As customers become more discerning
and data-savvy, their expectations around how and when retail brands
communicate with them will continue to rise. This will push more brands to take
a more sophisticated approach to marketing tech, adding extra layers of innate
intelligence through machine learning and A.I. into their marketing stack and
freeing up human marketers to do what they do best--create. We will see a
broader shift from rule-based marketing--where the marketer defines all the
logic--to innately intelligent marketing, where the marketer only sets the
framework, and the A.I. takes it from there.
As
marketers, when we build campaigns, we’re always looking for good conversation
starters. But campaign volume and variety are very much limited to the worker’s
capacity, and this hands-on work is tiresome. Some have more data than others, in all of them you’ll find
automation, and in many, the concept of connectivity. But the intelligence –
the essence – is left to the human user who needs to define the rules and
flows. One other thing to take under consideration is
that in most marketing plans, there’s significant crossfire.
Customers
receive multiple messages from different campaigns and it’s almost impossible
to manage priority and exclusion. You don’t really leverage the benefits of
machine learning and your use of the human intelligence is limited. Most systems include these three
components. If you define a journey and aim to start five
additional conversations with customers, you must either build a new journey or
find the splits in the existing journey. At a certain point, your hands are
tied – too much data, the guy who built the journey moved to another company –
and you find yourself in a deadlock.
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