Every digital marketer that’s paying attention is either wary, concerned, or deathly afraid of machine learning and artificial intelligence. These systems feature absurd processing power and instant analytical capabilities. They eat big data and crap hyper-targeted marketing. They take no breaks or vacation days and spend no time screwing around on Facebook (except to ingest behavioral insights to make themselves smarter). Various tech behemoths have branded their marketing AI in their own image. IBM (#client) has Watson, of course. Salesforce (#client) has Einstein.I’ve always thought Watson and Einstein existed to make these very complex systems more understandable. “Oh, that intersecting nexus of dozens of data feeds? That’s just Watson!” But now, I wonder if part of the benefit of this anthropomorphic approach to explaining AI is, perhaps unintentionally, to prevent marketers from totally freaking out about the future. “Watson isn’t going to take my job! He’s so funny and charming!” This is the marketing technology equivalent to distracting a child with a doll just before drawing blood. In truth, I do not believe AI (IBM calls it “cognitive”) is going to wipe the digital marketer off the map like a herd of grass-munching brontosaurs. As I said at the annual Sitecore (#client) user conference last week, when the robots do all the hard, tedious, time-consuming digital marketing work, the strategist becomes king. Because here’s the thing: For the foreseeable future, these systems must be TOLD what to do. Yes, machine learning, by definition, dictates that they get smarter and better over time. But they first must be taught what to look for and where—by us. If your job entails a lot of manual testing, list splitting, tweaking, optimization, and scorekeeping, you must learn how to manage the AI robots (and soon), or you may end up superfluous—as vestigial as our own appendix.
Social Media Robots Are HereFor the last two years or so, most of the work I’ve done and been exposed to in the AI-powered digital marketing world has been focused in these areas:
- Email testing and optimization
- Web content testing and optimization
- Mobile testing and optimization
- Behavioral data pattern recognition and ID of “best” and disenfranchised customers, as well as likely advocates and influencers