I first met Chris when we both worked together at Intercom, and have stayed connected especially as he’s crafted a unique role in CS Operations at Culture Amp. Culture Amp is a late-stage employee analytics platform used by companies like Canva, Etsy and Intercom).
Not only is his role part of a broader Revenue Operations group (vs traditionally in CS), but his remit also extends far beyond buying and implementing CS tooling. Specifically, he championed a digital-led customer experience program to drive scale and efficiency in serving SMB customers, while focusing on driving early activation.
Why?
Because his early analysis showed that customers who didn’t activate early enough had a 3x higher chance of churn.
What was the digital activation program?
The analysis established correlation and quantified the impact: customers who don’t activate within the first 3-4 months have a 3x higher rate of churn than customers who do.
The program was about delivering the same quality of support and engagement to smaller SMB customers through digital touchpoints like emails and in product experiences, while supporting them through a pooled approach of CSMs.
First we looked at customers who activate versus don't activate. There's a very small set of customers who never activate, and they obviously have a very high churn rate. We then looked at the timeline and asked: does it matter how early or late they activate?
What we found is that it’s less important how early they activate. They just need to activate by a certain point (i.e. 3-4 months). After that, it gets really risky. So the big insight is that it’s binary, as opposed to activating each day sooner would correlate to better retention.
And if you step back, it makes sense. For an organization to launch Culture Amp, the timelines are really set by HR. And they're usually not the sort of thing that they're going to want to accelerate or slow down. It might be a few months and that’s okay. But, if they haven't done it by a certain point, now it's risky.
The analysis established correlation and quantified the impact: customers who don’t activate within the first 3-4 months have a 3x higher rate of churn than customers who do.
Based on surveys, we see that 20% of revenue churn can be tied directly to poor or insufficient onboarding. But it's rare that companies have enough data to measure this accurately.
Yes, part of that is Culture Amp’s strong data culture, and part of it is where we’re at as a business. It allows us to quantify the business impact.
Everybody in the business assumed that early activation and churn were correlated, but you can't estimate business impact without knowing how much it’s affected.
So that's why I gathered all the data [for over a year to run the historical correlation]. Doing this analysis allows me to model what a 1% increase in activation means for the company in terms of ARR.
For your customer base, what were the qualitative reasons behind activating (or not)?
Activation for us is trying to say “what's the moment that a customer gets their first value that's unique from Culture Amp?”
So it could be launching a survey or performance cycle. We can track all of those elements through our platform and then track how early those events are happening.
Then for the customers who aren’t activating, we can do qualitative research to find out why. One of the biggest signals is whether the customer has an established launch date. So now, we’re working on implementing better ways to ensure we know when a customer expects to launch.
Another is that priorities, especially for SMB customers, can change very quickly in 3 months. And so they'll make a decision and then deprioritize an initiative or the company restructures. On one hand that makes sense, but on the other, if we can get an earlier read on these changes, Culture Amp is actually built to help in those moments and help an organization navigate those big changes.
Highlighting the actions a company can take (beyond sending more emails) is powerful. What have you discovered that’s counterintuitive?
I recently analyzed a number of elements to see its correlation with churn. Activation timing was one, but others were things like ongoing adoption.
I was surprised to see that there was a higher correlation between early activation and churn than adoption. So even if you had ramped up adoption before the renewal, that still isn’t as strong a signal as activating early.
What were you specifically looking at with adoption?
I was surprised to see that there was a higher correlation between early activation and churn than adoption. So even if you had ramped up adoption before the renewal, that still isn’t as strong a signal as activating early.
We have a fairly built out product analytics team. So they identified the 20-30 key signals that were the most connected to customer outcomes. Then we looked at the percentage of users for each customer who does those healthy activities within a certain timeframe. So it was pretty comprehensive.
It was less about volume of activity and more about saturation. So if you have a 300 person company, of those 300 users, how many are doing any of these things that we consider the core activities, versus how many of those events are taking place. Same with frequency. The frequency of an event can be thrown off by a single power user which doesn’t mean the company is getting value. It might mean one or two people are doing something over and over.
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For companies with the customer-scale, taking the time to quantify impact can give critical initiatives the kind of executive support and organizational focus that is needed. For smaller companies, these lessons are likely to be valid especially if you have a similar buyer persona or business model. But in any scenario where you’re anticipating or looking for growth, figuring out how to scalably help customers attain value will be critical.
