Amy Hu, H&R Block’s VP/Interactive Marketing and Online Experience, discussed this subject during a session at the Ad Age Next Conference in New York.
“We’re doing something a little untraditional,” she said. (For more, read WARC’s in-depth report: How H&R Block is building AI and machine learning into marketing.)
More specifically, she explained, the company is constructing its own ad-tech stack. And one driver in that process is the notion that artificial-intelligence (AI) components in the marketing mix “are coming out of the box”.
“They don’t clone exactly the way they say they’re going to clone,” she added. As a consequence, “getting the data holistically and merging it all together to see that customer journey” has become “super-important”.
And the need for agility comes into play for Hu because “there are no particular vendors or sales platforms” that can flawlessly react to the new sets of insights that will result from this process.
“So, we’re building on our own AI [offering] so we can do a lot more advanced analytics.” The outcome, according to Hu, is a “custom solution for H&R Block with H&R Block data”.
“We take that data, and we’ll have the AI be intelligent so we can be an activation arm at a super-targeted segment.”
The new, raw information generated by machine learning, of course, is useless unless marketers can “get all the data in correctly. And you have to know what to do with the data”.
To that end, Hu said: “We talk a lot about the collision of arts and sciences.” Modern marketers never are at a loss for data. But an over-reliance on such information can lead to “formulaic” content.
“There’s still no replacement for the soul, and for the nuances about: How do you use the data to fuel the creative?” Hu told the Ad Age delegates.
“Good content is still good content. For us, we try to serve good content that is contextually relevant, targeting [it] to the right audience … It’s a collision between arts and sciences.”
Sourced from WARC