Cédric, with your extensive experience in retail analytics, can you share what initially drew you to the world of predictive AI and retail marketing?

I spent the bulk of my career in data analytics for the retail sector, and as machine learning and AI models began to proliferate, it was a natural progression for me to immerse myself in those possibilities. The work we’re doing now at EagleAI is tremendously exciting, not just from a technological perspective, but also in terms of the impact we’re making for retailers and consumers across the globe.

Could you elaborate on the concept of hyper-personalization in retail? How does predictive AI facilitate more targeted and meaningful customer engagements?

In the past, retailers have built targeted marketing strategies by creating broad segments of similar consumers and targeting them with specific campaigns – many still do. Predictive AI turns those audiences of thousands of customers into segments of one, achieving that long sought-after pinnacle of customer-brand experiences: true one-to-one engagement.  

We call that hyper-personalization, and predictive AI enables retailers to achieve it at scale. For large retailers with customer bases in the millions, even with their resources and access to customer data, scaling personalization has been somewhat of a technological glass ceiling. Predictive AI makes one-to-one personalization a reality.

Predictive AI identifies opportunities for cross-selling and upselling by analyzing past purchases and customer preferences. It can then generate personalized product bundles or recommendations for complementary items. AI enables retailers to generate these offers from a near-infinite offer pool and do it at the precise moment that will influence a sale or specific action, combining existing data with contextual triggers to unlock new revenue development opportunities.  

For retailers at the beginning of their AI journey, what foundational steps would you recommend to ensure a smooth and effective implementation?

Again, taking the time to develop well-defined use cases and identifying scalable AI initiatives that can deliver ROI is an important foundational step. We would also recommend that retailers prioritize integrating AI into existing retail operations, like a current loyalty program, at first. Prior to implementation, they should evaluate current workflows and processes, acquire stakeholder buy-in, and train teams on how to use and get the most out of the AI tools they’re considering. And perhaps most importantly, work with partners that understand industry-specific nuances, can streamline the adoption process, and help establish a sustainable competitive advantage.

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