Dave Wright
Analyst · the Securities and Exchange Commission for more information on these risks and uncertainties. We may also refer to certain non-GAAP financial measures. A reconciliation of these non-GAAP measures to the most directly comparable GAAP measures can be found in our earnings release. We'll focus our remarks today on the key highlights and drivers. Additional detail is available in the earnings release. Joining us today are Dave Wright, our Co-Founder and Chief Executive Officer, and Jason Beesley, our Chief Financial Officer. Today's earnings is being webcast, and a replay will be available on our investor relations website following the call. Following our prepared remarks, we will open the call to questions. I'll now turn the call over to our CEO, Dave Wright. Dave, please go ahead
Thanks, Hamish, and good afternoon, everyone. We delivered another record quarter to start 2026. In Q1, revenue grew 43% year-over-year to $774 million. Adjusted EBITDA was $54 million, up 59% year-over-year. Before Jason walks through the financials, four metrics stand out to me. First, net revenue retention. We've said previously that NRR is one of the clearest indicators of the health and durability of our model. In Q1, NRR reached another record at 127%, up from 115% last year, reflecting the impact of optimization, marketplace expansion, and deeper brand relationships. Second, international growth. International revenue increased 101% year-over-year. We are beginning to convert international scale into improved efficiency and profitability, and we expect that to continue. Third, non-Amazon growth. Non-Amazon revenue grew 119% year-over-year, with strengths across TikTok Shop, Walmart, and Coupang. Fourth, our other monetization strategies grew 173% year-over-year, reflecting continued momentum beyond our core marketplace offering. To understand the drivers behind these results, it's helpful to step back and look at the platform and data that power them. E-commerce performance is driven by 4 variables: traffic, conversion, price, and availability. The same e-commerce equation we've referenced previously. These levers are highly interdependent and continuously shifting as changes in one area, like price or availability, dynamically influence performance in others, like conversion or traffic. Optimizing them together is complex. With scale across brands, data, geographies, logistics, technology, and AI, that complexity becomes an advantage for us. Our platform is designed to operate across these variables simultaneously, marketplaces, geographies, and channels. That scale allows us to improve outcomes for our brand partners while lowering costs across fulfillment, ad spend, and operations in ways that are difficult for a single brand to replicate. In our primary monetization model, we purchase inventory, which aligns our incentives with our brand partner's objective to grow consumer sales. We win when they win. The movement of physical goods under this model also creates a durable and competitive moat as AI continues to evolve. AI makes us more efficient rather than commoditizing what we do for brands. In simple terms, we break down a complex system into controllable levers at scale. That becomes both a growth driver and a cost advantage for our brand partners. Across brands, we see a consistent Pattern. When these levers are aligned, they can unlock a step function improvement in performance. For example, when a premium haircare brand started with us, in-stock was 79.6%. Since then, we improved in-stock to 96.1%, increased conversion 23%, which resulted in revenue growth of more than 15x. For a global tools brand, we launched their products across 25 marketplaces in one year, generating millions in international revenue and selling more than 100,000 units. These outcomes are the result of coordinated optimization across availability, content, pricing, logistics, and marketplace execution. Once the foundation is in place, we expand where demand is shifting across geographies, marketplaces, social commerce, and AI-driven discovery. That is the brand journey on our platform, and it continues to evolve. Two areas changing quickly for brands are social commerce and AI-driven discovery. We were recently named TikTok Shop's strategic partner of the year, reflecting our leadership on the platform. Over the last 12 months, we've launched more than 100 brands on TikTok Shop, activated over 365,000 creators, and grown our social commerce business triple digits again in Q1. One of the most competitive categories on TikTok Shop is beauty. Over the last few months, we've served as a launch partner for some of the largest beauty brands in the world. Social commerce has become a meaningful contributor for Pattern and the brands we work with. It has become an important entry point. As these brands grow with us, the opportunity to expand across marketplaces, geographies, and channels grows with them. LLMs are increasingly used at the start of product research. How consumers find, compare, and evaluate products before reaching a marketplace. Both channels operate on intent. Social commerce captures it through creators and content. LLMs surface it through semantic understanding, interpreting what a customer means, not just what they typed. Pattern is built to win in both. While full agentic transactions are developing more gradually than we initially expected, their influence on the customer journey is already meaningful. There are varying ranges and some debate on what percentage of purchases are influenced by LLMs, but I don't think there's much debate on the fact that it's significant and growing. We approach this from a data-first perspective. We have deep bottom of funnel search and conversion data across categories, which allows us to identify where brands have the highest probability of winning in LLM-driven discovery. We also have a strong understanding of consumer personas and intent, which we use to map how products should be positioned in these LLM environments. Taken together, this allows us to evaluate a brand's current presence versus its potential across LLM-driven surfaces and to optimize content positioning and availability accordingly. As agentic shopping develops, brand execution becomes even more important. Buyers' agents are likely to evaluate not only product relevance, but also whether a brand consistently delivers on what it promises, availability, delivery speed, customer service, returns, and overall brand experience. Those execution signals will have significant staying power in an LLM world, which will have meaningful influence on how products are surfaced and selected over time. We are laser-focused on these key metrics on behalf of our brand partners to ensure they perform well against these metrics for years to come. We are excited about the opportunities ahead and believe Pattern is well-positioned as commerce continues to evolve. With that, I'll turn it over to Jason.