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Measuring Product-Market-Fit


Jean-Francois Denault outlines a systemic approach to evaluating the commercial viability of a product.

Jean-Francois Denault outlines a systemic approach to evaluating the commercial viability of a product.

There is something about innovation that produces excitement. Successfully developing a new technology or discovering a potential treatment to an uncurable disease can make everybody in an organization excited. But successful innovation does not necessarily translate into commercial success. While you can find people who will be excited about your innovation, it is more challenging to find people excited to pay for that innovation. As such, a systemic approach to evaluate the commercial viability of a product becomes invaluable.

The Product-Market-Fit (PMF) methodology enables decision makers to effectively de-risk the potential commercial activity of their product. PMF is not only for startups. While the bulk of my projects in this space have been focused on small biotech or MedTech startups, I’ve seen increasing interest from larger corporations looking to ensure that there is a fit between their products and the market.

Understanding PMF

PMF is a process to validate that the value proposition in your product creates customer excitement to purchase your product, which will translate into actual sales. Measuring PMF insures that you measure the market intent in purchasing your product, and that you are able to move beyond the initial curiosity your innovation might provide.

The basic methodology to measure product-market fit resolves around engaging conversations with potential clients. As such, you contact early adopters or potential end-users, and evaluate their interest in the product or service. By interacting with your early adopters, you can measure their excitement as you describe your innovation and get a sense of their overall interest.

During those conversation, you can identify the elements they react positively to, and then focus on those key elements. You can also identify potential roadblocks. If multiple different end-users, for example, express doubts about one of your assumptions, or disagree on how the technology would fit or how it differentiates from current solutions, being early in the commercialization phase it is the perfect time to address these concerns and adjust your product.

You might find that your current product doesn’t have a market fit. Consumers might be unexcited by your proposed innovation, or the advantage offered by your technology might not be sufficient to displace existing products. In that case, you have still completed a positive PMF-knowing early in your commercialization cycle that your product is unaligned to market needs allows you to dedicate your efforts on retooling it. This might mean changing the target market, changing the product, or both. The advantage is it can be done prior to actual commercialization, and before money was invested in actual sales process of the product.

Importance of PMF for decision makers

Technologies are often developed in silos; development is often driven by technological opportunity, and excitement is driven by the innovation that is being generated. Unfortunately, the client’s perspective is often secondary to decision making. Is the client willing to pay? How does the client currently accomplish these specific tasks? How much does the client currently pay to purchase and use this technology?

A few years ago, I was working with a company that had developed some ground-breaking lab equipment. On the surface, the technology sounded promising: it would cut down analysis time by a multiple of ten, it reduced the number of manipulation (reducing human error), used a smaller sample size, and even had safeguards in place to reduce cross-contamination. Unfortunately, the company’s contact with end-users had been limited. As such, some innovations had been driven by technology opportunity rather than actual product demand. The product was getting close to commercialization, but there were still a number of questions: How much did the customer currently pay to accomplish this task? Was it often outsourced? Were there any specific issues with the current technology? Furthermore, there were still a number of technology choices left to make, decisions which needed direct input. The importance of the Product-Market-Fit was two-fold: 1) Will my end-user want to purchase my product? 2) How do I need to configure my product to insure maximum interest?

This is where the PMF fits in the commercialization process.

Identifying PMF

There are five simple steps to performing a PMF review

1.     Define your product

2.     Create your interview guide

3.     Prepare your end user profile

4.     Perform interviews

5.     Compile

The first step, product definition might seem basic, but it is necessary to define your product to identify all the possible the different features and options you might have, as well as any features that might still be undefined, and for which the PMF might provide useful information.

This is followed by the creation of an interview guide. A brainstorming session with interested stakeholders is a great way to start building your question bank. During this creativity phase, the objective is to cover all the topics you want covered during your PMF, so generate as many questions you think you will need to ask. You can weed out duplicates and unnecessary questions when you build your final interview guide. This preparation stage is essential as it ensures that the data is collected in a consistent manner, and the researcher does not forget any questions during interviews.

Next, prepare yourend user profile. By taking a moment to build that profile, it will be valuable for recruitment and to ensure that you interview the correct people. It is also necessary to identify if the end-user has purchasing decision power. If he doesn’t, it might be necessary to perform two rounds of interviews: one with actual end-users, and one with people who have authority to make actual purchases.

In my experience, this has been especially true for technologies that are used in university laboratories. In these cases, the end-users often found the technology very useful, but admitted there was little chance of purchasing the technology. Conversations with lab directors were necessary to reconcile end-user’s perspective with purchasing authority prerogatives.

In the next step, the planning goes into practice as end-users are contacted and you start performing interviews. From a practical perspective, this step of the PMF entails contacting potential clients directly. This is the only way you can develop a better understanding of their needs. Developing a deep understanding of potential clients is essential, so you can develop a significant value proposition.

Finally, compile your data and start your analysis. How do you know you have a good market fit? There is no exact number: more is better, obviously. If at least 40% of the potential customers you talked to expressed strong interest in your product as something they absolutely need, then it is a good indicator you have a good market fit on your hand. Lower than 40% and you might struggle to gain significant traction to reach your market. You might need to redefine your target market, or you might have to redefine your product. Sometimes, the solution might be to highlight the most compelling attributes, dropping some less popular attributes, or revisiting the product completely.

Life sciences: incentives, confidentiality issues and displacing the “Gold Standard”

Incentives are an important element to account for when budgeting for a PMF. A properly structured incentive system can increase participants’ response rates by 5 to 20%. In an article published in Health Service Research[1], the authors found that the response rate of doctors to a survey varied significantly depending on the form of remuneration offered. The amount of the incentive also has a significant impact on the response rate. A recent study[2] found that offering a modest compensation had little to no effect when surveying doctors. The minimum you will pay for an in-depth interview will vary with the profession of the participant as well as the length of the interview: it could range anywhere from $50 for a non-specialized participant to $350 for a specialist doctor.

Second, respect the confidentiality of the participants. If you have given them the assurance that you will protect their individual responses, be ready to do so. If you believe you cannot assure the participants confidentiality, or if do not intend to (by sharing the results to other stakeholders), be upfront about it so participants can have the option of opting out.

Finally, understand that most products will go against a “gold standard". This product is the one that is most commonly used, and against which new products are benchmarked both in terms of impact on human health as well as cost. While a product might be more efficient or make someone’s job easier, if it is costly compared to the current gold standard, it could be difficult to gain traction. As such, you might also need to evaluate the financial viability of your product versus this gold standard. Nonetheless, your PMF will be invaluable in understanding the gold standard, its advantages, as well as gaining a greater appreciation of its costs and frequency usage.


Jean-Francois Denault, MBAhas worked with over 50 different clients over 15 years, including companies such as J&J, P&G, ABBVie and Denka Seiken. He is the author of both the “Handbook of Market Research for Life Sciences” and the “Handbook of Marketing Strategy for Life Sciences”. He can be reached at jf.denault@impacts.ca.


[1] James KM, Ziegenfuss JY, Tilburt JC, Harris AM, Beebe TJ. Getting physicians to respond: The impact of incentive type and timing on physician survey response rates. Health services research. 2011;46(1 Pt 1):232-242. doi:10.1111/j.1475-6773.2010.01181.x.

[2] Cook DA, Wittich CM, Daniels WL, West CP, Harris AM, Beebe TJ. Incentive and Reminder Strategies to Improve Response Rate for Internet-Based Physician Surveys: A Randomized Experiment. Eysenbach G, ed. Journal of Medical Internet Research. 2016;18(9):e244. doi:10.2196/jmir.6318.

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