Hotel Revenue Dashboard — RevPAR, ADR and Occupancy From Your PMS Exports
Your PMS records every night sold; turning that into revenue strategy is the missing step. DataHub Pro builds a hotel revenue dashboard from the exports you already have — RevPAR, ADR, occupancy by segment — with Holt-Winters seasonal forecasting that sees the shoulder-season dip coming.
Updated 10 June 2026
What is a hotel revenue dashboard?
A hotel revenue dashboard tracks the trinity every operator watches — occupancy, ADR (average daily rate) and RevPAR (revenue per available room) — and breaks them down by the dimensions that explain them: room type, booking channel, market segment, day of week and season. Done properly, it answers the questions that decide rate strategy: is RevPAR growth coming from rate or from volume? Which segments are softening? What does the booking pace say about the months ahead?
Every property management system — Opera, Mews, Cloudbeds, Guestline, RoomRaccoon and the rest — records the raw material and exports it as CSV or Excel. But PMS reporting modules are built for operations, not analysis: they will print yesterday's figures, while the questions that matter are comparative and forward-looking. Comparing this October against the last three, decomposing a RevPAR move into rate versus occupancy, or projecting the spring shoulder season — that work usually falls to a spreadsheet, maintained late at night by a GM or a revenue manager the property may not have.
Seasonality is the heart of the problem. Hospitality demand has strong, layered cycles — weekly (corporate midweek, leisure weekends), annual (high season, shoulder, festive), and event-driven — and pricing or staffing decisions made without quantifying those cycles are guesses with consequences. A forecast that says "March looks like 71% occupancy, plus or minus 6 points" changes the rate conversation; a gut feeling about March does not.
DataHub Pro does that work from the exports you already produce. Upload nightly occupancy and revenue data and the platform computes RevPAR, ADR and occupancy by room type and segment, decomposes revenue movements, flags anomalies, and runs Holt-Winters forecasting — a method built precisely for data with trend and seasonality — with 80/95% confidence bands. Auto Report then generates the weekly revenue pack or the monthly owner's report as an editable document, on schedule, with every figure traceable to the PMS export.
The reporting problems hoteliers know by heart
Independent operators, small groups and serviced-apartment businesses describe the same gaps:
- The PMS reports yesterday; strategy needs next quarter. Operational reports tell you what happened. Rate and staffing decisions need pace, trend and forecast — which the PMS export contains but does not analyse.
- RevPAR moves without explanation. RevPAR up 6% sounds healthy — unless it is ADR up 11% masking occupancy down 4, with a volume problem compounding underneath. Without decomposition, good and bad news look identical.
- Seasonality is managed from memory. Rates and rotas get set on recollection of last year. Memory smooths the curve; data does not — and the difference is mispriced nights at both ends of the season.
- Owner reporting is a monthly evening lost. Owners and investors want occupancy, ADR, RevPAR and commentary. Assembling it from PMS exports by hand costs an evening per property per month.
- Segment shifts are noticed late. The corporate midweek base eroding 2% a month is invisible in totals until the quarter is missed. Segment-level trend analysis is exactly what nobody has time to run.
- Multi-property comparison is spreadsheet surgery. Each property's PMS export has its own quirks; a like-for-like group view means hours of manual normalisation before a single insight emerges.
DataHub Pro features mapped to hotel revenue work
From the platform's 50 analysis tools, these fit revenue management on a real property:
RevPAR / ADR / occupancy tracking
The core metrics computed daily from your PMS export, by room type, channel and segment, with period-over-period comparison built in — this year versus last, like for like.
Holt-Winters occupancy forecasting
Seasonal forecasting designed for exactly this data shape: weekly and annual cycles, trend, and honest 80/95% confidence bands. Try the method free on our forecasting calculator.
Revenue decomposition & variance
Variance analysis splits RevPAR movement into rate and occupancy effects, by segment — so you know whether to defend rate, chase volume, or fix a channel mix problem.
Anomaly detection by segment
Statistical flags when a segment, channel or day-of-week pattern breaks trend — the eroding corporate midweek base surfaces in weeks, not at the quarterly review.
Ask Your Data — auditable AI
"What was weekend ADR for deluxe rooms last quarter versus a year ago?" Plain-English questions, answers with a visible audit trail — ready for the owner's call.
Auto Report revenue packs
The weekly revenue meeting pack and the monthly owner's report as editable Word or PowerPoint documents, generated on schedule with AI commentary on what moved and why.
Worked example: from occupancy.csv to three revenue decisions
You upload occupancy.csv — two years of nightly data: rooms available and sold, revenue, room type, channel and segment, exported from your PMS. Three findings return in minutes:
RevPAR +6% — but it is fragile
Decomposition shows the headline gain is ADR +11% against occupancy −4%, concentrated in leisure weekends. Rate is doing all the work while the volume base thins — a different strategy conversation than "+6%" suggests.
