Melissa and Digital Commerce 360 (DC360) recently hosted a webinar titled “How to Optimize Data for Agentic Commerce: Preparing Your Ecommerce System for AI”. In this roundtable session, Robert Stanley, Sr. Director of Special Projects at Melissa, reviewed how organizations can turn long‑standing data quality practices into a powerful foundation for modern AI initiatives. If you’re interested in watching the full webinar, be sure to check it out on demand.
One message came through loud and clear in the webinar: if you want AI you can trust, you need data you can trust first. With more than 40 years of data quality expertise behind the approach, Robert explained how Melissa’s proven data quality practices can power today’s AI initiatives across retail and ecommerce. Instead of treating legacy systems and established processes like obstacles, the webinar showed how they can become valuable building blocks for more accurate AI outputs, well-structured open APIs and smoother workflows that grow with the business.
That kind of legacy-first strategy gives organizations a smarter way to scale AI with confidence. By grounding new technology in trusted data methods, teams can reduce errors and improve the quality, consistency and reliability of AI-driven results. For retailers and ecommerce brands, that means sharper decisions, more efficient fulfillment, better customer experiences and a stronger path to long-term growth.
By introducing data quality capabilities through open APIs, organizations can incorporate trusted data operations such as profiling, deduplication, enrichment and segmentation into downstream analytics and AI initiatives. In a retail environment, that can mean cleaner customer records, better audience segmentation, more consistent order data and stronger performance across marketing, merchandising and fulfillment workflows.
The webinar also explored how this approach supports end-to-end value delivery across the business, including:
- Accessing and federating data across legacy systems and other business-critical sources
- Profiling and transforming data through Melissa data quality resources and APIs
- Managing and segmenting high-value datasets used across retail and ecommerce operations
- Delivering trusted data into analytics, dashboards, customer programs and AI initiatives through open APIs and automated enrichment
The broader message was that AI readiness is not only about deploying new tools. It is about building on a trusted data foundation that allows those tools to perform effectively at scale. When retailers improve the quality, accessibility and governance of their data, they are better positioned to increase operational efficiency, support business growth and create more reliable customer experiences across every channel.
By applying proven data quality methods as you build AI applications, you can shift from fragmented systems to a more unified, AI-driven data strategy. Want to see how expert AI, semantic technologies and open APIs can reshape your data landscape? This recap is just a starting point. Watch the full “How to Optimize Data for Agentic Commerce: Preparing Your Ecommerce System for AI” webinar for a deeper look at the concepts, architecture and real-world examples.
Want more information about Melissa and our products? Reach out to us at www.melissa.com or call 1-800-MELISSA. Don’t forget to subscribe to our blog for everything related to data quality!