As a result, the self-check not only provides the startup with an individual assessment, but also clear instructions on which criteria (= topics) should be improved using which methods to validate the PMF. Each method has its own article in the ZHAW Entrepreneurship Resource Library, which contains an introduction to the method, step-by-step instructions and practical examples. Once a method has been successfully applied, the startup can reopen the self-check questionnaire, change the answer to the appropriate question and receive an updated PMF score.
👉 Why is product-market fit (PMF) crucial?
A product only sells itself when it is perfectly tailored to the target group. Those who achieve PMF grow organically - those who don't struggle with low sales figures.
👉 How does the PMF Boost help the ZHAW?
The ZHAW has developed a maturity model & self-check that helps start-ups to measure their PMF progress in four dimensions:
- User / problem (Does the market really need the product?)
- Market (how big is the potential?)
- Solution (Does the solution meet customer requirements?)
- Business model (Is the business model scalable and sustainable?)
👉 How does the evaluation work?
- 26 criteria are evaluated on the basis of evidence levels.
- The self-check generates an individual PMF score.
- Startups receive specific recommendations for action to improve weak points.
👉 What are the benefits?
- Clarity about the current PMF status.
- Prioritized next steps for optimization.
- Access to tried-and-tested methods from the ZHAW Entrepreneurship Library.
📩 Questions? Contact: pmf@zhaw.ch | Product Market Fit Boost | Online Self-Check Questionnaire
The PMF Boost in detail
One of the most important success factors for start-ups is product-market fit (PMF) - the moment when a product is so well tailored to the needs of the target group that it virtually sells itself. However, this state does not occur by chance, but requires a systematic approach, continuous feedback and often several iterations of the product.
Start-ups that reach the PMF often experience strong organic growth, high customer satisfaction and increasing demand. Companies that do not reach this point, on the other hand, struggle with low sales figures, a lack of customer loyalty and a high level of uncertainty. But how do you know if you have already reached the PMF? And what phases does a start-up go through on the way there?
To help with these questions, ZHAW has developed the PMF Boost. With the help of a maturity model and a self-check, startups can assess their own progress and derive targeted measures for the next step towards the PMF. The following sections first describe the content-related dimensions, the evidence level as the basis for the assessment using a questionnaire, the report created with it and finally the recommendations for action for startups derived from it.
Dimensions in the PMF Boost model
The maturity model distinguishes between 4 dimensions: User / Problem, Market, Solution and Business Model. The market is further subdivided into environment and segmentation, the business model dimension is further subdivided into distribution and viability. Each of these subject areas is further subdivided into different criteria, which must be systematically analyzed using appropriate methods in order to achieve the PMF. The complete maturity model can be seen in Figure 1:
Evaluation
The assessment of the degree of achievement of the PMF based on the 26 criteria in Figure 1 is carried out using a questionnaire that we have developed for each of these criteria based on different levels of evidence (see Figure 2). The questionnaire can be completed by startups as a self-check in order to obtain an individual assessment of their progress in achieving the PMF.
Essentially, the evidence levels are about finding out how broadly and deeply the individual criteria have been researched: The more proprietary data and therefore insights a startup has created to determine the promising approach in the respective criteria, the more likely it is to achieve the PMF and therefore the higher the score in the maturity model.
The Product-Market Fit Score
The answers to the questions in the self-check allow us to assess the evidence level achieved for each of the 26 criteria. On this basis, an automated report is created in which the scores of the individual criteria are aggregated according to the structure of the maturity model. Figure 3 shows the exemplary scores for the two subject areas of distribution and viability in the business model dimension. This startup, for example, has already achieved the highest evidence level for “Scalability” and thus the full score of 100. Fewer methods were used to validate the revenue model, the willingness to pay and, in particular, the ESG impact, resulting in lower scores. Overall, this startup received a score of 69 out of a possible 100 points in the area of viability. 60% of this score is included in the score for the Business Model dimension, with the remaining 40% coming from the score for the Distribution criteria. Overall, this startup achieved a score of 57 in the Business Model dimension.
The score from each of the 4 dimensions, User/Problem, Market, Solution and Business Model is aggregated in this logic using the respective answers to the criteria. Finally, a total score for the PMF is aggregated from the partial scores of the 4 dimensions. Figure 4 shows the overall score for the example startup; a total score of 66 out of a possible 100 points was achieved. The partial scores from the 4 dimensions and their weighting in the overall score are shown on the left-hand side. On the right-hand side, the aggregated scores from the 4 dimensions are visualized graphically in a spider diagram.
Recommendations for startups
The score obtained gives the startup an indication of how advanced its method-based validation of the PMF already is. A score of 100 is very difficult to achieve and is not absolutely necessary to achieve a successful PMF. Whether and how extensively startups should validate is a question of risk appetite and the remaining resources for a (delayed) pivot. However, there is always room for improvement! 😊 Thanks to the multi-level evaluation, startups can now see in which of the 4 dimensions the lowest score was achieved. Next, the evaluations of the individual criteria in the dimension with the lowest score can be informative as to where the greatest potential for improving your own PMF lies. After completing the self-check, each startup not only receives the score, but also an individualized recommendation as to which methods are suitable for improving the score for the respective criteria. Figure 5 shows an excerpt from the recommendations that the report generated for our example startup.
As a result, the self-check not only provides the startup with an individual assessment, but also clear instructions on which criteria should be improved using which methods to validate the PMF. Each method has its own article in the ZHAW Entrepreneurship Resource Library, which contains an introduction to the method, step-by-step instructions and practical examples. Once a method has been successfully applied, the startup can reopen the self-check questionnaire, change the answer to the appropriate question and receive an updated PMF score.
The PMF Boost was developed by Dr. Linard Barth, Dr. Manuel Holler, Dr. Martin Feuz and Dr. Jens Haarmann from the School of Management and Law at the Zurich University of Applied Sciences. We are grateful for any questions and suggestions and can be contacted at pmf@zhaw.ch
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