Can a Machine Think for You?
Can a machine think for you?
I expect most of you are going to go with “No.” You might balk at the entire idea. But I had a conversation with Adobe's Chris Wareham, senior director of product management for Adobe Analytics, last week at Adobe Summit where it became clear that, if they’re working, isn't that exactly what you're counting on your marketing tools to do?
“The state of the industry with data is to point a lot of really, really smart postgraduates with math at the problem and hope for good answers," said Wareham. "And that’s not scaling."
The bottleneck is that not everyone can be a data scientist, not everyone can do that kind of thinking, or has the training to do it themselves. Not everyone works effectively that way.
However, marketing departments today can't afford to wait a week for the DBA on their IT teams to turn those reports out. That's where Adobe's virtual analyst comes in. According to Wareham, "the gap we’re filling in the industry is the need for people to be data-driven even in very simple interactions that they have.”
Wareham compares it to the revolution in we've seen in website analytics. Once (probably before many of you remember) finding out how much traffic was coming to your website involved getting daily or weekly reports from a guy called "The Webmaster." Pretty quickly tools emerged to automate those reports, then deliver the numbers in real time. Google Analytics provides all that information, and a lot more we never dreamed of, in real-time.
“They were very complex things that made a very complex job really simple," says Wareham. "So we’re starting to apply those same types of capabilities to a customer analytics problem set. Broadening the data set, leveraging the machine learning to automate a lot of those analytics processes, so a less sophisticated person can get a lot more leverage out of the data.”
And that's where the robots come in. (Well, "virtual assistant," but that's really just one servo-enabled titanium chassis from the same thing, right?)
“Our usage of machine learning, our usage of things like the automated analyst, is really about applying machine learning to fix a problem,” says Wareham. To actually replace a data scientist takes more than reporting stats or tracking goals. The virtual assistant needs to be able to recognize the trends, opportunities and personas that a data scientist would, and that means breaking the rules. ... Or at least the business rules many databases use to automate marketing
“Wherever we see rules, that smells like smoke to us," says Wareham. "We want to get rid of the rules, and make everything that is currently rules-based algorithmically based, so it can learn, and it helps our customers get leverage out of the data.”
Robots breaking rules? Asimov would not approve, but it might be exactly the thing marketers need.
Whether this sounds joyous or terrifying probably depends on if you're picturing Johnny Five or The Terminator.
Either way, it's an interesting time to be a marketer.