Twenty minutes in a dashboard…
I speak with two or three founders every week. Subscription brands come up a lot. And there’s a moment I see time and again.
They log in with one question in their head. How many of last month’s paused subscribers actually came back? Is the 30-day plan churning faster than the 60-day? Did that September price change hurt retention?
Twenty minutes later they’re still clicking through tabs. Screenshot taken. Question still unanswered. So the decision gets made on gut feel… and the leak carries on.
Sound familiar?
So what have Juo done?
Juo is the Shopify subscription platform I work with, and the one I recommend. Last week they launched their new Analytics API, and the thinking behind it is simple. Get merchants the specific number they’re after, right inside whatever they already use. A spreadsheet, a script, a BI tool, or an AI assistant like Claude.
Here’s what’s in the release:
- 34 metrics across 6 time grains, all filterable and groupable
- 16 brand new metrics covering the customer lifecycle (started, churned, returned, paused, resumed), plus live recurring revenue and revenue per customer by period
- MCP access for everyone, so you can ask Claude (or your AI assistant of choice) straight from a chat window, alongside the standard REST endpoints
- A self-documenting catalogue, with every metric definition and filter available to look up
That last one’s my favourite. I’ve lost count of the meetings where a founder and their agency spend half an hour debating churn, only to realise they’re each measuring something different.
Where I’d start
Here’s where I’d begin with any subscription brand I’m working with…
1. What happens to your pauses? Pull paused, resumed and churned for the last two quarters. If most of your pauses end up as cancellations, your pause flow is doing the cancelling for you, just slower. I’d look at that first, before any acquisition work.
2. Which plan keeps people longest? Group churn by plan or delivery frequency. When one cadence churns faster, it’s very often timing. The product runs out before the next box lands, or it’s piling up in the cupboard. Try tweaking the default frequency before you reach for a discount.
3. Who comes back? The returned metric shows you customers who cancelled and later restarted. Look at what they have in common. Then build a win-back flow around exactly those folks in Klaviyo (the email platform I work with, and the one I recommend). Much better use of your list than blasting every lapsed subscriber with 20% off.
4. Is revenue per customer going up? Check it month by month. Live recurring revenue climbing while revenue per customer drops off? You’re paying for that growth. Worth knowing before you up the Meta budget again.
You won’t need an analyst for any of this. Type the question in plain English, check the definition in the catalogue, and act on it that week.
Why I’m excited about this
Subscription brands spend a fortune acquiring customers. Then, all too often, retention gets whatever time is left over at the end of the week.
Releases like this make it easier to keep asking the questions. One pops into your head on a Tuesday morning, you’ve got the answer by lunchtime and you’ve made a call by the afternoon. No waiting for the monthly report.
And that’s optimisation for me. Lots of small, regular decisions, made on real customer data, that compound over time.
More on this lever: The Retention Lever: How To Optimise Repeat Purchase Using Your Own Data.
Ian
