Finding product-market fit with the power of product analytics

Finding product

Product Market Fit can be discovered in a scientific & repeatable way and product analytics can guide you along this journey(Finding product)

Product-market-fit (PMF) is “the only thing that matters” — that’s a widely quoted line from a superstar venture capitalist, Marc Andreesen. For early-stage startups, the million-dollar question about finding PMF, therefore, is: how do you know if your product is a hit? The easy answer is: when your customers use it.

But the reality is a bit more complicated than that. It’s more than just tracking if your customer uses your product. It’s also seeing which customers use it, how they use it, knowing what compels them to keep using it, and if your product is used the way you intended.

When we talk about what PMF is and how you can measure it with product analytics, the key question for startups looking to measure PMF is: how to use your data to improve your product into one that customers find valuable.

These questions around PMF were discussed in-depth during a learning session moderated by Casie Millhouse, Co-Founder of Element XR, in conversation with Rafael Loh, Solutions Consultant APAC at Mixpanel. Rafael started the discussion by pointing out that “most companies are sitting on a gold mine of product data and don’t have the analytics tools to make it useful.”

Product analytics help startups better understand how valuable your product is to your users. At the end of the day, Rafael says we are “all building products for someone — users!” The dilemma faced by most early-stage startups that are on a journey to find PMF is how to measure PMF when they haven’t found it yet.

Rafael said, “since every startup has a different journey, the need for product analytics evolves according to the stage of the journey.” Basic product analytics needs are around analysing user acquisition and conversion analytics.  As the product matures, startups need to build a data stack to collect and connect more data sources for a more comprehensive view of how people engage with their product, to better inform product decisions. In the final stage, organisations build a culture that is data-driven and must continually ask questions to verify product development decisions.

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“You need to attract the right users so you can get more data,” said Rafael. “It’s really about analysing usage at the start to find out where users are coming from, who they are, why they drop off, at which stage they drop off, and you might want to compare conversion rates between users and time periods” he added.

Data thus becomes the fuel for iterative product development and experimentation: as product teams release new features, they will need advanced product analytics with the right tool to know if these new features are indeed having a positive impact.

Rafael also explained that making it easier for product teams to get the right answers to make development decisions is even more crucial when a startup is finding PMF since it allows startups to experiment quickly and adjust their offerings based on these insights.

To the question of whether data collected from concept sales or test pilots are viable for finding PMF, Rafael said that this data can “never be 100 per cent but it does give a good idea of how the customers see your product. It gives you your first direction.”

The key learning about PMF is that it always changes — customers change, products change, and business models evolve to adapt to changing market conditions. The time needed to move from using basic to using advanced product analytics to measure PMF differs from business to business. (Finding product)

Why do product teams still struggle to prioritize features and measure their impact?

With so much data at their disposal, Rafael thinks that many product teams are still not confident that they have the right analytics to make decisions around product development. Rafael points out that this often has to do with startups trying to answer product and user behaviour questions with tools that don’t quite do the job.

Some startups try to use marketing analytics to answer questions about their users, but it cannot address key questions around customer engagement and retention such as: why and how customers are dropping off, where they are dropping off, and how much time passes between activation and drop off. Knowing what users do and why they stick with your product is the key to measuring PMF.

Startups are also often attracted by codeless analytics, but a lot of no-code tools are not as precise and lead to poor data tracking. On the other end of the scale, in-house solutions using BI tools like Tableau or SQL are often slow to implement and require technical knowledge. Mixpanel’s self-serve analytics balances these two approaches and offers both depth and flexibility with the right ease of use. “Mixpanel does not require teams to have the technical knowledge and they are empowered to get the precise metrics they need without the need to rely on technical teams”, said Rafael.

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Having an Audience that Cares: Why PMF matters

The reason why PMF matters is that “if you address a market that wants your product then you will succeed, even if your company does not have the best product features or best business model.”

According to Rafael, finding PMF is about identifying features you need to build, having an audience that’s likely to care, and the right business model required to entice your customer to buy the product. That’s why most startups fail, as they tend to address the wrong market or have a product when there is no market need.

