding. For example, combine a survey (primary) with industry reports (secondary) to validate a market‑size estimate.

Primary data quality checks

• Pilot‑test questionnaires to identify ambiguous or leading questions.
• Use clear, neutral wording to minimise respondent bias.
• Record response rates; a low rate may indicate reliability problems.
• Check for consistency (e.g., repeat a key question in a different format).

Secondary data quality checks

• Compare figures from multiple reports (e.g., two industry analyses) – if they differ markedly, investigate why.
• Verify that the original data collection used sound methodology (adequate sample size, appropriate sampling technique).
• Check for any obvious outdated information (e.g., pre‑COVID‑19 consumer trends).

3.2.5 Data Analysis – Turning Data into Information

Quantitative analysis

• Descriptive statistics – mean, median, mode, range, standard deviation.
• Cross‑tabulation – explore relationships (e.g., age group vs. purchase frequency).
• Charts & graphs – bar charts, pie charts, line graphs, histograms.
• Software suggestions – Microsoft Excel, Google Sheets, SPSS (for larger data sets).

Qualitative analysis

• Thematic coding – identify recurring ideas or attitudes in interview/focus‑group transcripts.
• Content analysis – count the frequency of key words or phrases.
• Presentation – narrative summary supported by direct quotations.
• Software suggestions (optional) – NVivo, Atlas.ti.

3.2.6 Interpreting Tables, Charts & Graphs

Choosing the Appropriate Method – Decision Flow

1. Define the research objective and the specific information required.
2. Check the budget and time available.
3. Search for existing secondary data that could answer the question.
4. If secondary data are insufficient, outdated, or not specific enough, design primary research to fill the gaps.
5. Decide on a sampling plan (probability vs. non‑probability) and calculate an appropriate sample size.
6. Assess the reliability of all sources (triangulation, credibility checks).
7. Collect, analyse and interpret the data using suitable quantitative or qualitative techniques.
8. Combine findings from both primary and secondary sources where appropriate (mixed‑method approach).

Key Take‑aways

• Primary research provides data that are directly relevant, current, and under the researcher’s control, but it is usually more costly and time‑consuming.
• Secondary research offers a quick, inexpensive way to obtain background information and industry context, though it may be less specific or outdated.
• Effective market research often combines both types, uses an appropriate sampling strategy, checks reliability and validity, and applies basic quantitative or qualitative analysis to produce clear, actionable conclusions.