‘Today’s Marketer Needs to Be Data-Driven’: DiscoverOrg CEO Henry Schuck on Artificial Intelligence and the Future of Martech

By Dillon Baker

Einstein. Sensai. Watson: Three important words for the future of martech and artificial intelligence. Salesforce’s Einstein launched late last year, Adobe’s Sensai two months later, and IBM and Salesforce announced a partnership to sell their AI together, earlier this month. As an IBM representative told TechCrunch, “Within a few years, every major decision—personal or business—will be made with the help of AI and cognitive technologies.”

However, not everyone is impressed. Henry Schuck, CEO of marketing and sales intelligence platform DiscoverOrg, thinks the AI arms race isn’t a new phenomenon. According to him, many martech companies are just rebranding technology that has been around for years. He isn’t the only one feeling skeptical. In a recent article on The Content Strategist that examined AI hype, Sameer Patel, CEO of the smart automation software company Kahuna, said: “There’s just a lot taking old technology [and] plastering AI on it.”

As artificial intelligence continues to grab headlines, I spoke to Schuck to get his take on evolving skill sets for marketers, where salespeople fit in an automated future, and why some marketers struggle with marketing technology.

I know you’ve expressed some skepticism about artificial intelligence. Do you think it’s going to be a big part of marketing’s future?

I’m certain AI will be a part of marketing’s future. But part of my perspective on this is the way companies use the word “AI.” It’s like a fancy word to describe something that marketers, particularly B2B marketers, have been doing for years now. It’s really just predictive lead scoring.

Marketers have been doing that for the last decade with website tracking and their own leads, all without using AI. It’s really over the last four or five years that there have been dozens of predictive lead scoring companies that have added machine learning to that process. They bring in a bunch of different data elements to help you look at your customer base and then identify which customers are your “A” customers, your “B” customers, your “C” customers, your “D” customers, all based on a complex statistical model that looks at the activities that your customers and non-customers have done. Then they identify what your ideal customer looks like.

So I think it’s interesting that there’s all this buzz around something that’s been around the B2B marketing world a long time.

Do you think in some cases it’s marketing technology companies …read more

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