At the Adobe Summit this week in Las Vegas, Adobe unveiled the latest suite of updates for Sensei, the company’s platform for artificial intelligence that competes with IBM’s Watson and Salesforce’s Einstein.
The updates, which include an expanded partnership with Microsoft to pull the Microsoft’s CRM data into Adobe’s cloud, could help marketers improve spending across advertising platforms. They also come on the heels of competitors like Salesforce integrating with IBM on the same front, potentially furthering the AI arms race as machine learning becomes more understood and accepted.
But Adobe’s AI play is part of a broader plan to offer a more holistic suite of services through what it’s calling the Experience Cloud. (Part of that is the new Adobe Advertising Cloud, which aims to help brands and media buyers with data-heavy advertising buys.)
“With Sensei, we want to bring a lot of the machine learning we’re doing in different parts of marketing under one umbrella,” Anil Kamath, an Adobe fellow and vp of technology, told Adweek. “The other part is we’re bringing a common platform so that data used in making decisions—so if you are doing personalization or are targeting or operation of a campaign—people tend to use data only in the context of that silo.”
To Kamath, the goal is to break down the idea of “intelligence in silos.” He said there are three categories: customer intelligence, which focuses on a customer’s propensity to buy something; content intelligence, which seeks to understand how to pair the right content with the right consumer; and context intelligence, which focuses on other signals like location, time of day and where the ads are appearing.
While Sensei debuted only last year, it isn’t the first time Adobe has experimented with AI. In fact, it’s been using it under less branded contexts for more than a decade for things like targeting at a certain time, targeting to a certain audience, predicting impressions and allocating budgets.
“People used to be very wary of machine learning,” Kamath said. “It was a black box, and they didn’t know whether to trust it—and that’s changed now. It’s become more like table stakes. Everybody needs to have machine learning in order to compete effectively.”
He described machine learning from the perspective of “the three Vs of big data”: volume, variety and velocity. More data allows for more variety which allows for better real-time decision-making.
“At the end of the day, machine learning needs data,” Kamath said. “It learns from data, and I think having a sort of framework for managing your digital marketing stuff needs to happen before machine learning can play a role.”
Adobe wasn’t the only major tech company touting data and AI this week in Vegas. On Monday, IBM announced a partnership with Indian watchmaker Titan Company Limited, which is using IBM’s customer-engagement tools. And on Tuesday, IBM announced a new partnership with programmatic platform Rocket Fuel to embed Watson’s AI technology into Rocket Fuel’s systems to identify keywords and sentiments that might help predict how interested consumers are in certain ads.
According to Rocket Fuel CEO Randy Wootton, the partnership allows brands advertising with Rocket Fuel to “uncover value” in data that might not have been noticed by a human. He said Watson’s discovery service scans news stories every seven minutes to chose where a brand should advertise. The news is particularly well timed as another major player, Google, faces criticism for where its brands’ ads are appearing on YouTube.
“Marketers, at leading retailers for example, wants to sell more product, but they also care deeply about increasing their brand awareness and ensuring their brand safety,” Wootton told Adweek in an email. “They want to make sure their ads are shown only on sites and in a context that they think reinforces their brand.”
Another of attendee of the Adobe Summit, Wunderman global chief technology officer Stephan Pretorius, said there are new opportunities in marketing AI is advancing that many people don’t focus on. He noted, for example, natural language processing, the ability of a computer to understand language like a human. He said what companies like Google and Amazon are doing with devices like Home and Echo interest him even more than the platform-based AI being built into tools like Adobe and IBM.
Pretorius said people aren’t focusing enough on voice—What does a brand sound like? What should a brand sound like? If people can access devices like Amazon’s Echo Dot everywhere, how might that change more of the customer-facing interaction?
“For me, what’s really transformational is these new things,” he said. “Think about the evolution of interface. We went from punch cards to DOS prompts to touch screens to swipe screens. And then there is a chasm, and now you have voice. There is no interface. There is no typing. There is no visual interface. It’s pure sound.”
