Cable TV service providers worldwide are facing immense competition for customer retention and new customer acquisition, not only from traditional players, but also from a new breed of digital players like Netflix, Amazon Prime, Roku, and more.
These digital players collect vast amounts of customer data and use predictive analytics and machine learning to deliver highly personalized, contextual, and content-driven interactions. Conventional cable companies feel the pressure to make use of similar technologies and tools to stay competitive and know what their customers truly want.
- A steady decline in demand and high churn rates
- Lack of proactive and contextualized customer service
- The technology stack was not equipped to analyze large volumes of disparate data in real-time
The Gathr advantage
Gathr enabled a leading cable TV and telecom provider in the US to enhance its customer experience by providing a 360-degree view of its customers for micro-segmentation and targeting, running dynamic marketing campaigns, proactive error resolution, and contextualized customer service in real-time.
Gathr provided a unified platform for the client’s end-to-end data processing needs like:
- Ingestion and pre-processing of large volumes of real-time data from multiple sources
- In-memory data enrichment for contextualizing interactions across touch points
- Self-learning models for customer 360 on real-time data
- Actionable insight from contact center monitoring in real-time
- Real-time visualization and detection of service errors
- Tracking of service usage and engagement levels
- Micro customer segmentation for relevant offers and personalized experience
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
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.
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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