Dynamic Clustering, a new ad targeting methodology

This article is a summary of my proposed methodology to targeting web users with relevant ads, but without intrusion, e.g. without third-party cookies. The original version, including a broader depiction of the context, is a longer post in French : “Le régime sans cookies, le nouvel âge du ciblage sur internet

Basically, as related in many articles, including previous posts on this blog (see for instance “Giving up cookies for a new internet… The third age of targeting is at your door“), the usage of third-party cookies is bond to dwindle, if not to disappear. Some solutions have already been submitted, such as fingerprinting (still intrusive though) or unique identifiers (but too much linked to the major existing internet companies).

So, we need a non-intrusive contextual targeting solution, which takes privacy protection into account. This is the core idea of my proposed solution, e.g. “dynamic clustering“.

Ciblage_Données

How does it work?

  1. Based on ISP and/or Operator log files, browsing data will be collected and anonymized (for instance through a double-anonymization filter) so as to protect one’s user privacy; Anonymous
  2. Files will be cleaned (“noise-reduction” processes), and organized at various categorization levels, so as to generate multiple dimensions, all of them rich and flexible. This will allow to create “outlined profiles” for each unique anonymous user; Categorization
  3. Using these dimensions, clusters will be generated, made of users with similar usage behaviors, based on each advertiser’s hypothesis, creating hence an infinite number of target groups, whose volatility is an asset, as it will always cover the client issue of the given moment.

ClusterSo yes, the no-cookie diet is possible… And it goes along with a more virtuous targeting of the internet users…

Convinced by this new diet? Willing to collaborate to the recipe development? Let’s meet!

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