Professional and home services experiments including lead generation, booking flows, and trust optimization.
Across 2 services experiments, 50% resulted in a statistically significant win. Winning variants saw an average lift of +7.5%.
1 experiment was inconclusive, meaning the difference between control and variant was not statistically significant. Inconclusive results are still valuable — they tell you what doesn't move the needle, so you can focus testing effort elsewhere.
These results come from real A/B tests with sample sizes ranging from hundreds to millions of visitors. Use them to inform your own services testing strategy and avoid repeating experiments that have already been run.
Context: Users on the booking need validation from others before committing — without visible proof of success, they hesitate.
Problem: Each additional form field adds friction to the signup, increasing the chance users abandon before completing their submission.
Save your own experiments, get AI-powered test ideas, and build on patterns from 2+ real tests.
View Plans & Pricing