Facebook’s recent disappointing IPO has triggered a torrent of quasi-biblical prophets of doom. Michael Wolff has scribbled the most apocalyptic message on Belshazzar’s Facebook wall. Mene, Mene, Tekel u-Pharsin, Zuckerberg?
The daily and stubborn reality for everybody building businesses on the strength of Web advertising is that the value of digital ads decreases every quarter, a consequence of their simultaneous ineffectiveness and efficiency. The nature of people’s behavior on the Web and of how they interact with advertising, as well as the character of those ads themselves and their inability to command real attention, has meant a marked decline in advertising’s impact. At the same time, network technology allows advertisers to more precisely locate and assemble audiences outside of branded channels. Instead of having to go to CNN for your audience, a generic CNN-like audience can be assembled outside CNN’s walls and without the CNN-brand markup. This has resulted in the now famous and cruelly accurate formulation that $10 of offline advertising becomes $1 online.
As a casual user of Facebook, I am sympathetic to Wolff’s argument. I mainly use Facebook to periodically scan other people’s content, upload the odd Instagram of my friends at local DC bars, and reblog the Cheezburger Network‘s extensive database of cat pictures. Notice that this sentence does not include any reference to ads. I see them but pay them no mind. Wolff’s argument is counterintutive to many who have ingested the past ten years of arguments about the power of networks and the decline of traditional media advertising. But if true, they would mean not only the end of Facebook but also a corresponding destruction of much of the day-to-day social media infrastructure that we take for granted today.
Wolff contrasts Facebook with Google, which is ruthlessly cognizant that is primarily an ad company rather than a social space. Google, in Wolff’s retelling, has created value by controlling the space from which a buyer searches and a seller hawks and sells ad space very cheaply. In other words, Google is a “facilitator.”
Orgtheory.net, however, has a different take:
Facebook’s strategy is a little more opaque to me. Right now, it’s going gangbusters on ad dollars. Is that the main strategy? Envelope calculation: $100bn in market cap/a claimed 800m active users = $125. Does that sound right? Does that average user generate at least $125 of income for Facebook’s advertisers as a whole? I suspect Facebook’s strategy is mixed. It’s obviously ads because young people (=discretionary income) love Facebook. But I suspect that Facebook is gearing up to be a major platform, an all purpose social space where people can do things. That leads us into the world of apps and income sharing from apps. Developer Steve Yegge made this distinction in a much hailed rant on Google+. Yegge pointed out that Amazon had built an amazing library of APIs that allowed third parties to collaborate with Amazon and mine its databases. I suspect Facebook is committed to this direction. Ads create enough revenue, but the goal is to create an appapalooza on par with Apple’s App Store. It’ll be interesting to see if that’s worth $125 a user.
This analysis supports something that Matt Devost wrote here at CTOVision when the media was focused more on the duel between Facebook and Twitter. Devost argued that Facebook was trying to devour its competitors by copying their best features and merging them with the existing social chatter Facebook housed. Facebook’s simultaneous purchasing of Instagram and then developing of Facebook camera suggests the same. Certainly this makes sense when placed within the context of an advertising-based business model. The dominant question though, is whether an ad-based model is still valid if the trends Wolff has cataloged continue.
What might be next? Derek Thompson has also recently written on the idea of Facebook as a potential big-data platform that mines its users’ status updates for product information. Facebook as a big data platform that sells information to companies might work, particularly if the big data tools it utilizes are robust enough to process the sum of the complex inputs that users pour into it. It would also match the “facilitator” model Wolff has ascribed to Google’s strategy.
This post by AdamElkus was first published at CTOvision.com.
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