Unveiling the online journey with Rax

Posted on Posted in Customer Journey

Introduction

It is generally believed that there is a lot of valuable information hidden in people’s online-behavior data. By uncovering patterns in this behaviour, we could possibly achieve better segmentation and ad targeting, better website personalization, etc. However, looking for patterns in the (online) behavioral data is not easy. It requires being able to handle the temporal aspect of the behavioral data and most existing tools lack expression power in this area. Also, including the temporal dimension of people’s behavior in the analysis makes each person unique which makes it hard to come up with a predictive model.

We are setting up a research project whose goal is gaining better insights and better decision making based on online journeys. We are doing this research in cooperation with Pointlogic – a company with over 20 years experience in analysing data, especially for the media and advertising world. We are hoping that by combining our tools (like Rax) and expertise in handling temporal data with Pointlogic’s mathematical expertise and knowledge of the advertising world, we can discover new, valuable patterns in the data which will eventually lead to more efficient metrics to be used in predictive modeling of people’s online behavior.

Over on the Rax blog, we asked for 5 partners with data, that we would analyze for free, these slots were quickly taken. Please do not apply any more. Thank you.