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We’ve written before about the struggle companies are having realizing financial gains from artificial intelligence. Too often A.I. projects disappoint. Maybe part of the problem is one of expectations—many A.I. projects are too ambitious. Sometimes it is the simplest, most mundane uses of machine learning, that can have the biggest impacts.
Recently, I spoke to Michael Veselinovski, a senior account supervisor at the advertising firm Campbell Ewald, in Detroit. He says he used to spend a large portion of his time analyzing data from digital ad campaigns to figure out what was working and what wasn’t, as well as trying to gather statistics that could prove that campaigns Campbell Ewald had designed for its clients were actually delivering a return on investment. “For us it was a lot of manual work,” Veselinovksi says. “We had to come up with a hypothesis and then test it out.”
Then Campbell Ewald started using software from a California-based A.I. company called inPowered that specializes in A.I. that helps brands better position what’s known as native advertising—that is advertising that looks like journalism, but is designed to help create a positive impression of a particular brand or at least make it more likely the reader will buy a particular product or service. William Lever, the British industrialist who founded the company that would eventually become consumer goods giant Unilever, “once famously said, ‘half my advertising doesn’t work, I just don’t know which half.’ What we wanted to do is actually build a way to figure that out and make sure you’re only spending money on the half that works,” Peyman Nilforoush, inPowered’s co-founder and CEO, says.
InPowered’s software takes in data from past ad campaigns as a baseline, but then it generates new data by automatically running a series of small A/B tests. It uses these to figure out the best pieces of marketing content to run on a given website. It also figures out the best time and place within that website to position a “call to action” —such as a pop-up asking the reader to click through to another piece of content or a different site where the advertiser may be able make a sale. Critically, inPowered’s “content intelligence” platform figures out the best wording to use in the headline of that content and in those pop-ups to drive clickthrough rates.
For the insurance client, the system increased the number of people who clicked through to the life insurance calculator from less than 0.1% to 12%. “That’s 6,000 incremental clicks we’ve driven to the insurance calculator,” Veselinovski says. And those clicks are more likely to result in sales because people who have already landed on the insurance calculator are 40% more likely to engage with the next piece of content from the insurer, such as an online quote.
InPowered is not the only company making software like this. Competitors include BrightEdge, MarketMuse, and Concured. The sophistication of what each of these A.I. systems does varies. inPowered, for example, uses some natural language processing, the kind of A.I. that can understand and manipulate words, to figure out the best audience for a given piece of content. NLP is an area where A.I. has been making rapid progress, and inPowered has experimented with some cutting-edge NLP techniques, according to Nilforoush. But for the most part, the kind of machine learning inPowered and its competitors are using wouldn’t wow A.I. researchers.
But for the people using these systems, the effect is nonetheless transformative. Not only has it resulted in far better returns on their marketing spend for Campbell Ewald’s clients, it has changed how Veselinovski, the senior account supervisor, works. “The thing I love about A.I. and data is the discussion that happens afterwards,” Veselinovksi says. Rather than spending his day analyzing data, he now spends more time talking to clients about their brand positioning and overall marketing strategy. “When you can allocate more time to that discussion and the strategy, that is when the good ideas come,” he says.
In other words, this is a case where A.I. frees humans up to do the critical thinking and creative work they’re best at. And isn’t that what we really want from A.I.—that it will do the boring stuff for us?
Here’s the rest of this week’s A.I. news.