AI: The Door-To-Door Salesman Of The Future

Once upon a time, expensive, high-value products like Electrolux vacuums and the Encyclopedia Britannica were sold “door-to-door.” It wasn’t always a red-shirted Verizon guy pitching fiber optics.

Door-to-door meant that a man in a suit (it was always a man) would knock on the door to your house, you’d answer and let him in (it was a different time, man). He’d take one look at you, note what you were wearing and scan the room. Based on what he saw, he’d instantly segment, and personalize, the vast store of brand values, product and support information housed in the wetware of his noggin — and then he’d explain why his product was important and relevant to you, of all people.

Ultimately, though, that level of specialization and personalization could not scale to compete with mass media like radio and television. No matter how great a personalization artist any given door-to-door salesman was, he could only reach, maybe, hundreds of prospects in a year. He was outsold several orders of magnitude by a generic message played to tens of millions in a minute.

But Mike Nicholas, a founder of Born, the AI-focused agency subsidiary of MDC Partners, told me AI would soon change that math. In the near future, an AI brain will see you coming, scan your profile, review your recent interactions, and then instantly segment, and personalize, the vast store of brand values, product and support information housed in the hardware of its flash drive. And then, it will build a customized interaction — whether it’s a banner ad, spoken conversation or a video avatar — that conveys what’s most relevant to you, of all people.

The trick with AI, though, is that unlike a human door-to-door salesman, AI can scale to tens of millions, or more. Think about the movie "Her," and how heartbroken Joaquin Phoenix’s character was when he found out his AI “operating system,” Samantha, had grown into a super-intelligence simultaneously keeping company with millions of others, conversing in dozens of different languages, all while he thought he had her to himself.

But I digress.

I was reminded of my conversation with Nicholas when i spoke with Greg Dale, COO of Persado, a marketing AI start-up that uses machine learning to find language that emotionally resonates with consumers,  reportedly driving them to action. One of many companies pursuing artificial intelligence solutions to the individualization challenge, the new Persado One capability is a predictive model that “assigns a profile to each consumer that determines their likelihood to engage with certain language and emotions,” according to the company’s website.  

Dale explains: “Think of it as a flag inside the DMP that represents everyone’s emotional preference — or language preference, I should say.” In other words, it indicates an individual’s likely response to different emotional triggers embedded in content.

Persado’s DMP “flag” for your emotional triggers will be one of a multitude of very important data bits that a well-designed marketing AI algorithm can use to create one meaningful interaction — or a million, one at a time. Talk about great power and great responsibility!

The ethical dilemmas that will no doubt be introduced by machines using language to push emotional buttons are subjects for another column. Today, I’ll note only that while most marketers are still struggling to write business logic that fuels digital marketing ROI (skills that should be mastered by now!), there are agency guys like Nicholas designing real-time AI personalized experiences, and advanced tech guys like Dale building tools like emotional flags to enhance those experiences.

To paraphrase William Gibson, the author who coined the term cyberspace in his 1984 novel “Neuromancer,” this particular future is already here; it’s just very unevenly distributed.

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