Retention & Churn Analysis
The cancellation survey says “too expensive.” It nearly always says too expensive. What it does not say is that the account stopped using the one feature that made them stick around eight weeks earlier, that their champion left in April, or that they filed a ticket in May that never got a satisfying answer. Price is what people write in the box when the real reason is diffuse and they are already halfway out the door. Acting on that box means fiddling with pricing to fix a problem that was never about pricing.
The real story is in the trail. Skynet reads usage data, support history, and account records together, looks at what churned accounts had in common well before they cancelled, and finds the signals that actually predict leaving.
How it works
Look at the weeks before, not the day of
The agent reconstructs the run-up to each cancellation — what usage did, what tickets appeared, what stopped happening. Churn is a slow process that ends in a click, and the useful part is the process.
Find what the leavers shared
It compares churned accounts against retained ones to find what actually separates them, rather than what the survey said. Sometimes it is a feature never adopted. Sometimes it is one unresolved ticket.
Watch for the pattern live
Once the signals are known, the agent monitors current accounts for the same trail and flags them while there is still time to do something — not after the renewal has quietly lapsed.
Turn it into product work
The findings feed back into the roadmap. If accounts that never reach a certain point churn at three times the rate, that is not a customer-success problem to be handled — it is a product problem with a number attached.
Build it from a prompt
One instruction covers both the diagnosis and the early warning.
What you end up with is retention treated as a product question rather than a save-offer question. The pattern is named, the at-risk accounts surface early, and the roadmap gets to fix the cause instead of the symptom.