Gathr Case Studies Leading Cable TV and Telecom Provider Enhances Customer Experience with A Customer 360 View Using Gathr
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Leading Cable TV and Telecom Provider Enhances Customer Experience with A Customer 360 View Using Gathr

Gathr
Analytics & Modeling - Machine Learning
Analytics & Modeling - Predictive Analytics
Analytics & Modeling - Real Time Analytics
Telecommunications
Sales & Marketing
Predictive Maintenance
Real-Time Location System (RTLS)
Data Science Services
System Integration
The customer, a cable TV and telecom provider operating in over nine US states and serving nearly 5 million customers, was facing intense competition from traditional players and new digital players like Netflix, Amazon Prime, Roku, and more. These digital players were using predictive analytics and machine learning to deliver highly personalized, contextual, and content-driven interactions. The customer was experiencing a steady decline in demand and high churn rates. They lacked proactive and contextualized customer service, with their data analytics restricted to a historical analysis of a limited set of monthly calls. The absence of real-time dashboards and lack of customer data enrichment prohibited contextualization. Their technology stack was not equipped to analyze large volumes of disparate data in real-time.
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The customer is a leading cable TV and telecom provider that operates in over nine US states and serves nearly 5 million customers. They offer a range of services, including cable TV and telecommunications. The customer was facing challenges in retaining and acquiring new customers due to intense competition from traditional players and new digital players. They were experiencing a steady decline in demand and high churn rates. The customer was also struggling with a lack of proactive and contextualized customer service and an inability to analyze large volumes of disparate data in real-time.
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The customer implemented Gathr, a platform that enables real-time data ingestion, data transformation, data enrichment, advanced analytics, and machine learning. Gathr ingests and processes large volumes of unstructured data as it arrives, rapidly aggregates data from disparate real-time data sources, and quickly identifies correlations. The platform further enriches real-time actions with historical customer data and trends, enabling the operator to instantly deliver the most relevant and effective experience while the customer is still in the moment. Gathr also makes it easy to build, train, and deploy self-learning algorithms based on digital customer touch-points. These models allowed the provider to move away from traditional CRM powered customer views and leverage richer customer data sets to provide relevant, real-time customer experiences.
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Gathr enables monitoring and tracking of agent calls in real-time through call analytics, dashboards, and alerts.
Streaming event data from error reports are analyzed in real-time to detect how many customers are facing errors.
Gathr enables real-time tracking of service usage and customer engagement levels.
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