This is the subhead for the blog post

John Battelle described search engines as the “databases of intentions” – when a user enters a query into a search engine, that user is telling the search engine something about his wants and needs. Indeed, the entire point of a search engine algorithm is to decipher this user intent and serve up the most relevant results (and, of course, to stymie search engine optimizers at the same time).

You would think that a database of intentions would be the ultimate targeting opportunity for marketers, and – until recently – I would argue that this was indeed the case. The problem, however, with this database, is that it is an inferred database. Sure, we can infer that a user typing in “male pattern baldness” is a man who is balding, and in most cases we’ll probably be right. But what of the person who types in “mortgage” – is he (or she) looking to get mortgage quotes, learn about the current housing crisis, do academic research, get a job in the mortgage industry, pay their existing mortgage, or something else entirely? And then there are words like “laker” which could be about the Los Angeles Lakers, Lake Trout, or someone with the last name “Laker.”

As search marketers, we end up doing a lot of inferring. Often the difference between a successful and unsuccessful campaign rests on our ability to correct determine which keywords have the right inference for our campaigns. Since every search marketer is playing the same game, the result is that keywords with clear inference tend to receive much more advertising competition than keywords without. This is the difference between buying the keyword “Miley Cyrus” and “Buy Miley Cyrus CD.”

Wouldn’t it be great if users could tell us more about themselves? Their interests, their demographics, their personal history? To some degree, this information is available through behavioral targeting, or from user registration information on portals like Yahoo. But the behavioral targeting to date has only been broadly applied – you can choose a particular age range (18-35), or a particular geography, or sex, but none of this really presents an opportunity for personalized marketing.

Advertising on social media can, and likely will, provide the first opportunity for truly one-to-one marketing. The beauty of social media (at least right now) is that users have an incentive to provide lots of honest information about themselves. Think about your profile on FaceBook. You add your educational background, your interests, or relationship status, your current employer, and so on. You do this because you want to connect with old friends or meet new people like you. Indeed, the fact that your friends will see your profile is a further incentive to be honest since any wanton lies would be seen by people who know that you are lying.

This is much more valuable information than the behavioral targeting that can be gleaned from a user profile on Yahoo or from user-entered registration data on non-social networks. It’s commonly accepted that users who are forced to fill in personal data purposely lie about their demographics. As one columnist put it: “Users lie to protect their privacy, they lie to protect their identity, they lie because they think their data will be misused or shared with third parties, or they lie because opt-in/out policies are misleading or mistrusted.”

But at least for now, most social media users don’t lie. The result is a goldmine of not just inferences of user intent, but user-defined extensive descriptions of their intent. And this presents the first opportunity for marketers to truly create micro-behaviorally targeted campaigns.

Here’s an example of the micro-targeting currently available on FaceBook. Let’s say I want to sell Iowa Hawkeye football tickets to football fans in Iowa. And for whatever reason, let’s say that I want to upsell these users on a dating site. Check out the targeting FaceBook offers for this unique and granular user set:
80 people are in my target group – now that’s a narrowly tailored audience. Granted, this targeting excludes people on FaceBook who have not fully filled out their profiles, but you can only assume that over time the percentage of people who complete their profiles will only increase.

Much of this targeting can be done on Google – you can buy the exact match “Iowa Hawkeye Football Tickets” and geo-target your ad to Iowa only. But the ability to serve this ad only to Iowa graduates who are men, etc, etc is not – and likely will not – be available in Google for some time to come. Indeed, I recently pointed out just how bad the demographic data currently available in AdWords really is in a recent post.

Of course, the flip side to this entire argument is that we are currently at a point in the development of social media where users still trust the social media networks and advertisers haven’t truly embraced advertising on this medium. As a result, users are still honest about their personal data. At some point – perhaps soon – the scales may start to tip; once users realize that their personal information is being used by advertisers, their honesty may diminish or – as has already happened several times on FaceBook – they may revolt against the use of their personal data.

I believe, however, that despite some very public missteps in the user of personal data, the social media companies still have the chance to use this data in a way that satisfies privacy advocates but also provides the most targeted advertising available anywhere online. Who needs a database of inferred intentions anyway?