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How Deep Learning Will Disrupt Marketing

AI may only be beginning to make its mark on the world, but its effect on marketing is becoming more and more clear.

Take for instance, the tired marketing mantra of getting the right message to the right customer at the right time.

While that’s long been a goal of marketers, Brandon Purcell, a senior analyst at Forrester, said at Forrester’s AI Summit in New York yesterday that the the traditional marketing machine was only capable of identifying the “right customer” and “right time,” not the “right message.”

There is something, however, that could make this into reality. Deep learning, according to Purcell, is a “fast evolving set of technologies and algorithms used by researchers, data scientists, and/or developers to build, train and test artificial neural networks that can be used as predictive models to probabilistically predict outcomes and/or identify complex patterns in data.”

Quite simply, deep learning is the marketing red pill. And with deep learning, Purcell says, brands and marketers should use these AI-marketing innovations to deliver the “right message.”

How?

Well, deep learning is used to unlock insight from unstructured data, such as image and video analytics, speech analytics, facial recognition, and text analytics. It’s these capabilities, Purcell believes, that will change the way brands interact with consumers in the future.

“Deep learning will eventually help automate and optimize the entire customer journey,” said Purcell. “For marketers, AI will fulfill the promise of customer analytics, giving brands and marketers the ability to get the right message to the right customer at the right time.”

Purcell highlighted that certain platforms, such as deep learning and machine learning, will give marketers the ability to train their own machine to learn algorithms from scratch. However, if marketers and brands, were more interested in preparing with an automatic approach with a “fully-baked” AI solution, Purcell spoke about the following platforms and their strengths:

  • AI-enhanced analytics solutions: Surfacing insights
  • Intelligent research solutions: Surfacing potential product and service enhancements
  • Pre-trained vertical solutions: Specialized and technical applications
  • Intelligent recommendation solutions: Personalized and intelligent product recommendations

Of course, Purcell cautioned, the “models are only as good as the data,” so it’s better to be aware and prepared of these changes, if brands and marketers want to get the right message to the right customer at the right time.

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