What Metrics Should I Prioritize to Effectively Gauge PLG Success?

Tapping into True Value: A Metrics-Driven Approach to Product-Led Growth

What Metrics Should I Prioritize to Effectively Gauge PLG Success?
Blog Category:
Development
|
View All Blog Posts

The key to PLG success is figuring out what set of features builds a habit forming pattern for each use case

The theory behind product-led growth is that the way to achieve great revenue metrics (both growth and retention) is to create a deep connection between the users and the product.

A deep product connection is demonstrated by a user using your product, in a perpetual manner, to solve specific pain points or achieve specific goals. This is a really basic point that gets lost. But it is as simple as this…we use products that solve our needs. We stop using products when we don’t feel like that product is delivering value to us.

Thus the best metrics to measure to determine PLG success are metrics that show whether we are delivering value to customers. 

How do you define "product usage"?

Too many teams define product usage as does a user log-in or click buttons? This is the wrong approach and will lead to a lot of false positives. 

User Activation Rate is a measure of the percentage of your new users who use your product to solve their need/pain point. Making user activation rate specific to solving customer pains/needs will make it much more valuable than simply log-ins/clicks. Product Engagement Rate is the same metric but over a longer time period. The key is that both activation and engagement are determined by a product usage pattern that perpetually delivers value to your users. 

So how do you know if you are solving a customer’s pain points/needs? 

That sounds simple, right. But it's complex because not all users have the same needs/wants/pain points. And not all users have the same inputs - eg. data, processes, personnel skills, culture, etc. Certainly there are commonalities amongst your customer base, but there are also a lot of nuance differences across a customer base that impact perpetual delivery of value. 

Case study - Twitter (X)

Let’s use Twitter (or X or whatever it is now called) as an example. Measuring the total number of Tweets is not a good metric to determine PLG. Nor is advertising revenue.

Why do new users sign up for Twitter?

Some sign up because they want to get their message out to a big audience. Others have no intention to ever share their opinion, but want to read interesting content.

Knowing what success is for each user will help you determine if you are continually delivering value to them. For users who want to get their message out, a PLG metrics that aligns to value is the percentage of those users that tweet. Not just in the first seven days, but in 30 days, 60 days, 90 days after signup.

Does the experience of tweeting build a  habit forming pattern for that segment of users that drives ongoing product engagement? Maybe it isn’t the tweet. Maybe just Liking a tweet builds that deeper connection? Maybe it is following accounts that you like or even accounts that you hate that builds that deeper connection?

The key to PLG success is figuring out what set of features builds a habit forming pattern for each use case that drives a sign up, and then optimizing it.

Another example

I work with a customer that runs a team collaboration software. They want to get users to continuously update their team using the software. So their question for activation is, “what percentage of your users are consistently putting their updates into the platform at the 30 day mark? At the 60 day mark? at the 90 day mark?” Does doing it more than once in the first 7 days hook the user? Do other features impact the likelihood of a user building that habit forming relationship with the product?  

The core philosophy of product-led growth is that by driving a habit forming pattern with the product, that downstream revenue metrics will follow. Thus you need to know:

  1. Why each user is signing up? Of all of your use cases, which is most important for that specific user  to solve?
  2. What product features align to those use cases?
  3. What percentage of new users experience those features that align to their need? (i.e activation rate)
  4. Is that feature a habit forming experience that creates a perpetual desire to use the product? (i.e. engagement rate)

If you want to discuss how to do this with your product, we offer free office hours.

Join our LinkedIn Group - Using Data for PLG.

Contact Us

About Winware

Winware helps SaaS teams drive better trial conversion rates or higher retention rates by optimizing SaaS onboarding to align product features with customer's goals.