Virtually everyone who has worked in market research long enough, has been part of the process of scheduling, setting up, and designing the recruitment criteria around a qualitative research project. So, you’ve all probably seen quotas developed to recruit X number of males, X number of females, X number of those with household income levels below $75,000, X number of ethnicity B, X number of those who use our services 24-26 times a month, X number of brown-haired/blue-eyed/left-handed decision-makers, etc. The list goes on and on. Now, you may think that the whole brown-haired/blue-eyed/left-handed qualifier is a bit much, but the Bunker has seen parallel recruitment criteria before. In fact, sometimes we ourselves are guilty of this same overemphasis on quotas in qualitative research.
The lesson here is: treat qualitative research as exploratory research (if appropriate); don’t turn your next focus group screener into a mathematical formula to recruit participants.
Yes, there is some value in obtaining a good mix of respondents that closely mirror the makeup of the audience you are researching. That is often a necessity and can usually be taken care of, simply by creating separate buckets if you are doing multiple focus groups or multiple in-depth interviews (IDIs). Buckets, at the most basic level, could mean recruiting a group of your customers and recruiting a group of competitive customers. Obviously, in most cases, you would not want to mix those two segments to truly understand key issues and decision-making criteria behind each audience. But it truly depends on the topic you want explored.
For instance, let’s use ketchup as the product we want to explore. If the goal of your market research is to do a general study on usage of and perceptions of ketchup – it may be okay to mix both Heinz and Hunt’s ketchup users in the same focus group. However, if you want to determine the buying criteria for each, along with the where, how, and why you buy for each, it would be better served to create separate focus groups – a bucket of Heinz users and a bucket of Hunt’s users – and compare findings.
Is there value in creating quotas for qualitative research? Yes, absolutely. I am not arguing that. Sometimes it is appropriate to create quotas to sharpen up a recruit. Relating back to the ketchup example, perhaps from past purchasing data you want to create a group of younger females with no children who purchase groceries and compare the findings to a group of mothers who purchase groceries for their family. All valid suggestions. But how do you feel about creating two separate Heinz groups – one that purchases Heinz once every 3-6 months and one group that purchases Heinz less often? Would there be any major differences there? What if a growing trend with ketchup purchases is among fathers who barbecue? Because you predisposed this target market, you lose the opportunity to learn from them because the quotas limited you.
When you feel your quotas are getting too precise and too “needle-in-a-haystackish,” don’t be afraid to bring your research team back down to earth and remind them that the true purpose of qualitative research is not to gather statistically reliable and representative data. Segmentation marketing is key to product and service success, but before you roll out those strategies, it would be wise to save the mathematical formulas for quantitative work.
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