Skip to main content
inconclusive

Listing: Bulleted Reassurances

Hypothesis

If we implement 'Bulleted Reassurances' on listing pages (This experiment attempted to increase the number of leads on a lead-funnel), then key conversion metrics will improve.

Social ProofCategory PageCross-Industrysocial_proofcopytrustdesktop

Test Results

50,698
Sample size

Key Learning

Context: How prices are displayed on the listing directly influences perceived value and willingness to buy.

What was tested: REAL-WORLD TEST: 'Bulleted Reassurances' was tested on a live listing page. The test involved 50,698 real visitors. Full statistical results require paid access. Test methodology: This experiment attempted to increase the number of leads on a lead-funnel. As the first step, users were being asked to upload a file. The control sh...

Result: No statistically significant difference was detected. Inconclusive social proof tests often mean the proof type or placement didn't match what users need at that moment. Try a different format or position.

How to Apply This to Your Site

This experiment tested listing: bulleted reassurances but produced no statistically significant change. The test was run on a category page page in the cross-industry industry. Inconclusive results suggest this particular change may not be a priority — focus testing effort on higher-impact areas.

Before you test: Consider that social proof tests typically require large sample sizes to detect small effects. Run your test for at least 2 full business cycles to account for weekly traffic patterns.

What Was Tested

This experiment attempted to increase the number of leads on a lead-funnel. As the first step, users were being asked to upload a file. The control showed the file types that were allowed, whereas the variation changed the copy to show a number of benefits for taking that action. The text-based benefits included the: receiving feedback, prices and lead times.

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.

Related Experiments

Explore More Experiments