5 Metrics to consider when looking at Product-Market-Fit

Product-Market-Fit, or PMF, is this elusive state of a business that challenges startup founders, business leaders, small business owners, solopreneurs and almost everyone in between. If we are in business to make money and deliver value to our customers, we need to think about this. Broadly speaking, Product-Market-Fit is the point where our offering, be it a product or a service, resonates with our customers that they become enthusiastic buyers. Notice that I don’t put users and buyers in the same bucket. This is because a user may not be the buyer, and in that sense, is not a customer. When I speak of PMF, I am referring to the alignment between our offering and the ones who pay us for it. What would make our target customers enthusiastic buyers is for another discussion in a following article where I will explore how we could hack the PMF journey by shortening the process and lowering the cost of doing so.

Here are five metrics we can look at when assessing if we have reached PMF and should double down on marketing to gain more traction and scale. I have divided them into Metrics that Don’t Matter and those that Do.

Metrics that DON'T Matter

1. User count isn’t it, unless the user is the product

Some advocate looking at user count to determine if a product has attained a fit with the market. But be clear: many users don’t mean good business monetarily, that is if you need them to pay you to use the service you provide. During the pandemic, we saw many users jumping on to technologies that enabled remote working. In the education space, we saw many teachers signing on to products that enabled them to deliver and manage lessons online. They were desperate to lay their hands on anything that could help them keep going as schools closed and students were confined to the four walls of their home to continue learning. So we saw many edtech companies soared in user count. They then used this metric to raise lots of money (and many did). When covid-19 ended and the world recovered, these companies found themselves badly hit – ultimately, the users didn’t want to use these products in the first place. They were forced to do so because the world didn’t offer a way to continue living life then. Thus, the moment the option to get back into the physical space was available, they jumped at it and jettisoned these online products that they signed on to.

Also, having many users with low conversions to paying customers is not good, since ultimately, revenue is the main goal in any business. If our users don’t pay us and we don’t have a way to make revenue from these users, then having many users who are not paying may only suggest that our product has achieved a fit with the market where payment is not essential.

2. Revenue may not be it

What if we have revenue from these users? Is that good enough and would that suggest a product-market-fit? Well, it depends. For example,

• if the revenue comes from users who initially signed up with us and quickly decided to drop us after a short period of say, 1 or 2 months, it suggests that our product isn’t sticky enough to gain top of mind. A high churn rate is a matter of concern. High revenue with high churn suggests that there is great marketing but no product-market-fit – if a customer doesn’t return to buy again, chances are we may have lost that customer, or

• if our users stick around and pay, as indicated by low churn rate, it’s good. But if this is all there is with no significant growth month-on-month, then it also doesn’t suggest a PMF either. There are many reasons for them not terminating the service – it could be that this group of early adopters liked the service enough to let it running in the ‘background’, or that the cost of the service is low comparative to their income that they could afford to let it hang around and use it when they feel like it. We see that happening to upper middle-class families subscribing multiple TV streaming services while not liking any one in particular. Contrast this with those who spend a lot more subscribing to football or specific sports channels and would organize friends’ gatherings every weekend to watch a match. The latter suggests a fit with the target market while the former may be prone to cancellation at any point in time.

This is why PMF is so elusive: if the product doesn’t stick, it becomes a problem. But when it does stick, it could still become a problem.

So, if revenue and user counts are not the right metrics to look at, what is?

Metrics That Matter 

3. Track Promoter Scores

I prefer to look at Net Promoter Score (NPS), or what I would call a Mean Promoter Score (MPS) for a product to its target customers. Both NPS and MPS reflect how much a user would promote our product to his/her friends. These scores are derived from an arbitrary score that users would give when asked how likely they would recommend our product/service to their friends. NPS has been written extensively and it varies from industry to industry. Personally, I prefer a more straightforward MPS, which just averages out the scores from the sample of users surveyed.

On a scale of 1 to 10, any average score that is higher than 8 suggests some form of PMF and the company should double down to help these users promote its product/service on their behalf.

For products whose MPS is below 6.5, the company should either redesign them or get them off the market before the cashburn to promote these products hurt the company – this is straightforward and the leaders only need to be decisive.

But what if the score is between 6.5 to 8?

