Booking: Booking Page Optimization
Hypothesis
UX improvements to 's booking page will reduce friction in the booking flow and increase the percentage of visitors who complete a service booking.
Test Results
Key Learning
Context: Users on the booking need validation from others before committing — without visible proof of success, they hesitate.
What was tested: Service booking pages require strong trust signals — testimonials, guarantees, and team credentials reduce booking hesitation. Increased time on site alongside higher conversion can indicate users are finding more relevant information before deciding. Local service businesses converting at 3.5%+ are top performers — getting there from 2.8% represents meaningful competitive advantage. Home services buyers have high trust requirements
Result: No statistically significant difference was detected. This null result is still valuable — it narrows the search space and helps calibrate your minimum detectable effect for future tests.
How to Apply This to Your Site
This experiment tested booking: booking page optimization but produced no statistically significant change. The test was run on a checkout page in the services industry. Inconclusive results suggest this particular change may not be a priority — focus testing effort on higher-impact areas.
Before you test: Consider that layout tests typically require adequate traffic to reach statistical significance. Run your test for at least 2 full business cycles to account for weekly traffic patterns.
What Was Tested
a home cleaning services company, worked with Oddit to optimize their online booking conversion. Booking conversion improved from 2.8% to 3.5% — a 25% increase in bookings. Time on site also increased 25%, suggesting users became more engaged with the site content (likely spending more time reviewing service options or trust signals) before booking.
Methodology
Build On These Learnings
Save your own experiments, spot winning patterns across your test history, and stop repeating what's already been tried.
Related Experiments
Does Restructuring Plan Detail Cards Improve Click-Through?
Test the variable users actually complain about — not the variable that's easiest to redesign. This test is a textbook case of treating form when the problem is content. Cross-brand qualitative research had consistently flagged three specific confusion themes: (1) pricing structure is opaque — users can't predict what they'll pay; (2) plan names are brand-driven rather than benefit-driven, so the names themselves don't communicate what the user is buying; (3) no side-by-side comparison — vertical layouts force users to scroll and remember instead of compare in parallel. Visual hierarchy is a presentation improvement; it does nothing about pricing opacity, naming clarity, or comparison difficulty. The test reached its planned sample size and produced a directionally-negative result at the noise floor — because organizing unclear content doesn't make the content clearer. The transferable insight isn't about visual hierarchy specifically; it's about the importance of mapping qualitative complaints to the test variable. If the user research says 'I don't understand what this plan costs,' the test should manipulate cost-clarity. If it says 'I can't tell these plans apart,' the test should manipulate differentiation. Layout tests are appropriate when the complaint is about layout — not when they're a default reflex.
Restructuring Homepage Hierarchy to Surface Personalized Offers
The story behind this win is the iteration discipline. The first attempt at this homepage redesign changed two systems at once (messaging + routing) and produced an ambiguous result: the entry metric moved slightly positive while downstream metrics moved meaningfully negative. The team correctly identified that the routing change — which inadvertently replaced direct links to a personalized plan-search experience with modal-driven entry into a generic flow — was the downstream killer. The iteration restored the original routing and kept ONLY the homepage hierarchy changes. All funnel metrics moved directionally positive in lockstep (entry +2.38%, mid-funnel +7%, conversion +11.81%) — none stat-sig individually but consistent enough across the funnel to justify shipping. Element-level diagnostics confirmed the mechanism: the segment CTAs the team intended to promote saw a 26-30% lift in unique-visitor interaction, while the unchanged hero banner stayed flat (as expected). Two key behavioral observations: (1) page-length reduction surfaced a 4x lift on a previously buried bottom-of-page zip code input — proving the secondary lesson that 'less page' can mean 'more conversion real estate'; (2) desktop strongly outperformed mobile, with the suspected cause being mobile's lead-with-form pattern (zip code above hero) — putting the form before the message creates friction. The broader transferable insight: when a messy test confounds multiple variables, the right move is to isolate one variable in the next test, not to abandon the hypothesis.
Content Page: Maybe Later on Content Page
Context: Key actions on the content page disappear as users scroll, creating a gap between intent and the ability to act.
Checkout: Multiple Steps
Problem: Friction during the checkout process causes users to abandon right when they're closest to converting.