Reducing Customer Churn Using Advanced Analytics

by Harpreet Singh, PhD (Founder of the largest Data Science consulting marketplace on the planet)

Given the high costs of customer acquisition in myriad industries, reducing customer churn through an intelligent segmentation of your customer base is essential to business viability. You need to leverage your customer data to reduce customer churn and reap maximum benefits from a well-segmented and thoroughly analyzed customer database.

Challenges and Opportunities

Customer attrition or churn is a rate that measures the number of clients whose business is lost over a particular timeframe. In highly competitive industries where substitute products or services are readily available and the cost of retaining an existing customer is significantly lower than the cost of acquiring a new one, reducing customer churn is the key to long-term profitability. Customer segmentation—dividing a customer base into geographic, demographic, behavioral, and income categories so as to more effectively target products and services—is the key to reducing customer churn. The better segmented your customer data, the more efficiently you can invest scarce resources in those consumers who are most likely to respond to your offerings and the more able you will be to iteratively refine your products and services so as to retain their loyalty.

The challenge for many businesses is that the data required to reduce customer churn is:

• Not gathered from across the organization using the best data mining techniques
• Not analyzed using the most sophisticated and innovative algorithms
• Not stored securely in line with the latest data security practices

At Experfy, through our customer analytics practice and machine learning platform, we have helped diagnose and overcome a large number of customer data challenges and develop a program of action to harness that data to reduce customer churn in a number of industries. I intend to shed light on more detailed use-cases for specific industries in a later post to demonstrate the importance of domain knowledge.

Solution

Tackling churn requires deep expertise in customer lifetime value modeling and the measurement of ROI in marketing. The foundation of our approach is to analyze how an organization gather data about its customers and what data gaps it must address. Our mission is to enhance organizational capacity to mine customer data or capitalize on existing data which is both a technological and a business structure issue. Who are your customers? How do they behave? What data should be collected about them? How should we be gathering information about them? How do we place that data in the hands of those who can best use it? What technologies and business practices facilitate this?

Once that fundamental challenge is addressed, Experfy helps our clients harness sophisticated Big Data techniques such as machine learning and predictive analytics to calculate and analyze an organization's churn rate—percentage of customers whose business is lost per quarter or year; anticipated profit potential and lifetime revenue per customer by income, geography, demographics, etc.; discount rate—the cost of capital used to discount future revenue from a customer; retention cost—the amount of money required to retain a customer per quarter or year; and other metrics that may be important to your specific business. Having acquired and analyzed the data, we make a strategic recommendation as to how best to harness it. Specifically, we design strong and highly personalized loyalty programs by identifying those services, support, and promotional offers that your most valued customer segments require to remain in good standing or increase their spending with your company. We also help organizations identify customers that you don’t want because their risk profile is too high or their contribution to your bottom line is too minimal to warrant the investment.

Finally, Experfy's training platform helps train organizations in how to secure customer data. This latter point should not be underestimated as the personal information and deep consumer insights that makes effective customer targeting possible also makes that data attractive to thieves. The battle to secure customer data is an iterative and ongoing one that requires ever-increasing sophistication. Failure in this struggle can have profoundly negative consequences for your brand as Yahoo! and Target have unfortunately learned. Experfy is helping organizations determine the weaknesses in their approach to data security and how to best protect one of their most valuable assets: customer data.

For more information on actionable recommendations to reduce customer churn, see Experfy's customer analytics practice area. To build institutional knowledge within your organization, see Experfy's training track focused on customer analytics.