Basket and Cross-Sell Analysis | What Sells Together?

You probably have a piece of information sitting unused: which products get bought together. This is the foundation behind everything from shelf placement in a supermarket to “customers who bought this also bought that” recommendations on an e-commerce site — yet most small businesses never actually extract it from their own data.

Basket analysis (market basket analysis) scans your historical order data to find which products get bought together more often than chance would explain. The result is cross-sell and bundle ideas backed by numbers, not just intuition.

What Data Do You Need?

All that’s needed is an order-level product list — which products were in which order. Your e-commerce platform’s order export, your POS system’s receipt records, or a list extracted from your invoices is enough. The more orders you have, the more reliable the findings.

For businesses selling a small number of product types (10-20), this might seem like something you could do by hand, but the real patterns usually show up in unexpected pairs and triples — combinations that are hard for the human eye to spot.

The Real Value Is in the Unexpected Matches

Obvious pairings like “people who buy coffee also buy sugar” are already known — they don’t tell you anything new. The real value of the analysis is finding matches you wouldn’t have guessed, but that the numbers support — for example, seeing that a specific accessory sells together with a specific product category in a way you didn’t expect.

Once these matches are found, they get used in three places: “bought together” suggestions on the product page, a last-minute offer at checkout, and bundle/campaign design. All three raise average basket value without any additional ad spend.

Turning It Into Bundle and Campaign Ideas

A raw list of matches isn’t useful on its own; you need to evaluate and prioritize which match has a high profit margin and which one is good for clearing excess stock. We do this evaluation together.

What you get as output is concrete bundle recommendations: which products together, at what price, on which channel (site, checkout, ads). Implementation is handled by your own team or your e-commerce platform.

How do we start? First, we have a free 20-30 minute initial call. We talk about what you want and what’s realistic. If it looks like a good fit, I send you the scope and price in writing, then we begin. You can reach me through the contact page.

Frequently Asked Questions

I sell services, not products. Is this analysis useful for me?

The same logic applies to service businesses — we can see which services get purchased together or in sequence by the same customer. For example, it’s possible to find which additional service customers of a particular consulting offering tend to move toward shortly after.

How many orders do you need for the analysis?

There’s no exact number, but in practice, reliable patterns get harder to find below a few hundred orders. If your order count is low, we’ll still take a look, but we’ll interpret the findings more cautiously.

Is this different from my e-commerce platform’s “recommended products” feature?

Most off-the-shelf e-commerce plugins work on simple “also viewed” logic and aren’t based on actual purchase data. Basket analysis looks at completed sales, which makes its recommendations more accurate.

Who integrates the results into my site?

The analysis and recommendations come from me; technical integration is handled by the developer or plugin on your e-commerce platform. If you’d like, I can also point you toward which plugin would make this easiest.