Booking funnel and direct booking calculator
See where website visitors drop out before booking, what a small improvement at one step is worth, and how much more a direct booking keeps than the same booking through an OTA.
Your monthly numbers
The pre-filled figures are an illustration only, not benchmarks. Replace them with one month of your own data.
Sessions or visits in the month.
Visits that checked dates or availability.
Visits that started entering guest or payment details.
Confirmed direct bookings on the website.
Total booking revenue divided by bookings.
Editable. Use the rate in your own OTA contracts.
Optional. Payment, booking engine or other per-booking costs.
Funnel results
| Step | Count | Conversion from previous step | Drop-off |
|---|---|---|---|
| Visits | - | - | - |
| Availability searches | - | - | - |
| Checkout starts | - | - | - |
| Bookings | - | - | - |
What if one step improves?
For example 10 turns a 30% step rate into 33%.
Direct versus OTA: what is kept
A what-if figure, not a forecast.
Where to find each number
| Input | Usual source | Watch out for |
|---|---|---|
| Website visits | GA4 sessions for the month | Exclude staff and agency traffic where possible. |
| Availability searches | Booking engine search events, or a GA4 event when dates are submitted | A booking engine on another domain needs cross-domain tracking, or searches look like exits. |
| Checkout starts | GA4 begin_checkout or the booking engine's guest details step | Count each visit once, not every page reload. |
| Bookings and value | Booking engine reports or GA4 purchase events | Use confirmed bookings and the same currency and tax basis throughout. |
| OTA commission | Your OTA contracts and invoices | Include programme or visibility fees that raise the effective rate. |
How to use the results
- Enter one month of data from the same date range for every step.
- Find the step with the largest drop-off. That is usually the best place to start.
- Test the likely cause at that step, for example rates that differ from the OTA price, a slow booking engine on mobile, or surprise fees at checkout.
- Use the what-if model to put a value on a modest improvement before spending on a fix.
- Compare the commission kept per direct booking with what it costs to win that booking, so marketing spend stays below the commission it replaces.
Tag the links that bring guests to the website with the UTM builder and checker, so each funnel step can be split by channel.
Frequently asked questions
What is a booking funnel?
Where do the numbers come from?
begin_checkout. Bookings and booking value come from the booking engine or purchase events. Use the same date range for every number.What OTA commission rate should be entered?
Why does the calculator include direct booking costs?
Is the what-if model a forecast?
Is any data sent to NJoy Consulting?
Private by design
Everything runs in your browser. Nothing you type is uploaded, stored or sent to NJoy Consulting or anyone else. No signup.
Related tools and guides
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