The plan is to build a global digital ad network that uses offshore labor to create thousands of versions of ads. Then, using data about consumers and computer algorithms, the network will decide which advertising message to show at which moment to every person who turns on a computer, cellphone or — eventually — a television.
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Greater production capacity is needed, Mr. Kenny says, to make enough clips to be able to move away from mass advertising to personalized ads. He estimates that in the United States, some companies are already running about 4,000 versions of an ad for a single brand, whereas 10 years ago they might have run three to five versions.
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Digitas uses data from companies like Google and Yahoo and customer data from each advertiser to develop proprietary models about which ads should be shown the first time someone sees an ad, the second time, after a purchase is made, and so on. The ads vary, depending on a customer’s age, location and past exposure to the ads.
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Mr. Kenny said that Digitas constantly struggles to find enough employees with the technical expertise to use complex data to slice and dice ads for companies like General Motors and Procter & Gamble. As Digitas invests in countries like China and India, he said, the Publicis Groupe will benefit from the global talent pool — and perhaps create more demand for advertising in those countries.
Two very different conceptions of labor are at work in these short descriptions of the Digitas strategy. On one hand, vast legions of low-wage but talented communications workers from across the globe are necessary to generate thousands of different advertising permutations for each campaign and code them with the metadata required for smart computer algorithms to invoke them effectively. These workers would seem to fall somewhere between the "clerical" and the "creative" in the pecking order of advertising agencies. But in either case, the commodities that they produce -- bite-sized, hyper-targeted advertising messages -- are imbued with a huge investment of information labor.
On the other hand sit the targets of these advertisements, the presumably affluent and information-saturated consumers who view these ads not only on old-style mass-marketed and relatively impersonal television screens, magazine pages, and billboards, but on the hyper-customized margins of the web pages they visit throughout the day on their laptop computers, cell phones, and portable gaming devices. What we might think of as their attentional labor time -- the work that these coveted consumers do in the moment that their eyes and brains flit to the advertising message that pops up on their digital screen -- is so valuable as to be analyzed and specified by complicated computer algorithms working on both the back end and the front end of their web interaction, algorithms which use as their raw material both the real and assumed demographic information about these coveted consumers and the matching advertising metadata so carefully produced and entered by those low-paid marketing information laborers around the globe.
What results for me is a vision of immense disparity in global communicative labor: the communication skills of so many being used to transmit messages of such unimaginable granularity into the communicative lives of so few -- all for the purposes of profit maximization. It's an uneven pattern that we can probably see in other realms of message-making as well, from political speech to non-profit fundraising to, yes, academic knowledge production. I wonder if there's value in analyzing such disparities in the labor and value of communication patterns more closely.
