So-called Data Management Platforms (DMPs) exist to provide an overview of the existing data silos and to be able to link them with each other (and thus to work on dissolving them). A DMP collects and processes data points of different origin into a uniform picture of all information on the behavior of each individual user.
The special feature of a data management platform is that not only user data can be collected, but also evaluated, so that it can be used for e-commerce measures. Due to the fast pace of many online marketing channels, this often happens within a few milliseconds.
Modern data management platforms record both first party data und third party data.
Collected first party data, for example, contains information such as:
- click-in channel
- number of products viewed
- purchased products
Third Party Daten hingegen reichern das Nutzerprofil mit z.B. folgenden Informationen an:
- age
- sex
- interests
How does a DMP technically work?
The different cookie IDs of the data points used are recorded and mapped so that an overall picture of all existing data is created at user level.
If everything is set up correctly, target groups can be formed in real time. These are then used to improve the customer approach.
For example, with the knowledge that a user is female and has viewed various products in the yoga category on the website for some time, specific yoga teasers for women can be placed on the starting pages when returning to the shop.
Via so-called DSPs (Demand Side Platforms), these target group profiles can also be used for advertising purposes, e.g. for personalised banner advertising.
In order to increase the reach of the target group-specific approach, there are also data management platforms that are able to determine statistical twins. Using an algorithm, users who are similar in behaviour to known users are identified and provided with appropriate measures.