of 4— Set Custom Instructions for Competitive Analysis

What you'll accomplish

You'll build a repeatable workflow that takes raw rate shopping data from Lighthouse (or any rate tool) and turns it into a structured weekly competitive intelligence briefing — with pattern analysis, positioning recommendations, and a written rationale you can send straight to your GM. Instead of staring at columns of competitor rates and forming your own interpretation in isolation, you'll have a consistent analytical framework that takes 10 minutes a week to run.

What you'll need

ChatGPT Plus subscription ({{tool:ChatGPT.plan}} — {{tool:ChatGPT.price}}/month)
Access to Lighthouse, OTA Insight, or any rate shopping tool
Ability to export or manually record comp set rates (7-30 day forward window)
10 minutes on a set day each week (Monday morning works well)

Turn Rate Shopping Data into a Weekly Competitive Intelligence Briefing

Step 1: Set Custom Instructions for Competitive Analysis

Add competitive context to your ChatGPT Plus custom instructions (see the Revenue Reporting guide for how to access Custom Instructions). Include:

Copy and paste this

Competitive context for [Hotel Name]:
- Comp set: [Comp 1 — brand, room count, segment], [Comp 2], [Comp 3], [Comp 4], [Comp 5]
- We typically position [at parity / at a premium of $X-$Y / as value leader] vs. the comp set
- Our key differentiators: [e.g., location, renovation, review score, F&B, loyalty program]
- Rate floors: $[X] weekday, $[X] weekend, $[X] peak/event
- We use [Lighthouse / OTA Insight / manual checks] for rate shopping
- When evaluating competitive moves, I want: pattern identification first, then positioning recommendation, then rationale I can share with the GM

Tools:ChatGPT Plus