Etsy drives incremental revenue with search, advertising upgrades

The marketplace has internal "squads" focused on specific areas of improvement.

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Photo by Kelly Sikkema on Unsplash

Etsy mounted a strong showing in the holiday quarter, posting “very strong” performance to close out 2022.

While a lot of talk lately is on the external factors shaping retail, Etsy executives spoke more about the internal improvements they made to the marketplace in areas such as search and advertising.

Here’s a look how the company focused the team, and the results that these initiatives drove:


Inside Etsy, a big focus is the Right to Win. This describes focus areas where the company seeks to make marked improvements.

“Each year, we pick a select set of customer experiences where we believe we can make material improvements in ways that result in materially better experiences for buyers, more sales for sellers and better returns for investors,” said CEO Josh Silverman. “Etsy teams, often working in what we call a squad, are tasked with a single customer experience to improve in ways that achieve a specific financial target.”

In 2022, executives put a focus on advertising. In particular, they called on the team to make ads more relevant for buyers, while at the same time keeping seller ROAS above targets. The result was a better experience for customers, Silverman said. It also delivered results to the tune of over $100 million in incremental annualized revenue.

Silverman broke down how the squads function:

Squads have a great deal of freedom to test fast and learn fast and a strong bias to action. They often push more than one release per week, typically to 50% of Etsy's audience, so we can quickly measure whether that release has demonstrably lifted GMS or moved the target metric.

Importantly, we meet monthly to review the progress made by each squad. By doing this across our entire portfolio of work, we're able to understand the degree of payback we're getting or not from our investments, how they're impacting daily performance and adjust our work accordingly to ensure we're moving the ball forward to improve customer experiences and meet our targets.

For Etsy Ads, product enhancements throughout the year drove “better-than-anticipated performance,” said CFO Rachel Glaser.

“This included utilization of neural network embeddings, a type of machine learning advancement to increase ad relevance, which drove more clicks and purchases,” Glaser said. “We also launched a more visually engaging ad experience with videos on the homepage that increase conversion and return on ad spend for sellers.”


Etsy also made a concerted effort to improve the search experience on the marketplace throughout the year. Results will only compound

As Silverman put it, “With about 120 million live listings, getting you to the good stuff is really important.”

Search was also an area that saw continuous cycles of testing and scaling. The search team launched 120 experiments that were ramped up.

Among those were Etsy Lens, which allows users to provide a picture in the search field as opposed to words. Etsy is also improving neuro models, which helps search make sense of meaning as opposed to words.

“In fact, the neuro models we're using use the same kind of underlying algorithms that ChatGPT uses,” Silverman said. “So we're already using some of the underlying technologies that you're seeing from great innovators like Open AI, and it's having great impact.”

Improvements bring additional opportunities to make the path to purchase easier. Search results could now have a buy button embedded, enabling people to buy items directly from the results page, rather than having to go to an additional listing page.

Going forward, the company is looking to add more multimodal search that allows users to combine pictures and words. Silverman also wants search results to become more personalized to a particular user.

The company is also focused on what search results do for the business. It pays close attention to the processing power used, and weighs the cost added versus the results that the feature drives.

“Having multiple objective functions has been very helpful. How do I do something which drives conversion rate but also drives repeat visit rate?” Silverman said. “Those two actually might not be the same in terms of search results, so training our models to solve for more than one thing at one time.”

Development of chat-like interfaces is also top-of-mind given the rise of ChatGPT, and Silverman said that type of innovation is “very possibly” a future feature.

“We are constantly testing what's on the frontier,” Silverman said. “And if it makes our experience better and it does it in a way that's profitable, we're going to do it.”

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