“Finding PMF is never a straight path,” Rafael explained. “Combining intuition with being data-informed can dramatically increase your chance of success in reaching PMF. This helps you to get to the point where you’re making products that people want, turning over a profit, and building a sustainable business.” (Finding product)

Common myths about product-market fit

Rafael said that the most important metrics to measure PMF are engagement and retention metrics. “If we look at engagement and retention, it’s never a one-time journey — you might acquire millions of users but retention and engagement, in the long run, is what determines PMF. The question startups must continually ask is: is my product useful for users?”

Rafael addressed some of the common myths that have sprouted around PMF, including:

  • PMF is always a discrete, big bang event: finding PMF is never something that happens in a single moment in time.
  • It’s patently obvious when you have PMF. It takes time to understand. Finding PMF is a subtle process that needs to be understood as a continuous process.
  • Once you achieve PMF, you can’t lose it. It is possible to lose PMF.
  • Once you have a PMF, you don’t have to sweat the competition: Rafael cited the case of Airbnb which lost a large amount of business after the COVID-19 hit. They recognised the loss of PMF and changed their product to include digital experiences. While they did suffer losses, the company was able to quickly adapt to find a new PMF. It shows that PMF is not something that will continue forever or can be taken for granted.

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Rafael was asked who is responsible for monitoring PMF in a startup. PMF is never always the sole responsibility of the product manager even if they do have visibility into every aspect of the product and business. Product teams need feedback from leaders, marketing teams, and customer teams because these teams on the ground know what is happening in the real world and can provide a full view of what is happening in the market.

What does product-market fit look like?

You can spot some of the classic signs of a product with good PMF, such as, when there is visible excitement among potential customers and there is a genuine buzz when they hear about the launch or look at your product even in the pre-product launch stage. Typically, people are willing to queue for early access to the product.

Post-product launch, PMF is mostly visible from how users stick around and engage with the product. Users are disappointed if your product goes away, and the product organically sees exponential usage and growth.

Cost-efficient growth is also a healthy sign of a product finding PMF: when customer acquisition costs are consistently lower than customer lifetime value, it means that customers are clamouring for your product.

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While the above signs are a good representation of PMF, Rafael added that PMF can also be considered analogous to user retention for product teams. (Finding product)

PMF means retention, user activation, and habit-forming

User retention is a very good indicator of PMF. Even for startups with exceptional customer acquisition numbers, active users quickly drop when user retention is not there. For a product where the natural frequency of the typical use case is more than one month, the product enters the “forgettable zone”, and you must re-acquire the customer.

PMF is about defining that habit-forming moment that shows that users are likely to become engaged. Teams looking to find PMF should focus on defining these moments for their products. That is why companies like Slack or HubSpot define this habit-forming behaviour in terms of “x out of y days in which the product has been used,” said Rafael.

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Therefore, product enhancements should be done to increase retention and engagement metrics. Rafael said product development should be about asking “is the new feature allowing users to stay in the product and get a better experience?”

Rafael pointed out that a key aspect of Mixpanel is that it allows you to see if new features help in retaining users. “We need to know if a new feature is helping customers find more value in the product. This is one way to find PMF. The second way is to look at reverse or negative metrics. If they cannot find what they are searching for they will churn out and leave,” he continued. The idea is to look at potential reasons you are not retaining users, he explained.

Key takeaways on finding PMF

Finding PMF is a milestone that makes fundraising easier. VCs will be knocking on your door the moment they see a PMF. Rafael said that PMF can be discovered in a scientific and repeatable way. It is closely linked to retention, and you can find it by understanding the “Aha” moments and habit-forming moments to define and optimise your activation funnel. (Finding product)

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Finally, leveraging strong product analytics tools like Mixpanel, can help you gather measurable and actionable insights to guide you along this journey of finding PMF. To listen to the full discussion between Casie and Rafael, click here to view the full webinar.

Pranav Vadehra

Pranav Vadehra

B2B Content Strategist and Business Journalist