Product Advisor

The Product Advisor is an AI-powered solution for e-commerce platforms that makes complex and consultation-intensive products easier to find. Instead of relying on traditional keyword searches, it understands user intent, technical parameters, and context (e.g., “M12, IP67, 24V”) and provides relevant product recommendations. The goal is to create a context-based buying experience directly within the store that guides users to the right product faster, thereby increasing conversion rates and revenue.

The solution is designed for e-commerce companies with complex, technical, or product-specific products, such as those in the industrial, mechanical engineering, or technical components sectors. It is particularly well-suited for organizations with fragmented data landscapes (PIM, DAM, CMS, shop systems) where traditional search is insufficient. The Advisor is also ideal for companies that want to improve their conversion rates and better guide users through large product portfolios.

The Product Advisor increases the conversion rate by reducing zero-result searches and guiding users to relevant products more quickly. Instead of returning irrelevant search results, the AI identifies the user’s actual purchase intent and takes technical specifications and context into account. This reduces bounce rates, increases time on site, and leads to more search queries resulting directly in a purchase—which translates to higher revenue per search interaction.

The Product Advisor integrates seamlessly into existing e-commerce architectures without the need for replatforming or major system overhauls. It connects to existing data sources such as PIM, DAM, or CMS systems and uses them contextually. The solution is embedded directly into the existing shopping experience, ensuring that users do not encounter any disruptions and can continue to navigate within their familiar environment.

No, existing systems do not need to be replaced. The Product Advisor was specifically designed for fragmented system landscapes and operates as an intelligent layer on top of existing platforms. This eliminates the need for a time-consuming replatforming process. Companies can continue to use their existing infrastructure while significantly improving the search and advisory experience.

The implementation takes place in five steps: First, systems are connected and KPIs are defined (Connect & Understand). Next, data is integrated and enriched (Ingest & Enrich). This is followed by integration into the user experience. Results are then tested and validated (Track & Validate). Finally, the system is continuously optimized (Optimize & Evolve) through feedback and A/B testing.

The Product Advisor solves the problem of fragmented data sources by consolidating information from PIM, DAM, CMS, and other systems and interpreting it in context. Instead of isolated data silos, this creates a unified, intelligent database. As a result, the AI can accurately understand user queries—even those involving complex technical requirements—and reliably match them with the right products.

Unlike traditional search, the Product Advisor doesn't rely solely on keywords; instead, it understands genuine user intent and technical contexts. Unlike chatbots, it remains fully integrated into the store and doesn't take users out of the purchasing process. It combines product search, advice, and contextual understanding into a single, seamless experience without any disruption.

Key performance indicators (KPIs) include a higher search conversion rate, fewer zero-result searches, lower bounce rates, and longer session durations. In addition, product discoverability improves in complex catalogs. Companies benefit from increased engagement, better data quality, and a measurable increase in revenue per search query thanks to more precise recommendations and context-based results.