Metrics to focus on before and after product/market fit. How to better understand your product at different stages?

Product/market fit is the make-or-break factor for a company. It helps businesses understand whether their product has market appeal and they can dive into the product growth stage with confidence.

We interviewed experienced product managers from different companies about metrics that help product teams achieve better results at different stages of product development. They shared their thoughts on the following:

• What approaches and metrics should the product team focus on before reaching product/market fit?
• What approaches and metrics should the product team focus on after reaching product/market fit? 
• What changes should product teams make to shift from pre- to post-p/m fit work?

We would like to thank all the experts who shared their experience with us and helped us answer these important questions.

• Phil Anderson (Senior Product Manager (PM-T) – INTech, Amazon) 
• Shiva Hullinakatte (Senior Product Manager at AT&T)
• Alex Merwin (Head of Growth, Healthcare & Life Sciences Startups at Amazon Web Services)
• Daniel Johnson (Founding Partner at We Scale Startups, Lead Growth Mentor at Google)
• Sam Juraschka (General Manager & Director of Product at BCG Digital Ventures)

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Q: What approaches and metrics should the product team focus on before reaching product/market fit?

Before product/market fit, a company is still trying to figure out its ideal customer base and use cases for their product. At this stage it’s important to use qualitative data and be as close to your customers as possible. Here are some of the key ways you can explore customer needs and better navigate product development stage:

• Directly talk to your customers: arrange surveys and interviews
• Pay attention to how many users stay with the product and how many churn
• Validate your assumptions and try to mitigate risks
• Keep an eye on word of mouth about your product

Shiva Hullinakatte (Senior Product Manager at AT&T)

At this phase, it is important to get qualitative indicators of product performance along with engagement. Surveys can be a great tool to understand product fit and performance.  They help gauge how disappointed customers would be if a feature didn’t exist. In one of my previous roles we launched a rule-based chatbot to help our members get answers to top questions without having to contact our customer care center. We wanted more information on how useful this product was to our customer base. Hence, we implemented a simple survey that took qualitative feedback and asked how much they would miss this feature if it was not available. The number of people who would be disappointed was very low. It also translated to reduced engagement. So we used the responses to pivot and we eventually shelved the product without an ideal use case. 

Alex Merwin (Head of Growth, Healthcare & Life Sciences Startups, Amazon Web Services)

In the beginning it’s essential to track customer adoption and recurrent usage metrics. It will help guide your feature development. I used to work for video advertising company SpotX. My team was responsible for the API that our buy-side partners used to access auctions and submit their bids. We measured the number of bids submitted and the bid rate and compared these metrics with the anecdotal insights from our customer success team. We knew there was a customer who had more advertising demand than we saw in their adoption and usage metrics. So we had an in-person review with their product and integration team. They were looking for data to assess the value of an impression opportunity accurately. But our API didn’t provide it. We updated our API to include the new elements, which increased the customer’s service usage. 

Daniel Johnson (Founding Partner at We Scale Startups, Lead Growth Mentor at Google, Mentor at Oasis and GrowthMentor)

There is not a particular set of metrics that can tell any business when it achieves product/market fit. However, the following metrics will help us find out if our company is headed in the right direction.

1. NPS score. The Net Promoter Score is a score that ranges from -100 to 100. It measures customer satisfaction and loyalty towards a brand based on the customer’s overall evaluation of the product or service. 

2. Churn rate. It reflects how a company’s customers stop doing business with it. Churn may also refer to the number of people who cancel or don’t renew their subscriptions. The lower your churn rate, the more customers you retain. At WSS, we measure these metrics by sending out surveys to our past clients and calculating the average working time with our clients. 

3. Word of mouth. If customers talk about our services with others, they will eventually become our product’s sales representative to a certain extent. Clients will be more likely to spread the word about our services if we can meet their expectations and achieve better results than the market average. Therefore, we have been trying to maintain and improve our standards and provide clients with professional services. Moreover, we have also set up a referral program with many benefits on our web page to encourage clients to refer us to their networks even more. 

