This is the foundational customer work teams skip
Seek first to understand, or something like that.
Yesterday I wrote about 4 constraints customer success teams work in that other teams don’t have to stress.
This is a continuation of that idea, working through how to start dealing with those constraints creatively and effectively.
In other words, this is about turning the hard parts of keeping customers happy into undeniably valuable and fun work. Today let’s explore how to get started.
And hey. Thanks for being here.
Spreadsheets are still the number one thing I come across when I ask people to show me how they prioritize their customer work. There are more teams running retention work from Google Sheets than Gainsight*.
*At least among the companies I speak with.
Here’s what that looks like in practice, maybe you’ll see yourself in this story:
A founder recently showed me the spreadsheet his team built to track their biggest customers’ health scores. It was beautiful.
Everyone in the company can open this Google Sheet, look up a customer, see which features they use or don’t use, and see a High / Medium / Low risk score.
This same company uses Vitally, a customer success platform.
“Why are you still maintaining this spreadsheet if you’re paying for Vitally?" I asked.
“The team trusts it.”
I shared this story with a friend who helps Saas companies turn their CS practice into a revenue center. “That’s crazy common,” he said.
Signals you can see and trust
Building a spreadsheet isn’t a workaround or a failure of any customer success platform (CSP). It’s the team choosing signals they can see and watching them somewhere they trust.
Having a data point or a signal isn’t enough. It has to be something you know is right and it has to come from a source that you know isn’t going to massage it.
The first thing any team turning their attention to retention needs to put in place is a set of signals the team actually uses. For many that’s a spreadsheet. For a lot that’s a CSP.
But for now, let’s think about how to just get going.
Retention work is not a sprint (yet)
So the first thing to look at when you’re ready to work on keeping customers happier for longer is the signals you have.
This it the Crawl step. There’s not experimentation or real action yet.
People (me) skip this and move to trying new things with customers too quickly. Experiments are great, but with a finite set of companies to experiment on, they can be costly if done wrong. Bad experiments cost customers, which costs money (Constraint #1).
Get your data in order. I’m a fan of quantifiable data, so I default to things like product usage patterns, call recording analysis over lots of calls, etc. Data should be a mix of quantitative and qualitative to get a sense of what’s really happening and what customers say is the reason.
Observe your data. Boring, yup. Can AI do it, kinda. One day AI will be able to tease out all the meaningful patterns in our data, but for now us humans have some weird edge. We spot things and we can pair the quant and the qual together in ways that are just… human. Watch your data. Play with it. Take a walk and think about it. Patterns will surface.
Don’t do dashboards yet. That’s too abstract.
Build the picture before running the play
The team that built the spreadsheet, they had to see what was happening before they started running any retention or expansion plays. Smart. When looking at the spreadsheet, I could see that they know what normal vs bad vs good looks like.
You have to observe your data for a bit to get to that point. But it doesn’t have to take forever and most teams — your teams too if you have product analytics running and a call recording tool — can get this done in a week if there’s good historical data on hand.
Define the period of time you’re going to watch your data. Start building a picture of what behaviors and patterns lead to good outcomes and bad. This is a baseline to work from. It’s kind of the starting line.
Data sources to start with:
Product analytics — if you’re already tracking it, great. If not, start. It’s free with tools like Posthog and Accoil. You can see how people really use your products, not just what they say they’ll do.
Call recordings — a lot of CRMs have them baked in and there are plenty standalone options like Granola, Fireflies, Spinach. If you’ve been using one for a while, find the customer calls and start analyzing with Claude or whatever LLM is hot right now. If you don’t have call recordings, get a tool and start calling customers.
A cool new tool for reviewing what customers are saying:https://useformat.ai/
Surveys and whatnot — my least favorite data, but if you have NPS or feedback questionnaires or G2 reviews, parse those too.
Customer data — from billing to entitlements to seat count or consumption, learn about your customers in relation to everything above.
Spreadsheeting is pretty easy now with AI, so you don’t have to build a thing of beauty like the team above did. Bring everything together and start to watch it. You’ll see things and go “ooh!”
It won’t take long to start walking
After getting your data in order, you get to be creative. Pick a signal and decide what you’re going to do with it.
And after some simple signal + action experiments, you can start to build systems across your book of business.
Crawling isn’t a downgrade, it’s the foundation
The team who built the spreadsheet aren’t behind the times. They’re setting the foundation for making their CSP and other tools do better work for them.
The more I think about how valuable current customers really are to a business, the more exciting this work gets. Yeah there are contraints, but without them it’s hard to know where to start.
So, set the foundation and let’s build from there. More thoughts soon on how to get up to pace walking and then running.
Peace,
Peter