B2B Search Merchandising

Deliver relevant, personalized experiences that strengthen customer relationships.

The Challenges of B2B Search Merchandising

Delivering accurate and relevant search results is crucial to any merchant, however B2B companies face several unique challenges when it comes to implementing and optimizing B2B search merchandising. These challenges include large product catalogs with numerous product attributes, customer-specific pricing, and searches that include technical jargon, part number, and unit of measure. Customer’s increasingly expect efficient, personalized buying experiences that account for geographical location and product availability.

B2B Search Merchandising that Drives Growth

FindTuner’s powerful and flexible B2B search merchandising features deliver personalized search experiences that handle B2B search challenges with ease.  FindTuner optimizes the buying experience while addressing the complexity of B2B requirements to provide accurate and relevant search results. FindTuner scales without fear of being cost prohibitive.

Deliver Engaging, Efficient and Frictionless B2B Search Merchandising Experiences

Machine Learning for B2B Search Merchandising

Continuously see search results improve with machine learning that uses customer behavior, buying patterns, offline purchase data and your analytics. Elevate a customer’s previous purchases to deliver an efficient buying process.

Promote Important Products

Shape the ideal buying experience by promoting products, product groups and brands for any search or navigation. Use FindTuner’s precise product promotion features to control the most valuable positions in your search results.

Configure Guided Navigation

Generate dynamic facets from catalog data with no manual effort. Create custom links to any related content. Improve the buyer’s navigation experience by renaming, reordering or hiding any facet or value.

Capitalize on Buyer Profile Data

Handle customer-specific catalogs with ease. Leverage the customer’s location, industry, and interests to provide personalized B2B search experiences. Recommend complementary products based on search behavior, product associations, and historical data.

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What Customers Are Saying

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