Sam Juraschka (General Manager & Director of Product at BCG Digital Ventures) 

At a pre-product/market fit stage, a PM should be thinking about metrics to support your qualitative user research. This typically helps to validate and derisk big assumptions across the business, product and tech stack.

In early-stage products I use a whiteboard when working across workstreams like product, operations, and business development. It helps to define the key learning goals and set targets for the test phase. Going workstream by workstream, we share our riskiest assumptions and come up with ways to test them. We can track completion of certain product flows, operational flows, successful user registration, feature usage, or payment processing.

Oleg Ya (Founder at GoPractice, ex-Facebook)

Before product/market fit, qualitative data is much more important than quantitative data. Teams should be as close to the customers as possible. They can use interviews, surveys, or manual onboarding/support to do that. These methods enable you to get feedback quicker and understand your customers better. It helps navigate this unpredictable and ambiguous product development stage where the team is trying to find out how exactly the product can make users’ lives better.

Metrics would be useful too, but usually as additional indicators of the value your product creates for users. At this stage, I would choose just a few key metrics that would represent how much value your product creates for users (value metrics) and a few product metrics to see how users interact with the product. More on product metrics, growth metrics, and added value metrics.

Q: What approaches and metrics should the product team focus on after reaching product/market fit? 

When your product has proved that it is valuable to users, you can start building a business around it and enter the growth stage. Before, you were focused on just creating value for end users. Now, your main goal is to find ways to deliver this value to the target customers. That’s why growth metrics should become your focus at this stage. It’s good to start with choosing an appropriate North Star Metric and then break it down into the sub-metrics that affect it: new users by channels, active users, revenue, market share, etc. 

However, this doesn’t mean that the team should stop improving the product. One direction you can take is making the core product better. To measure progress here, you can use value metrics. Another viable option is to invest into optimizing key product flows and conversions. The best way to measure this is through product metrics (key funnel conversions, retention, purchase conversion, etc). 

As the product grows, it becomes important to complement qualitative methods with quantitative data that can help figure out how different users react to different changes. To better understand what is happening with the product, you can group users based on use cases (jobs-to-be-done) or buying personas.

Let’s dig deeper into metrics that can be helpful:

Shiva Hullinakatte (Senior Product Manager at AT&T)

After reaching product/market fit, my key metrics fall into measuring engagement and ensuring that users continue to use our product. I have been part of multiple online digital experience organizations. From an engagement metrics perspective, I look at the number and trends of online transactions, key funnel conversion metrics and a key qualitative metric that measures the ease with which our customers accomplished those tasks online. Along with surveys, these metrics can be used to continually monitor and improve the product.

Alex Merwin (Head of Growth, Healthcare & Life Sciences Startups at Amazon Web Services)

Once you’ve seen the “hockey stick growth” pattern, you need to group customer usage by buying personas. Is your usage coming from a small group of dedicated users within a customer segment, or are your users only engaging sporadically and spreading usage across a more extensive user base within the customer’s organization? Understanding this makes a big difference in how you plan your go-to-market strategy. 

At SpotX, our buy-side API partners were technology providers themselves, and the end customers were advertising agencies and sophisticated brands who licensed software for participating in video ad auctions to place paid media. We began to ask our buy-side API partners to include ‘seat_id’ in their API responses so we could group the buying behavior across end customers. We used these insights to tailor our supply-side publisher acquisition strategy to approach publishers that would be valuable to a broad buyer base. 

One lesson I learned is that you need to be deliberate about defining the value proposition for your customers to make any change to their API configuration, as it takes time and money for them to do so. In our case, we had a direct line of communication with the end customers through a dedicated sales team, so our value proposition to buy-side API partners was about better understanding the end customer needs and driving more usage for their software. This worked pretty well for us. 

Daniel Johnson (Founding Partner at We Scale Startups, Lead Growth Mentor at Google, Mentor at Oasis and GrowthMentor)

There are three metrics that a company should use:

1. Retention. The customer journey should not end with the first purchase. The brand should know how to keep these customers engaged and interested in their products or services. One effective customer retention strategy we have done in the past is retargeting ads and producing promos and discounts for the current customers. This way, the customers will keep patronizing the products, and there is a big chance that they will promote the brand through word of mouth. Understanding the customer funnel is also extremely important because brand-customer relationships should be continuous and engaging.

