@12andDone You're exactly right. That's the core of it. The real dashboard shows exactly that: specific signals ("usage dropped 40%", "login gap", "payment failures"), not a bare risk number. The demo video just didn't show that part.
Want to see it?
I’m building ChurnSense: it tries to flag B2B SaaS customers drifting toward a cancel weeks early.
Still early, zero paying customers yet (demo data in the video).
What would make this actually useful to you?
If you run a B2B SaaS with 50–500 customers and churn keeps you up at night:
I'll set up ChurnSense for you free for 3 months.
You get: daily risk scores, Slack alerts, AI save emails.
I get: feedback and (if it works) a testimonial.
DM me or reply here.
@Joshua_WD Shipped it. New accounts now get dampened based on actual first-activity, not just when we ingested the row, so a fresh signup and a year of imported history don't get treated the same way anymore.
Appreciate you pushing on this, better product for it. Wanna try this out?
Building ChurnSense in public.
Generic churn models miss context: daily logins can mean “healthy” for a dev tool, but not for an HR platform.
So I built per-tenant models that learn each customer's own baseline.
Shipped it. Here’s what it looks like:
@Joshua_WD Honest answer: nothing protects them yet. There's tenure logic at training time, but it doesn't carry through to the live score you'd actually see on a new account's dashboard. Real gap, not solved, tightening it up now.
@Joshua_WD Good question. Two clocks:
Tenant: heuristic cold-start until ~20 confirmed churns, then real-outcome training.
Account: needs enough activity for a reliable baseline. Still refining the exact minimum.
Happy to dig into specifics.
most "health scores" are weights someone invented in a spreadsheet and never checked. churnsense trains a model on your own churn outcomes and names the 5 factors behind each at-risk account, so the slack alert is actually actionable: https://t.co/PsXhuguYBA