Leap Stores partners with premium brands to provide brand control and revenue growth on Amazon. Led by Jeff O’Bryant, the agency combines proprietary software, MAP compliance, data analytics, and product distribution to maximize brands’ potential on Amazon.

By using PickFu to optimize the main image, Leap Stores was able to take its client’s product from zero first-page rankings on Amazon to ranking on the first page for most of its top keywords. Here’s the story.

One of Leap Stores’ clients, a brand that sells custom products on Amazon, launched a new product in a highly competitive market. To succeed, they needed their product to rank organically on the first search results page, grabbing (and keeping) shoppers’ attention.

Based on past results, the client expected to see their product ranking on the first page after about a week – but that didn’t happen. After making strategic adjustments to the listings, amplifying ad spend, and re-launching the listings, the jump in organic rankings they expected was still not kicking in.

Despite the amount of data available to Amazon sellers, Leap Stores didn’t have an easy or fast way of getting high-quality feedback from potential customers. Jeff tried using Amazon’s Manage Your Experiments tool to A/B test his client’s listing, but it took weeks for the results to come back. They needed a better (and faster) way to boost the rankings.

After a friend recommended PickFu’s DIY polling platform, Jeff started running Click Tests to optimize his client’s main image:

1) Jeff simulated a search results page using his client’s and their top competitors’ main images, and asked respondents (a panel of US-based Amazon Prime members) which image they would click on first when shopping for the product. As expected, respondents overwhelmingly clicked on the competition’s main images instead of his client’s.

2) Having identified the most successful images, Jeff used them as a reference point to make gradual enhancements to his client's main image. After each tweak, he conducted further polls to assess the impact of the changes. Since he started receiving feedback within minutes after launching each poll, he was able to make iterations and run new tests quickly.

3) Eventually, after several iterations and about a dozen polls, the client’s main image was winning with 70% of the clicks in the PickFu tests. Jeff decided to re-launch the product on Amazon using the optimized image.

Just five days after launching, the client’s product (featuring the new PickFu-tested main image) was ranking on the first page for the majority of their target keywords. The optimized main image provided a huge boost to the product’s click-through rate, which propelled it to the top of the search results. 

Several months later, it’s still going strong and even gained an Amazon’s Choice badge.

“We all make assumptions about what’s going to work and fall into the trap of ‘this feels right to me,’” says Jeff. “But you’re putting yourself at a disadvantage if you rely on your gut. Especially in e-commerce, everything should be data-driven.”

The fast, high-quality feedback from potential customers was a highlight of using PickFu for Jeff – understanding not only which image people will click on, but why they click on it.

In the end, Jeff ran about a dozen PickFu polls, spending roughly $500. But the cost was well worth it to capture those highly coveted clicks from shoppers: “If you can’t get first page rankings on Amazon, you won’t have an ROI at all.”