Requirements
A leading US-based wireless and telecommunications service provider wanted to optimize call center cost by tracking the desktop activities of the call center representatives in real-time. This required 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
- Track various applications being used on the desktop
The client also wanted to track desktop activities when the agent is:
- On call
- Not on call
- On call and kept customer on hold
Solution
Gathr 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 data further in Storm pipelines and process them. The following Gathr bolts were used to process the data:
- Enricher Processor: Provided support to look up and enrich raw data by adding metadata required for further correlation
- Timer Processor: Collected events within a time-based window and sorted them to maintain their sequence
- Gathr persister components were used to persist
Business Benefits
- Annual overall cost reduction of $5 million
- Improved agent productivity with ability to handle more than 30 calls per day
- Improved customer experience
- Reduced agent idle time to 15 minutes per day
- Reduced overall after-call work activities of agents to 30 minutes per day
- Handling of CPNI information compliance
- Identification of anti-company and union propaganda
Meet Gathr.
The only all-in-one data pipeline platform
- One platform to do it all - ETL, ELT, ingestion, CDC, ML
- Self Service, zero-code, drag and drop interface
- Built-in DataOps, MLOps, and DevOps tools
- Cloud-agnostic and interoperable
Data
Ingestion-
Change Data
Capture -
ETL/ELT Data
Integration -
Streaming
Analytics -
Data
Preparation -
Machine
Learning
Expert Opinion
Gathr is an end-to-end, unified data platform that handles ingestion, integration/ETL (extract, transform, load), streaming analytics, and machine learning. It offers strengths in usability, data connectors, tools, and extensibilty.
Customer Speak
Gathr helped us build “in-the-moment” actionable insights from massive volumes of complex operational data to effectively solve multiple use cases and improve the customer experience.
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