KDnuggets Home » News » 2011 » Dec » Publications » Case Study: 1275% Boost in Ability to Identify Churning Customers  ( < Prev | 11:n30 | Next > )

Case Study: 1275% Boost in Ability to Identify Churning Customers


 
  
Fast-growing mobile telecommunications operator 2degrees increased their ability to identify customers at risk of churning by 1,275% using 11Ants Customer Churn Analyzer


2 degrees 2degrees is New Zealand's fastest growing mobile telecommunications company - in less than three years they have transformed the landscape of New Zealand's mobile telecommunications market. Entering very much as the challenger, and battling with incumbents entrenched in the market for over 18 years. 2degrees has won over 580,000 customers, and has revenues of more than $100 million in just their third year of operation. Last year's growth was 3761%.

[full case study (PDF) ]

11Ants Analytics 2degrees put 11Ants Analytics solutions to work quickly with very satisfying results. The initial project was to focus on an all-too common problem in the mobile telecommunications industry - customer churn (customers leaving). For this they deployed 11Ants Customer Churn Analyzer.

2degrees were interested in identifying customers most at risk of churning by analyzing data - such as time on network, days since last top-up, activation channel, whether the customer ported their number or not, customer plan, and outbound calling behaviours over the preceding 90 days.

A carefully controlled experiment was run over a period of three months, and the results tabulated and analyzed. The results were excellent - the customers identified as churners by 11Ants Customer Churn Analyzer were a game-changing 1275% more likely to be churners than customers chosen at random. This can also be expressed as an increase in lift of 12.75 at 5% (the 5% of the total population identified as most likely to churn by the model). At 10% lift was 7.28.

Read the case study here .


KDnuggets Home » News » 2011 » Dec » Publications » Case Study: 1275% Boost in Ability to Identify Churning Customers  ( < Prev | 11:n30 | Next > )