Behavioral Targeting in Online Advertising

April 18, 2009
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In my new job as a data mining consultant at FinScore, I’m currently working on behavioral targeting for online advertising. The client is a telecom company in Switzerland. The main idea behind the project is to show ads, on the company’s website, that are dependent on the profile of the visitor. In theory, online advertising is much more powerful than radio or TV advertising for example. This is mainly due to the lack of possible “targeting” in such medias.

This targeting is quite trendy these days since it is part of the foundation of the Web 3.0, which means a web based on personalization and recommendations. Google recently started to use behavioral targeting for AdSense. Here are more details about how Google targeting works.

Back to my project, the first part consists in aggregating ad impressions and clicks from web logs. This newly created data base will be mined to build a behavioral model for each distinct user. This model is applied to visitors who didn’t see ads in order to decide which ads to show them. The final objective is to increase the CTR (Click Through Rate) of visitors.

For the technical part, I use SAS tools. As I have already discussed on Tweeter, SAS to

In my new job as a data mining consultant at FinScore, I’m currently working on behavioral targeting for online advertising. The client is a telecom company in Switzerland. The main idea behind the project is to show ads, on the company’s website, that are dependent on the profile of the visitor. In theory, online advertising is much more powerful than radio or TV advertising for example. This is mainly due to the lack of possible “targeting” in such medias.

This targeting is quite trendy these days since it is part of the foundation of the Web 3.0, which means a web based on personalization and recommendations. Google recently started to use behavioral targeting for AdSense. Here are more details about how Google targeting works.

Back to my project, the first part consists in aggregating ad impressions and clicks from web logs. This newly created data base will be mined to build a behavioral model for each distinct user. This model is applied to visitors who didn’t see ads in order to decide which ads to show them. The final objective is to increase the CTR (Click Through Rate) of visitors.

For the technical part, I use SAS tools. As I have already discussed on Tweeter, SAS tools such as DI Studio, are not easy to use and their GUI are quite old. SAS Base language, although powerful, is not as straightforward as R for example. However, the SAS support is really good and their answer time is usually less than a day. For the web mining part, I have read the book Mining the Web: Transforming Customer Data into Customer Value (I will soon write a small book review about it). For the SAS part, I’m reading the excellent The Little SAS Book (I really recommend it to you, if you’re a SAS user).

I will write more posts about this project once I have interesting results. For more information about online advertising and behavioral targeting.

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