Jio aims at increasing revenue growth by providing a superior customer experience to its over 340M subscriber base
Jio sees providing the right experience to customers as being critical to reaching its target subscriber base of 400 million subscribers by 2020. To deliver a superior quality of experience and support this massive subscriber and network growth, they need to gain deep insights into the health of the network and services consumed by customers, as well as optimized network infrastructure and supporting operations.
In order to achieve these objectives, Jio set up a big data and analytics strategy and partnered with Guavus to execute it. They deployed our AI-enabled analytics solutions to measure real-time customer experience and predictive analytics to automate troubleshooting of the network and generate subscriber insights for use in marketing. In addition, they are taking advantage of our analytics platform and expertise to develop custom analytics applications quickly on their own for their key business group stakeholders.
“Our networks generate 4 to 5 petabytes of data each day. If this data can be properly analyzed in real-time using big data analytics and predictive analytics techniques, we can both improve the health of our network through intelligent automation and offer multiple, customized personal services to our customers. Guavus’ solutions enable us to do this – we can make data-driven decisions that allow us to deliver a great experience to our customers while bringing intelligent automation to our operations,”
Anish Shah, President of IT, Reliance Jio
Since the beginning of the partnership with Guavus, Jio has been able to demonstrate the following results:
Address the call muting problems on VoLTE, actively identifying call muting issues and potential call drop behavior in real-time, enabling resolution of network issues at up to 5 times faster. This new capability has also enabled Jio to reduce the likelihood of poor quality of experience (QoE) for VoLTE subscribers by 50%.
Attribute a QoE score to an individual subscriber, allowing them to identify factors such as mobile subscriber devices that have a higher propensity to mute calls. Such insights helped Jio’s customer care organization to accurately identify problematic devices as the root cause of the call muting issues 100% of the time.
Identify the exact population of subscribers experiencing call muting issues, which improved the mean time to repair (MTTR) by 50%.
Thanks to the Guavus Reflex analytics platform, they can identify missing data feeds that were critical to their analytics needs. This discovery capability helped Jio improve the completeness and accuracy of data analysis and their data ingestion architecture for their big data lake.
Utilizing the Guavus solution, Jio’s data engineering and data science teams are now able to create new analytics use cases and accelerate the delivery of analytics-powered applications to the business.