What Behavior Are You Targeting?

LinkSmart“Data Driven Thinking” is written by members of the media community and containing fresh ideas on the digital revolution in media.

Today’s column is written by Pete Sheinbaum, CEO of LinkSmart, which provides text-linking optimization solutions for web publishers.

It happened to me a year or so ago, but it happens to millions of people every day. I was in the market for some new snow tires and did what most do. I asked ‘The Google.’

Without leaving my living room, I was greeted with several good-looking choices on the best snow tires for my vehicle and the climate I live in here in Boulder, Colorado. I clicked on the (second) search result and landed on a great review. But something was strange… the page I was reading tire reviews had been invaded with women’s luxury shopping ads.

Glancing up and to the right of the web page, there was a big, beautiful ad for…Gilt. Strange, I thought, but went back to reading the review. About half way down the page, I chose to click on a link to a more specific review on Continental tires that the author had written. I clicked, landed on that page, and that strange thing happened again — another big ad for Ideeli this time. Why was I getting ads for Gilt and Ideeli on a snow tire site?

Three reasons: Wife’s computer + AdSense + Cookies = Poor Targeting

Behavioral or psychographic/demographic targeting has been around for a long time now, but they are saddled with one fatal flaw: the one-person one-computer/device construct is no longer the norm. We have multiple computers, phones, tablets, etc. that we access every day and every single one is collecting data.

While those devices can create a decent profile of the primary user, we no longer use them in a singular way. Think about how you’ve interacted with technology devices today, we are moving from one device to the next more frequently than ever before.  Also in the case where there is one ‘common’ machine, you have ‘cookie confusion,’ a tangled web of disparate user sessions that generally perplexes the Skynets that are monitoring us. Moreover, if they do get it right about who is using the computer at any given time, they are serving up ads that could be relevant for what I was doing hours, days, even weeks ago. Stale is an understatement.

While the aforementioned may be only applicable to me, I’ve had it with this kind of targeting.  If a person is reading an article about choosing a golf club, show them golf ads. If you’re reading an article about how to make an apple pie, I think you should be shown food ads. But please don’t show me ads about designer shopping when I’m looking for snow tires.

What’s the fix? Targeting users based on intent. Readers and their clicking habits present web sites with a great deal of information that is not stored in the cookie. What page are they on? How did they get there? What links are they clicking on to navigate from page to page? This information can tell you a great deal about what a user’s intent is, and smart systems will pair relevant ads with this knowledge.

Additionally, advertisers need to acknowledge that users’ context and intent can switch many times during a single session. I start on food, then I switch to sports, then golf club reviews, and finally autos. It doesn’t necessarily matter where I was an hour ago, or a day. It doesn’t necessarily matter how old, young, rich, not rich, I am (all of which have been culled from thousands of user sessions across hundreds of sites, and the cookies that are being planted on me for re-targeting). Today systems should be more sophisticated, focusing on the here and now, not the there and then. Ad-serving technologies must leverage what signals readers are offering them in real time and embrace the idea of Real-Time intent.

While any degree of targeting may still be better than no targeting at all, ad buyers should beware of serving ads to husbands surfing their wives computers.

Follow Pete Sheinbaum (@sheinbaum), LinkSmart (@linksmart) and AdExchanger (@adexchanger) on Twitter.

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  1. Thanks Pete for your contribution.

    The cookie ‘dilemma’ has been well known in online measurement circles for more than a decade. The major measurement groups have been trying to model actual visitors by removing UB measurements which are corrupted by cookie blocking, cookie deletion, multiple people per machine and multiple machines per person. It’s an inescapable fact that cookie-based RTB methodology is as flawed as using a monthly UB figure to represent “unique audience”.

  2. Great post Pete, totally agree with the premise and conclusion. Begs the question of how an advertiser gathers such timely and granular intent data – it’s going to be very very hard without the involvement (and implicit blessing) of the individual.

    However, I’m not so sure that user overlap on the same device matters so much once you start looking at data generated in the last minute or hour.

    • Thanks for the response Marc, and great question. Most advertising campaigns begin with a target audience / group. They create a flight with a group and a desired outcome. Within that campaign, there are several tactics and sets of creative. If, for example, you wanted to sell more golf equipment (Titleist), you would target golfers. But since Titleist sells balls, clubs, etc. they might build different sets of creative. Each set of creative can be called into action utilizing the historical intent data of generic users on a site. For example, show a 300×250 Titleist golf ball ad every time a user clicks on ‘golf ball’,’[Brand] golf ball,’ ‘distance golf ball,’ etc. Since you know how often these words are clicked on within a site, you can predict how many advertising opportunities you have.


  3. Matt Anthony

    So the only good targeting is contextual targeting? There’s no value in broader user profile targeting? Then the whole industry’s march towards the latter and de-emphasis of the former must be misguided then … ?

    • Hi Matt, and thanks for the comment!

      As I mentioned, any targeting is better than no targeting at all. However, the user’s context can and does switch often even within a session on a site. It is just my opinion that the closer you can get to targeting the last known action of a user (or their current / most recent context / intent), the better.


  4. I’d argue that the problem of multiple users sharing the same computer is much LESS common today than it’s ever been. As tablets become the more prevalent form factor, they will become even more personal – much more like the relationship we have with a phone, which is rarely shared. This problem of user sharing is a tiny fraction of the impressions seen, and not statistically one that matters much.

  5. John McLane

    This may have been a clear-cut example of targeting gone wrong, where they thought they were displaying ads to your wife. And your point about device level behavior is right on. But if/when we ever get to a world of perfect targeting, those same ads might still be shown on that screen at that time – if Skynet figures out that, in your family, the wife is the one making tire-buying decisions, or that you’re a member of the group of men receptive to the same logic that merchandises beer and diapers together.