Who hurts
Shopify merchants with 50+ SKUs and a flat average order value.
The problem
Bundles are assembled by intuition — usually the products the founder likes — and priced by rounding down. Most convert badly and quietly cannibalise full-price sales.
What you build
Mine co-purchase and co-view data for genuine affinities, model the margin at several discount levels, and recommend bundles with a projected AOV lift and the discount that maximises profit rather than volume.
Why now
Basket analysis is a solved technique that never reached small merchants because it needed a data person. It doesn't anymore.
Validate it this week
Run the analysis free for five merchants. Ask them to launch one recommended bundle and report the result in thirty days.
Why you'd keep winning
Category priors from many merchants make recommendations good even for stores with thin data — a real cold-start advantage.
The honest risk
One-shot value. After the good bundles are found, the subscription is hard to justify — build in ongoing seasonal re-analysis.
The prompt is written to make an AI argue with you before it writes code — that first round of pushback is worth more than the scaffold.