Introducing Marketing-Stack Management, Powered By Enterprise Machine Learning | AdExchanger
Perhaps the most viable path lies somewhere in the middle, between consolidation and building one’s own stack. With this approach, the same data that is already being captured in a DMP can be used to build a holistic decisioning engine that looks across an increasing number of digital marketing tools and consumer touch points to decide what message to present to what user in what channel.
The result is an enterprise-centric learning system that sits atop a series of ad tech stacks and executes against marketing directives in as close to real time as the points of distribution allow.
This is not yet another mar tech product, but rather a process. It requires analyzing current available data sets, including gaps between systems, as well as the distribution interfaces of the existing media channels. Think of it as marketing stack management, powered by enterprise machine learning (bring on the acronyms).
Doesn’t exist, and won’t be effective without a performance monitoring component as well as a cyber protection component.
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