30 min
The Role of Interoperable Data in Enhancing the Retail Customer Experience DataDriven Podcast
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- Technology
In this episode, host Chris Detzel interviews Venki Subramanian, Senior VP of Product at Reltio, about using data to drive growth and efficiency in the retail industry. They discuss the key priorities retail companies are focused on, such as acquiring customers, increasing customer lifetime value, improving operational efficiency, and managing risk and compliance.
Venki explains how technologies like master data management help retailers unify data across different systems and touchpoints to deliver superior customer experiences. He shares examples of retailers leveraging data and AI/ML for applications like demand forecasting, inventory optimization, computer vision, and virtual assistants.
The discussion covers the importance of real-time, interoperable data in facilitating omni-channel retail experiences. They talk about the role of predictive analytics and emerging capabilities like edge AI in retail decision making. Venki emphasizes the need for composable architectures that allow retailers to integrate different technologies using standard interfaces and interoperable data.
Key takeaways include starting with targeted business outcomes, proving value iteratively, and focusing on use cases that provide the best ROI when adopting new data/AI capabilities. Venki concludes that retailers who leverage composable architectures and interoperable data will differentiate themselves and drive growth.
In this episode, host Chris Detzel interviews Venki Subramanian, Senior VP of Product at Reltio, about using data to drive growth and efficiency in the retail industry. They discuss the key priorities retail companies are focused on, such as acquiring customers, increasing customer lifetime value, improving operational efficiency, and managing risk and compliance.
Venki explains how technologies like master data management help retailers unify data across different systems and touchpoints to deliver superior customer experiences. He shares examples of retailers leveraging data and AI/ML for applications like demand forecasting, inventory optimization, computer vision, and virtual assistants.
The discussion covers the importance of real-time, interoperable data in facilitating omni-channel retail experiences. They talk about the role of predictive analytics and emerging capabilities like edge AI in retail decision making. Venki emphasizes the need for composable architectures that allow retailers to integrate different technologies using standard interfaces and interoperable data.
Key takeaways include starting with targeted business outcomes, proving value iteratively, and focusing on use cases that provide the best ROI when adopting new data/AI capabilities. Venki concludes that retailers who leverage composable architectures and interoperable data will differentiate themselves and drive growth.
30 min