Gathr Case Studies Top US Airline Boosts Real-time Customer Experience Across Channels with Gathr

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	Top US Airline Boosts Real-time Customer Experience Across Channels with Gathr Gathr

Top US Airline Boosts Real-time Customer Experience Across Channels with Gathr

Gathr

Technology Category	Analytics & Modeling - Predictive Analytics Analytics & Modeling - Real Time Analytics
Applicable Industries	Aerospace
Applicable Functions	Sales & Marketing
Use Cases	Predictive Maintenance Real-Time Location System (RTLS)
Services	Data Science Services
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. Read More
About 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. Read More
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. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Predictive Analytics

Analytics & Modeling - Real Time Analytics

Applicable Industries

Aerospace

Applicable Functions

Sales & Marketing

Use Cases

Predictive Maintenance

Real-Time Location System (RTLS)

Services

Data Science Services

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 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.

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.

Impact #1	Enhanced customer experience across channels and scenarios.
Impact #2	Proactively analyze log data to detect website and mobile app outages in real-time.
Impact #3	Apply built-in predictive models and machine learning operators on customer data to predict customer preferences and choices.

Impact #1

Enhanced customer experience across channels and scenarios.

Impact #2

Proactively analyze log data to detect website and mobile app outages in real-time.

Impact #3

Apply built-in predictive models and machine learning operators on customer data to predict customer preferences and choices.

Benefit #1	The airline’s capacity to perform data searches increased from 2 days to 30 days.
Benefit #2	The application triggered an alert to the call center in real-time whenever someone from a specific customer segment logged into the system, leading to higher customer satisfaction ratings and more conversions.

Benefit #1

The airline’s capacity to perform data searches increased from 2 days to 30 days.

Benefit #2

The application triggered an alert to the call center in real-time whenever someone from a specific customer segment logged into the system, leading to higher customer satisfaction ratings and more conversions.

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Overview

Top US Airline Boosts Real-time Customer Experience Across Channels with Gathr

Operational Impact

Quantitative Benefit