Lesson 7.4.1

7.4.1 Anticipating buying behaviour Quiz: OCR Business, Unit 7

20 questions

Written by Revision Ninja · Last reviewed 11 October 2026

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Lesson 7.4.1, Anticipating buying behaviour: 20 multiple choice questions for the OCR Business (H431), Unit 7: Marketing, written with Revision Ninja.

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The 20 questions

  1. What term describes collecting original data directly from potential consumers to anticipate buying behaviour?

    • Secondary research
    • Quantitative data
    • Primary research
    • Desk research

  2. Which market research method involves gathering a small group of consumers to discuss a new product concept?

    • Consumer panel
    • Desk research
    • Test market
    • Focus group

  3. A business uses historical sales data to predict future demand. Which technique is being used?

    • Quantitative forecasting
    • Primary research
    • Qualitative forecasting
    • Test marketing

  4. What type of data measures opinions, attitudes and reasons behind consumer purchasing decisions?

    • Quantitative data
    • Qualitative data
    • Secondary data
    • Numerical data

  5. What is the main purpose of test marketing a new product in a single region?

    • Lower production costs
    • Reduce financial risk
    • Eliminate competition
    • Guarantee sales volume

  6. Which sampling method ensures every member of the population has an equal chance of selection?

    • Stratified sampling
    • Random sampling
    • Convenience sampling
    • Quota sampling

  7. A business selects respondents based on specific demographic proportions like age and gender. Name this method.

    • Cluster sampling
    • Random sampling
    • Simple sampling
    • Quota sampling

  8. Which tool uses large datasets and algorithms to predict individual customer purchasing patterns?

    • Big data analytics
    • Delphi technique
    • Consumer panel
    • Test marketing

  9. What term refers to a recruited group of consumers who provide ongoing feedback over time?

    • Consumer panel
    • Focus group
    • Random sample
    • Quota sample

  10. If a firm's sample size is too small, what is the most likely impact on market research results?

    • Increased validity
    • Lower bias
    • Reduced accuracy
    • Higher cost

  11. What statistical trend analysis technique smoothes out short-term fluctuations in historical sales data?

    • Moving averages
    • Extrapolation
    • Break-even analysis
    • Correlation analysis

  12. Extending a past sales trend line directly into the future assumes which key condition?

    • Rising inflation rates
    • Increasing market share
    • Falling product costs
    • Unchanging market conditions

  13. Which qualitative forecasting method gathers opinions from a panel of independent industry experts?

    • Delphi technique
    • Focus group
    • Consumer panel
    • Brainstorming session

  14. A retailer analyses loyalty card data to identify which items are frequently bought together. What is this?

    • Test marketing
    • Field research
    • Market basket analysis
    • Desk research

  15. A business calculates a 3-month moving average for sales: 100, 120, 140. What is the moving average value?

    • 130 units
    • 100 units
    • 120 units
    • 360 units

  16. Why might a business prefer secondary research over primary research when anticipating market trends?

    • Higher relevance
    • Up-to-date data
    • Competitive advantage
    • Lower cost

  17. What risk arises if market research asks leading questions when gathering consumer preferences?

    • Research bias
    • Data saturation
    • Sampling error
    • High variance

  18. Which market research tool tracks online user navigation and clicks to anticipate purchasing intent?

    • Focus group
    • Quota sampling
    • Clickstream analysis
    • Field survey

  19. Sales for Q1 to Q3 were 200, 300, and 400. Using linear extrapolation, what is the predicted Q4 sales?

    • 300 units
    • 600 units
    • 500 units
    • 400 units

  20. What is a major limitation of using historical sales data to forecast future buying behaviour?

    • High collection cost
    • Requires primary data
    • Too much detail
    • Ignores sudden changes

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