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Amidst all the concern about Google Desktop and Gmail compromising user privacy, it seems that folks have forgotten that Google’s competitors – in particular Yahoo, MSN, and Amazon – have far greater depth of user data, both in breadth and time period.
If you are a registered Yahoo user, you’ll start to notice that advertisements are eerily similar to Web sites you are visiting off Yahoo. For example, I recently bought VoIP service from SunRocket. As I struggled through trying to get the product to work, I visited the SunRocket Web site numerous times for installation instructions. These days, when I login to Yahoo Mail, guess what? Lots and lots of SunRocket banner ads.
And Amazon’s users are no doubt familiar with the “customers like you also bought” recommendations that permeate the site. MSN has fused behavioral targeting into the new MSN Ad Center by enabling advertisers to chose demographics to target to.
Generally speaking, there are three ways that these companies are getting this information: 1) When you register for Yahoo and MSN, you are asked for demographic information. 2) Cookies on your computer; 3) Collaborative filtering (matching your user behavior to that of other users and concluding that if both you and another user liked Book A, each of you will also like other books that the other has purchased).
Privacy concerns aside, this is a potential goldmine for search engine marketers. Right now, we are all “keyword focused.” We limit ourselves to keywords that are directly (or at least highly tangentially) related to the product we are selling. For example, if you are selling bottled water, you would no doubt purchase keywords like “bottled water” and “water home delivery”, you might purchase “soda alternative” and “healthy living”, and you would doubtfully purchase “iowa basketball” or “new light fixtures.”
But what if you knew that an MSN registered user had been surfing bottled water sites all day long? Even if that user typed in “Dr. Seuss” as his search query, you would probably nonetheless pay a premium to get your bottled water ad showing up on this user’s search results.
Again, if you put aside privacy fears for a moment, this is actually a win-win-win scenario for the advertiser, the search engine, and the consumer. From the consumer perspective, the ads that are shown are of the highest relevance. Creating an algorithm to serve ads based on actual user behavior, the behavior of similar consumers, and the actual search query entered into the search engine is far more powerful than simply relying on the keyword itself.
For the publisher, this sort of targeting is a way to increase CPC prices across the board. The CPC keyword market is highly inefficient, precisely because advertisers are left to guess which keywords are relevant to their target consumer. And whenever guessing is involved, it inevitably results in many advertisers missing the right keywords (hence the obsession with “the long tail of search”). By combining keyword buying with demographic and psychographic targeting, the search engines essentially can create an uber-advanced search matching system that guides advertisers to the right consumers, irregardless of that advertiser’s keyword generation competency.
Finally, for the advertiser, targeting eliminates the aforementioned guesswork of matching keywords to the right users. At the end of the day, savvy advertisers are concerned not with CPC cost but rather EPC (earnings per click). I would much rather pay $10 a click for a consumer who I know will buy $25 of product from me than $.25 a click for a consumer who will only by $.20 worth of goods.
At this point, you may be thinking “isn’t this already being done?” Well, yes, it’s true that there are behavioral targeting companies out there – Revenue Science, Tacoda, and Kanoodle seem to be the ones I hear about most frequently. It’s also true that MSN Ad Center offers limited behavioral targeting, though this is a far cry from the collaborative filtering of Amazon or the targeting of Yahoo CPM banners. So it’s true that behavioral targeting exists, it just doesn’t really exist for the majority of search spending – namely on Yahoo and Google.
And this is an area where Yahoo, MSN, and Amazon have a huge advantage over Google. Google simply doesn’t have this level of user data. They lack the registration data because they don’t ask for demographic/psychographic information when you sign up for their services; they lack the collaborative filtering because they don’t sell millions of products like Amazon; and they lack the cooking because privacy advocates would go crazy if they attempted to cookie all users.
In John Battelle’s book, The Search, he describes search as “the database of intentions.” In other words, Google and Yahoo have tons of user-created data (i.e., search queries) that indicate user intent. I would argue that search is but one ‘database of intention.’ Shopping sites like Amazon and Shopping.com have databases, portals like Yahoo have another, and search engines like Google have yet another.
As Yahoo, Google, MSN and Amazon struggle for paid search dominance (or, I guess according to Yahoo’s CFO, second place to Google), it amazes me that this hasn’t become core to any of Google’s competitors’ offerings. In Al Ries and Jack Trout’s great book, The 22 Immutable Laws of Marketing, they write that if you can’t be number one in a category, create a category that you can be number one in.
Google is the biggest search engine, that’s beyond dispute. And I doubt any of Google’s competitors will unleash a better search algorithm than Page Rank anytime soon. Amazon, MSN, and Yahoo, however, all have the ‘database of intentions’ to be the number one behavioral targeting marketing company. And because these are proprietary databases, no Google search algorithm can penetrate this data. In other words, it’s a defensible advantage, powerful, and unique.
Hmm. Maybe it’s time Google wannabes stop trying to build the best algorithm and start leveraging what they’ve already got!