Recruiting channels for a B2C usability study
Awareness of recruiting trade-offs.
Compare panels for speed versus in-product intercepts for authenticity, weigh cost, screening rigor, and bias.
WHAT THIS TESTS The interviewer checks whether you grasp that how you recruit determines whose behavior you observe, and therefore how trustworthy your findings are. It tests practical judgment about cost, speed, and bias rather than rote method knowledge.
A GOOD ANSWER COVERS Name two contrasting channels and compare them on the three axes. A paid research panel or recruiting agency is fast, often delivering participants in days, and lets you specify demographics through screeners. The downside is cost per participant and the risk of professional testers who behave unnaturally, plus weaker fit to your actual audience. An in-product intercept, such as a banner inviting real current users, gives high-quality, representative participants who genuinely use the product, often at low marginal cost. The trade-off is slower fill rates, dependence on traffic, and a skew toward already-engaged users, missing churned or new ones. Mention screener questions and incentives as quality levers in both cases.
COMMON WRONG ANSWERS Naming a single channel with no comparison. Treating cost as the only axis. Ignoring sampling bias, especially that panels attract repeat testers and intercepts miss non-users. Assuming more participants always means better data for a qualitative usability study.
LIKELY FOLLOW-UPS How many participants do you need for a usability test. How do you write a screener that filters out professional testers. How would recruiting differ for a niche B2B audience.
ONE CONCRETE EXAMPLE For a consumer budgeting app, you intercept active users in-product to study a new transaction view, getting authentic behavior cheaply but slowly. To also reach people who abandoned the app, you use a panel with a screener targeting lapsed budgeting-app users, accepting higher cost for speed and reach. Combining both balances representativeness against timeline, and you weight findings knowing the panel may include less typical participants.
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