This ‘neither-here-nor-there’ score is a headache for business leaders because it suggests that the product isn’t bad but isn’t great either.

In this situation, we need to find out just what is missing that isn’t making our customers rave about product? We might have made something people like, but definitely not something they LOVE. We need to make things people love (quoting Y Combinator’s motto). It could be that our products are good to have around, but not a must-have. It could also mean that we may be targeting the wrong customer, or we could be solving a problem way bigger with the same solution for another customer. Whatever the reasons behind this lackluster score, we need to dig deep and uncover it. It calls for mix of experimentation, thick-skinned approach to talk to the customer and an open mind to rethink, retool, redesign what we have.

We also need to examine if our customers are dropping us readily to see if there is a deeper narrative. We need to look at Churn.

4. Pay attention to Churn Rates

Taking a broad view of churn, the rate of churn really just means how likely will the customer drop our product or service after a period of time. For a subscription-based business, it can be easily measured by looking at customers who stay with us period-to-period versus those who stop using our services after the typical period of business – this could be a week, a month or a year, depending on the nature of the business.

The higher the churn, the lower the chance to make money off that customer, and the lower the Lifetime Value of the customer (I will discuss more on this metric in the next section).

When taken together with MPS, we can see different narratives emerging. In my book on startup to exit, The Fast Founder, I framed the balance between Churn Rate and Promoter Score into four quadrants, indicating different levels of PMF (pp 157). With these two pieces of data on hand, business leaders can better decide on what to do with the product/service that they have launched into the market.

5. Look at LTV : CAC Ratio

LTV, or Customer Lifetime Value, represents the total revenue a customer generates throughout their relationship with your business. For businesses with very strong brand value, the LTV can be high even if they may be making money from one-off sale on a model that isn’t necessarily a valuable one as perceived by many venture capitalists. The thing that makes these businesses valuable is that these customers keep coming back and make repeated (“one-off”) purchases because these brands have such powerful top-of-mind that they almost set the standard for the product or service category.

When it is difficult to determine just when a customer will end the relationship with us, we take an average of how long the customer will stay with us. For instance, Netflix calculates an average LTV of $291.25 per subscriber over 25 months.

Whether a business is one that has recurring revenue (eg. a subscription-based or a retainer-based business) or one-off-sale-based revenue, we can see that Churn Rate plays a direct role in determining the LTV of the customer. A high churn would naturally reduce the LTV. To maintain the revenue of the company, we would need to spend more money acquiring new customers. This leads us to the next metric: the Customer Acquisition Cost or CAC.

CAC is the average cost to get a paying customer. It reflects our investment in marketing and sales efforts that help us get traffic to our site, generate leads, warm the leads, and make the sale. So why does CAC play a role in PMF? Well for one, if we need to spend a lot to get customers, it may suggest that our product isn’t that awesome enough for our current customers to tell others about it, or it isn’t that inspiring enough for the mainstream media to talk about it as an ADO (refer to my discussion in Chapter 2 of The Fast Founder).

But when we put CAC together with LTV, it can be prescriptive as LTV:CAC ratio is a critical metric that helps assess product-market fit. It compares the customer lifetime value (LTV) to the customer acquisition cost (CAC).

A healthy LTV to CAC ratio is typically around 3x. Lower than this ratio may indicate a lack of product-market fit.

For early-staged startups, some VCs have recommended tracking LTVs based on the net profit that a customer brings to the startup and that a ratio above 5 suggests an opportunity to invest more in sales and marketing.

So what can we do when our products or services don’t seem to achieve PMF? Or how can hack the PMF journey so it less like shooting in the dark?

Here are some ways I can think of, for example:

1.     Don’t be the only person addressing the problem

2.     Do things that don’t scale

3.     Iterate towards an ADO

4.     Don’t be ashamed to stop and start over

5.     Find the hidden asset

6.     Talk to Customers But don’t rely on their feedback

Let me delve further in the subsequent articles of this newsletter!

Eric Lam

I help entrepreneurs & business owners scale their enterprises for exit at Recast Ventures.

I wrote the book 📘📙The Fast Founder: from Startup to Exit in 36 Months 📕📗 -- It made AmazonSG’s #1 Bestseller (Small Business) in 2 weeks and Kinokuniya Bestseller in 5 weeks.