Innogy is Germany’s leading energy company, with revenue of around €44 billion, more than 40,000 employees and activities in 16 countries across Europe. With its three business segments Grid & Infrastructure, Retail and Renewables, Innogy addresses the requirements of a modern, decarbonized, decentralized and digital energy world.
Innogy wanted to fulfill the role as connector between generating and consuming energy. This enables each customer to participate in the transformation of the energy industry. Moreover, they focus on green energy, sustainable solutions, such as solar panels in cooperation with service partners and the usage of smart devices in combination with data-driven services. They want to renew their approach by becoming more customer-focused.
Innogy’s contact center agents lacked a global overview on the client and house specifics, which lowered the quality of their commercial conversations. The next best offer was not generalized over different channels, which was confusing and frustrating for clients. Innogy also receives a large number of customer calls with questions on their invoices. Treating these calls is time and cost intensive, so the company was looking for a way to reduce the number of received calls and as such decrease the cost and load on their call center.
A main goal was to predict and pre-empt callers most likely to phone-in with appropriate information and offers. Data was stored in different systems, making it difficult for Innogy to get a clear view on an individual’s overall behavior. Innogy needed to act proactively, control the costs and plan the contact center load more effectively. It was difficult to know how new customers would react to their first invoices due to little history in data. Decisions were often made by ‘gut feeling’ rather than being data-driven.
