Foot Locker has opted for the Customer Data & Experience Platform (CDXP) from British specialist Ometria. The shoe and clothing retailer wishes to accelerate its data-driven customer marketing to deepen relationships with its customers. The data platform is supposed to help creating a cohesive and personalised shopping experience across channels.
Foot Locker wants to systematise customer data, which the company collects via its FLX Rewards loyalty programme on the platform. This way it expects to build deeper and more meaningful customer relationships. Stephanie Bleymaier, Vice President Loyalty & CRM at Foot Locker, explains in a press release: “Ometria’s data capabilities deliver real-time, actionable insights to our marketing team.” This enabled the company to offer its customers a more personalised shopping experience.
Ometria has developed its CDXP specifically for retailers. The platform consolidates all customer data collected and makes it available to the various communication channels. Users of the solution include Sephora, Monsoon, Creed and Vivienne Westwood.
One source feeds all channels
The Ometria CDXP draws data from all available sources, such as loyalty programmes, POS systems, merchandise management, e-commerce platforms, mobile apps and customer service, and consolidates them into meaningful buyer profiles. In this way, a holistic picture of the customer is created in real time. From this, the system derives preferences and predicts possible shopping behaviour.
To create meaningful profiles, even for anonymous buyers, the software detects identifiers, for example from emails or cookie tracking data. The solution serves as a single source of truth for all customer contact channels and as a consent management platform for obtaining and documenting the necessary consent.
Retail data trains AI
Ometria uses proprietary AI models, specially trained with data from the retail sector. These are set to create suitable offers for customers based on their preferences for certain products, colours, fits or other characteristics. AI should also help to target them at a predicted time when a customer is likely to make the next purchase. It also calculates the expected customer lifetime value (CLV), the potential value of the customer during their relationship with the company.
Generative AI supports the user to create marketing campaigns more quickly. With the help of just a few key terms, it promises to automatically generate marketing messages in the company’s house style according to the target group.
