It should be stated right off the bat that the team at Accelerant Research has enormous appreciation for quantitative segmentation research. We LOVE conducting these sophisticated quantitative research studies for our full-service clients which result in elegant, highly targetable, easily digestible segments of the target customer population. Large-scale segmentation studies have a long shelf life, internally, and provide a ton of strategic value to organizations. However, in our role as white-glove qualitative research recruiters we’ve noticed a disturbing trend in the insights industry when it comes to blindly relying on segmentation algorithms to identify segment members for participating in focus groups or other qualitative research studies.
For those with less experience in such research studies, a segmentation algorithm is a shortened, summary version of the larger-scale segmentation results, which can be inserted into future screening questionnaires to identify customer segmentations among the survey population. The segmentation algorithm is a fantastic, on-the-fly means to identify segment members, which can be used in a plug-and-play fashion for future quantitative surveys. However, using these algorithms for qualitative research is not so simple.
Often, we are handed a segmentation typing tool to use during our recruiting process in order to identify members of a given segment, but if we rely solely on this quantitative type of assessment, clients are often disappointed when individual recruits don’t behave in their interview as a member of their segment is expected to behave. Segmentation output is very elegant and strategically impactful, but the individual data points that comprise your segments are messy. The final segmentation analysis is based on hundreds or even thousands of cases, which is what makes them so powerful. However, when you deconstruct the segmentation and go back to look at individual survey participants, the results are far less clear – sometimes a small shift in a survey response (e.g., selecting 6 instead of 8 on a 10-point survey scale) can jettison a research participant from one segment to another. When recruiting participants for qualitative research, we’re right back to that messy, individual-level assessment of participants’ “fit” with a given segment. As such, relying strictly on a segmentation algorithm or typing tool to definitively define these segment members for qualitative research can be a recipe for disaster.
If we’re not careful, this can lead to an awkward disconnect in the backroom of a focus group facility, where participants are correctly segmented based on the algorithm, but in their interview, they say and do things that make them sound like they should be members of a different segment.
What can be a simple and highly effective tool in bringing your segments to life is sharing the segment profiles with your qualitative recruiters, in addition to the typing tool algorithm. What these profiles do is allow us to focus on recruiting participants that behave like the segment should, rather than blindly recruiting into a segment without the benefit of such context. When we use the segmentation algorithm as a starting point of identifying segment membership, and the segment profile information for refinement, we create a powerful one-two punch that ensures research participants who sit down for qualitative interviews are exactly the right audience. This type of recruiting rigor requires partnership between Accelerant’s recruiting team and the client to make sure these details are communicated properly, but when that partnership is in place, it makes for a fantastic client experience at the end of the day.
The consultative partnership described above is just one example of Accelerant’s approach to service that we take on each qualitative recruiting project (i.e., we sweat the details). We invite you to request a cost estimate from us as a first step and experience the difference that we provide for yourself. Simply give us a call (704-206-8500) or send us an email (email@example.com).