Level Nine Sports began as an ecommerce company first before opening its brick-and-mortar stores in Utah. With its in-person shoppers, it could easily direct them to the products they wanted or needed and showcase top sellers, new products, or sale items.

But how could it do that effectively online? Level Nine Sports’ challenge became offering an equally great customer experience online as it could to shoppers who were walking into a physical store. This included connecting shoppers with products they desired and with inventory that the company wanted to move.

With nine brands and individual websites, N Brown is one of the most diverse retailers in the United Kingdom.

As it is for every online retailer, displaying relevant search results and category information is essential for N Brown. With a previous search provider, the N Brown online merchandising team was forced to publish a lot of rules to ensure its algorithm was as tailored as possible to those using it.

N Brown was looking for a solution that could help it be proactive rather than reactive in regards to market trends and help build the relationship between marketers and merchandisers internally. Enter Bloomreach Discovery.

As Sur La Table worked to elevate its ecommerce experience, the team needed a product discovery solution that integrated tightly with Salesforce Commerce Cloud (SFCC), without introducing a complex ecosystem of disconnected point solutions. The brand sought a unified approach that could simplify operations, improve search relevance, and support long-term digital growth.

Here’s what Sur La Table was up against:

• Fragmented and overly manual search tools. The existing search engine relied on rigid keyword rules, required constant human intervention, and couldn’t interpret natural, conversational queries. Customers struggled to find the products they were looking for, and search quality depended heavily on manual upkeep from the merchandising team.
• An outdated recommendations engine that lacked intelligence. The out-of-the-box recommendation tools from the previous provider were expensive, disconnected from SFCC, and not adaptive to evolving shopper behavior. Even worse, the team had limited visibility into why certain recommendations appeared, which led the team to invest too much time in tracking down answers and implementing manual fixes.
• Difficulty understanding and supporting real shopping behavior. Without an intent-aware search experience, Sur La Table couldn’t guide shoppers effectively through its extensive culinary catalog. From cookware and cutlery to tools and accessories, customers often hit dead ends instead of discovering relevant, complementary items to their purchases.
• A desire to streamline technology without sacrificing capability. The brand wanted to replace multiple point solutions with a single, unified AI platform that delivered strong search, merchandising, and recommendations without increasing operational complexity.