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Churn & Predictive Analysis

Accurately forecast customer churn through Advanced Analytics

Customers waiting to buy  the iPhone 6 and iPhone 6 Plus outside the Apple store at IFC in Central. 19SEP14

The Problem

Our client, a multinational telecommunications company was presently facing above-average levels of customer turnover, compared with industry levels. With the increasing price competition from new companies and resellers, the commoditisation of telecommunication services and consequently declining margins, customer retention and accurate churn forecasting are of critical importance.

High levels of customer churn result in a declining market share, loss of revenue and deterioration of brand equity. Accurate churn forecasting enables senior management, through the use of advanced analytics and data science, to take required actions.

Our Soultion

Through the application of Statistics and Data Science, we were able to identify key variables driving customer defection in the company’s most profitable business units.

In order to determine which variables were driving this behaviour, we reviewed customer satisfaction data across the most relevant business units. Having determined the different components in the data, we proceeded to develop a churn prediction model that isolated the key drivers behind the customer dissatisfaction. The model was rolled out for the entire organisation.

“There are only two sources of competitive advantage, the ability to learn more about our customers faster than the competition and the ability to turn that learning into action faster than the competition”


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L8, 11 York Street, Sydney 2000


(02) 8246 7213

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