analyse simple market research data

3.2.1 Methods of Market Research

Learning objective

Analyse simple market‑research data and draw conclusions that can inform business decisions (Cambridge IGCSE Business Studies 0450, AO2/AO3).

Why market research matters

• Identifies customers’ needs, wants and preferences.
• Provides the information needed to set the right product, price, promotion and place (the 4 Ps).
• Reduces the risk of launching a new product or entering a new market.
• Offers a benchmark for evaluating the success of marketing activities.

Key concepts

• Primary research – data collected first‑hand for a specific purpose.
• Secondary research – data already published or collected for another purpose.
• Qualitative research – explores attitudes, motivations and feelings (e.g., interviews, focus groups).
• Quantitative research – measures opinions or behaviours numerically (e.g., surveys, questionnaires).

Primary vs. secondary research – benefits & limitations

Sampling – getting a representative sample

• Random sampling: every member of the target market has an equal chance of being chosen – reduces sampling bias.
• Convenience sampling: selects respondents who are easiest to reach – quicker but can introduce bias.
• Sample size must be large enough to give reliable results but balanced against cost and time.
• To avoid bias:
  • Use neutral wording and avoid leading questions.
  • Ensure the sample reflects the population’s age, gender, location, income, etc.

Types of bias that can affect market‑research data

Factors that influence the accuracy of market‑research data

• Question wording and order (see questionnaire bias).
• Respondent honesty and willingness to answer.
• Sample size and how representative the sample is.
• Method of data collection (online, face‑to‑face, telephone, observation).
• Timing of the research – seasonal effects or recent market changes.
• Data validation – checking for missing data, outliers and internal consistency.

Ethical considerations (brief)

• Obtain informed consent before collecting data.
• Ensure anonymity or confidentiality where appropriate (e.g., GDPR compliance).
• Do not mislead respondents or manipulate results.

Common methods of primary research

1. Questionnaires – written or online sets of closed‑ended (and occasionally open‑ended) questions.
2. Interviews – face‑to‑face or telephone conversations; can be structured, semi‑structured or unstructured.
3. Observation – watching customers in a natural setting (e.g., store traffic, product use).
4. Focus groups – guided discussion with a small, homogenous group of participants.
5. Test‑marketing – launching a product in a limited area to gauge response before a full roll‑out.

Common sources of secondary research (with examples)

• Company records – sales reports, customer databases, internal market analyses.
• Trade publications and industry reports – e.g., Retail Gazette, Food & Drink International.
• Government statistics – Office for National Statistics (UK), US Census Bureau, Eurostat.
• Online databases and market‑research agencies – Statista, Euromonitor International, Mintel, IBISWorld.
• Academic journals and university research centres.

Presentation of research results

• Tables – exact figures; useful for reference and calculations.
• Bar charts – compare categories (e.g., colour preference, brand choice).
• Pie charts – show parts of a whole (e.g., market‑share percentages).
• Histograms – display frequency distributions for quantitative data.
• Line graphs – illustrate trends over time (e.g., sales growth).

Evaluating research methods (when each is most/least suitable)

Steps to analyse simple market‑research data

1. Check the data for completeness and accuracy – look for missing values, obvious entry errors and outliers.
2. Organise the data – enter into a table or spreadsheet, label columns clearly.
3. Calculate basic totals, percentages and averages – use formulas such as Percentage = (frequency ÷ total) × 100 or Average = Σ (midpoint × frequency) ÷ total.
4. Identify patterns, trends or outliers – compare categories, look for the highest/lowest values, note any unexpected results.
5. Interpret the findings – relate the numbers back to the original research question.
6. Make recommendations – link the interpretation to the 4 Ps (product, price, promotion, place) and suggest concrete business actions.

Worked example – Customer‑preference survey (T‑shirt colour)

A small retailer surveyed 120 customers about their preferred colour for a new T‑shirt. The raw responses are shown below.

Data analysis (using the six‑step process)

1. Check data – totals add to 120; no missing values.
2. Organise – data already in a clear table.
3. Calculate percentages (Percentage = frequency ÷ total × 100):
   • Red: 45 ÷ 120 × 100 = 37.5 %
   • Blue: 30 ÷ 120 × 100 = 25.0 %
   • Green: 20 ÷ 120 × 100 = 16.7 %
   • Black: 15 ÷ 120 × 100 = 12.5 %
   • White: 10 ÷ 120 × 100 = 8.3 %
4. Identify pattern – Red is the most popular colour (over one‑third of respondents); Blue is the second‑most popular; White is the least popular.
5. Interpretation – The majority of customers prefer warm or bold colours (Red + Blue = 62.5 %). This suggests a strong market for “fashion‑forward” items.
6. Recommendations linked to the marketing mix
   • Product: Order larger stock of Red and Blue T‑shirts; keep a limited range of Green, Black and White.
   • Price: Consider a modest premium for Red if it is perceived as a trendier colour.
   • Promotion: Feature Red and Blue prominently in advertising, social‑media posts and in‑store displays.
   • Place: Ensure the popular colours are displayed at eye level and in the online “featured” section.

Linking research to business decisions (the 4 Ps)

• Product – design or modify features based on customer preferences and feedback.
• Price – set a price that reflects perceived value, willingness to pay and competitive positioning.
• Promotion – choose messages, media and timing that resonate with the target audience.
• Place – decide on distribution channels and locations where the target market shops.

Practice question

A coffee shop asks 80 customers how often they visit per week. The responses are shown below. Use the steps above to calculate the average weekly visits and comment on the pattern.

To find the average, assign a midpoint to each range (0–1 → 0.5, 2–3 → 2.5, 4–5 → 4.5, 6 or more → 6) and use the formula:

Average visits = Σ (midpoint × frequency) ÷ total customers

After calculating, discuss whether the coffee shop should:

• Introduce a loyalty scheme for frequent visitors.
• Adjust opening hours to match peak visitation periods.
• Promote “slow‑day” offers to encourage customers in the 0–1 visit group.