Flybuy MenuAI analyzes every view, every cart, and every purchase to surface what your menu reports can’t: which items to promote, what to bundle, where guests are dropping off, and why over half your menu may be dead weight.
properties
orders analyzed
guest sessions
menu items
F&B outlets
Over half of menu items at every property analyzed generate low visibility and low revenue, often earning less than a single top performer. These items create decision fatigue and hide your best sellers.
Around one in five items convert at rates well above the property average, up to 12x, but are buried where guests rarely see them. Moving these items to prominent positions costs nothing and generates immediate revenue.
Late night conversion runs 2-5x below peak dayparts across every property. The menu isn't optimized for when guests actually order: it's the same menu at 2 AM as it is at noon.
No POS integration. No engineering lift. The platform runs on ordering data you’re already generating.
Your existing ordering data: item views, cart completions, payment methods, dayparts, outlets — feeds the platform. We analyze the full guest journey, not just what sold.
AI/ML models surface hidden gems, menu bloat, bundle opportunities, momentum items, conversion gaps, fee issues, and payment-based merchandising signals for each property. .
Your team receives a property-specific action plan with exact CMS changes: reorder items, create bundles, fix configurations, adjust pricing. Same week. Zero engineering.
Request a complimentary portfolio analysis. We’ll show you the hidden gems, the dead weight, the momentum items, and the conversion gaps your current reporting is missing.
From flagship resorts doing $1M+ in mobile orders to boutique hotels with a single restaurant, the platform adapts to the scale and surfaces what matters.
At one property, a single appetizer generated $5.86 in revenue per impression (12x the property average) from only 105 views. It was buried deep in the menu. Moving it to the top of the dinner category costs nothing.
Market basket analysis showed that when room charge guests order a breakfast sandwich and coffee, they add fruit 68% of the time. Formalizing this as a $22 bundle captures a combination guests are already choosing.
At a boutique property, 57 out of 95 items had zero purchases despite being browsed hundreds of times. Naming duplicates, non-food items in the food menu, and dead entries were killing the conversion rate. Every fix was free.
Anomaly detection flagged a mimosa item whose weekly revenue jumped from $39 to $120 (a 205% increase). Instead of leaving momentum items to chance, the platform identifies them in real time so you can amplify what's already working.
At every property analyzed, room charge and credit card guests spend within a few dollars of each other. But room charge guests over-index at breakfast and credit card guests over-index at lunch. This changes how you merchandise a menu.
At a high-volume property, 15 items that previously generated $100–$900 per week dropped to zero. Menu renames, accidental disabling, and configuration errors caught by anomaly detection, recoverable the same week.
