CIO Era Magazines

Retailers face significant challenges due to poor-quality product data, which can disrupt business processes, hinder product searchability, and diminish customer satisfaction, ultimately impacting revenue. Gartner estimates that bad data costs organizations an average of $12.9 million per year, highlighting its detrimental effects on decision-making and data ecosystems.

To address these issues, GroupBy, a SaaS-based e-commerce search platform, hosted a webinar in September, in collaboration with Google Cloud partner Sada and Rethink Retail. The event, titled “Bad Data, Big Trouble: How to Turn the Corner on Poor-Quality Product Data,” emphasized how AI can enhance data quality, improve search relevance, optimize customer experience, and boost revenue. Key strategies included implementing standardized data collection, regular data reviews, and AI-powered solutions for efficient data management.

Arvin Natarajan, GroupBy’s product director, noted that nearly all retailers struggle with poor data, which affects applications dependent on accurate information. He emphasized that better data quality can enhance operational efficiency, support growth, and improve brand reputation. Through GroupBy’s platform, which leverages Google Cloud’s Vertex AI, retailers gain unique access to a sophisticated search engine that processes trillions of events daily, offering insights into user intent and enhancing the digital shopping experience.

Vinny O’Brien, E-commerce Strategist at Rethink, shared a past experience at eBay where faulty data indexing led to significant revenue loss from hidden product listings. This example underscores the importance of accurate data, which can be challenging to achieve across vast product catalogs without a standardized approach.

Joyce Mueller, director of retail solutions at Sada, described bad data as a longstanding issue resulting from incomplete, inconsistent, or incorrect entries. She stressed that clean data pipelines and consistent data specifications are essential for optimal product discovery.

The panel concluded that overcoming these challenges requires a combination of AI tools for data enrichment, regular audits, and a clear data governance strategy. These measures can help retailers improve data quality, enhance customer satisfaction, and ensure more robust sales performance.