
+10.6%
Increase in Search Add-to-Cart Rate
+4.7%
Uplift in Average Revenue Per User Sitewide
How SwimOutlet Boosted Revenue and ATC Rates with Marqo
Company Overview
SwimOutlet is America's most popular online swim shop, trusted by professional athletes and recreational swimmers. Founded in 2000 and headquartered in Campbell, California, the company offers a broad catalog spanning performance swimwear, accessories, beachwear, and water-sport gear, serving customers across North America.
As SwimOutlet's catalog and customer expectations continued to grow, the team identified an opportunity to further evolve their on-site search and product discovery experience. With increasingly nuanced shopper intent and a growing volume of long-tail queries, SwimOutlet sought a solution that could better interpret context, understand domain-specific language, and adapt relevance dynamically.
Managing discovery across more than 20,000 SKUs placed increasing demands on SwimOutlet's search experience — the team needed a system capable of understanding their catalog at a deeper semantic level while maintaining flexibility and operational efficiency.
Why SwimOutlet Evaluated Marqo vs. Constructor
SwimOutlet evaluated Marqo as a replacement for Constructor after finding that static ranking models couldn't keep pace with the nuances of swim-specific shopper intent. The team needed a platform that could learn from real behavioral signals — not just apply pre-configured rules.
Marqo's pixel-based behavioral tracking and catalog-trained relevance offered a fundamentally different approach: rankings that improve continuously as customers search, click, and purchase — without requiring manual rule management for every new collection or season.
Challenges
SwimOutlet's catalog spans competitive performance gear and recreational products, each attracting shoppers with very different search behaviors. A keyword-based system couldn't bridge the gap between how swimmers searched and what they actually needed.
Domain-Specific Query Handling — Queries like "size 10 jammer" or "polarized open water goggles" were not handled well by keyword search, forcing swimmers to scroll through irrelevant results.
Long-Tail Query Volume — The increasing volume of long-tail queries could not be addressed through manual tuning and static rules at the pace of catalog expansion.
Search and Browse Fragmentation — The team needed to unify search and browse experiences under a single discovery platform with consistent ranking logic.
Performance Visibility — Limited visibility into session-level interactions made performance tuning slow and reactive rather than data-driven.
A swimmer searching "size 10 jammer for competitive training" knows exactly what they need. Getting them there without friction is the difference between a sale and an abandoned session.
Solution
SwimOutlet deployed Marqo's pixel across their site to continuously capture shopper interaction signals — including clicks, add-to-cart events, purchases, and browsing behavior. This data trained a custom LLM tailored to SwimOutlet's swim-specific catalog and shopper vocabulary.
Marqo unified search and browse under a single discovery platform with consistent ranking logic. SwimOutlet later expanded Marqo to power AI recommendations as results from search validated the approach across the broader site experience.
Behavioral Signal Tracking: Marqo's pixel installed on SwimOutlet's website to continuously track clicks, add-to-cart events, purchases, and general user behavior — enabling both general and user-specific optimization.
Custom LLM Training: Pixel data ingested by Marqo's platform to train a custom LLM and continuously improve search relevance without generic models or manual setup.
Swim-Specific Relevance: Strong understanding of descriptive queries, domain concepts, and swim-specific intent reported after implementing catalog-trained relevance models.
Unified Discovery Platform: Consistent application of ranking controls across search and browse, with SwimOutlet later expanding Marqo to power recommendations.
Results
SwimOutlet tested Marqo using a controlled, production AA/BB test, with 50% of traffic assigned to each solution. SwimOutlet reported improvements in discovery quality and performance. By blending semantic understanding with real-time interaction signals, the system surfaced results that more closely aligned with customer intent.
Increase in Search Add-to-Cart Rate
Uplift in Average Revenue Per User Sitewide
“As acquisition costs climb, the smartest investment we've made is in our own site experience. Marqo changed the way customers search. This isn't just conversion optimization anymore — it's marketing efficiency at scale.”
Alexander Sienkiewicz
Chief Marketing Officer, SwimOutlet
What This Means
SwimOutlet's results show that AI-native search pays off in a highly technical, domain-specific catalog. A +10.6% lift in search add-to-cart rate and +4.7% uplift in sitewide ARPU are not marginal improvements — they represent compounding revenue gains from every search session. When shoppers find exactly the right product faster, they buy more, return more, and trust the experience more.
Swim-specific queries now surface the right products without friction.
+10.6% lift in search add-to-cart rate, validated in a controlled production test.
Marqo now powers search, browse, and recommendations across SwimOutlet's site.
Results reflect a controlled AA/BB test conducted on SwimOutlet's production environment with 50% of traffic allocated to each solution. Outcomes may vary depending on catalog size, traffic volume, and implementation configuration.
Moving Forward
What Comes Next for SwimOutlet
With search and collections now unified under Marqo, SwimOutlet is continuing to build on its success by expanding Marqo's capabilities across the site experience. Marqo has become the foundation of SwimOutlet's discovery experience: scalable, composable, and shaped by real shopper behavior.
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