Corporate midweek anomaly
Anomaly detection flags Tuesday–Wednesday corporate-segment room nights running 18% below the seasonal norm for five consecutive weeks — traceable to one corporate account's changed travel policy, and worth a phone call this week.
Spring shoulder forecast: 71% ±6
Holt-Winters projects March–April occupancy at 71% with confidence bands, against 78% last year — quantifying the gap early enough for a targeted campaign rather than a panic discount.
Auto Report turns the same analysis into the weekly revenue pack and the owner's monthly report, on schedule. Every figure traces back to the PMS export — useful when the owner asks where a number came from.
How it works — three steps, no implementation project
There is no onboarding call, no integration scoping and nothing for IT to install. The workflow is the same whether you are testing on one file or running scheduled reporting across a team:
- 1. Bring your data. Upload an Excel or CSV export from the systems you already use, or connect Google Sheets, SharePoint or Shopify for sources that should stay live. DataHub Pro auto-detects your columns — no template to conform to.
- 2. Run the analysis. The KPI dashboard builds itself on upload. From there, pick from 50 analysis tools — Pareto, cohort, RFM, anomaly detection, variance, what-if, Holt-Winters forecasting — or ask questions in plain English with Ask Your Data, where every answer shows the operations behind it.
- 3. Ship the report. Auto Report turns the analysis into an editable Word or PowerPoint document with charts and AI-written commentary. Schedule it, and the recurring version arrives without you — same method, fresh data, every time.
Plans that scale from a single file to a whole team
- Free — $0, forever. One user, 3 uploads a month, 8 core analysis tools and watermarked PDF export. No AI features, no credit card — but a genuine way to test the workflow on your real data before paying anything.
- Pro — $14.99/mo, or $9.99/mo billed annually. All 50 analysis tools, Ask Your Data auditable AI, Auto Report DOCX/PPTX export, scheduled reports and team roles. This is the plan most teams on this page run.
- Enterprise — custom pricing. Everything in Pro, plus white-label reporting, SSO, unlimited usage, multi-client workspaces and organisation-level audit-log governance.
Every plan runs on UK/EU infrastructure under GDPR, and uploaded data is never used to train AI models — on any tier.
What DataHub Pro is not
It is not a PMS, a channel manager or an automated revenue management system — it does not push rates to OTAs or change prices on its own. It is the analysis layer between your PMS data and your decisions. Many independent properties use it precisely because a full RMS is more system (and more money) than the property needs.
Frequently asked questions
What data do I need from my PMS?
A nightly export with rooms available, rooms sold and revenue — ideally broken down by room type, channel and segment. Opera, Mews, Cloudbeds, Guestline and every mainstream PMS produce this as CSV or Excel. Two years of history makes seasonal forecasting properly accurate; less still works.
How does the occupancy forecasting work?
DataHub Pro uses Holt-Winters exponential smoothing, a statistical method designed for data with trend and seasonality — which hotel demand has in layers. Forecasts come with 80% and 95% confidence bands, so you see the uncertainty as well as the central estimate.
Can it tell me whether RevPAR growth is rate or volume?
Yes. Variance decomposition splits RevPAR movement into ADR and occupancy effects, by segment and room type — the difference between celebrating a headline and understanding it.
Does it work for a group of properties?
Yes. Upload per-property exports and compare like for like across the group, with anomaly detection flagging the property whose pattern breaks trend. The group view that currently takes spreadsheet surgery becomes automatic.
Can it analyse F&B and ancillary revenue too?
Yes — any revenue data in CSV or Excel can sit alongside rooms data: F&B covers, spa bookings, parking. Total revenue per available room (TRevPAR) analysis works the same way as the rooms metrics.
Can the weekly revenue pack be automated?
Yes. Scheduled reports re-run the analysis on new exports and Auto Report generates an editable Word or PowerPoint pack — occupancy, ADR, RevPAR, pace versus last year and AI commentary — before the revenue meeting.
Is it a revenue management system (RMS)?
No. An RMS automates pricing decisions; DataHub Pro informs them. It gives an independent property most of the analytical value of an RMS — decomposition, seasonality, forecasting — without the integration project or the enterprise price.
Is guest data handled under GDPR?
Yes. Data is hosted in UK/EU infrastructure under GDPR and never used for AI training, with a DPA available. Revenue analysis works on aggregated nightly data, so most properties never upload guest-identifiable records at all.
What does it cost for an independent hotel?
Free tier: 1 user, 3 uploads a month, 8 core tools — enough to trial on last season's data. Pro is $14.99/mo ($9.99/mo annual) for all 50 tools, forecasting, AI and scheduled packs. Enterprise covers groups needing SSO, team roles and white-label owner reporting.
See next season before it arrives.
Upload two years of PMS data. Get RevPAR decomposition, segment anomalies and a seasonal forecast with confidence bands — in minutes.
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