IBM > Case Studies > eircom Group Ltd. - Advanced analytics used to craft customer experiences that improve satisfaction and retention

eircom Group Ltd. - Advanced analytics used to craft customer experiences that improve satisfaction and retention

Company Size

1,000+

Region

Europe

Country

Ireland

Product

IBM SPSS Modeler 15
IBM SPSS Statistics 20
IBM SPSS Collaboration and Deployment Services V5.0

Tech Stack

IBM SPSS
Predictive Modeling
Sentiment Analysis

Implementation Scale

Enterprise-wide Deployment

Impact Metrics

Customer Satisfaction
Productivity Improvements

Technology Category

Analytics & Modeling - Big Data Analytics
Analytics & Modeling - Predictive Analytics

Applicable Industries

Telecommunications

Applicable Functions

Sales & Marketing

Services

Data Science Services

About The Customer

eircom Group Ltd. (eircom) is a communication services provider founded in 1984. The company provides services such as fixed-line, mobile, and broadband services. Located in Dublin, eircom has approximately 5,000 employees serving more than two million fixed-line and mobile customers. Through its Meteor and eMobile brands, it serves 20 percent of the country’s mobile customers and 40 percent of the broadband market. The company is also deploying a new fiber network to reach 600,000 homes and businesses by the end of 2013.

The Challenge

eircom Group Ltd., a communication services provider based in Dublin, was facing a significant challenge due to fierce industry competition and the increasing risk of customers easily switching service providers. The company was experiencing an annual loss of EUR1.5 billion due to customer churn. The company needed a solution to identify the factors contributing to unfavorable customer experiences and to identify customers most likely to switch communications service providers.

The Solution

eircom implemented a solution using IBM SPSS Modeler 15, IBM SPSS Statistics 20, and IBM SPSS Collaboration and Deployment Services V5.0. The solution uses sentiment analysis and predictive modeling to determine which factors contribute to unfavorable customer experiences and to identify customers most likely to switch communications service providers. The solution helps the company analyze multiple data streams and automatically sends prediction alerts about customers and patterns with a high probability of churn. Because of the timely alerts, eircom can take immediate action to improve customer satisfaction and retain more customers.

Operational Impact

The solution enables eircom to reduce the time required to process customer data by 75 percent through automation of certain aspects of the analytics process.
As a result, the company’s analysts now spend 80 percent of their time developing data analyses and only 20 percent of their time processing it.

Quantitative Benefit

The client realized a 6 percent increase in customer retention as a result of identifying the most effective ways to improve the customer experience.
This improvement had direct correlation to the 40-point rise in its NPS results.