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Predicting customer churn

Anticipation of customer churn

It is between five and fifteen times more expensive to gain new customers than to retain the current ones. Churn prediction is a very powerful weapon to know soon which customers will abandon the company, in order to increase the degree of retention, to build a solid CRM strategy and to save acquisition costs.

The challenge: Anticipation of customers’ abandon

• Predicting the churn rate in order to anticipate.
• Detecting which customers are about to abandon.
• Knowing the real value of the potential loss of those customers.
• Taking the necessary preventive measures to reduce or avoid their abandonment.

The Solution: BIRT Analytics

• Puts advanced analysis techniques into practice, such as Profiling, with the aim of identifying which variables define the churners and which don't.
• Analizes the evolution of each customer and his interactions with recent churners from their environment through Pivot Table and other advanced analytics techniques.
• Provides a long term forecast and detects soon customer value loss through Decision Trees.
• Identifies loyalty factors and allows to put personalized retention plans into practice.

BIRT Analytics’s Benefits

• Counteracting the gaining actions from competitors, reducing risks and avoiding non predicted escapes.
• Saving costs from prospections and acquisitions, gaining efficiency and competitivity.
• Making the most of the customers base.
• More capability to react, due to a soon customer value loss detection.
• Optimizing business resources just after knowing the real value of each customer's loss.
• Providing users with autonomy and decision capability and reducing IT's workload and costs.
• Analyzing big volumes of data instantly and easily.

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Related webinar available

Predicting and avoiding customers Churn

Target: Marketing and CRM

Goals:

Learning how Quiterian Analytics responds to the challenge of predicting customers’ churn:

• Getting to know which customers churn in order to retain them on time.
• Anticipating to reduce risks and avoid loss.
• Making the most of the customers’ portfolio and saving costs.
• Optimizing resources and automating processes.

Contents:

• Churn definition.
• Churners’ profile.
• Churn prediction.
• Risk measurement.

Presented by:

• Víctor Muakuku, Senior Consultant at Quiterian

Related documentation available

Marketing Advanced Analytics [Brochure]

It is between five and fifteen times more expensive to gain new customers than to retain the current ones. Churn prediction is a very powerful weapon ...

Download

The challenge of predicting customers' churn [White Paper]

It is between five and fifteen times more expensive for a company to gain new customers than to retain the current ones. Because of this, knowing soon...

Download

Customer Analytics [Brochure]

BIRT Analytics lets you capture the value of Big Data that speeds right by most enterprises. It analyzes massive volumes of data coming in from multip...

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• Integration
• Segmentation & Campaigns
• Cross and up selling
• RFM Analysis
• Predicting customer churn
• Sales Force