Agentic AI is reshaping retail by automating operations and enabling hyper-personalized shopping experiences, but success hinges entirely on data quality. Consulting firm BCG reports a 4,700% YoY traffic increase to US retail sites from GenAI browsers and chat services (Retail Dive - Technology). These engaged shoppers spend 32% more time on site, browse 10% more pages, and show a 27% lower bounce rate from retailer emails (Retail Dive - Technology).
For AI agents to autonomously find, compare, and purchase products on behalf of consumers, retailers must provide a foundation of high-quality, machine-readable data. The article outlines four critical data quality operations: cleanse and update customer records in real time; enrich records with demographics, geographics, and missing contact information; match and merge duplicate records into single, accurate profiles; and monitor data across the entire lifecycle. Without these practices, retailers risk biased AI results, wasted marketing spend, and diminished customer engagement as third-party AI platforms capture more of the buyer journey.
Retailers that anchor their AI initiatives in disciplined, accurate customer data will unlock competitive advantage through improved automation, scalability, and real-time decision-making—essential capabilities as agentic commerce becomes the norm rather than the exception.