The True Cost of Low-Quality Market Research Survey Participants

In healthcare market research, there’s constant pressure to hit quotas quickly and affordably. But when the priority shifts too far toward cost per complete, another cost quietly creeps in - one that’s harder to quantify, but much more damaging: the cost of bad data.

At a surface level, a low-quality respondent might just seem like a mismatched title or an inattentive survey taker. But in high-stakes environments like asset valuation, hospital system assessment, rare disease research - inaccurate or unverified responses can distort the insights that shape strategic decisions. For consulting firms, pharma companies, and device manufacturers, these distortions translate directly into operational risk and wasted budget downstream.

So, what does “low-quality” really mean in the context of HCP recruitment? It’s not always obvious. Sometimes it’s a participant who doesn’t truly fit the target profile despite qualifying through a screener. Other times, it’s a respondent who speeds through the survey or provides contradictory answers. In the worst cases, it's someone entirely misrepresented- posing as a clinician or executive when they aren't.

This happens more often than many research buyers realize. Panels that lack strict verification measures or that pull repeatedly from the same limited pools can end up serving the same low-engagement respondents across multiple projects. These individuals often learn how to “pass” screeners without actually meeting the criteria, simply because they’ve seen enough of them.

The downstream effect? Flawed recommendations based on flawed data.

What’s often missed is how these issues affect the credibility of the research itself. A consultant walking into a client presentation with weakly sourced HCP insights may lose not just the current engagement; but the trust that fuels future work. That makes low-quality respondents a reputational risk as much as a data problem.

At Medical Mile, we approach this differently. While we won’t dive into all the details here, our recruitment model prioritizes verified, actively screened respondents with specialty and setting confirmed in advance. We segment by role, engagement history, and project relevance - not just by titles in a database.

Here’s the part that matters: good data doesn’t have to be slow or expensive. It just has to be deliberate.

When clients ask us how to save budget, we start by asking what quality standards they’re willing to bend. Because the truth is: poor data is always more expensive. It might just take longer to show up in the results....

Omar Asi

Medical Mile Research