2. Growth rate. Growth rates are the compounded annualized rate of change in a company’s revenues, earnings, dividends, or even macro-level measures such as gross domestic product and retail sales. A high growth rate can assist a firm in acquiring assets, attracting new talent, and funding investments. Furthermore, it enhances business performance and profits and indicates that a company has reached product/market fit and maintained its position for an extended period. At WSS, we carried out revenue and profit reports quarterly to see our general performance and predict our future growth rate.

3. Market share of a company. An industry’s market share is the percentage of total sales generated by a specific company. This metric estimates how large a company is in comparison to its competitors. It is pretty challenging to measure the exact market share of a company. Therefore, at WSS, we use our quarterly reports and market research to evaluate our general performance in recent months compared to our competitors.

Sam Juraschka (General Manager & Director of Product at BCG Digital Ventures) 

In growth-stage teams, you will have a growing backlog of functionality adjustments and new additions. To understand the impact on the product and business, the backlog should be evaluated on a prioritization framework, which is usually based around the north star metric of a product. 

Phil Anderson (Senior Product Manager (PM-T) – INTech, Amazon) 

There is not an exact moment where you feel you have reached product/market fit. If we define product/market fit as having achieved a steady stream of users signing up and paying for your service, the main thing I would be monitoring is active usage, cancellations, and referrals. The decline of active usage is usually a leading indicator (since the dirty secret of SaaS is that many inactive users still pay and only end up canceling when their card expires). At my previous company BudgetSimple, I found myself at a point where users liked it themselves, but were not recommending it to their friends. This was clearly a missed growth opportunity and something I focused on later in the business lifecycle.

Oleg Ya (Founder at GoPractice, ex-Facebook)

Achieving product/market fit means that the product creates enough added value for some users to make them choose it over alternatives. It means that your product is now ready for growth. Therefore, you should start focusing not just on the product but also building and growing a business around it.

As the product gets bigger, it becomes more and more difficult to rely just on qualitative methods to understand what is going on and how different changes affect different users. There are just too many moving parts now. This makes it increasingly important to use quantitative data and metrics to make data-driven decisions.

The specific metrics will depend on the product and the task it solves for its users. I believe that the team should come up with value, product, and growth metrics that describe their product and business really well. These metrics will give the team a good understanding of how different changes affect end users and their behavior.

Q: What changes should product teams make to shift from pre- to post-p/m fit work? 

In the pre-product/market fit stage, your key focus should be on finding the product that people love and choose to solve their problem. Afterwards, you must concentrate on engagement and delivering the value that you created to those who can benefit from it. It is time to focus on removing all the bottlenecks that limit the delivery of value: technical risks,  product quality, etc. 

Sam Juraschka (General Manager & Director of Product at BCG Digital Ventures) 

More mature product teams often move away from frequent qualitative testing after they reach product/market fit. Typically teams are overwhelmed with demands, like a heavy backlog and aggressive expansion plans. As a result they have little or not time to get in-depth user feedback. Mature teams can lean heavily on product analytics and customer support inboxes to track the pulse of their users. You still need hands-on qualitative feedback from your users to add color to the data you are collecting. And it can also re-energize teams, help prioritization efforts, and prevent overbuilding.

Shiva Hullinakatte (Senior Product Manager at AT&T) 

The biggest change is what measurement you focus on in the pre vs. post product/market fit phases. In the pre p/m fit stage, the key focus should be on getting qualitative feedback to improve the product, and in the post p/m fit, the key focus should be on engagement. Fundamentally, product teams should continue to have the same data-driven rigor to measure what really matters in both phases. 

Phil Anderson (Senior Product Manager (PM-T) – INTech, Amazon) 

I would always be paying attention to the key metrics of active usage and new user adoption at all phases of the business. You could partly think of it as a hierarchy of needs:

First you just need people to sign up → then to stick around → then to pay → then to keep paying → then to refer friends  

For example, you wouldn’t want to pre-optimize for referrals when you don’t know if anyone even wants your product.