Hotel Channel Mix Analyzer
Convert bookings from Booking.com, Expedia, Airbnb, direct and walk-in into percentage shares and see how concentrated your distribution is.
Monthly Bookings by Source
High reliance on Booking.com. Check what would replace those bookings if it dropped.
Mix Visualization
Visualization loads after the page is interactive. Current normalized mix:
- Booking.com45.0%
- Airbnb20.0%
- Expedia15.0%
- Direct/Web15.0%
- Walk-in/Other5.0%
Actions to reduce OTA dependency
- Improve direct conversion: fix speed, clarity, and booking steps before reaching for discounts.
- Capture repeat guests: consent-based email and simple loyalty perks bring guests back without a paid channel.
- Price your direct channel freely: in the EEA, Booking.com can no longer require rate parity, so you can set lower direct rates or add value (parking, breakfast, late checkout). Check other OTA contracts first.
- Measure net contribution: compare OTA commission and payment costs against direct marketing CAC, not just “share”.
What is a hotel channel mix?
A hotel channel mix is the share of bookings that arrives through each distribution source: OTAs such as Booking.com, Expedia and Airbnb, direct website bookings, and walk-ins or other sources. This analyzer converts monthly booking counts into percentages and rates concentration risk based on the largest single channel. Heavy dependence on one OTA leaves rates, visibility and commission costs in someone else’s hands.
Formula
Channel share % = Channel bookings ÷ Total bookings × 100 | Risk: top share > 55% = High, > 40% = Medium, otherwise Low
Shares always add up to 100%, so raising one channel lowers every other channel’s share. The risk rating looks only at the largest channel, not at combined OTA share, and its 40% and 55% thresholds are this tool’s rule of thumb, not an industry standard.
Worked example: the default 100-booking month
- Bookings: Booking.com 45, Airbnb 20, Expedia 15, Direct/Web 15, Walk-in/Other 5, for a total of 100.
- Shares: Booking.com 45.0%, Airbnb 20.0%, Expedia 15.0%, Direct 15.0%, Other 5.0%.
- Booking.com is the top channel at 45.0%, above 40%, so the risk rating is Medium.
- Cut Booking.com to 40 bookings: the total becomes 95 and its share is 40 ÷ 95 = 42.1%, still Medium.
- Cut Booking.com to 35 bookings: the total becomes 90 and its share is 35 ÷ 90 = 38.9%, so the rating drops to Low.
Even at a Low rating, OTAs still deliver 70 of those 90 bookings (77.8%), so check combined OTA share as well as the top channel.
Reading your risk rating
- A Medium or High rating names the channel you depend on most. That is the channel where a ranking drop, contract change or commission increase would hurt most.
- Add Booking.com, Expedia and Airbnb together to see total OTA share; the rating does not do this for you.
- The tool counts bookings, not revenue. If OTA bookings are longer or pricier stays, run the mix again using room nights or revenue for a fuller view.
- Set targets in percentage points, such as moving direct share from 15% to 18% over a quarter, and re-enter the numbers each month to track progress.
Frequently asked questions
What is a good channel mix for an independent hotel?
There is no single correct mix; it depends on location, guest profile and season. For context, the HOTREC European Hotel Distribution Study 2026 reports that in 2025 hotels took 51.3% of bookings directly and 29.9% through OTAs across Europe, and 59.7% and 31.9% in Germany. Those direct figures cover more than website bookings, so do not compare them with the Direct/Web slider alone.
Why is relying on one OTA risky?
A single OTA controls your ranking, the commission you pay and its own policy changes. If most bookings come from that channel, any change there flows straight into occupancy and revenue. The same HOTREC study found Booking.com alone held 66.1% of OTA bookings in Europe and 69.2% in Germany, so OTA share is often one-platform share.
Should I measure channel mix by bookings or by revenue?
Bookings are quick to pull and show volume dependency. Revenue or room nights are better for profitability decisions because channels differ in length of stay and average rate.
Sources