Hotel F&B AI Marketing Platform · Shane · Vanderbilt Owen MBA · Spring 2026
| Node | Role | Function |
|---|---|---|
| Marketing Manager | Entry point | Feels the pain, speaks ROI, champions the product |
| F&B Manager | Co-champion | Revenue pressure owner, validates the problem |
| General Manager | Economic buyer | Approves budget, doesn't feel pain directly |
| Data Layer | Status | Notes |
|---|---|---|
| POS Data | MVP ✓ | Spending patterns, menu performance, daypart gaps |
| Booking Data | MVP ✓ | Guest frequency, in-house vs walk-in, check size |
| Local Market Data | MVP ✓ | Competitive intel, local events, foot traffic |
| Loyalty / OTA Data | Upgrade | Locked by third parties — adds precision, not required for MVP |
| Output | Description | |
|---|---|---|
| Revenue Gap Detection | AI identifies underperforming dayparts and cover shortfalls | |
| Campaign Recommendation | Specific tactic, channel, offer, and timing — generated automatically | |
| Deployable Asset | Actual campaign copy ready for execution by marketing manager | |