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Top US Airline Boosts Real-time Customer Experience Across Channels with Gathr
Technology Category
- Analytics & Modeling - Real Time Analytics
- Analytics & Modeling - Predictive Analytics
Applicable Industries
- Aerospace
Applicable Functions
- Sales & Marketing
Use Cases
- Real-Time Location System (RTLS)
- Predictive Maintenance
Services
- Data Science Services
The Challenge
The airline was experiencing a massive growth of high-speed data coming in from various online and offline customer touch points and operational systems; nearly 5TB of data was coming into its systems every day at an input data velocity of 7,000 events/second. The massive volume of data limited data searches to only two days of data logs; preventing analysis of customer behavior patterns and anomaly detection based on a longer and more relevant time window. The traditional technology stack was unable to manage the rapidly growing volume of high-speed data.
About The Customer
The customer is a major US airline that operates one of the most comprehensive route networks with approximately 4,500 flights a day to 338 airports across five continents. The airline was experiencing a massive growth of high-speed data coming in from various online and offline customer touch points and operational systems. The airline was looking for a solution to efficiently manage, analyze, and draw actionable real-time insights from its continuously growing and complex customer and operational data.
The Solution
The airline chose Gathr to efficiently manage, analyze, and draw actionable real-time insights from its continuously growing and complex customer and operational data. Gathr makes it easy to ingest and manage high volume of data which otherwise the airline giant took days or weeks to harness using a traditional technology stack. Using a scalable architecture, Gathr enables future support for even larger data sets coming in at higher speeds. The platform improves searches with a customized web interface for queries, and easy onboarding of additional services and application logs. This data can now be enriched, cleansed, and prepared as it arrives, for various downstream applications in real-time.
Operational Impact
Quantitative Benefit
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