How WPP operationalizes platform and data engineering for AI marketing

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Between chaotic levels of market fragmentation and economic volatility, marketing and communications agencies can no longer rely on the human intuition they’ve traditionally used to win clients and optimize their ad spend. WPP is replacing that guesswork with an AI-powered view of shifting market dynamics, giving brands predictive certainty that lets them invest with confidence while moving at the speed of the market. That’s the value of WPP Open, its agentic marketing system. But before it could begin applying sophisticated AI models to power those insights, WPP had to overcome a critical engineering challenge: the marketing data that made up the models was fragmented across hundreds of global agencies. While this dynamic made it nearly impossible to deploy AI tools efficiently and securely, access to models was only part of the equation. And  until it built a reliable way to ingest, clean, and serve data to those models, WPP couldn’t unlock the true potential of generative AI. To solve this, WPP partnered with Google Cloud to construct a unified data backbone and  custom platform engineering path. Now, by standardizing its serverless compute patterns and data processing workflows, WPP is able to  securely deploy targeted marketing campaigns in days instead of months. Architecting a centralized, service-based data foundation  An important part of this effort was accelerating data availability and centralizing management. To do this, WPP adopted a service-based project structure for its current production environment. Rather than isolating every workload into separate …

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