Reduce Your Churn With Augura

Customer acquisition costs up to 20 times more than customer retention, so increasing retention has become one of the priorities for every Marketing Manager Anticipate customers likely to churn, reduce your churn rate, your retention cost and your efforts to retain the right customers acting with this TM Forum based end to end scenario

Churn prediction models try to understand the behaviours and attributes which affect customer churn. This model’s accuracy is obviously critical. If the Marketing Manager is unaware of the clients’ high risk of leaving, he will not act in time. Should the Marketing Manager act on satisfied clients, arpu will be reduced without real cause.

To enable the model to increase its accuracy, it must have relevant data that may affect churn. Augura is able to obtain this data from different sources throughout the organization and prepare them to be incorporated into the analytical model.

Augura’s team of data scientists looks for the algorithms to find the model that best fits the operator’s actual cases. From here they obtain several results which are combined so as to reach the churn reduction scenario:

· predicting each customer value: Value based segmentation is often associated with customer billing. However, the calculation of customer value can be extended by using other data from the operator. Augura is able to recover and add a variety of data sources ( use of services, associated costs, demographic data…), calculate customer value with all these data, and take the results to the operator systems and processes.

· predicting each customer QoE: Augura gives the operator the solution to obtain the QoE perceived by the end user. To obtain these value multitude of data and indicators are collected from several systems (operation, network, billing, CRM, ….) and from agents installed in the customer´s end devices. Augura calculates MOS index, the measurement of actual user experience, applying analytical techniques to detect patterns, revising and improving the characterization of MOS

· predicting each customer churn score: Augura processes data from many different areas of the company to identify behavior that is indicative of churn. For example demographic information, historic of products, usage of services, call-drops, complaints, care issues, or overage…
Augura produces a comprehensive report of customer churn risk either on a scheduled basis or on demand. This report constitutes the customer’s unique identifier and associated churn risk score. The churn/retention manager can tune the output of this report by specifying a threshold churn risk score, such that only high risk customers above this score are returned in the report.

· predicting each customer churn motivations: This use case provides the most likely cause(s) for which the risk scoring for churn is high for each customer. Once the retention manager has the information personalized offers can be made, reducing the retention cost. Moreover it permits the identification of churn cases which have no solution therefore avoiding unnecessary cost on unretainable customers. Finally it also allows to identify pain points in different areas of the company to establish improvement plans.

· predicting each customer best retention offer: Targeting customers with loyalty/retention offers which aren’t adapted to their needs is a wasted customer retention opportunity. Once the customers with risk of churn, and the reasons for the risk, have been identified Augura can predict the offer with the highest acceptance probability. Augura can identify successful retention offers applied to different customers, and the analytic model is able to predict the best retention offer for each customer based on risk and reason for churn and other customer data.

All steps are continually revised to accommodate the constant changes in the customer portfolio (new variables are taken into account, new analytical models which adapt more efficiently to the results…)

Beyond The Prediction: Act!

These predictions are only the first step in reducing the churn, which is the final objective. Augura’s team ( powered by Optare solutions) based on vast experience in systems integration for telecommunication operators worldwide, can incorporate these insights into the processes and systems needed across the organization, automating all the task. (NBA, Marketing Automation…)

Reduce Churn With Augura Churn Reduction Use Case

Augura’s churn reduction solution goes beyond churn predictions to automate the best possible actions with the right customers. Contact us for details on how we can help reduce churn.