Churn-Analysis Tools

Today's churn-analysis tools fall into two categories: analytical tools based on usage patterns and analytical tools based on billing data. Usage-based tools watch for customer usage patterns and try to predict when a customer will leave. Diagnostic models based on usage can be as simple as tracking price-plan changes or as complicated as watching certain customers' day-to-day usage. A usage-based model, for example, might record that a customer on a $75 monthly service plan switched to a $49 plan. The next month, he switched to a $29 plan. That pattern signifies the customer is significantly altering his usage and likely will churn soon.

More complex usage-based churn-analysis tools also can monitor daily or weekly usage patterns. These diagnostic models are exceedingly complex, and few carriers have the appropriate personnel to implement them. This diagnostic model can predict, based on daily usage patterns, when a particular customer will churn. For example, if a customer uses his phone often during the week and rarely on weekends, but then he suddenly shifts to weekends only, your usage-based tool would alert you to a potential casualty. The customer may have linked up with another carrier for weekday calling and stayed with you for free weekend calling.

Usage-based analysis tools require human resources, database systems, network capabilities and marketing expertise. Few carriers have these complex analytical tools because they are difficult to implement, affect many parts of the business, require senior management to change how it runs the business and require significant resources that otherwise might be used to acquire new customers. But the good they do far outweighs their cost.

Most carriers use simple billing-based churn-analysis tools. Billing-based tools involve looking at the bottom line to predict when a customer's total bill changes, which may signify impending churn. More carriers use this model because it is simpler and cheaper. However, whether billing-based churn analysis is truly cost-effective and works well enough to increase profits in the long run still is up for debate.

Billing- and usage-based tools are a good start. Unfortunately, they are not effective enough to fend off churn for long. Newer, more sophisticated diagnostic models and tools are on the way, however, and they will amplify significantly your efforts to respond to churn before it gets you.

The next generation of churn-analysis tools is more complex and involves more variables. It will look at thousands of data pieces, such as where a customer called, when he called and his cell-site movement patterns, to determine when he is likely to churn. These churn-analysis models have not been fully implemented by any carrier yet, but they are coming. Some carriers have been able to implement portions of this model, although the models they use are proprietary. Churn analysis at the next level will require a heavy commitment and careful planning, which many carriers are unwilling to do.

When thinking about acquiring or developing a churn-reduction tool, be sure to consider the implications on your entire organization. Churn reduction must be a strategic and operational imperative at the highest levels, or your implementation will be piecemeal and may not achieve your desired results.

When you decide to target and fight churn, you must develop a cross-functional team to assist in developing the tools you will use. That means including people from IT, marketing, sales, billing, customer care and network management and asking how it will implicate their departments. Without input from front-line employees, any churn-analysis tool will not function as well as itcould.

Small and mid-size carriers with churn problems need not lose heart. You can take steps to combat churn with success.

1. Get to know basic lifestyle information about your customers so that you can offer tailored retention packages from your churn tool kit.

2. When customers call to get information on their service, change service plans or ask a question, learn something new about them.

3. Build a few custom fields into your customer databases to track lifestyle information.

4. When customers sign up for service, make them fill out a short questionnaire that will enable you to know what type of retention programs they will respond to. The more things you learn about your customers, the better equipped you will be to build a relationship with them.