Travel · Growth
Checkout total price test
Reading a test of showing the full price, taxes and fees included, before checkout.
Total price upfront vs. fees at checkout
+7.9%
Significant winStarted bookings completed
095% interval +2.6% to +13.2%
Total price upfront
Fees at checkout
control
Who it's for
Growth, pricing and product teams who run booking flow experiments in a feature-flag tool.
What it solves
Analyze the price display test on the exposure data in your warehouse, with the same booking definition as your dashboards and booking value as a guardrail.
Questions it answers
What was the effect on completed bookings?
Booking completion rose from 30.2% to 32.6%, a 7.9% lift (95% interval +2.6% to +13.2%).
Did the guardrail metrics hold?
Average booking value and the cancellation rate stayed within their guardrails.
- Did showing the total price lift booking completion?
- Is the lift significant, and how wide is the interval?
- Did average booking value or cancellations move against us?
- Which markets and devices responded best?
The impact
- Ship pricing changes on evidence
- One booking definition for experiments and reporting
- Catch tests that lift bookings but lower booking value
The data it needs
- Exposure events from your experimentation or feature-flag tool
- Booking step and confirmation events
- Booking value and cancellation tables
Read in place in your warehouse. Nothing is copied out.
Related use cases
Checkout total price test: frequently asked questions
Run this on your own data.
Start free on your warehouse, or book a demo and we'll show it on your data.