If you’re using Siri, Alexa, Google Home, Netflix, Instagram and Hulu, you already intuitively know that most of our digital lives are already enhanced by artificial intelligence and machine learning.
As AI and machine learning continue to permeate our digital lives, marketing is rapidly becoming an AI- and machine-learning data science (which is awesome), and marketing teams must evolve and adapt accordingly in order to gain accurate insights and make ever deeper connections with the customer.
So here are 3 examples on how AI and machine learning are turning marketing into a data science, and most importantly who is looking at this data and making decisions, from content and creative to customer support.
What we see today is a complete streamlining of the creative process with AI helping to identify key elements derived from the data harvested and apply them to the building blocks of creative content such as graphics, video and text, which in turn are integrated in the larger creative frameworks such as website design, image recognition, email content, blog copy, and more. Insight engines will rapidly become the future-proof way for marketeers to source adequate content they can be absolutely sure that their customers will want to engage with.
assistants and natural language recognition
With Siri, Alexa and Google Assistant becoming a part of our mornings and evenings at home and in the car, conversational interfaces are finally establishing themselves as useful consumer technology.
So as an increasing number of consumers are learning and experimenting their digital experiences through bots, modern marketeers will need to understand conversational AI in order to get in front of their own customers more efficiently.
For example, airlines and banks have been using rudimentary conversational AI for the past 10 years. Now today, the list in long of startups working on big data, machine learning and Ai technologies to disrupt and displace customer service by knowing exactly how and when to route incoming client issues.
drop, measure, repeat
Data-driven marketeers today are sitting on piles and piles of data, and making sense of it requires a completely different skillset. What was “guesswork” and the old-school’s “set it and forget it” campaigns even 5 years ago is unacceptable today with the advent of new AI-based tools that are greatly enhancing the marketeer’s arsenal for the better. Today we are using AI to optimize targeting and the date we collect is sued as a training set for future campaigns in an ever-more intelligent data drop-measure-iterate infinite feedback loop.
My name's phil mora and I blog about the things I love: fitness, hacking work, tech and anything holistic.
Thinker, doer, designer, coder, leader.
Head of Product at Sikka Software.
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i blog about the things I love: fitness, hacking work, tech, Experiences and anything holistic.
> Head of Digital Product at Nutrien