The magic eye

It's been said that vision is the art of seeing the invisible. Service providers, in an attempt to capitalize on an undefined future, are looking to refocus service offerings and take advantage of trends the competition can't see.

The situation can be likened to looking at a "magic eye" picture-a 3-D image in which, by shifting focus, the Statue of Liberty appears in what seems to be a field of American flags, for example.

By seeing with a magic eye, players in the converging communications market of tomorrow will be able to shift their focus and identify new sources for sustainable, competitive advantages (Table 1).

For example, a service provider using a magic eye recognizes that billing, which used to be a back-office operation, is now an effective front-line weapon in the battle for customers.

Billing systems generate invaluable information, but if that data is used simply to generate bills, it becomes an untapped resource of opportunity. Savvy carriers use billing information to create knowledge that can be used for customer acquisition, retention and growth strategies.

A service provider's ability to meet competitive challenges depends on creating sustained differentiation in a lightning-paced, aggressive marketplace. Certainly distribution and product mix are important. Providers need to be where the customers are-at the malls and in the stores that consumers already know and trust, and in the purchasing offices and boardrooms where corporate decisions are made. They also must deliver competitive products and product bundles that attract and retain a customer base while targeting the most profitable, high-value customers.

Sustained differentiation, though, must be based on the ability to strategize and plan creatively-to use a magic eye-to establish long-term relationships with customers. This ability grows from an accurate analysis of the service provider's current and future ability to deliver value now and down the road.

Data mining for dollars To grow in a highly competitive business, a service provider should always strive to offer the best combination of price, service and performance. To do this, knowledge of the customer must drive strategy, planning and execution.

Data mining-the process of digging into and analyzing existing data-offers service providers great opportunities to get closer to customers. By combining billing data with other databases and applying sophisticated predictive modeling technology, service providers can identify customers that are at risk or are candidates for additional services.

Data mining doesn't always require the latest technology, but it does require a magic eye that looks beyond the obvious to find and use the hidden knowledge to drive marketing strategies. This knowledge can help accomplish a number of things, including targeting high-value subscribers with customized promotions, acquiring new customers, reducing churn and analyzing distribution channels.

For example, if a customer consistently pays late, it certainly doesn't help cash flow. But what else can that data communicate? What proactive responses can it trigger? Maybe the billing data signals that the subscriber has an equipment problem or is receiving poor service quality. Maybe it's simply that the customer now is using the phone only for emergencies.

Either way, those late payments should trigger a service representative to call a customer. Perhaps a less expensive or realigned package will help improve the customer's experience with the service and the carrier's bottom line.

Another useful way to see the hidden picture with data mining is to form clusters. By sorting a billing database by length of service subscription vs. average billing amount, groups of like customers can be identified. Further investigation may classify these groups as potential switchers or heavy users. Once the customer clusters are identified and labeled, targeted programs can provide greater value and strengthen providers' relationships to each group.

Cross-sell and up-sell information from previous promotions and campaigns also can be data mined to target specific customer groups with specially designed programs. For example, a provider might target those with the highest propensity to buy, the lowest propensity to churn and the best distribution channel, and then select the best rate plan for that cluster of customers.

Churn management and distribution Using a new-found magic eye, providers also can mine billing data to develop a churn management solution. Accumulated billing information stored in a data warehouse must be analyzed to define and profile various segments of a selected customer base (Figure 1).

With this information, service providers can identify and prioritize customers according to which are most likely to switch carriers. This is often called the churn index. Combining the churn index with a calculated lifetime value of the customer-determined from other information in the data warehouse-can define an optimum rate plan for high-value customers.

This optimum rate index should be available to customer service representatives who can apply the appropriate techniques across the customer life cycle. Feedback from service representatives then can be used to evaluate the financial implications of a wide range of actions.

Similarly, billing and other customer care information can be mined to analyze distribution channels. This offers the ability to measure and rate the performance of retail, direct sales, agents and carrier-owned stores by finding such hidden pictures in billing information:

* Average cost of acquisition.

* Average life and lifetime value of subscribers acquired.

* Number of credit or fraud problems by distributor.

* Number of times the same customer is acquired.

* Market penetration of a given distributor compared with the norm.

Finally, a critical component in leveraging information is being sensitive to customer needs and preferences. Integrated customer information systems can offer a single view of the customer and enable service agents to answer individual inquiries personally, quickly and efficiently.

Regardless of the technologies implemented, a magic eye view will let service providers recognize and leverage opportunities into sustainable competitive advantages.

Rather than missing opportunities and losing customers, today's companies are learning to see the hidden picture in the data they already have and are using that data to care better for customers, keep them and increase business while acquiring new ones-all with a magic eye.

Although the payoffs for mining billing information can be tremendous, the process requires a great deal of integration and coordination among groups within an organization. Different pieces of information need to come together to help develop a magic eye (see figure).

In the center of the diagram is a data store-the actual data warehouse. The top half of the diagram represents the back end of the operations, where the information flows in. The bottom half is the front end where data flows out. The top left represents information extracted from the billing system and other sources of data such as demographics, which have been cleansed and loaded into the database.

The top right represents information gathered from the customer service operation. This includes customer contact data and feedback information gathered by customer service representatives. Keep in mind that the database should track the information provided to the service reps, such as scripting information, which can improve promotional campaigns.

The bottom left quadrant of the diagram represents the decision support systems that are analyzing the data from the data store from a business analysis perspective.

This includes an analysis of the information that provides feedback to continually improve the system and keep up with customer and industry trends that affect it. This information can be shared with the marketing department and any internal or external analysts, who can tweak the results based on their own marketing research and customer feedback.

Notice that part of the customer care component extends to the bottom portion of the diagram, which represents the front end. This is where the system actually pulls information from the data store and provides the strategy to customer service reps who can then act on the information as dictated by the customer management program.