See exactly where shoppers abandon
Map the path from product page to basket, checkout and order confirmation. See the drop-off at every step and which traffic sources bring shoppers who actually buy.
See how shoppers move from product page to checkout, find where they abandon their basket and test the changes that win back the sale.
You spend heavily to bring shoppers to your store, and most of them leave without buying. They browse a product, add it to their basket, then disappear at shipping costs, a confusing checkout step or a payment error you never see.
Splitsense shows you the whole journey with one script. It tracks which products and sources bring buyers, where shoppers drop out between product page, basket and payment, and replays the sessions behind every abandoned checkout. Then the agent runs A/B tests on the pages that matter most.
Because traffic, behaviour and revenue live in one place, you can follow a shopper from their first page view to their order, and fix the step that is costing you the most sales.
Start with the steps where shoppers leave. Watch why, test a fix and keep the version that sells more.
Map the path from product page to basket, checkout and order confirmation. See the drop-off at every step and which traffic sources bring shoppers who actually buy.
Filter replays to everyone who added to basket but never paid. See the shipping cost that put them off, the coupon field that distracted them or the payment error that stopped them.
Test product photos, descriptions, reviews and delivery messaging. Splitsense drafts the variants, splits your traffic and ships the version that sells the most.
See visitors, orders and revenue by source, campaign, country and device, so you can spend more on the channels that bring buyers, not just clicks.
Connect your store to bring in orders and revenue, so every experiment is measured on sales, not just clicks. Works with any theme in a couple of minutes.
The agent compares shoppers who bought with those who abandoned, flags the moments that matter and suggests the experiment most likely to lift your conversion rate.