Metrics-Driven Market Validation: New Kid in Town!
A clever, cost-saving way to test and tweak the business model of technology startups
In a recent blog, we discussed how important it is for startups to focus on the value they want to create for their customers. And how important it is for them to gather as much information as possible about the customer and their interest in the product, even before building the actual product.
Our Metrics Driven Market Validation (MDMV) approach can save money, reducing time to market, funding needs, and unnecessary pivots. MDMV combines data-driven hypotheses with iterative processes to validate market interest before full-scale product development begins, and encourages entrepreneurs to focus on relevant KPIs from day one.
Let’s start with a hypothetical innovation: Suppose you have invented a technology for a new cleaning robot that is small, powerful, and smart. The robot can operate even while people are working and moving around it, bringing a new level of cleanliness to many environments.
MDMV suggests the following approach:
Step 1: Identify the most promising customers for the simplest possible version of the robot.
First, Let’s call our current version of the robot – as rough as it might be - the “pilot product” and the organizations the “pilot users.”
Regarding the pilot product: We’re not talking about a mass-produced product. We’re talking about the functional prototype as it is or with minimal adaptions. We don’t need all the certifications, the beautiful case, the packaging, the service offerings, etc.; we work with what we have now.
What’s a good pilot user? This organization has such a significant need for the product that it is ready to test it even in its pilot version. The need is so big that the organization is prepared to pay something, even for the pilot version. It doesn’t need to be the full price, but the price should be so high that it needs corporate approval (and not a payment out of the expense budget of a sole individual). The fact that they pay something is a proof of commitment to this pilot project.
Our purpose of the pilot project is to learn as much as possible: What do users like? What needs to be improved? How and when do they use the product? How do they handle the deficiencies of the pilot product?
It’s not trivial to find such an organization. MDMV suggests the following approach:
Build a list of target customer segments (“ICP” – “ideal customer profile”). These are types of organizations that you believe could be pilot customers. Be as specific as possible. It’s not “any hospital”, but: “rooms in the hospital that are frequented by the public, staff, and patients and where, therefore, the need for cleanliness is especially high; the hospital ideally should have an above-average re-infection rate of patients so that the urgency to use our product is especially high.”
For each customer segment, identify metrics or KPIs that (1) quantify the problem we solve and (2) will be improved by using our product. In our example, a KPI could be an infection rate. Based on other studies discussing cleanliness, using the robot will reduce the infection by 15% to 20%.
Now, find the person within the ICP who benefits most from an improved KPI (here: infection rate). The idea here is that many organizations have a similar structure; for example, a hospital is usually divided into several departments covering a medical field. The department is run by a department head, often a recognized expert in the field. So, we would have to find the department that typically suffers most from high infection rates. Let’s say that this was the infectious disease department. Therefore, in our case, the ideal person to talk to would be the head of this department because they would profit most from a reduced infection rate.
It’s important to understand that these people do not buy your product. They buy the benefit, which is a reduced infection rate.
Next, let’s talk to these people. You would, for example, draft an e-mail saying briefly that you found a novel way to reduce infection rates by 15% to 20% (based on studies A, B, and C), that the technology works but a commercial product is not yet available and that you would like to pilot the product with them. If they react, schedule a meeting and talk to them: Discuss how the pilot needs to be set up so they can see that the promised benefit will be achieved. Discuss their contribution.
Many of these discussions will fail. If they fail, try to understand why: Is the promised KPI improvement not large enough? Then the ICP hypothesis was wrong. Do they rather not want to experiment? Then, again, the ICP hypothesis needs to be refined. Is the price too high? Then we might lower the price or, again, refine the ICP hypothesis.
Repeat this process for all other customer segments you have identified. AI can be a great help for finding customer segments; a prompt in our example could be: “Assume we have a new type of cleaning robot that is very small, powerful, and intelligent so it can work even when people are around it. Which were organizations that would profit most from such a cleaning robot?” You might use the AI to make the results more specific: “Which department in the hospital would profit most from such a robot?”
For our cleaning robot, an initial shortlist of potential customers might look like this, according to ChatGPT:
Hospitals and Clinics
Schools and Universities
Office Buildings
Retail Stores and Supermarkets
Hotels
Public Transportation
Airports
Restaurants and Cafés
Obviously, you can’t serve all these segments, but it’s important to talk to as many of them with the approach suggested above so you gain an understanding which of them could be your “beachhead segment” (the one into which you would introduce the commercial product later).
Step 2: Work with early adopters with paid pilot projects
Once you have processed your list of ICPs, it’s time to get real and work with your customers on the paid pilot projects. Learn as much as possible: Validate hypotheses about the product’s value, lock in early adopters, and refine the product based on user feedback.
The pilot should cover your costs, but you do not necessarily need to make a profit here. At this stage, you need market proof.
Ideally, you would work with 3–4 customers in each customer segment to minimize the risk of focusing too narrowly on one customer. Each customer has special requirements that apply only to them; you need to talk to several customers to identify these specialties and the common requirements.
Ideally, you repeat step two several times and use the possibility to continuously refine your value proposition based on your client’s feedback. You’ll find that the pilot versions for the different segments might differ because the segments' needs differ. You can then:
Build a product that covers the needs of all the segments
Focus on one segment and deprioritize the others;
Build a product family.
The decision depends on the business cases for each segment and your resources. Focusing on this stage is essential: Serving too many segments simultaneously is a relatively certain way to kill your startup. Ideally, you’ll start with 1, at most 2, segments.
Step 3: Talk to investors or continue bootstrapping
Once you have made it that far, you know that there is a market need, you can serve the customers, you know which segment you’ll focus on first. The question is now: How to scale? Topics to consider might be certifications, mass production, customer service, hotlines, marketing, sales, distribution, logistics, and many more.
However, one question might be prevalent: How can we finance this growth? Here’s the point where investors could come into play: business angels, strategic investors, or, even later, venture capital companies.
A valid alternative can be to continue bootstrapping if you can generate profits or have other means to cross-finance the development of your company.
Summary
MDMV helps you find customers rapidly; the key component here is to focus on the benefits your solution creates, not the features of the solution. Once you understand the needs of the customers and the really required features of the solution, it’s easier to scale up the company and find investors to fund this growth.