Lift basket value, drive repeat purchase, reactivate lapsed.

Retail and ecommerce teams have years of basket and behavior data, most of it under-used. RFM cuts and broad lifecycle stages describe yesterday's customer; they don't surface the segments where today's lift actually lives.

The cohort that buys premium on weekends but never on weekdays. The cart abandoners who convert when shown a specific bundle, not a discount. The shoppers whose 'inactive' label is a seasonal pattern, not churn at all.

Neuralift surfaces the cohorts behind loyalty 02 Loyalty → , AOV growth, offer response 06 Offers → , and acquisition lift 04 Acquisition → , then ships each as activation-ready IDs into CRM, site personalization, and paid. Discovery runs over your transaction history, browse logs, and offer-response data without manual feature engineering. It adapts to whether you operate on a 5-segment broad CRM or a 30-cohort granular plan. Every recommendation comes with a play assignment, a channel mix, and a Lift Potential forecast of the revenue upside each cohort could unlock, so you can model where to focus first. Built to plug into Shopify, Salesforce, Klaviyo, Google, Meta, and TikTok without a six-month integration project.