As markets become more mature, competitive and undifferentiated, many companies find themselves struggling with high customer attrition (churn). Companies try to cover up by acquiring new customers by means of profit-eroding attractive acquisition offers, which in many cases, encourages churn behavior as competitors adopt similar acquisition strategies. In order to address the root cause of customer attrition, it is vital for companies to identify the “dissatisfiers”. The “dissatisfiers” may result from several factors (dimensions); for e.g., poor products, service, lack of trust, company policies, perception/brand issues or dissatisfied segments and in most cases - a combination thereof.

Since the “dissatisfiers” can exist on several dimensions, analysis of historical data can provide invaluable insights. However, the real challenge of churn related data analytics does lie in the execution of the analysis, but rather in the generation of insightful interpretation with a big-picture view of things and actionable remediation plan. Going by the 80-20 rule, companies stand to benefit the most by identifying the “dissatisfiers” that have maximum impact and are most addressable. Due to complex nature of such analysis, a structured and comprehensive approach to data analytics is required.

Diamond has developed a technique, “Churn Heat Map”, which is a useful tool that can allow companies to identify churn drivers in an efficient and reliable way. The tool is used to analyze historical customer attrition data to generate a color coded heat map of churn rate modulated by the severity of churn and volume on a grid of churn drivers and customer segments. The churn drivers and customer segments are chosen from standard attributes in order to address specific needs of a problem. The rules for color coding are also customizable (for e.g. red color may indicate above industry churn for a segment). The “Churn heat map” is a useful in customer attrition remediation projects in a variety of industries - telecommunications, financial services (credit cards, banking, brokerage etc.), media, and many more industries plagued by churn/attrition problems. Such a tool provides the following benefits:

• Allow rapid hypothesis generation
• Help identify relatively addressable and significant pockets of churn (low hanging fruit)
• Serve as a reporting tool for visually monitoring the efficacy of churn remediation activities
• Leverage experience and knowledge across products, markets, and geographies by constantly enriching the model with additional categorization variables

Several off-the-shelf software such as SAS Cube, SAS Enterprise Guide, SQL Server, SGI MineSet 2.5 can be customized and leveraged to implement such a tool with limited development effort.

A sample application of such a tool when applied to a telecom churn data analytics is shown below:

The above figure shows the logical flow of transformation of historical marketing data into a churn heat map, which can then be readily leveraged to generate hypotheses, which once validated can yield actionable recommendations leading to early wins in a churn remediation initiative of a company.

An interesting response to an article on the future of business intelligence that came out last week. The blog talks about issues along the BI value chain and the need for innovation. However one issue might be the highly fragmented value chain itself and therefore some vertical integration might also make economic sense.  One interesting factoid that jumped out:

Most data warehouses are built by hand, which suits systems integrators just fine (all those yummy billable hours) but does not serve customers well. TDWI reckon an average data warehouse takes 16 months to deploy, USD 3 million to build and costs 72% of its development costs in support every year.

Do customer education campaigns and efforts have a positive ROI?
Here is a case in point. We recently helped a client in diagnosing the high churn levels of newly acquired customers. After performing customer research on this segment, we realized that only about a quarter of the customers understood how their chosen product features compared to the spectrum of available offerings by our client.

Thus, many customers who were dissatisfied by their specific product features switched providers (rather than moving to a different plan with their existing provider) as they were unaware of the alternatives. This highlights the need of better customer education and experience during the sales process which is aligned with meeting the needs of the individual customers.

“When making a purchase, a consumer has a choice between using frequent-flier miles, cash, or some combination thereof. Which will he or she choose? Another consumer has an opportunity to participate in a special program to get a free car wash after paying for a certain number of washes. What’s the best way for the car-wash owner to motivate the customer to participate?”

Here is a very good summary of the latest in the area of customer loyalty in academics. Article and associated papers talk about efficacy of ‘combined currency’ (dollars and miles) programs, ‘artificial advancements’ and ’status’.

As marketers use more complex loyalty schemes and techniques, the importance of testing marketing campaigns becomes very important. Proper campaign management processes and governance structure within the marketing department helps the companies to structure test and roll out the most profitable marketing campaigns to the customer base.