How to Ask HCPs About New Product Adoption

The Problem With “Likelihood” Questions

In pharmaceutical and medtech marketing research, one of the most common questions we ask is some variation of: “How likely are you to prescribe or use this product once it is approved?” Predictably, the answers skew optimistic.

Healthcare providers (HCPs), especially in the US, tend to overstate their willingness and intent to adopt. Some of this is professional curiosity, some is social desirability bias, and some is simply the natural enthusiasm we all express when presented with something new and potentially beneficial for patients. They might simply want to appear agreeable to get invited back to take the next marketing research survey.

But if we take respondents' statements at face value, our forecasts and launch plans risk being built on sand. The key challenge is that the way we ask the questions often fail to account for the contingencies and timing that drive real-world adoption.

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Beyond Interest: Getting Specific About Intent

Current marketing research practice often centers on adoption scales, interest ratings, or even expected patient volumes. These tools can be useful, but they miss the underlying dynamics of when and why an HCP will actually act. For example:

• Will the HCP adopt immediately, or only once guidelines and/or peers endorse the product?
• What happens if the HCP hits an insurance roadblock if they prescribe it soon after approval?
• In the case of precision therapeutics, will they test patients in advance, preparing for rapid initiation, or will they wait for ... (guidelines, peer endorsement, insurance coverage, etc.)?
• Are they planning to call patients proactively and set up appointments outside of the regular follow-up schedule, or are they more likely to wait until someone asks about it?
• Do they have any patients they've 'warehoused' in anticipation of this treatment?

These nuances matter. A physician who tells you they’ll use a product but adds, “once my colleagues start using it” is signaling something very different from one who says, “I already have three patients I’ll bring in the week after approval.”

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Dimensions of Adoption Worth Exploring

To move closer to reality, we can frame questions around dimensions that reflect urgency, timing, and contingencies:

1. Urgency: Do they plan to initiate utilization immediately, or wait?
2. Catalysts: What conditions must be met (insurance coverage, samples, peer endorsement, inclusion in guidelines)?
3. Proactivity: Will they prepare patients in advance (testing, consultations) or take a wait-and-see stance?
4. Deferral: Is there genuine intent to delay -- or even avoid -- use, at least for the foreseeable future?

By acknowledging that not adopting right away is a valid response, we can better discriminate between enthusiasm from action.

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Why This Matters for Forecasting and Planning

The distinction is not academic. Forecasting models, uptake curves, and marketing investment plans all hinge on realistic assumptions about early adoption. If we overestimate the speed of adoption, supply chains, sales force activity, and payer strategy can all be misaligned. Conversely, capturing the contingencies behind adoption decisions provides a roadmap for targeted interventions -- whether that means accelerating guideline inclusion, expanding patient testing infrastructure, or equipping peer advocates.

One practical approach I’ve found helpful is to ask two time-bound questions:

• Near-term adoption: “What will your usage look like in the first six months post-approval?” (And "It's ok to say, 'I'm not going to use it that soon.'")
• Settled adoption/peak share: “Where do you see yourself in 5-6 years, once payer coverage, guidelines, and clinical experience are established?”

This combination allows us to model the early uptake versus the long-term potential -- both critical to launch planning.

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Inviting Dialogue

Asking better questions doesn’t require us to make research more complicated; it requires us to make it more realistic. By reframing how we explore HCP intent, we can bridge the gap between stated enthusiasm, or perhaps feigned enthusiasm, and actual adoption behavior.

I’d love to hear from others in the insights, forecasting, and commercial strategy community: How do you approach this challenge in your own research? What question wordings or frameworks have been effective for you?

The way we ask may be just as important as the answers we receive.