One reply is an anecdote. Forty is a decision.
Every conversation is classified automatically and read against everything else you've heard — so patterns surface on their own instead of waiting for you to notice them.
The real interface, with sample data from a fictional company. Click through it.
Tagged the moment it arrives
Every conversation is classified by churn reason without you reading it first — pricing, missing features, competitors, onboarding friction, low usage, and more.
Read across the whole history
The analysis holds every interview in mind at once and notices that six people said the same thing in six different ways. That's the part humans are genuinely bad at.
Weighted by what it costs you
A pattern in three $19 accounts and a pattern in three $400 accounts are not the same finding. Insights carry the MRR behind them so you can rank against your actual roadmap.
Tags are a starting point, not a verdict
Classification exists so you can find things — every interview, filtered to a reason, in one click. It is not there to replace reading what people said.
More detail
Every tag can be changed, and the original text is always right beside it. You are never reading a summary of a summary, and you can always check the machine's reasoning against the actual words.
- Missing features32%
- Too expensive24%
- Switched to competitor18%
One reply is an anecdote. Joined to everything else you have heard, it becomes a position on a list.
What to fix first
The output isn't a chart for you to interpret. It's a specific claim — this pattern, this many customers, this much revenue — with the customer quotes it's drawn from and a confidence level attached.
More detail
You can also cut the same data by segment: by plan, by tenure, by price point. Starter customers and enterprise customers usually leave for opposite reasons, and averaging them together hides both.
The quarter you stopped guessing
You have eleven things on the roadmap and room for two. Insights tells you that nine of your last twenty-four cancellations mention the same missing capability, worth roughly $1,100 MRR a quarter at the current rate — and shows you the six quotes it's reading. Now the prioritisation argument has evidence in it.
Questions about this
What if the AI gets a churn reason wrong?
You can see and change every tag. Tags are a starting point for finding patterns, not a verdict — and the original text of every conversation is always right there next to the tag, so you're never reading a summary of a summary.
AI output in WhyLeft is treated as a suggestion throughout. Insights and recommendations come with the quotes they're derived from so you can check the reasoning yourself.
Which AI models does WhyLeft use?
Anthropic's Claude. Fast, cheap models handle classification and tagging; stronger models write the follow-up questions and the cross-interview analysis. Model choice is configured per workflow rather than hardcoded, so it improves as the models do.
Does my customers' personal data go to the AI?
No. Automated AI processing — tagging, follow-up generation, insights, recommendations — receives the reply text and non-identifying metadata only: plan, price, dates, churn tags. Never a name, never an email address.
The one exception is deliberate and founder-controlled: when you personally ask Wylo Copilot a question about a specific customer, it can retrieve that customer's identity — inside your own authenticated workspace only, through the same authorization boundary as your dashboard.
Related
Your next cancellation is coming.
It can be another number on a chart, or the reason you build the right thing next quarter.
No credit card. Cancel in one click — we'd rather you tell us why.