Multiple: Checkout Funnel Optimization for Fashion Retailer Launching eCommerce
Hypothesis
A large brick-and-mortar fashion retailer launching ecommerce for the first time will have addressable UX problems especially in checkout, and mobile conversion will lag behind desktop due to a desktop-first build. External CRO expertise can accelerate learning and close conversion gaps quickly.
Test Results
Key Learning
Context: Mobile users experience the multiple differently — smaller screens, touch targets, and limited attention require purpose-built design.
What was tested: New ecommerce launches benefit from CRO engagement from day one — early data collection prevents months of unoptimized traffic. Mobile traffic majority with desktop-level conversion rates as a benchmark means mobile checkout is always the first priority. Proper analytics configuration (correct goal tracking, funnel visualization) is a prerequisite for valid test results — often missing at launch. Large offline retailers' brand recognition doesn't automatically translate to online trust signals
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 multiple: checkout funnel optimization for fashion retailer launching ecommerce but produced no statistically significant change. The test was run on a landing page page in the e-commerce industry. Inconclusive results suggest this particular change may not be a priority — focus testing effort on higher-impact areas.
Before you test: Consider that form 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
Rainbow Clothing (1,300 US stores) hired Invesp shortly after launching their ecommerce store in 2012. The CRO team handled all development work for experimentation while Rainbow's internal team managed a platform migration. Analytics configuration, team training, and mobile checkout optimization were key focus areas. The 28% conversion increase was achieved in 6 months.
Methodology
Build On These Learnings
Save your own experiments, spot winning patterns across your test history, and stop repeating what's already been tried.
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Checkout: Remove Coupon Fields
Problem: Coupon and promo code fields on checkouts can distract users — they leave to hunt for codes, reducing completion rates.
Checkout: Fewer Form Fields
Context: Each additional form field adds friction to the checkout, increasing the chance users abandon before completing their submission.