Regardless of the industry - the focus is always on the customer. The objective of every business is to win and retain customers and to ultimately increase their value. For many businesses, customer loyalty and winback are standard processes. Whereas other businesses may have focused on only one of the two processes, unaware potential of the other. However, even if both processes exist in one business, they are largely handled independently of one another.
A customer who has been convinced of a business's product or service becomes one of the most valuable assets of the business. The acquisition of new customers is generally more expensive than customer loyalty or loyalty programs. In addition, the probability of success is higher for retained customers, as well.
Businesses are often unaware of how the processes 'customer loyalty' and 'customer winback' complement or exclude each other and/or how these two very important measures interact.
Can a customer who has already been addressed in the course of customer loyalty measures and nevertheless decided to terminate, be won back at all by customer winback measures? Or are valuable resources and funds wasted in this case? And, on the other hand, if a customer can be won back by means of e.g. special offers, why haven't these offers been made to him during the retention process?
These questions were answered by TU Munich, in cooperation with b.telligent, within the scope of the research project PROSET. We have already reported on this project in a previous article (CI Insights: PROSET).
As in the first part of the project, the data of a telecommunication service provider, in particular the incoming calls in the contact center, are analyzed. For this purpose, special offers are made to certain customers who are identified as so called 'Customers at Risk'.
Firstly, the success factors of retention and winback are identified in the course of the project. Among others, the following aspects are examined:
Subsequently, the connection between retention and winback is analyzed.
As in every project, there also are some challenges to overcome in this context.
The analysis, for example, has to take into account the effect which cannot be illustrated by the data, such as e.g. the call center agents' skills or how long the call center agent has already been working for this business. Statistical models, such as e.g. the fixed effects model, are used for this purpose.
Here, a close coordination with the call center agents and managers is also required. The hypotheses and the resulting recommended actions must be developed in cooperation with the department. The objective is a holistic optimization of the interaction between retention and winback.
The project will continue until the end of July 2014. Then, the results will also be published in our Customer Intelligents Insights Blog.
Do you want to replace the IoT core with a multi-cloud solution and utilise the benefits of other IoT services from Azure or Amazon Web Services? Then get in touch with us and we will support you in the implementation with our expertise and the b.telligent partner network.
Domain Lead Customer Engagement & MarTech
Interactions with customers in the field of energy supply are rare – a single contact a year is not uncommon. Best possible contact management is correspondingly important. This project focuses on the communication channel comprising the inbound call center.
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