Within energy marketing in particular, this will be key to winning over more clients, maximising margins and building loyalty amongst existing clients. To this end, advanced analytics solutions and models will be applied, allowing us to predict customer churn so that the business can anticipate it with a range of mechanisms, such as pricing or marketing strategies; predict the optimal price to be applied to clients when renewing products or services in order to maximise my margin; or segment my current clients to increase the knowledge I have about them. In the connected mobility business, we may be talking about making fleet maintenance more efficient through the different solutions we have, analysing data collected from fleet activity to determine hotspots, anomalous behaviour, or the behavioural habits of fleet consumers. Thanks to this, it will be possible to better understand how the fleet is used in order to apply business activities to meet the identified needs.
Churn prediction, optimal price prediction on product and service renewals, and customer intelligence