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Whenever we recruit participants, we are looking to get a representative sample of our actual (or desired) users.
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It is important, nonetheless, to try to identify any selection bias in our recruiting, so we can take that into account when we analyze our results, or when we do our next study.
What is selection bias?
From Wikipedia’s article:
Selection bias is the selection of individuals, groups or data for analysis in such a way that proper randomization is not achieved, thereby ensuring that the sample obtained is not representative of the population intended to be analyzed.
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In other words, certain recruitment methods may yield a skewed selection of participants, rather than the representative sample that we normally want.
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The most common way to reduce selection bias is to use several different types of recruitment. For example, instead of just running a web ad (which only yields site web visitors), we could also use customer lists to reach those customers who don’t use the website.
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While we will never eliminate all bias from our studies, these steps should help minimize it so we can be reasonably confident in our results.
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Next: Coordinating audiences and channels