Over the past year, FindTuner took several meaningful steps forward by expanding platform support, deepening insight into shopper behavior, and extending automation across the eCommerce ecosystem. Together, these advancements reinforce a single goal: helping our customers turn search into a measurable, controllable driver of shopper experience and revenue.
Expanding the FindTuner Platform
This year marked a major expansion of where and how FindTuner can be applied. With the release of FindTuner 3.10, we extended FindTuner’s merchandising and AI capabilities to Elasticsearch and OpenSearch, in addition to Apache Solr. Many retailers and B2B merchants choose these platforms for their speed, scale, and flexibility. However, delivering meaningful, revenue-driving shopper experiences requires more than technical performance; it requires the ability to apply merchandising strategy, business priorities, and AI-driven optimization to every search interaction. FindTuner brings that layer of control and intelligence to Elasticsearch and OpenSearch, enabling teams to fine-tune relevance, promote key products, personalize discovery, and guide shopper journeys without sacrificing automation or performance. This expanded platform support allows organizations to apply consistent merchandising strategy across more of today’s leading eCommerce search foundations.From Search Activity to Actionable Insight
Another major focus of the year was visibility. As shopper expectations continue to rise, search and merchandising teams are under increasing pressure to understand what’s working, what isn’t, and where to focus next. With the introduction of FindTuner Insights, we addressed a long-standing gap left by generic analytics tools by connecting shopper behavior directly to search merchandising decisions. FindTuner Insights provides merchandisers with direct, self serve access to search specific analytics, without relying on generic dashboards or centralized analytics teams. Teams can see how shoppers interact with search and navigation, identify high volume or underperforming queries, understand revenue impact by strategy or product, and uncover clear opportunities to improve discovery. Beyond reporting, Insights creates a continuous feedback loop between merchandising actions and shopper outcomes. Using capabilities such as clickstream analysis, funnels, cohorts, and A/B testing, merchandisers can evaluate strategy performance, refine tactics, and clearly demonstrate the impact of their decisions. This turns optimization into an ongoing, data-driven process rather than a periodic review.Agentic AI and MCP
This year we also introduced the FindTuner MCP Server, a new integration layer designed to extend FindTuner’s reach and enable greater automation across the modern eCommerce ecosystem. The FindTuner MCP Server allows AI agents and workflow tools to connect directly with FindTuner through no-code and low-code workflows. This makes it possible to automate merchandising actions, exchange contextual intelligence between systems, and integrate FindTuner’s optimization capabilities into broader digital experience platforms and AI-driven processes. By enabling interoperability and intelligent automation, the MCP Server positions FindTuner as a central, connected component in a data-driven eCommerce architecture supporting teams as they adopt AI-assisted workflows while retaining human oversight and strategic control.Looking Ahead
Taken together, this year’s advancements reflect a clear direction for FindTuner:- Intelligence that blends AI, automation, and human strategy
- Insight that makes shopper behavior understandable and actionable
- Control that empowers merchandisers without slowing teams down
