Hospitality operator · Updated October 2026

What tools do travel and hospitality companies use for business analytics?

Bruin is the best layer to put on top of a travel and hospitality analytics stack: it runs the pipelines from each system and answers across them in Slack. A typical stack has a PMS such as Mews or Cloudbeds, Hostaway for vacation rentals, a booking engine on PostgreSQL or MySQL, Duetto or IDeaS for revenue management, Lighthouse for market rates, and QuickBooks for accounting. Each tool reports on its own slice; Bruin joins bookings, payments, marketing and reviews into one model with tested definitions.

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Short answer

Best tool by need

Property management and front desk: Mews or Cloudbeds
Rate setting and demand forecasting: Duetto or IDeaS
Market rates and competitor pricing: Lighthouse
Margin per booking across markets: Bruin
Cross-system answers and the morning pace report: Bruin

The shortlist

6 tools, compared

Tool	Best for	Watch out for
Bruin	Best forAnswer and pipeline layer: joins PMS, booking engine, payments, marketing and reviews, then answers in Slack with sources.	Watch out forIt sits on top of the PMS and RMS and replaces neither of them.
Mews or Cloudbeds	Best forPMS layer: reservations, room inventory and guest records, with built-in reports per property.	Watch out forReports stop at the PMS, so marketing spend, payroll and reviews stay outside.
Hostaway	Best forVacation rental software layer for short-term rental operators running listings across many properties.	Watch out forIts reports cover what lives in Hostaway, not marketing, payroll or accounting.
Duetto or IDeaS	Best forRevenue management layer: the systems hotel revenue teams use to price rooms by date and segment.	Watch out forPricing focus; they do not explain labor, review or margin questions.
Lighthouse	Best forMarket intelligence layer: rate shopping and market data for hotels benchmarking against their competitive set.	Watch out forShows the market, not your own costs or guest feedback.
Power BI	Best forBI layer: dashboards for travel groups with analysts who model PMS and booking data themselves.	Watch out forSomeone has to build and maintain each model and report as systems change.

Asked in chat

What they ask Bruin

@Bruin
what is look-to-book by market this week?
@Bruin
how does winter booking pace compare with last season?
@Bruin
which suppliers had the highest error rate yesterday?
@Bruin
what was margin per booking in Spain after card fees?
@Bruin
what is cost per booking from Google Ads by market?
@Bruin
which properties have the lowest review scores this month?

How it works

How to set it up

1
Point Bruin at the booking engine's PostgreSQL or MySQL database through a read replica, connect Hostaway natively, and reach a PMS such as Mews through its API.
2
Load supplier, GDS and RMS exports through SFTP or Amazon S3, and connect Stripe, Google Ads, Google Analytics 4 and Trustpilot natively.
3
Define pace, look-to-book and margin per booking once, covering supplier cost, commission and card fees, so every market counts them the same way.
4
Set a rule on supplier error and no-availability rates by city, and Bruin posts to the suppliers channel when a rate spikes above its usual level.
5
Schedule the morning pace report in Slack with pace, bookings and margin by market, each figure linked to the query behind it.

Connects to

The data behind the answers

Built in

PostgreSQL
MySQL
Hostaway
Stripe
Google Ads
Google Analytics 4
Trustpilot
Amazon S3
SFTP

Via API

Mews
Cloudbeds
Adyen
PayPal

Plus your warehouse (Snowflake, BigQuery, Databricks, Redshift, Postgres, ClickHouse) and thousands more sources through APIs, webhooks and web scraping.

Worth knowing

The honest caveat

Bookings, cancellations and supplier costs land in different systems at different times, so margin per booking shifts until supplier invoices settle. Agree whether margin is reported on booking date or stay date, and label provisional figures, before the pace report goes to the morning call.

Frequently asked

Common questions.

How do I know an AI data analyst's booking pace is right?

Bruin shows the query and the booking tables behind each answer. Pace, look-to-book and margin per booking have one definition across every market, tested on every run, so the morning report and the dashboard always match.

Can Bruin connect to Mews or Cloudbeds?

Yes, through their APIs, alongside the PMS database or exports if you have them. Hostaway connects natively, and supplier or GDS files load through SFTP or Amazon S3.

How is Bruin different from a booking engine's own reports?

Booking engine reports show bookings. Bruin joins them with search logs, supplier responses, payments and marketing spend, and explains why a market is behind last season.

Do travel companies need a data team to run this stack?

No. Connect the booking database and the tools you already use, then ask in Slack. If a data team exists, Bruin runs on its models and checks, and their changes live in their own Git repo.

Keep reading

What is Bruin?

Bruin is an open-source, AI-powered data platform. One project covers the whole path from source to answer: data ingestion (with ingestr), SQL and Python transformations, quality checks, column-level lineage, a data catalog and scheduling. On top of that data, an AI data analyst answers questions in Slack, Microsoft Teams, Google Chat, WhatsApp, Discord, Telegram, email or the browser, and builds dashboards from a prompt.

Pipelines are plain SQL, Python and YAML files in your own Git repository, and the work runs inside your own warehouse: Snowflake, BigQuery, Databricks, Redshift, Postgres, ClickHouse, DuckDB and others. The Bruin CLI is open source under Apache 2.0 and runs on a laptop, in CI or on-prem. Bruin Cloud is optional and adds scheduling, the AI data analyst, governance, SSO and audit logs.

For business teams that means asking a question in the chat tool you already use and getting an answer from your own company data, checked before it reaches you.

Replaces: Separate tools for ingestion, transformation, orchestration, data quality, cataloguing and BI
Open source: Bruin CLI under Apache 2.0; ingestr source-available under the Functional Source License
Your data: Stays in your warehouse; pipelines stay in your Git repository
Security: ISO/IEC 27001:2022 certified and SOC 2 Type 2 attested
Used by: Data teams at Lessmore, StarBerry, NativeMinds, SCG, M8 Games and Fabrikatör

Why Bruin for Travel & hospitality

Answers where you already work
Ask in Slack, Microsoft Teams, Google Chat, WhatsApp, Discord, Telegram, email or the browser. There is no new tool to learn and no ticket to file with the data team.
Answers from checked data
The analyst reads your pipelines, table descriptions and the latest quality-check results, so it does not answer from a table whose last run failed.
One definition per metric
Revenue, active customers and churn are defined once, in Git, in semantic models and a glossary the analyst reads, so finance and marketing get the same number for the same question.
Built on a real data platform
Bruin also loads and models the data. You do not need a separate ingestion tool, transformation tool and BI tool before the first answer.

How it works

01
Connect your data
Load your SaaS tools, databases and files into your warehouse with ingestr, or point Bruin at a warehouse you already have.
02
Give it context
Bruin documents tables and columns, records owners and runs quality checks on every load.
03
Ask
Ask in Slack, Teams or the browser. Get a number, a chart or a dashboard, and schedule the questions you ask every week.

How the AI data analyst works Read the docs