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Quantifying Product/Market Fit
When operating on a scale, you likely have more than a few signs that tell you whether your product/market fit is increasing. But how do you measure these?
It’s easy to answer whether you have a product/market fit: can the revenue your customers pay for your product sustain (or even grow) your business? If the answer is yes, then congrats, you’ve likely successfully solved and monetized a problem! But how can you know whether your product-market fit is strong enough or if you’re focusing on the right audience?
Segment your customers
In order to start analyzing your product/market fit, first, you’d need to segment your customers. This is easier to do for digital products than physical ones, and in the rest of the article, our focus will be mainly on digital.
The attributes of how you divide your customer base can be different for business-to-consumer (B2C) and business-to-business (B2B) products. In any way, you’re looking for an attribute that can result in well-defined and diverse groups. For example, you can try to segment by key behaviors, demographics, industry, geographical region, revenue by customer, software package tier, and the list goes on. To get an even better picture, it’s recommended to use two attributes together, one vertically and one horizontally:
Before we continue, it’s important to note that measuring product/market fit is not an exact science. In most cases, you cannot directly measure it, and you will be forced to use proxy metrics — data points trying to represent the value of something else. But as long as they’re closely related to what you’re trying to measure, it should be a good alternative.
To get a grasp on product/market fit, you can take a look at data points separately for new and existing customers, then combine what you see.
Track key metrics for new customers
Although tracking relevant metrics for new customers is important for all companies, it’s especially critical for products early in their lifecycle. As these products don’t usually have hundreds or thousands of customers, the best way to quantify product/market fit is through the satisfaction of new users.
When measuring this, you can draw similarities to measuring conversions on an e-commerce website. While in e-commerce, user interaction is mostly transactional (you’re there to complete a job or buy an item), similar principles apply when you want to measure long-term user commitment, for example, in the case of subscription products.
No matter whether you’re selling a single-purchase product or a long-lasting subscription, you should measure what percentage of interested users convert into paying/satisfied customers.
This metric can be a subscription conversion rate, purchases made in a physical store from all who entered, or a positive satisfaction score after weeks of using a product. Consistency is critical here; you should be measuring the same things in the same way for all customers to ensure comparability. For example, don’t send satisfaction surveys after 1 week for some customers and after 4 weeks for others.
If you’re early in your monetization journey and don’t have a lot of users yet, you can go upper in the marketing funnel and measure metrics there. Deal success percentage for B2B or signup completion rate for B2C products are two good examples.
Once you have your metrics, lay them over to the customer segment matrix that you’ve built earlier. After this, you should have a good indication of which customers are easily saying “Yes!” to your product and which segments you’re struggling with.
What to do if all the segments perform equally good or bad? Try to adjust your segment definitions or experiment with other attributes.
Measure the satisfaction of existing customers
Harvard Business Review says that acquiring new customers is 5–25 times more expensive than retaining existing users. So, with this in mind, let’s look at how we could quantify product/market fit with our current user base!
While monthly/weekly active users can be helpful, they’re usually not good enough indicators of whether your users are reaching their goal with the product. Try to look for more indicative metrics and think about ways to measure customer health.
Do enough users answer your satisfaction survey (using net promoter score or similar methodologies)? Do you look at the subscription renewal rate after the 2nd month or 2nd year? If you’re operating a B2B software-as-a-service product, what’s the churn risk status for your customers, or which segment actually churns? These are just a few examples you could look at; the exact metric will depend on your product and what you can measure.
Once you have the data, do a similar segmentation split as earlier for the new users to get a hunch of where you’re performing the best. Do you see any segments where you’re losing customers faster? Are there any high-performer groups that tend to stick to your product? In any case, you should see some relevant results if you have the correct segments.
Coming up with the conclusion
If you were able to come up with good metrics to quantify your product/market fit for new and existing customers, now it’s time to combine them! Ideally, they shouldn’t tell two very different stories about how your product is fitting to your user segments.
Remember, there is always noise in the data — individual scenarios where customers didn’t choose you not because you wouldn’t be a perfect solution for their problems, but because something unexpected came up. So the more customers you have, the less chance that individual edge cases will affect your analysis.
To get more advanced findings, try to weigh your customer segments by the segment size (number of users) or the revenue they generate — based on how flat your pricing is. As five unhappy customers in one segment are not the same as 500 in another.
Please keep in mind that these metrics are only proxy metrics to quantify product/market fit, so it’s not an exact science. Take any insights you get out of your analysis with a grain of salt, and ensure that you have enough evidence before making any decisions!