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PLG Metrics (+ my template)
Hi all 👋
If you already subscribe to my newsletter, you’ll know that I’ve written extensively about topics intersecting PLG and data, such as how to measure engagement.
Today I wanted to go one step further and share a great set of metrics that I like to see companies measuring when I advise them in PLG,
Find my full PLG metrics template here on June.
North star metric
Let’s start simple, with one metric.
North Star metrics are critical and serve as a beacon to directionally align your growth strategies around.
For PLG companies, your north star metric should be an engagement metric,
But not your default xAU style metric (daily, weekly or monthly active users).
An engagement-based metric should be about the core value.
The core value for Snyk was teams fixing security issues.
It wasn't the fact that we could find vulnerabilities or show them; it was whether the team was fixing those vulnerabilities.
So fixing was the core value.
We knew that security is a team sport, and we cared (philosophically and commercially) about teams being successful.
So our engagement-based north star metric wasn't user-based, it was team-based.
We used the phrase “team fixing” to incorporate both of these ideas.
And then, we thought about natural problem/usage frequency.
For Snyk that was around teams paying down their security debt on a weekly basis.
This aligns well with standard dev team cadences - you’d expect some form of security debt paydown on a weekly basis.
So, our north star became Weekly Fixing Organizations (WFO).
Everything else waterfalls from here.
You start to derive initiatives not just in the growth and product teams but across multiple teams around the company.
Of course, north star metrics are not intended to be moved directly.
They’re the beacon, but they typically lag in measurement, and are driven by a set of more granular and actionable contributing metrics.
Engagement states was one such metric for Snyk.
Our engagement states weren’t volume based but based on the frequency of fixing.
We defined three core buckets of engagement states plus the dormant state.
Dormant: A team who had not fixed issues on any day in the last 30 days.
Casual: A team who had fixed on between one and three unique days in the last 30.
Core: A team who had fixed on between four and seven unique days in the last 30.
Progressive: A team who’d fixed on eight or more unique days in the last 30.
All are independent of the volume of fixes.
This was about establishing and measuring fix habits.
There was a huge amount of though, analysis, data science and iteration that went into defining and operationalising our PLG metrics at Snyk.
So get your north star and start to build out the contributing engagement metrics from there.
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Other PLG metrics (and my template)
If your growth strategy is similar to Snyk’s and you’re aiming to acquire thousands of free users before you introduce any monetisation, then you're going to be more focused on product-centric metrics in your early days than anything else.
But you’ll also likely be tracking the cost and efficiency of user acquisition channels to try and optimise the mix as you grow.
Of course, even pre-monetisation, you've also got to be thinking about your revenue model and what that will look like. You've probably got a bunch of hypotheses that you want to validate.
To improve all of those above, you need to measure the right things. I call them the “PLG metrics”.
They cover acquisition, retention (inc activation & engagement), and monetisation.
I shared a list of fundamental PLG metrics with the June team here.
If you’re not measuring these metrics, the article comes with a handy template you can reuse once you plugged in a data source.
Hope this saves you some time!
Until next time!
PS: While you’re over there, check out the podcast interview I did with the June team where we go into all this and much more!
Noah Desai Weiss on how Slack builds product on Lenny’s Podcast
3 interesting reads: