It is customary to divide online advertising into two categories: direct response and brand advertising. I prefer instead to divide it according to the mindset of users: whether or not they are actively looking to purchase something (i.e. they have purchasing intent).*
When users are actively looking to purchase something, they typically go to search engines or e-commerce sites. Through advertising or direct sales, these sites harvest intent. Google and Amazon are the biggest financial beneficiaries of intent harvesting.
When the user is not actively looking to buy something, the goal of an online ad is to generate intent. The intent generation market is still fairly fragmented and will grow rapidly over the next few years as brand advertising increasingly moves online. P&G – which alone spends almost $4B/year on brand advertising – needs to convince the next generation of consumers that Crest is better than Colgate. This is why Google paid such a premium for Doubleclick, Yahoo for Right Media, and Microsoft for aQuantive (MS’s biggest acquisition ever).
In 2003, Google introduced AdSense, a program to syndicate their intent harvesting text ads beyond Google’s main property Google.com. The playbook they followed was: use their popular website to build a critical mass of advertisers; then use that critical mass to run an off-property network that offers the highest payouts to publishers. AdSense became so dominant that competitors like Yahoo quit the syndicated ad business altogether. Today, Google has such a powerful position that they don’t disclose percentage revenue splits to publishers and extract the vast majority of the profits.
It is widely believed that Facebook will soon follow the AdSense playbook by introducing an off-property ad network. They’ll try to use their strong base of advertisers to dominate intent generating ads the way AdSense dominated intent harvesting ads.
But to win the intent generation ad battle, data is as important as a critical mass of advertisers. For intent harvesting, users simply type what they are looking for into a search box. For intent generating ads, you need to use data to make inferences about what might influence the user.
This is what the introduction of the Facebook Like button is all about. Intent generating ads – which mostly means displays ads – have notoriously low click through rates (well below 1%). Attempts to improve these numbers through demographics have basically failed. Many startups are having success using social data to target ads today. But the holy grail for targeting intent generating ads is taste data – which basically means what the user likes. Knowing, for example, that a user liked Avatar is an incredibly useful datapoint for targeting an Avatar 2 ad.
Publishers who adopt Facebook’s Like feature may get more traffic and perhaps a better user experience as a result. But they should hope the intent generation ad market doesn’t end up like the intent harvesting ad market – with one dominant player commanding the lion’s share of the profits.
* Most text ads are about intent harvesting and most display ads are about intent generation, but they are not coreferential distinctions. For example, with techniques like “search retargeting” (you do a google search for washing machines and the later on another site see a display ad for washing machines), sometimes intent harvesting is delivered through display ads
Chris Dixon is Cofounder of Hunch. He’s also a personal investor in early-stage technology companies, including Skype, TrialPay, Gerson Lehrman Group, ScanScout, OMGPOP, BillShrink, Oddcast, Panjiva, Knewton, and a handful of other startups that are still in stealth mode. He is a member of Founder Collective.
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