Despite being touted as the only thing startups should think about if they want to succeed, many founders and entrepreneurs have a tough time measuring product/market fit. And if you can’t measure it, how do you optimize for it?
As Rahul Vohra explains in his story about finding product/market fit for Superhuman:
The descriptions of product/market fit all seemed so post hoc, so unactionable.
After receiving such positive feedback on our post on why startups should look into Google Data Studio, we knew we had to do a follow-up. And where’s a better place to start than product/market fit?
There’s no be-all end-all method of measuring product/market fit, but that’s where Data Studio comes in handy. As a tool that can connect and visualize different data sources, Data Studio can track all the different metrics that contribute to product/market fit in a centralized, easy-to-read dashboard. Here’s what we would include in our product/market fit dashboard:
The 40% Rule
Let’s start with how Rahul resolved his product/market fit crisis. He took inspiration from Sean Ellis’ observation:
Achieving product/market fit requires at least 40% of users saying they would be ‘very disappointed’ without your product.
To get to this magical 40% number, Rahul simply sent out a survey to the couple hundred test users he had at the time. He then analyzed the results and made adjustments to his product roadmap until he hit that target.
In Google Data Studio, you can track this % of users by feeding your survey results from Google Form, SurveyMonkey, or Typeform etc. into a Google Sheet. As you collect more survey responses, Data Studio can display that information in real-time. And depending on how you setup your Google Sheet, you could also dynamically segment your survey responses by those who would be “very disappointed without your product” (and those who wouldn’t be) for further analysis.
We can’t talk about product/market fit without mentioning a16z partner, Andrew Chen. In his presentation on Zero to Product/Market Fit, Andrew focuses on overall engagement and organic acquisition for consumer product startups. That means looking at your organic signups and daily active users.
As most consumer product startups live on a website or app, these metrics can easily be monitored by connecting your Google Analytics account to Data Studio. You can then filter your acquisition by traffic source and plot your acquisition growth to make sure it’s on track to product/market fit. According to Andrew, that looks like hundreds of signups per day with at least 30% active usage from day one of signup.
For SaaS startups, Andrew has a different set of metrics for measuring product/market fit centered around monetization, such as free-to-paid conversion rate, lifetime value and cost per acquisition ratio, churn rates, and monthly recurring revenue.
This is where Google Data Studio really shines. Gathering all this data on a regular basis is usually a chore for most companies (startup or not) because it dips into metrics that typically span multiple platforms and/or departments.
With 100+ data connectors, Data Studio helps centralize everything in one all-seeing dashboard. For example, you could sync your revenue and churn data from Stripe, advertising costs from Google Ads and Facebook, and conversion rates from Google Analytics.
Inspired by Data Studio? Have any other ideas on measuring product/market fit that’s not covered here? Get in touch at firstname.lastname@example.org; we’d love to hear your thoughts!