Online and offline become 1: a new era has begun (part 2)

June 30, 2010
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This is the second part of the post Online and offline become 1: a new era has begun. In this post, I discuss the second article by David M. Raab.

Bridging the Gap Between Online and Database Marketing

This is the second part of the post Online and offline become 1: a new era has begun. In this post, I discuss the second article by David M. Raab.

Bridging the Gap Between Online and Database Marketing

Raab starts his article with the following subtitle: “Centralizing information is valuable even when it cannot be tied to a specific individual“. This is true since data mining models can be built based on anonymous visitor profiles (i.e. non-identified visitors). Of course, much more information can be gathered when visitors are identified. This is the case for ISP (Internet Service Providers) or for any other website where the visitor can do a login. Once logged, we have a customer view of the user instead of the more simple visitor view.

Raab makes an excellent point: “If it were easy to integrate online with offline data, the database marketers would have been doing it all along“. So true. But difficult doesn’t mean impossible. There is a lot of ways to track a user on a website such as the IP address, a specific user ID if logged, a cookie ID, etc. Non identified persons can also be targeted. You can for example build a model on identified visitors and then apply it to anonymous visitors.

Raab continues by giving examples of information available in online channels, such as cookies, IP address, mobile phone location, etc. Another important message in his article is that “nearly all IP addresses can be mapped to a geographic location, which in turn can be linked to geodemographic databases such as Nielsen PRIZM clusters. Again, this information can be used to target messages to unidentified individuals“.

When the visitor is identified, one can use the CRM data from the company. When anonymous, one way is to use external database as mentioned above. Another way would be to build a model using identified visitors to infer socio-demographic and geo-demographic information of anonymous visitors. This is the way we have chosen our Customer Online Targeting tool.

Personally, I found these two articles very interesting. I think people really start to realize that online and offline data should not be treated separately. They are both useful to construct an Extended Customer Profile (ECP) of visitors. Feel free to share your opinion by leaving a comment.

You can read the whole article of David M. Raab here: Bridging the Gap Between Online and Database Marketing