Market Research: Foundations to Practice · Sampling and Panels
Quota Sampling and Weighting
Even a large sample can badly misrepresent a population if it isn't balanced across the segments that matter for the decision at hand. This chapter covers the two main tools for managing this.
Quota sampling sets target numbers of respondents for specific population subgroups, such as age bands or geographic regions, ensuring the achieved sample reflects the actual population's composition on those specific dimensions, rather than allowing a sample to skew disproportionately toward whichever subgroups happen to be easiest or fastest to recruit within the available panel.
Key Takeaways
- Quota sampling sets target respondent numbers for specific subgroups to ensure the sample reflects the actual population's composition on key dimensions.
- Without quotas, panel recruitment tends to skew toward whoever is most readily available, rarely a demographically neutral, representative slice.
- Weighting adjusts collected data after the fact, giving underrepresented respondents' answers more mathematical influence to approximate the true population result.
- Weighting only corrects for measured dimensions with reliable benchmarks; it cannot fix unmeasured panel-selection bias between panel-joiners and non-joiners.