Where a business loses money after the sale.
Customers were asking for their money back and nobody could say why. I brought the data from eight systems into one place and analysed it. The causes were gaps in onboarding, missed sales calls and reminders not sent on time. I built the fixes around them, and refunds came down by $400k.
What I found
The business could tell you what it sold. It could not tell you which customers had got value, which were about to ask for their money back, or why.
No single view of a customer. Answering "who is this, what did they buy, did they show up, are they at risk?" meant someone opening five tabs and stitching it together by hand.
The data was in eight places. Payments, the product database, scheduling, call recordings, the learning platform, email, Slack and Sheets. None of them talked to each other.
Refund prevention was manual and late. A large share of paying customers never logged in at all, which is the loudest refund signal there is, and nobody was catching it systematically.
The trackers went stale. The spreadsheets that ran daily work went out of date as soon as someone stopped updating them, and were trusted anyway.
Why customers were leaving
Once the data was in one place and analysed, three causes stood out.
Gaps in onboarding. Customers paid and then didn't get going.
Missed sales calls. Calls that should have happened, didn't.
Reminders not sent on time. The nudges that keep a customer on track went out late, or not at all.
What I built
One place that is both the source of truth and the daily worklist, built around the customer rather than around the tools.
A live value ladder. Every paying customer sits in exactly one state: never logged in, logged in but no value yet, reached value, or refunded or left, each with a refund-risk score.
An activation funnel that names the leak. Every milestone from payment to outcome, shown as a share of paying customers, so the biggest drop-off is obvious at a glance.
A post-mortem on every refund. When a customer refunds, the system pulls together payments, product usage, calls booked and actually held, and email engagement, and gives a verdict on why, with links to the recordings.
Team worklists. Leadership scorecard, onboarding, delivery, refund desk and call review, each with its own live list of who needs attention and why.
Push instead of pull. Daily digests go to the right Slack channel, so booking misses reach the person booking calls and onboarding lag reaches the onboarding lead.
What it changed
Refunds came down by $400k. Customers who never logged in, went quiet or crossed a risk threshold now show up in a save queue automatically. That's money that stayed in the business.
The day runs off a live worklist. Each team opens one view and sees who needs attention and why, instead of rebuilding it from five systems every morning.
"Why did this customer leave?" has an answer. Every refund comes with its causes, so the fixes go where the money is.
The win wasn't a dashboard. It was bringing eight disconnected systems into one place so the real causes of refunds were visible, then fixing them: onboarding, sales calls and reminders. Refunds came down by $400k.
If revenue is growing and margin isn't, the leak is usually after the sale.
If something in your numbers doesn't add up, I'm happy to take a look.