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Product: Product Page

Hypothesis

If we test a similar change on our product pages as tested, then our conversion metric will likely improve based on their implementation decision.

TrustProduct PageE-commerceindustry_leakamazonwinner

Test Results

Key Learning

Problem: Friction during the product process causes users to abandon right when they're closest to converting.

What worked: implemented this UI change (Mar 29, 2021). Implementation suggests positive internal results

Takeaway: Even small lifts compound — across thousands of sessions, this adds up. Trust signals work best near decision points — test specific placements around forms, pricing, and checkout for maximum impact.

How to Apply This to Your Site

This experiment demonstrated that product: product page can improve conversions. The test was run on a product page page in the e-commerce industry.

Before you test: Consider that trust 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

(Canadian) recently ran this A/B test where they added these three little reassurances on some of their products. This experiment is similar to the maturing Benefit Bar pattern that addresses common objections to a purchase.

Methodology

Confidence Level
70%

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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