Instinctively, we pull our hand back without conscious thought, because the response to the stimulus takes a short cut and originates in the spinal cord because of the need for quick action.
According to venture capitalist Peter Levine, computing may soon need this type of shortcut. Levine said in a Wall Street Journal article that he sees a shift in computing coming — moving away from the cloud (centralized) to the return of edge computing (decentralized), because the wave of IoT and AI innovations are driving the need to have decisions made in milliseconds.
As Levine points out, a connected car is basically a data center on wheels. “It has 200-plus central processing units” that do “all its computations at the endpoint and only pass back to the cloud… important bits of curated information.” Just as your hand doesn’t have time to send a signal to the brain, autonomous vehicles need to react instantaneously to the situation.
Data, insight, and now action will be moving to the point of engagement in this future view. Now think about the potential challenges for marketers in staying on brand, and controlling the message with thousands, or even millions, of touchpoints acting independently. Today, the best messaging and value proposition work can, and usually does, go off the tracks the moment it makes its way to sales and service reps.
Marketers live with the daily issue of cross-channel attribution. Add cross-channel communication to the mix, and we’d better have some really good tracking tools! Sure, we can pre-set the messages and design algorithms to present them at the right moment in the buying cycle, but controlling and tracking the delivery of each message in the context of an overall brand story will be extremely challenging.
But keep in mind, machines aren’t great at delivering a “human” message. For example, do you really get the “warm fuzzies” from all those “HBD” messages on Facebook, or the “Congrats on the New Job” notifications on LinkedIn?
Machines have been great at helping us be more informed, but they have also have made it easy to turn highly personalized interactions into transactional tasks, void of any emotional connection.
The first wave of machine learning has been about improved efficiencies, productivity and predictability. As Jeff Bezos stated in his brilliant letter to shareholders, “Machine learning drives our algorithms for demand forecasting, product search ranking, product and deal recommendations…much of the impact of machine learning will be of this type – quietly but meaningfully improving core operations.”
As the next wave approaches, we must be cautious about how it is applied to the buying process. The focus should be on making humans more human, so potential customers don’t get burned.