predicting behaviour

Predicting customer behaviour in the Prisa Group

Today, digital media are moving to a subscription and pay-for-content model that allows them to maintain recurring revenues. To do this, it is essential to have user profiling of their websites to predict customer behaviour.

The Data area of Prisa Noticias decided to launch in the middle of the year a project created by Google to finance strategic projects for the media. This project is part of the 'Partner Program'. The objective is the profiling of users and the application of predictive models (subscription, abandonment, etc.) to predict customer behaviour.

Bosonit was the specialised company in charge of the user profiling part of the project.

Parts of the project

Firstly, the main purpose of the project was to define the objectives and improvements of the system to be implemented, taking into account the client's needs (what data they wanted to collect from navigation).

Secondly, the focus has been on the design and subsequent deployment of the architecture components within the Google Cloud Platform. The components had to enable the collection, processing and storage of navigation events in real time.

These are produced by its users, both on the El País website and on its mobile app.


The purpose of this process has been to create a real-time customer file that serves as a starting point for the development of predictive modellingusing tools from machine learning included in the ecosystem itself. In other words, it will make it possible to identify which content the user has visited, with the aim of associating each one with the advertising campaign that best suits their preferences. This will increase the likelihood that the advertising content will actually be consumed by the user.

In addition, a series of KPIs have been created to create dashboards using Business Intelligence.



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