NewsBeat

December 2019 NewsBeat 5 formerly employed by the most powerful companies in Silicon Valley: Yahoo!, Google, Microsoft, eBay, Facebook, Netflix, Pandora and Amazon. They weren't always easy to get hold of. I'd send an email in late October, and perhaps they would have an hour in January, at some ungodly hour in Europe. And then there was the language barrier. These guys did not speak English, but fluent Economese. My Economese is not all bad, but two hours of Hausman tests, incremental bidding, and exogenous variation is too much, even for an enthusiast such as myself. Still, mixed in with the jargon, there were enough anecdotes to make your head spin. They would utter one line in plain English that I'd end up mulling over the rest of the day. The story that emerged from these conversations is about much more than just online advertising. It's about a market of a quarter of a trillion dollars governed by irrationality. It's about knowables, about how even the biggest data sets don't always provide insight. It's about organizations and why they are so hard to change. And it's about us, and how easy we are to manipulate. One thing was gradually becoming clear: these guys are messing with the magic. And nobody knows it. Or as Garrett Johnson, who used to work for Yahoo!, told me: "I don't have anybody pounding down my door telling me I'm messing with their magic, because … well, they don't even know who I am." ________ Steve Tadelis was the most accessible of the bunch. He instantly replied to my email: "I would be delighted to talk." Tadelis told me about his work for eBay, a broad grin lining his face. It all started with a surrealistic phone call to a data consultant. Tadelis was a professor of economics at the University of California, Berkeley when he went and spent a year at eBay in August 2011. During one of his first conversations with eBay's marketing team, they invited him to sit down with their consultants. The consultants could tell him how profitable each of eBay's ad campaigns had been. And since Tadelis was an economist, maybe he'd like to quiz them about their methods. "Proprietary transformation functions," one of the consultants had said on the phone when Tadelis reached out. They used proprietary transformation functions, had 25 years of experience, and a long list of prominent clients. When Tadelis pressed them he realized that "proprietary transformation functions" was only a clever disguise for your garden-variety statistics. You take the weekly expenditure on ads, combine it with the weekly sales, and voila! Fold the mixture into a scatter plot and see what happens. Easy as that! "This is garbage," Tadelis thought. Correlation, as any Statistics 101 class will inform you, is not causation. What do these impressive numbers mean if the people who see your ad are the exact same people who were going to use eBay anyway? eBay is no small fry. Surely lots of people looking for shoes end up on the online auction site all by themselves, whether they see an ad or not? Picture this. Luigi's Pizzeria hires three teenagers to hand out coupons to passersby. After a few weeks of flyering, one of the three turns out to be a marketing genius. Customers keep showing up with coupons distributed by this particular kid. The other two can't make any sense of it: how does he do it? When they ask him, he explains: "I stand in the waiting area of the pizzeria."

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