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Blog · Alternatives and comparisons · Hospitality

How to choose analytics software for hospitality: questions, data and traps

How hotel groups should choose analytics software: start from the questions, check the data you hold, ask vendors ten questions, avoid the traps.

By CoviragePublished 24 September 20264 min read
The short answerStart from the questions hotel groups ask every month, not from features. List the exports you already hold, ask every vendor what it needs before the first answer and whether its AI calculates figures, and check that every total reconciles. Then compare the first-year cost, all in.

Most buying decisions for analytics start from a feature list. For hotel groups the better start is the questions that come back every month, the files already on hand, and the traps that make a tool look right in a demonstration and wrong in the first board meeting.

Start from the questions

The question The measure behind it
Which corporate accounts are behind their commitment? Corporate production against commitment
Where is pace behind the same date last year? Pace against same date last year
Which accounts use one property where they could use five? Property penetration per account
How much group business washes? Group conversion and wash
What does each channel cost us per booking? Channel cost per booking
Are we seeing our key accounts at cadence? Account coverage at cadence

Any tool you consider should answer these from your data, not from a sample. Ask to see it.

The data you already hold

  • Reservations data with booking dates
  • Reservations by rate code
  • Rate agreements
  • Account travel pattern
  • Sales and catering system
  • CRM
  • Commission statements
  • Demand history

If a vendor needs a warehouse built before it can read these, count that in the cost and the time.

Ten questions to ask any vendor

  1. What does it need in place before the first answer? A warehouse, a data model, a modelling language, a partner? Ask for the list and the typical weeks.
  2. Who does the setup, and who maintains it? Your team, the vendor, or a partner, and what that costs after year one.
  3. Does the AI calculate figures, or choose from computed ones? A language model that writes queries or code can produce a plausible wrong number. Ask what it is allowed to do.
  4. Does every total reconcile to a control figure? Ask to see a bridge that does not sum and what the product does about it.
  5. Can every figure be opened to its rows? An answer nobody can check becomes a debate in the meeting.
  6. What does it cost in the first year, all in? Licences, consumption, implementation, modelling and training, not only the seat price.
  7. How does data arrive, and who holds credentials? A file your systems already export, a scheduled drop, or a live connection with the vendor holding keys.
  8. What happens to the data, and where is it stored? Residency, retention, deletion, and whether names can be replaced with identifiers.
  9. Can we see it on our own data before we sign? A demonstration on a sample dataset tells you little about your own.
  10. What does the tool do when it cannot answer? It should say so. A confident guess does more harm than no answer.

Checks specific to hospitality

Ask whether the tool enforces these, and what it does when they fail:

  • Segments: Segment room nights sum to the property total; property totals to the group
  • Groups: Rooms blocked = picked up + washed + released
  • Accounts: Every negotiated rate code maps to one account
  • Space: Available hours = sold + unsold + out of service

The traps

Production against commitment. Rates are negotiated annually and the promised volume is seldom checked during the year.

Property penetration. Each property reports its own accounts. Nobody lists where an account stays in the group and where it does not.

Pace by segment. Total pace looks fine while one segment falls behind.

Measures to leave out

Occupancy alone. Without rate and segment it says little about sales.

Sales calls made. Coverage at cadence, by production.

Revenue against last month. Seasonal; use the same period last year and pace.

A scorecard

Criterion Weight Tool A Tool B Covirage
Answers our six questions on our own data High
Time to the first answer High
Needs a warehouse or data team Medium
AI calculates figures, or only explains computed ones High
Every total reconciles; figures open to rows High
First-year cost, all in Medium

Where Covirage fits

Covirage reads the exports above, answers the questions with figures our tools compute and check, and is set up for you within a week. See analytics software for hospitality compared, AI analytics for hospitality and Covirage for Hospitality.

For the measures in full, with formulas and exports, read Sales KPIs for hotel groups.

Questions people ask

What should hotel groups look for in analytics software?

The answer to their own questions, from the data they already hold, with every figure reconciled. Features matter less than what the tool needs before the first answer and who maintains it.

Is a BI suite enough for hotel groups?

It can be, with a warehouse and someone to build and maintain the model. Without them, the dashboard shows what changed and the explanation is still an analyst's job.

What data do hotel groups already hold?

Usually: reservations data with booking dates, reservations by rate code, rate agreements, account travel pattern, sales and catering system, crm. Most analytics questions in this industry can be answered from those exports.

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