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In the product design process, it is often desirable to quickly obtain information about current user behaviors for topics that cannot be obtained through existing data or instrumentation. Perhaps we would like to understand the use of products we do not have access to or perhaps the action we would like to know about (such as using a coupon) is an action taken outside of a system that can be instrumented. Traditionally, large market research surveys would be conducted to answer these questions, but often designers need answers much faster. We present a study investigating the reliability of fast survey platforms such as Amazon Mechanical Turk and Survey Monkey as compared to larger market research studies for technology behavior research and show that results can be obtained in hours for much smaller costs with accuracy within 10% of traditional larger surveys. This demonstrates that we can rely more heavily on these platforms in the product design process and provide much faster planning iterations that are informed by actual usage data.
Bentley et al. (Mon,) studied this question.
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