In two previous articles, we introduced Insights, a powerful new analytics capability in FindTuner. The first post explained what Insights is and how it works; the second post explored the types of merchandising and optimization use cases it supports.
This article looks at a third dimension: how FindTuner Insights relates to traditional web analytics tools such as Google Analytics. While we didn’t develop Insights to replace those platforms, we built it to fill a crucial gap that conventional analytics tools don’t and can’t address. Insights equips merchandisers with the visibility they need into search behavior to enhance product discovery and drive better outcomes.
Why Online Retailers Rely on Analytics
Online retailers have long depended on analytics to understand how shoppers engage with their websites. Tools like Google Analytics reveal where visitors came from, what pages they viewed, how long they stayed, and which elements they interacted with. For understanding external traffic patterns and broad behavior trends, these platforms remain vital.
But eCommerce requires more than an outside-in view of traffic and session activity. The most critical insights for improving product discovery come from inside the site, from the search box, navigation paths, product interactions, filters, and the decisions shoppers make as they narrow toward a purchase. This is the area where conventional analytics tools provide only partial visibility and where FindTuner Insights delivers clarity.
Where Conventional Analytics Fall Short
Traditional analytics platforms weren’t designed to explain the internal patterns that drive successful product discvoery. They focus on traffic and behavior at a high level but lack the depth needed to uncover the relationships between shopper intent, search behavior, and purchasing outcomes.
- Limited internal website behavior visibility
- Not optimized for product discovery
- Siloed teams and siloed data
- Not configured for eCommerce search
Conventional analytics tools track clicks and page interactions, but they rarely reveal what matters most in retail: how shoppers move through search and navigation, which behaviors ultimately led to conversion, and where friction occurred along the way. They don’t distinguish between a query refinement and a dead-end search, or show which product positions resonated with shoppers. They capture activity, but not the intent or the journey behind it.
Because these platforms treat all websites similarly, they lack awareness of core eCommerce search concepts like ranking strategies, attributes, facets, promotions, filters, and curated experiences. They can’t show how these elements influence purchasing decisions or which merchandising strategies succeeded or fell flat. For search teams and merchandisers, the lack of eCommerce search-specific insight limits their ability to understand what actually drives discovery.
The teams who manage analytics tools are often separate from the people responsible for shaping product discovery. As a result, they receive incomplete data, delayed reports, or insights stripped of the context required for making decisions. Search optimization becomes reactive instead of proactive, and opportunities to improve the shopper journey are missed. Insights closes this gap by delivering search and navigation analytics the FindTuner application thus removing delays and silos entirely.
While traditional analytics tools can be extended with custom events and tagging, doing so requires significant configuration and ongoing maintenance. Even then the resulting data is rarely as precise or comprehensive as search teams need. Insights eliminates this overhead. It arrives ready to capture the signals that matter for eCommerce search and navigation and delivers value immediately.
Connecting Merchandiser Actions to Outcomes
Understanding shopper behavior is essential, but Insights goes further by tying that behavior directly to the decisions merchandisers make in FindTuner.
This connection is unique. Insights shows not only how shoppers acted, but how those actions were influenced by:
- Behavioral ranking signals
- Product and brand promotions
- Curated collection pages
- Facet and filter adjustments
- Category level strategies
Instead of guessing whether a promotion worked or whether a curated experience improved discovery, merchandisers can see the impact clearly. They can measure whether a boosted brand increased engagement, whether a facet change reduced friction, or whether a curated result set drove more conversions. This closed feedback loop is something conventional analytics tools simply don’t provide.
Augmenting Conventional Analytics
Conventional analytics tools still have an important role to play. Retailers rely on them for understanding how shoppers arrive at the site, which search engines or keywords drove traffic, and how high-level site elements perform.
Insights complements this perspective by revealing what happens once shoppers begin exploring the site, including where discovery succeeds or breaks down, how intent evolves, and how merchandising strategies influence the journey. It delivers the depth of insight required to improve relevance, reduce friction, and guide shoppers toward the products they seek.
By connecting shopper behavior, intent, and conversion directly to merchandising actions, Insights transforms search optimization from a guessing game into a measurable, repeatable process. Retailers gain the clarity they need to improve the shopper experience and the confidence to make decisions that drive real business results.
