Download PDF
A Leading Wireless & Telecom Services Provider Reduced Annual Call Center Cost by $5 Million
Technology Category
- Analytics & Modeling - Real Time Analytics
Applicable Industries
- Telecommunications
Applicable Functions
- Business Operation
Use Cases
- Real-Time Location System (RTLS)
Services
- Data Science Services
The Challenge
A leading U.S.-based wireless and telecommunications service provider wanted to improve call center performance, increase customer satisfaction, and have greater insight into the activities of its call center representatives. To achieve this, the Fortune 50 Company wanted to analyze the desktop activities of the call center representatives around the clock. The client wanted to monitor desktop activities in real-time while the representatives are on duty. From an operational perspective, this meant creating a centralized system where operations personnel would be able to track idle time, track what websites are being used for how much time, track outlook usage, and track various applications being used on the desktop. The client also wanted to track desktop activities when the agent are on call, not on call, and on call and kept customer on hold.
About The Customer
The customer is a leading U.S.-based wireless and telecommunications service provider. It is a Fortune 50 company that wanted to improve call center performance, increase customer satisfaction, and have greater insight into the activities of its call center representatives. The company wanted to analyze the desktop activities of the call center representatives around the clock. The company wanted to monitor desktop activities in real-time while the representatives are on duty. From an operational perspective, this meant creating a centralized system where operations personnel would be able to track idle time, track what websites are being used for how much time, track outlook usage, and track various applications being used on the desktop.
The Solution
StreamAnalytix delivered a three part solution. The team developed a Data Collector component to ingest data from multiple sources and send it to the respective Kafka topics. Built-in Kafka Channels were used to ingest the data further in a Storm pipeline and process them. The following StreamAnalytix bolts were used to process the data: Enricher Processor for providing support to look up and enrich the raw data by adding more metadata required for further correlation, and Timer Processor to collect the events within time-based window and sort them to maintain the sequence of events. Further, StreamAnalytix persister components were used to persist processed data in HDFS, ElasticSearch and Apache Phoenix. The solution enabled the client to improve agent productivity dramatically by reducing idle time. It also increased customer satisfaction and handled CPNI information compliance.
Operational Impact
Quantitative Benefit
Related Case Studies.
Case Study
Vodafone Hosted On AWS
Vodafone found that traffic for the applications peak during the four-month period when the international cricket season is at its height in Australia. During the 2011/2012 cricket season, 700,000 consumers downloaded the Cricket Live Australia application. Vodafone needed to be able to meet customer demand, but didn’t want to invest in additional resources that would be underutilized during cricket’s off-season.
Case Study
SKT, Construction of Smart Office Environment
SK T-Tower is the headquarters of SK Telecom. Inside the building, different types of mobile devices, such as laptops, smartphones and tablets, are in use, and with the increase in WLAN traffic and the use of quality multimedia data, the volume of wireless data sees an explosive growth. Users want limitless Internet access in various places in addition to designated areas.
