Marketing AI can now pick which customers to target 3.9x better than guessing

Researchers tested four machine-learning methods for predicting which individual customers will buy if you advertise to them, using 14 million real customer records from an e-commerce company. The best method ranked customers by purchase likelihood so accurately that targeting the top 20% of prospects captured 78% of all sales gains — meaning you could cut your ad spend dramatically and still move the same volume.

This is the first systematic test of these methods at real industrial scale with real customer data. Until now, companies were mostly guessing which targeting method worked best, or relying on small academic benchmarks that don't transfer to actual customer bases. The test shows that a specific machine-learning approach (S-Learner) consistently outperforms others, which means marketing teams can now make a more confident choice about which software to buy. The practical effect is immediate: if you're spending money on ads, you now know how to spend less of it while hitting the same target.