Models Are People Too
Ever have one of those moments when it feels like time is slowing down? I had one yesterday when I asked a group of big advertisers what I thought was a simple question. It was followed by a long, awkward pause, a bit of stammering, and then some answers. They just didn’t happen to be answers to the question I asked.
The question was posed in response to a comment by John Walthour, director of consumer insights at consumer packaged goods giant General Mills, who said, “Models don’t make decisions, people do.”
The comment came midway through a panel in which Walthour and other big marketers discussed the how marketing mix models are contributing to their business results, and the consensus seemed to be that they while they are an important tool, they are just another resource for the marketing teams to consider in making their strategic and gut decisions. Given what we cover in RTM Daily -- you know, the increasing role automation and machine learning are playing in actual decision-making -- I followed up by pointing out, “Yes, but people make decisions to use models,” and asked if each of the panelists could give me a ballpark estimate for how much of their current decision-making was done by machines, and how much it would be three years from now. And that’s when time slowed down, and I had one of those, “Why do I ask these questions” moments.
What surprised me was not the flummoxed response. After all, these were marketing execs with the term “insights” in their title, so if a machine could do what they could do, well… What surprised me was the response of the people in the audience. First it was the people sitting at my table who I could hear tittering. Then at the break, they said, “Great question, terrible answers.” Then others at the the day-long forum said the same thing to me, and at least one cited it on stage during a breakout session.
Granted, most of them were not marketers, per se, but people who either supply media, data, technology or models to them, but it was like one of those the emperor has no clothes moments. The problem is, I didn’t ask the question to uncover that fact. I really wanted to know how automation and machine learning was impacting the decisions of big marketers, and where they thought it was heading.
After all, the whole point of ARF forum was to understand what role mix models are currently playing in influencing their marketing and media decisions, and to figure out how they need to evolve to deal with a “multi-screen” media world -- especially one where “Big” and granular data alike are streaming at them at megabits per nanosecond. You know, the volume and speed of information that machines are better at parsing than humans can.
Heck, isn’t that the reason the original mix models were created back in the early 90s. I sort of remember talking to Ed Dittus, founder of Media Marketing Assessment (MMA), who pioneered the field back then, when the data wasn’t so big or fast. HIs point then was that machines were better at processing all that data than people, and I’m guessing the need has only grown greater as the volume and complexity of data signals has grown exponentially in recent years.
In retrospect, I think I may have asked the wrong question. Maybe I shouldn’t have asked them how much they rely on machines to help them parse information to make their decisions -- now, or in three years time. Maybe I should have asked them how they plan to come up with actionable consumer insights from all that data without becoming more reliant on machines.
I would really like to know.
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