CRM-ready data warehouses contain detailed data from all customer activity threaded together, at least minimally, by the shared customer dimension which was discussed in my last two columns. In my next several columns, I will talk about the value proposition in the capture and integration of the various major customer interaction systems including contact centers, e-systems and workforce management systems.

Deriving the full value from customer contact data requires the integration of all contact records, regardless of how or where they were received. Data might represent phone contacts routed to a regional call center, e-mails sent to a service organization or Web interactions between sales agents and prospects surfing a company's Web site. The ability to optimize the business to better meet the needs of customers depends on knowing what those customers are doing, regardless of the communication channel they use, and how or where their contacts were routed within an enterprise-wide contact infrastructure.

The kind of data consolidation that yields this knowledge has traditionally been the goal of enterprise data warehousing projects. However, because operational systems, such as financial applications or call center management software, are increasingly provided by third-party vendors rather than in-house IT organizations, the trend is to depend on application vendors (often the provider of the operational application) for data collection and analysis.

As these vendors develop packaged data mart solutions that give access to the data collected in their applications, businesses have the opportunity to gain insights that can contribute materially to their success.

Customer relationship management (CRM) is one of the most critical functions in any business today, and detailed contact center data is an essential tool for effective CRM strategies. Managers know the potential this data offers to help them run individual contact centers more efficiently. However, benefits extend beyond the contact center to the entire enterprise. Contact center data that is easily accessible for data mining and analysis is the foundation for stronger customer relationships, more effective promotion management, improved agent performance, more effective product development and better infrastructure management.

Realizing the full potential of contact center data requires more than the reporting tools normally used in contact center operations. These one-dimensional tools are usually inadequate for data mining and analysis. The databases that support operations are tuned specifically for operational reporting, not for analytics. Historical content is limited, and each database represents only one operational function or one contact channel. What companies need ­ especially companies with a high volume of contacts across multiple channels – is a solution that integrates multichannel contact data and uses proven data warehousing techniques to transform operational data into analytical information.

Such a solution would enable businesses with multiple contact centers to view multiple contact channels and distributed contact center sites as one operation. An enterprise- wide, analyzable view of detailed customer contact data could become the foundation of a successful CRM strategy and yield return on investment in several ways. We'll explore the first way – improved customer relationships – in this column.

Managers need to analyze the number, type and volume of complaints or inquiries and draw conclusions about where improvements are needed in everything from customer call hand-ling to product development. Using detailed contact data, businesses must develop customer profiles that can help them serve customers better and develop targeted marketing campaigns that more precisely give customers what they want.

Relationship management involves more than just delivering excellent customer service and effective marketing campaigns. For maximum profitability, a business must consider the value of each customer to the business. Contact center data can reveal which customers buy most often or buy the most expensive products. By comparing new customers with the profiles of existing customers, businesses can accurately predict how profitable these new customers are likely to be.

Once premier and high-potential customers are identified, they can be routed to elite agents for special treatment, targeted for special promotions and otherwise treated like the valuable assets they are to the business. Businesses can devote their most costly resources to their most profitable customers and give the less profitable customers self-service options.

Customer profiling can improve resource allocation in other ways as well. Detailed knowledge of customer contact patterns can help businesses identify opportunities for cross-selling and up-selling, increase sales for specific products, adjust fees to usage patterns and direct less-profitable contacts through the least costly channels.

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