The company manages a large and dynamic product portfolio in a highly competitive e-commerce market. Identifying relevant products quickly and optimizing the assortment are critical for sales growth. Existing processes rely on fragmented data sources, limiting the speed and accuracy of decisions. To address these challenges, the company tested an AI-based product discovery solution.

The tool was tested over two months in a proof of concept within real workflows. Internal data was analysed to measure its impact, and findings focused on how well it detected market gaps, supported decision-making, and integrated into existing processes.

The proof of concept showed that the tool can support product gap detection and competitor benchmarking. Its potential was limited by incomplete data, lack of full system integration, and the need for targeted change management. While early results were promising in highlighting market opportunities, the tool requires further refinement before delivering its full value. Recommended next steps include improving data quality, integrating it more closely with existing systems, and embedding it within a broader product discovery process. This would allow the company to better leverage the tool for assortment planning and long-term competitiveness.