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Customer Churn - Telecommunications


Scenario

Customer churn is a major issue for most telecommunications companies. With number portability reducing stickiness, and aggressive pricing wars, marginal profits are leading to poor economic service models.

 

Business Requirement

Carriers need to be able to analyse at least 12 months of customer data to identify those customers more likely to churn. Decisions can then be made as to what measures to take, what marketing programs to use, and services to offer to retain these at-risk customers.

  • Identify customer call patterns and usage habits to establish baselines, changes, trends
  • Define customer profitability
  • Determine the impact of price/offering changes on customer usage behavior
  • Identify CRM drivers/events that significantly impact customer call patterns and usage behaviour

Business Problem

Most current BI solutions lack the processing power or database capacity to run CRM analyses quick enough, or with enough historical data, for the carriers to make proactive, well-informed decisions around churn management.

For instance, one major wireless carrier uses Business Objects for CRM analyses on 1.4 TB of data, with 72 GB of daily updates. This application is located on an Informix XPS data warehousing platform. Query times take up to 12 hours, and due to database capacity constraints, the query can only run against three months of data, insufficient to identify a true trend.

This is presenting a barrier to the carriers ability to respond proactively to at-risk-customer activity.

 

Solution

The carrier implemented a Netezza Performance Server [NPS] system to handle complex CRM analyses of its CDRs.

 

Business Outcome

The NPS data warehouse appliance now supports comprehensive customer and financial analyses against 24 months of data, in less than 15 minutes. 20 times faster than the carrier’s legacy system.

Any churn threats are quickly and proactively identified, along with customer service
problems and trends and up-sell opportunities.

This will translate into substantial savings in retained customer revenues.

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BI Case Study Index | Bank EBM | CSP's | Education Forecasting | Local Government | Manufacturer | Port Profitability | Postal Logistics | Retail DCM | Telco Churn | Telecom Data Environment | Telecom Data Retention | Telecom RA

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