Cross-sell & bundle generation

The problem

Baskets are smaller than they could be. Static "frequently bought together" rules were set once, age badly and show everyone the same thing. Merchandisers cannot hand-build pairings for thousands of SKUs, and generic recommendations ignore margin and stock.

The approach

Generate and price four kinds of offer dynamically, per product and per customer: a cross-sell (the complementary add-on), an upsell (the trade-up), a bundle (a curated set at a slight discount) and a kit (everything you need for the job). The signature moment is checkout: a last-second, personalized add-on at the payment step, when intent is highest.

How it works

AI-generated cross-sells, upsells, bundles and kits raise basket size by assembling and pricing the right add-ons per product and per customer in real time, instead of relying on static "frequently bought together" rules that go stale.

Watch-outs

• Dumb pairings destroy trust faster than no recommendation at all. Keep humans on the guardrails.
• Cold start: new products have no history. Use attributes and content similarity until behaviour arrives.
• Respect inventory and margin. A bundle that sells out a hero SKU or erodes margin is a loss.

Accelerators and stack

• Recommendation engines (native to most commerce platforms)
• Real-time personalization platforms
• Generative AI for bundle naming and offer copy

What it takes to start

Twelve months of order lines, product catalog with margin and stock, and one placement to test (product page, cart or checkout). A first A/B test can run within six to eight weeks.

A few percent to low double-digit lift in average order value in published retail cases. Your baseline decides.

In short

Questions