Customer Churn Solution

Discover which of your customers are likely to churn with historic data and predictive analytics

To sustain your business, you need customers to purchase your products and services. Understanding when a customer is at risk to cease his or her relationship with your company could be crucial in account management and financial planning.

Churn rate, when applied to a customer base, refers to the proportion of contractual customers or subscribers who leave a supplier during a given time period. It is a possible indicator of customer dissatisfaction, cheaper and/or better offers from the competition, more successful sales and/or marketing by the competition, or reasons having to do with the customer life cycle.

With BlueGranite's solution offering, we can help you predict which customers are likely to churn given historical information from previous customers. This will give you a more targeted approach at customer retention and relationship management.

The Value of Existing Customers

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HIGH RETENTION RATES
A 2% increase in customer retention is the same as decreasing costs by 10% [2]

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SELLING WITH EASE
The probability of selling to an existing customer is 60 to 70%, selling to a new prospect is 5 to 20% [3]

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INCREASED SALES OVER TIME
Repeat customers spend 67% more in months 31 to 36 than in their first 6 months [4]

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FREE VALUED ADVERTISING
Repeat customers refer more people to businesses through word-of-month [4]

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COMPOUND INVESTMENT
Referred customers can spend 150 to 175% more than the people that refer them [4]


Increasing customer retention by 5% can increase profits by 25%-95%! [1]

1Harvard Business Review - https://hbr.org/2014/10/the-value-of-keeping-the-right-customers | 2"Leading on the Edge of Chaos" by Emmett C Murphy | 3”Marketing Metrics” by Paul Farris, Neil Bendle, Phillip Pfeifer, and David Reibstein | 4Bain & Company - http://www.bain.com/publications/articles/the-value-of-online-customer-loyalty-and-how-you-can-capture-it.aspx

ABOUT CUSTOMER CHURN

  • Answers the question: Which customer is behaving like a customer that has churned in the past?
  • Based on past history of customers that have churned, this prediction uses other inputs such as financials, demographics, and more.
  • Uses traits such as buying behavior, frequency, and variability to generate actions based on algorithmic decision making.

  • Can be implemented on the cloud (using Microsoft Azure and Cognitive Services) or as an on-premise solution (using your current architecture).

Solution SUMMARY

  • 3 to 4 week QuickStart performed at client's site
  • Includes data exploration, machine learning model building, results delivery, and full-scale implementation recommendations

  • Discovery topics may include prediction results delivery and discussion, Azure-based or on-premise architecture plan, and Power BI dashboard concepts
  • Funding available for qualified clients
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