IT pilot fish works at an internet ad company, and his team is always hunting for better ways to match ads from the advertising buyers -- or "producers" -- with the users who will look at them.
"Based on keywords and some associated information, like where the user is generally located, our system would pick several ads that it thought a user would be interested in," says fish.
And at some point, fish's team finds the secret sauce: The system becomes really good at picking ads that interest each user. As a result, those users are buying more often. Advertisers are happier, and so is fish's team, which is finally beginning to provide a return on the investment in their project.
But then one of the larger producers starts to cut back the amount of money it spends placing ads each month. Wait, why?
Turns out that producer has done the math on its own ROI. The producer is getting paid to deliver ad responses. Since the more effective algorithm means more users are responding, the producer can meet its quota by buying fewer ads.
And as more and more producers decide to cut their spending, thanks to the great job fish's company does at finding users to respond to the ads, the result is predictable: Fish's employer is getting paid less for doing a better job than its competitors.
"The solution from our marketing and sales people was to modify the efficiency of the search algorithm differently for each customer," fish says. "After that, our system only delivered accurate-enough ads to satisfy that producer's budget for the month.
"The producers got what they wanted and were happy for the amount of money they spent. And if they wanted more -- and wanted to spend more -- we simply changed the parameters to be 'less bad' than they currently were."
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