The modern marketer has a single-most, overarching and critical objective: to deliver the right message at the right time to the right audience, efficiently.
This holy grail for most marketers isn’t just a lofty goal, it’s unobtanium—where the most we dare hope is to learn a few things during our quest for it.
Or at least that’s what I thought before I heard from 70 marketing executives, practitioners and AI enthusiasts who provided their insights on the future of AI, as it relates to marketing.
It’s not about what we see in Westworld or Skynet or even Joshua . And it’s not about taking the jobs of humans. Instead, the future of AI promises marketers an opportunity to connect with customers, in a personal way, with speed and precision.
For some marketers, expert definitions and explanations of artificial intelligence are a jumbled heap of big words and concepts.
As a marketer, it’s important to stay focused on the “what” and avoid getting bogged down by the “how,” especially for those who may feel intimidated by technology.
So here's my stab at simplifying AI for the non-technical marketer:
Who should read this?
Growing up, my dad would say, "If you have a hammer, all you see are nails."
And similarly, "Don't hammer a nail with a monkey wrench."
A marketer's competitive advantage is often their ability to find and use the right tools for the job. But with the marketing technology landscape of solutions exploding (now over 5,000 solutions strong), keeping up is a struggle. And that struggle is real.
Marketing executives, technologists, practitioners and anyone who is involved in the customer journey should read this report. It's broken into four parts:
The Impact of AI on Modern Marketing, Part I
According to an IBM report, 73 percent of CEOs say cognitive computing, or AI, will play an important role in the future of their organizations.
And, according to Gartner’s emerging technologies hype cycle, we’re still at the “Peak of Inflated Expectations;” with machine learning a few years away from mainstream adoption.
However, when we look at martech (solutions focused on helping marketers connect with customers) we’re much deeper into the cycle. AI is already a key component in many martech solutions and promises to evolve exponentially along with the martech landscape.
A few AI terms and definitions from a martech perspective
By no means is this a comprehensive list of AI terms, but rather just a few of the core terms you should understand as a marketer.
Machine learning, a set of algorithms used by intelligent systems that learn from experience, is an approach to AI that gives marketers the means to take huge amounts of data to build target audiences, personalize messaging and leapfrog potential buyers in their customer journey.
Real-world applications include automatic text summarization, sentiment analysis, topic extraction, named entity recognition, parts-of-speech tagging, relationship extraction, stemming, text mining, machine translation, and automated question answering. But the future of AI in marketing promises so much more.
Deep learning is a method, or technique, to achieve machine learning. Differentiated from task-specific learning, think of deep learning as uncovering layers upon layers of intelligence where the higher layers provide explanation and the lower, or deeper layers, provide more abstract concepts.
Recommender systems, like those on ecommerce sites, use deep learning to build relationships and get to know the customer with every interaction, both on and off the site, penetrating each layer to provide more accurate recommendations, personalized content and even offers.
If you’ve ever taken an IQ test, you know that your ability to recognize patterns weighs heavily on the results. “Humans are amazing pattern-recognition machines and the ability to transform recursive probabilistic fractals” into concrete, actionable steps is what sets us apart from machines.
The Impact of AI on Modern Marketing, Part II
There are a multitude of frameworks and visualizations to help marketers map the buyer’s journey. And irrespective of the framework you use, the reason we map this journey is to achieve the ultimate culminating goals:
In order to do this, we look at where the prospective buyer is in the journey and determine the message that will resonate most, given what we know about them.
Marketers are optimistic that AI will help move the needle in terms of delivering