Have you ever been invited to a dinner with friends, only to show up and see your seat has been taken by the another 18-34 y/o male from Nevada with one child under 5? Of course not! But that happens to survey respondents all of the time, simply because that information – that there’s no longer a seat for them – is not getting passed along, or at least not in timely fashion.
We think survey APIs can solve for this frequent but overlooked occurrence plaguing surveys and respondents. An integration between survey information and the PureSpectrum platform continuously updates quotas, keeping information accurate and up to date for panels to send the right respondents at the right time. A research agency that connected their surveys to PureSpectrum via API shared metrics from a couple of studies where they were also manually managing panels simultaneously.
The results below show the material impact that a survey API integration can have on overquota rates:
Project 1 (in light gray) saw a 2.8x better conversion rate and only a 1% overquota rate with the PureSpectrum API integration when compared to all other manual suppliers. Project 2 (in dark gray) saw a 3.3x better conversion rate and only a 3% overquota rate.
If a dinner party analogy isn’t relatable, why should stakeholders in the research process care about overquota terminations? The Respondent: It saves them from a bad experience. Not qualifying for a survey is consistently listed as a top reason for not doing surveys. Overquotas are an avoidable termination. The Panel: Less respondent churn means less recruitment cost. When the information is transferred system to system, you can achieve better conversion without labor intensive attention. The Researcher: As the downstream recipient, fewer overquotas mean happier respondents in your surveys, making delivery easier. And, if you aren’t burning through your vendor’s panel, there are better costs for better conversion, even if it’s “not calculated in IR.” Lower overquota rates means less respondents wasted for panels and lower costs for researchers.
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