Wireless markets worldwide are maturing rapidly and there are few underserved markets left to tap for new customers. Therefore, Orange, one of the world’s largest operators of mobile and Internet services, was looking for ways to increase customer retention while encouraging subscribers to buy more services.
Before the data lake: The customer could only perform standard network-level analytics and wanted to go deeper to analyze millions of source and destination IP addresses to gain visibility into subscriber data usage at the individual level. Understanding subscriber usage can help wireless providers capture more revenue through offers of tiered pricing or specific packages for social media, video streaming or map applications.
With the data lake: Orange was able to capture, ingest and apply metadata to terabytes of call details records (CDRs) created by the wireless network. Zaloni then correlated network data (IPFIX/Internet Protocol Flow Information Export, DPI/deep packet inspection, bulk stats) with CDRs to create meaningful, actionable subscriber insights.
Results: Orange was able to capture and analyze user-level data, graphically visualize subscriber usage as it occurred, and modify pricing plans and data packages tailored to its subscriber base. In addition, the customer leveraged machine-learning to identify its most profitable customer segments.