| Behavioral Vs ContextualTargeting |
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| Written by Sachin Devand | |
| Friday, 15 February 2008 | |
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Contextual vs Behavioral Targeting
Contextual and Behavioral are two very different types of targeting methodologies employed by ad servers and ad networks to deliver advertiser campaigns. Depending on who you ask about what they think is the best form of targeting you might get different answer. Why is contextual targeting better? People who support contextual targeting believe that the context of the page is a good indicator of what a user is interested in. Targeting based on this information is valuable and can provide lift in performance of advertiser campaign. The idea here is that if you show ads that are contextually relevant to the context of the page then the chances of a user clicking on them is higher compared to traditional methods. Companies and research firms have done tests to prove that this form of targeting indeed provides an improvement in campaign performance. Google’s adsense and adwords are example of such targeting and is supposed to be very successful. Why is behavioral targeting better? People who support behavioral targeting believe that context of a page is very momentary and does not provide accurate and enough information about the probability of a user to click on a given ad. They believe that one needs to ‘follow’ the user across the internet and ‘observe’ what they are looking at before you can tell what they might be interested in. Behavioral targeting claims that you can draw precise conclusions about the likely hood of a user clicking and converting on a given ad. They can make correlations between various user activities for a given period of time and the chance that a user is interested in a given advertised product. Which one is really better? This is a tough question and like I mentioned before, based on who you ask this question you might get a different answer. These are two very different forms of campaign targeting which seem to be quite successful. There are companies doing well in both these domains. There are so many different ways of targeting an advertiser campaign that isolating the impact of one particular criterion is very difficult. For example, how can you be sure that when you did a contextual or behavioral targeting for a campaign the fact that the user was a certain age, from a certain geographical location, using the system at a certain point of time etc did not have any role to play in them clicking on the ad. Some advanced ad servers can also perform yield optimization for advertiser campaigns. This means the ad server can make a judgment about an impression based on all the above parameters for a given user before it places an appropriate ad. In this case, all the above parameters go into a machine learning system which predicts the probability of a user clicking on a particular ad from a particular advertiser campaign. Even though it is hard to compare whether behavioral targeting is better than contextual targeting, one thing, in my opinion, that can be said about these forms of targeting is that they may perform better if they were used in conjunction with each other than them being used in isolation. For example, if the system could ‘remember’ the contexts of the pages a user has been on for duration of seven days and draw some kind of correlation based on this information, then it might be more precise because it is a blend of both contextual and behavioral targeting. The contextual data can go into the learning system which was earlier using just the simple data available like ZAG (zip code, age, geo), day part, frequency etc. Contextual data is in most cased richer in information that the traditional form of targeting data. Thus, a system learning on contextual data gathered for a user over a period of time will be able to do a better job of predicting a user behavior than one which is devoid of it.
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| Last Updated ( Thursday, 21 February 2008 ) |
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