Increasing Subscription Rates Through Deeper Customer Understanding
A British Newspaper were keen to know more about readers, what motivates them, and how together we deepen their engagement combining data and science.
The British Newspaper has 28 data tables of data schema covering 25 million individuals, 250 million interactions and 267 million email actions. How could they use this data to increase their subscription rates and find more insights from the data.
Our client found it tough to find value and insight in their data which came from different legacy systems. They wanted a deeper understanding of their highest potential prospect groups to take up subscriptions and what kind of content these subscribers are interested in. They needed to understand subscribers from many different angles but lacked a framework to do so.
Outra cleaned and analysed data which included 267 million email actions to review their approach to data before applying science to build a multi-layer custom segmentation of their customers, in order to help drive up subscriptions rates through a deeper customer understanding.
The solution was a multi-step process that began with developing a new Engagement Index. We drew in key engagement data into the analysis which then enabled us to create a benchmark. Pen Portraits were provided against each of the bands that indicated vital behaviours per engagement group.
From this baseline we will build a content segmentation from the new data available. Building content categories and themes that are important to different groups which will assist in the development of content in the future as well as recommending other related content. Outra developed a complete custom customer segmentation to act as a framework for targeting and content development.
The next phase in this project builds in deep learning to help develop acquisition and churn models based on the learning of the custom segmentations.
They now understand who is likely to subscribe and for which subscription offer. Combined with the content data we are now able to recognise micro-triggers in behaviour which may be indicative of larger actions both positive and negative. Ie: increase in shopper or an unsubscribe.