Checking hotel prices on every booking site at once (and catching rate parity problems)

Description and use

Automated hotel price monitoring via Google Hotels detects parity gaps between a hotel’s own site and OTAs, reducing manual effort and improving revenue management.

Problem

Hotels lose revenue when their own site lists higher prices than OTAs, creating rate parity problems that are hard to detect manually.

Outcome

The monitor identifies a 15.93% parity gap for Hotel Botânico on 2026-10-23/25, demonstrating the tool’s ability to surface undercutting OTA prices quickly.

Workflow

• 1. Provide input JSON with hotel names, daysAhead, rollingDates, nights, adults, currency.
• 2. Actor queries Google Hotels page for each hotel.
• 3. Actor extracts price list for requested dates, discarding rows with mismatched dates.
• 4. Actor outputs JSON rows with lowest price, official site price, parityGapPct, and change detection in monitor mode.
• 5. Optional Python script consumes dataset, filters gaps >5%, and sends alerts to Slack.

Evidence

Google Hotels Rate Monitor on Apify

Source

Look at parityGapPct. The hotel's own site is almost 16% more expensive than the cheapest OTA.

No subscription: $0.005 per run start, $0.003 per hotel and date checked, $0.0005 per change row.