The journey from data to intelligence
As consumer engagement has matured, we have evolved from a discussion of tactics (email, SMS, push notifications), to a discussion of the data that powers those tactics (CDP, analytics, insights), to finally landing on the paramount discussion of the intelligence that powers the interactions. Five years from now, I predict that we will not be talking about which types of customer outreach strategies are superior, nor about a single view of the customer. Instead, we will be examining what intelligence we have about every consumer, how we arrive at that intelligence, and how we can capitalize on that to add value. Hence, the emergence of an intelligence layer.
An intelligence layer differs from analytics at large. Analytics drive insight after the fact, once data is stored, available for analysis. Intelligence, on the other hand, entails knowing every customer on a deeper level behaviorally, and serving what they need at any given moment in time. Intelligence opens up the possibilities for real-time predictive engagement; it’s proactive, rather than retroactive.
The Journey from Data to Intelligence
With the rise of the cloud, data has become more democratized. And, it should be. The assumption that any one enterprise will own or have control over all the data that is needed to understand consumers is futile. Hence, my opinion has always been that Customer Data Platforms, or CDPs, as a category will be hard to establish over the long term. Data will always belong to its own source, and so a management layer that can access the different sources of data through various means (adapters, APIs, batches, etc.) is imperative. Especially considering the fact that data is a dynamic, continuous flow in today’s world, constantly generated in real-time, such a layer is crucial to tap into different sources for the most updated information wherever it resides.
Building and owning an intelligence layer, contrarily to a data layer, gives an enterprise agency. At the heart of the intelligence layer is knowing how to harness a continuously evolving stream of data to determine insight at any moment in time and use it, with acknowledgment of the notion that the intelligence itself could quickly become stale and have to evolve in the next moment of time. The intelligence will have to pair historical context with the evolving/continuous context of the consumer and be predictive about outcomes to add value to the consumer’s journey at any given moment.
In the sphere of consumer engagement, we need to evolve the discussion from tactics and data to intelligence, since both tactics and data are producing diminishing returns at this point. The time has come to appreciate the fact that the only way to push the needle from a 2%-4% conversion rate and CTRs at the lower end of that scale, is to embrace intelligence to add value. Consumers will only engage if they truly feel that their needs are understood. Marketing and consumer engagement have focused for too long on a broad-based approach to engagement, and in this age of plenty, the consumer is calling for us to turn the page on that chapter and move to intelligent 1 on 1 predictive engagement.