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A U.S.-based utility that serves approximately 1.1 million electric and 790,000 natural gas users needed to upgrade its legacy systems. The company wanted to provide its customers with better energy options and engage them more effectively by catering to their needs and offering them personalized experiences. The utility also wanted to develop a system where data drives optimal business decisions. Along with the use of smart devices, the company realized that analytics plays a major role in gaining deeper customer insights from data. The utility partnered with Cognizant’s utilities digital experts, seeking help in leveraging analytics to improve its data management capabilities and eventually reduce customer defections due to unprecedented competition.
We applied analytics to predict and handle the utility’s increasing call volume—estimated at 4 million calls annually—as well as inform customers of impending outages and their resolution by text or email. We proposed a two-track approach, first creating an intelligence platform for the existing IT landscape and then using a business track to create a use case inventory and a prioritization framework. We also implemented the SAP Master Data Governance module for master data management. Solutions were designed to provide customers self-service capabilities, such as bill explanations and payments, financial assistance requests, service interruption updates and service event planning, across multiple channels, including online, mobile and customer care centers, and to help customer service agents make better real-time decisions.
Our analytics implementation gave the utility the ability to view data as a corporate asset and support data-driven decision-making. Insights from the analytics program were expected to yield a 7 percent reduction in the amount of time customer care agents spend on the phone with customers and a 13.6 percent decline in customer calls to call centers. The company also estimated a net savings of $1 million annually due to a drop in the number of service calls.
expected drop in talk time, driving cost savings
expected reduction in customer calls
projected savings annually due to fewer service calls
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