Why first-time buyersnever come back
A purchase analysis tool that finds what stops SuperYou customers reordering, and what wins the second order.
What the data says
Five things decide the second order
Buy 1 Get 1 buyers almost never return
Start them on the variety pack
First taste decides it
Every day of delivery past three costs repeat orders
One tool, four questions
Built for the retention team
Each panel is a tab in the tool. Open it to filter, compare and read the detail behind every chart.
Who comes back?
Repeat rate by first product, offer, price, channel, delivery time, rating, flavour, city tier and age.
Who's about to leave?
A machine-learning model scores every recent first-time buyer on their chance of not ordering again.
Why do they leave?
Reviews from one-time buyers, tagged by their main reason and sized.
What brings them back?
A randomised day-21 test of four nudges shows each one's real effect on the repeat rate.
Machine learning
The model sees it coming
Trained on customers' first orders and tested on it never saw. It ranks who is likely to leave, so outreach goes to the right people first.
One nudge doesn't fit all
Use of AI
Where AI does the work
Churn prediction
Logistic regression and a random forest are trained on first-order data and compared on held-out customers. The better model scores every recent buyer, and permutation importance shows what drives the score.
Built with Claude
Claude (through Claude Code) wrote the data simulation, the model pipeline, the dashboard and this site from the project brief.
Live Claude features
Review theme discovery, a win-back plan writer, plain-English questions on the data and personal win-back messages were designed, but were not implemented due to API issues.
See every number for yourself
Six tabs: overview, drivers, churn model, reasons, win-back plan and method. Every chart is computed from the same 5,000 customers.
Open the tool