A lack of transparency in price trends was eroding trust and slowing down conversions. Meanwhile, our analyst provided data: users who had seen past discounts were 30% more likely to complete a purchase. This led us to our hypothesis:
“If we provide users with a dynamic price history chart on the product detail page, we’ll see an increase in purchase conversions and a reduction in the time spent deliberating.”
“If we provide users with a dynamic price history chart on the product detail page, we’ll see an increase in purchase conversions and a reduction in the time spent deliberating.”
“If we provide users with a dynamic price history chart on the product detail page, we’ll see an increase in purchase conversions and a reduction in the time spent deliberating.”
We believed that a transparent price history would help users feel more confident. To test this hypothesis, we organized a 4-day sprint that combined research, prototyping, and testing.
The A/B test results painted a clear picture. In the group with the always-visible chart, 90% of users noted that it immediately caught their attention and helped them assess the deal’s value, while 75% said it would speed up their decision to buy. In the tap-to-expand chart group, 80% found it useful, but only 55% noticed and opened it without prompting, highlighting an issue with discoverability. Interestingly, nearly half of the users in both groups requested price drop notifications.
These insights prompted us to create a second iteration, where we integrated push notifications for price changes to boost user confidence and reduce the fear of missing out on a better deal. We also refined the chart’s microcopy, adding a tooltip: “Today’s price is the best in 30 days,” to make the information even clearer. To confirm the effectiveness of these changes, we planned a larger-scale A/B test with real platform users, tracking conversion rates, time on page, and engagement.
