For Hotel Revenue Managers ·
What you'll accomplish
You'll use Claude Pro's large context window (up to 200,000 tokens) to upload full STR reports, budget documents, and competitive analysis files — and get back detailed narrative analysis you can send directly to owners, asset managers, or GMs. Claude Pro handles the documents that are too long for free tools to process accurately, making it the right choice for monthly owner reports, budget season narratives, and annual comp set reviews.
What you'll need
Claude Projects maintain persistent context across multiple conversations — similar to ChatGPT's custom instructions, but with more powerful file-based knowledge storage.
Property: [Hotel Name], [room count] rooms, [brand/segment], [city/market]
Comp set: [Comp 1 – brand, room count], [Comp 2], [Comp 3], [Comp 4], [Comp 5]
Target metrics: RevPAR MPI [X], ADR Index [X], Occupancy Index [X]
Reporting audiences:
- GM: operational focus, wants action items and forward outlook
- Ownership/Asset Manager: financial focus, wants variance explanation vs. budget and year-over-year
- Sales team: needs displacement context and booking pace
Rate strategy: [2-3 sentences on your pricing philosophy]
Current market challenges: [1-2 sentences on what's affecting your market right now]
Budget year basis: [year and key assumptions]
Claude Pro can handle files directly:
File size limits: Claude Pro handles files up to 10MB and total conversation context up to 200K tokens — enough for a full STR annual benchmarking report plus your budget document simultaneously.
Build a reusable prompt sequence for monthly owner reports:
Part 1 — Data upload prompt:
I'm preparing the [Month Year] owner performance report for [Hotel Name]. Here is our performance data:
[Paste or upload: RevPAR, ADR, Occupancy vs. budget and prior year; STR comp set index scores (MPI, ARI, RGI); any major factors — events, renovations, new supply, rate actions]
And here is the STR monthly report: [upload file or paste key tables]
Please analyze our performance: where did we outperform, where did we underperform, and what are the top 2-3 explanatory factors for each variance?
Part 2 — Narrative draft prompt:
Based on that analysis, write the narrative section of our owner monthly report. Structure:
1. Performance Summary (2-3 sentences: headline number, comp set context)
2. Variance Explanation (what drove the gaps vs. budget and prior year)
3. Market Context (what was happening in the competitive environment)
4. Forward Outlook (30-60-90 day view and rate strategy)
Tone: professional, data-driven, forward-looking. Audience: asset manager who reads 10 hotel reports monthly — be direct and don't bury the lead. Length: 350-450 words.
STR monthly analysis:
Here is our STR benchmarking report for [month]. [Upload file.] Summarize our competitive position: overall RevPAR index vs. prior year and budget, which index (MPI, ARI, or RGI) is our biggest gap, and what does that gap tell us about where we're losing or winning against the comp set?
Budget variance narrative:
Our RevPAR came in at $[X] vs. budget of $[X] — a [+/-X]% variance. ADR variance: [+/-X]%. Occupancy variance: [+/-X] pts. Write a 2-paragraph budget variance explanation for an asset manager. Be specific about causes; don't hedge with vague language like "market conditions."
Annual budget narrative (budget season):
I'm writing the narrative for our [year] annual budget. Key assumptions: [list 4-5]. Three scenarios: Conservative ($[X] RevPAR), Base ($[X]), Optimistic ($[X]). Write the narrative section that explains our assumptions and scenario logic to an ownership group. ~500 words. Include one paragraph on competitive landscape and one on new supply/demand drivers we're watching.
Comp set displacement analysis writeup:
We received a group inquiry: [X] rooms for [X] nights at $[X] group rate. Our transient forecast for those dates: [X]% occupancy at $[X] ADR. F&B contribution from this group: $[X] per attendee. Write a 1-page displacement analysis memo explaining whether to accept or decline the group, and the financial logic behind the recommendation.
Post-event performance debrief:
[Event name] just finished. Here's what we forecasted vs. what happened: [paste comparison]. Write a structured post-event debrief memo: what we expected, what actually occurred, top 3 reasons for the variance, and what we'd do differently for the same event next year. ~300 words.