Hybrid search promises better search experiences by combining lexical precision with semantic understanding. But for many retailers and B2B sellers getting real value from hybrid search can be challenging. Enabling semantic models can be complex and once hybrid search is live, search teams often lack clear visibility into how it’s actually performing compared to traditional keyword search.
With the latest enhancements to FindTuner, we focused on solving both sides of that problem: simplifying hybrid search adoption and providing clearer insight into how shoppers interact with search and navigation.
Built-In Support for OpenAI and Gemini
FindTuner now includes built-in support for leading embedding models from OpenAI and Google Gemini making it significantly easier to activate hybrid search. These capabilities work seamlessly across Elasticsearch, OpenSearch, and Apache Solr allowing merchants to enable hybrid search quickly within their existing search infrastructure.
Retailers can get started without custom implementation and dramatically reduce time to value for AI-powered search experiences. These new built-in options provide a fast, reliable starting point for organizations adopting hybrid search, while FindTuner continues to support any embedding model of a customer’s choice.
New Insights That Deliver Greater Visibility
Activating hybrid search is only part of the equation. To optimize hybrid search teams and merchandisers need clear, objective insight into shopper behavior and search performance. That’s why we also introduced two new additions to FindTuner Insights that are designed to help retailers understand what’s happening after search results are delivered.
Together, these Insights provide time-based behavioral visibility and meaningful performance comparisons giving teams the confidence to evaluate hybrid search and make informed tuning and merchandising decisions.
Semantic vs. Lexical Click-Through Rate Insight
One of the most common questions retailers ask is whether semantic search results are actually outperforming traditional lexical results. The new Semantic vs. Lexical Click-Through Rate Insight answers that question directly.
This Insight compares shopper engagement between semantic and lexical search results at the search-term level making it easier to see how engagement is distributed and where semantic relevance is delivering value. With this visibility, teams can quantify the impact of hybrid search and optimize with data instead of assumptions.
Shopper Activity Trends Insight
The Shopper Activity Trends Insight focuses on understanding how shopper behavior evolves over time. It provides time-series visibility into key activities across search and navigation, including searches, clicks, cart additions, and purchases.
By analyzing these behaviors over configurable time intervals retailers can identify trends, monitor seasonality, and better understand how engagement changes. This insight supports smarter tuning and merchandising decisions by grounding optimization efforts in real shopper behavior.
Want to Learn More?
If you’d like to see how FindTuner works with Elasticsearch, OpenSearch, or Apache Solr, or explore how hybrid search and Insights can improve the eCommerce search experience, please contact us for a demo.
