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AI USE CASE

Cross-sell & upsell recommendations

Surface the right next-purchase suggestion for every customer, in real time.

Typical budget
€20K–€70K
Time to value
10 weeks
Effort
6–14 weeks
Monthly ongoing
€600–€3K
Minimum data maturity
intermediate
Technical prerequisite
data engineer
Industries
Retail & E-commerce, SaaS, Finance, Hospitality
AI type
recommendation

What it is

A recommendation model trained on transaction history, browsing behaviour and product affinity feeds personalised next-best-product suggestions to your e-commerce site, app and CRM. Boosts average order value 8–15% and gives sales reps concrete talking points for account reviews.

Data you need

12+ months of transactions and product catalogue with attributes.

Required systems

  • crm
  • ecommerce platform
  • data warehouse

Why it works

  • Hybrid model combining collaborative + content-based
  • Live inventory check before showing recommendations

How this goes wrong

  • Cold-start problem for new customers ignored
  • Model recommends out-of-stock items

When NOT to do this

Don't deploy on a catalogue smaller than 200 SKUs — manual merchandising wins.

Vendors to consider

This use case is part of a larger Data & AI catalog built from 50+ enterprise transformation programs. Take the free diagnostic to see how it ranks against your specific context.