Telco Corporation Case Study

At a Glance

Telco Case Study

Challenges

Accessing and visualizing massive telecom datasets at scale in real-time
Identifying network performance issues that would cause customer churn
Collecting and measuring network usage data and customer experience across competitors

Impact

Reduced customer churn
Real-time detection of network performance issues
Competition comparisons that inform opportunities for customer growth
Proactive hardware maintenance schedules

How Entel Benefits from HEAVY.AI

Multi-factor location data, such as signal strength and data speeds at specific towers, helps determine schedules for antenna upgrades before hardware deteriorates

Comprehensive measurements of customer experience across the network and competitors improves understanding of QoS and decrease customer churn

Real-time, granular visualizations of network performance data enables fast detection and resolution of performance issues

Dashboards help marketing managers easily identify competitive comparisons, tailor service offerings to each customer segment, and better determine opportunities to grow their customer base

No-code data joins

Objectives

The volume and complexity of Entel’s data exceeded the capability of legacy tools to adequately access, analyze, and visualize it quickly and at scale. In this lag, network performance issues went undetected, which led to customer churn. Entel required an advanced data analytics and visualization solution to deliver instant network performance insights.

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Solutions

Entel adopted HEAVY.AI’s analytics solution to map and analyze massive, complex data in a fraction of a second. They identified network performance issues and solved them before customers were significantly impacted. Hardware-accelerated (e.g., GPU) dashboards facilitate fast, precise monitoring and analysis of 200 million records per month from their network and mobile data sourced from Tutela Technologies, Ltd.

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