Product Market vs. Go to Market Fit

I am sure everyone knows what a product market fit but I would argue that many of the leaders don’t really understand how to measure it. In my experience, the more experienced leaders have a good ‘sense’ of product market fit but the great leaders use data to back that ‘sense’.

A good way to figure out if someone really understands product market fit is by simply asking - “How do you know that your product or service has product-market fit?”

Unfortunately, many leaders will just say, “We closed a $5M ARR deal and followed that up with two other deals that are $3M ARR and $1M ARR”. Others will respond with a similar argument that they can generate revenue.

I would argue that revenue is a terrible indicator of product-market fit. Generating revenue with a few deals could mean that you could have a message-market fit, or have a really exceptional discount that customers just can’t ignore or maybe you provided a white-glove approach with a beta customer that impressed them or maybe you prioritize building features for that customer to meet their requirements.

I highly recommend reading Hacking Growth by Sean Ellis*. In that he talks about the magic number for product/market fit which is 40%. Companies that struggled to find growth almost always had less than 40% of users respond “very disappointed” in the survey, whereas companies with strong traction almost always exceeded that threshold. In short, it means that 40% of customers say that they would be worse off if your product did not exist. This truly talks about the product experience and the value delivered by your product.

This is great, but this model is a lagging indicator. What companies need is a leading indicator for product market fit. Something that you can observe on a daily, weekly or monthly basis to say if you have a product market fit. Something that shows how your customers behave with your product. Some great examples are:

• Slack: If 70% of customers send 2000+ team messages in first 30 days, then there is product market fit

• Dropbox: 85% of customers upload 1 file in 1 folder on 1 device within 1 hour

• Hubspot: 80% of customers use 5 features out of 25 features in the platform within 60 days

However, you need to be careful to apply this across different cohorts of customers and not as a blanket metric. Co-horts should be based on the type of business you are in. For example, we could base it on verticals like education, fitness, healthcare etc and different industries can have a different metric. For example, fitness can have a higher usage metric than, say, healthcare or events vertical.

With product market fit, we look at customer retention as the primary goal, and this mostly applies to early adopters of customers. The Product Manager teams and the Business Development team should do most of the work of this. Note: When I say early adopter, I don’t mean early in terms of time; I mean, in terms of adoption. This phase could be as short as a few months or as long as a couple of years until you hit the right level of product/market fit. Note that I specifically use the term business development and not sales team. More often than not, this phase will probably lead to new product feature development and will be the phase where there will be very high feature velocity.

Ok, we talked about Product Market fit, so then what’s a Go to Market fit? GTM fit is about acquiring and retaining customers consistently and scalably (I have the wiki link to show that scalably is a word 😀 ) . GTM fit is all about scalable unit economics. GTM fit’s target market is the early majority of customers, and the playbook should be codified and should be scalable. The Business Development teams should do most of the GTM fit work along with a select group of sales champions or better yet, have a dedicated Business Development team along with a small group of sales specialist focused exclusively on your product. This work should lead to the development of sales playbooks, campaigns, demand gen collaterals and everything else that goes into making things scalable. If you see that you have to involve the engineering teams and/or the product manager for most of the opportunity, then you don’t yet have a product market fit. You may think you do, but you really don’t. The reason the product management teams and engineering teams are getting involved with customers is primarily for 2 reasons - 1) The business development teams don’t yet have the competency to sell or position the product on their own or 2) There are requirements that keep coming up that are outside of the norm of what a product can offer and a product manager or engineering team is needed to help figure out an alternative solution for customer or talk about the roadmap to convince the customer that they can invest in the product.

One critical aspect of the GTM fit phase is pricing. In the product market fit, pricing doesn’t really matter that much as almost every deal is a custom pricing deal. The pricing model has to be right for the GTM fit phase, and this is an important aspect of getting past this phase. This will ultimately lead to the growth fit phase, where the goal is the revenue growth rate. If you see yourself doing a ton of custom pricing deals, then thats a good indication that you are not yet in the GTM fit phase or you have not yet acheived the level of pricing where deals can happen without custom agreements. I would be a fool to suggest that revenue does not matter until you hit the growth fit phase. Revenue is, of course, important, but what’s more important is the focus on making sure that you have identified your phase accordingly. Trying to use the models and data of revenue from product/market fit phase to project the growth rate for GTM/market fit isn’t very logical and is more likely a ‘guessing game’ than a proper model. You will likely try to fit the model than actually using the model to project the growth rate.

P.S: *I don’t necessarily agree with the term ‘hacking’ though, especially with growth as it suggests that it's a niche area and hacking by its very term isn’t something that is scalable. 😀