Next-Best Offer Engine for Last-Minute Bookers

Hotels and travel operators routinely see high-intent visitors in the final 48-72 hours before arrival but lack the real-time personalization to convert them without wide discounts. Manual rules or one-size-offers either leave revenue on the table or erode ADR and brand value.

Build a real-time decisioning layer that scores each visitor and serves a calibrated offer that balances conversion probability and margin impact. Combine booking-system signals and external context with human-approved offer catalogs and a governance layer for pricing and brand rules.

• Train a propensity-to-book model (XGBoost/LightGBM or small neural network) using first-party data: search/room views, loyalty tier, past stays, lead time, device, cookies, and CRM tags.
• Layer a price-elasticity and margin simulator to predict net revenue impact of each offer, constraining recommendations to minimum margin thresholds.
• Deploy a real-time scorer/decision engine (feature store + REST API) integrated with the booking engine, mobile app, and call-center desktop to deliver personalized coupon, bundle, or upsell suggestions.
• Operate with human-in-the-loop controls: offer catalog approval, A/B experimentation framework, monitoring dashboard, and audit logs for pricing compliance.

Operators typically see conversion lifts of 5-15% on late-window traffic and a 3-8% improvement in net revenue per booking versus flat discounts, while reducing the need for broad promotional campaigns. Over a season, that translates to higher occupied room nights with preserved ADR and clearer measurement of incremental revenue attributable to personalization.