Marketing AI Is Overhyped, and That’s Good

Today, marketing AI is a know-it-all with a short resume. Just like Big Data and personalization, it is also a catch-all phrase that is becoming harder to define. As a result, it is no surprise that most marketers are rolling their eyes at the topic. Nevertheless, this is also the time to take the topic seriously, unless you plan to retire into seclusion in the next few years.

AI
“artificial-intelligence-2228610_1920,” Creative Common license. | Credit: Flickr by Many Wonderful Artists

Today, marketing AI is a know-it-all with a short resume. Just like Big Data and personalization, it is also a catch-all phrase that is becoming harder to define. As a result, it is no surprise that most marketers are rolling their eyes at the topic. Nevertheless, this is also the time to take the topic seriously, unless you plan to retire into seclusion in the next few years.

New research by marketing automation provider Resulticks shows that 73 percent of marketers are either skeptical, neutral or simply exhausted by the hype around marketing AI. In addition, large numbers of marketers think that vendors using industry buzzwords are full of it. This is not surprising, considering how most vendors are probably over-selling their AI solution. In the same Resulticks study, only 18 percent of marketers claim that AI vendors are delivering the goods as promised and 43 percent felt they were over-promised.

However, for those of us who have lived through (and even reveled in) industry catchphrases, from “marketing analytics” to Big Data to “MarTech,” these statistics indicate that “Marketing AI” is on a strong growth trajectory. This is because the combination of huge industry-level investments and a few success stories is generally a recipe for a new frontier of innovation. Some time ago, I wrote an article on the VC investments being made in data-driven marketing technology and many of the technology solutions were still evolving innovations, like marketing automation. Today, the phrase “Marketing AI is also heading toward becoming broad and meaningless, with heavy investments in the sector. In a few years, underneath that generic umbrella will evolve smart, pragmatic solutions which will become part of the standard tool kit. For example, under the Big Data and MarTech labels, we now have well-adopted solutions, such as CRM, programmatic buying and marketing automation. While there are still bugs and varying degrees of success, there is also a large body of fruitful use-cases which demonstrate how these tools can be very effective.

So, what is a marketer to do in this environment where marketing AI has yet to evolve to a stage where it is a stable and valued marketing tool? The most important step is to set low expectations and begin to dip your feet in the water. Experimenting now is critical, as new skills sets and operating frameworks will be required to fully take advantage of the coming AI-driven innovations, and building those individual and institutional capabilities will take time.

Can a Machine Think for You?

I expect most of you are going to go with “No.” You might balk at the entire idea. But I had a conversation last week that pointed out that, if they’re working, isn’t that exactly what you’re counting on your marketing automation tools to do?

“As soon as we started thinking for you, it really became our civilization.” — Agent Smith, “The Matrix,” 1999, Warner Bros.
“As soon as we started thinking for you, it really became our civilization.”
— Agent Smith, “The Matrix,” 1999 Warner Bros.
People don’t make memes of this quote. For me, one of the most memorable lines of the movie.

Can a machine think for you?

I expect most of you are going to go with “No.” You might balk at the entire idea. But I had a conversation with Adobe’s Chris Wareham, senior director of product management for Adobe Analytics, last week at Adobe Summit where it became clear that, if they’re working, isn’t that exactly what you’re counting on your marketing tools to do?

“The state of the industry with data is to point a lot of really, really smart postgraduates with math at the problem and hope for good answers,” said Wareham. “And that’s not scaling.”

The bottleneck is that not everyone can be a data scientist, not everyone can do that kind of thinking, or has the training to do it themselves. Not everyone works effectively that way.

However, marketing departments today can’t afford to wait a week for the DBA on their IT teams to turn those reports out. That’s where Adobe’s virtual analyst comes in. According to Wareham, “the gap we’re filling in the industry is the need for people to be data-driven even in very simple interactions that they have.”

Wareham compares it to the revolution in we’ve seen in website analytics. Once (probably before many of you remember) finding out how much traffic was coming to your website involved getting daily or weekly reports from a guy called “The Webmaster.” Pretty quickly tools emerged to automate those reports, then deliver the numbers in real time. Google Analytics provides all that information, and a lot more we never dreamed of, in real-time.

“They were very complex things that made a very complex job really simple,” says Wareham. “So we’re starting to apply those same types of capabilities to a customer analytics problem set. Broadening the data set, leveraging the machine learning to automate a lot of those analytics processes, so a less sophisticated person can get a lot more leverage out of the data.”

And that’s where the robots come in. (Well, “virtual assistant,” but that’s really just one servo-enabled titanium chassis from the same thing, right?)

“Our usage of machine learning, our usage of things like the automated analyst, is really about applying machine learning to fix a problem,” says Wareham. To actually replace a data scientist takes more than reporting stats or tracking goals. The virtual assistant needs to be able to recognize the trends, opportunities and personas that a data scientist would, and that means breaking the rules. … Or at least the business rules many databases use to automate marketing

“Wherever we see rules, that smells like smoke to us,” says Wareham. “We want to get rid of the rules, and make everything that is currently rules-based algorithmically based, so it can learn, and it helps our customers get leverage out of the data.”

Robots breaking rules? Asimov would not approve, but it might be exactly the thing marketers need.

Whether this sounds joyous or terrifying probably depends on if you’re picturing Johnny Five or The Terminator.

Johnny Five, "Short Circuit," 1996 TriStar Pictures.
Johnny Five, “Short Circuit,” 1996 TriStar Pictures.
"The Terminator," 1984, Orion Pictures.
“The Terminator,” 1984, Orion Pictures.

Either way, it’s an interesting time to be a marketer.