The speed at which companies are adopting customer-centric practices is exploding. While the Web has become a catalyst for this acceleration, firms are struggling to integrate consistently all their customer interaction channels.
Companies that have successfully transformed from a product focus to a customer focus have found that such a transformation requires a balanced investment in organization, process, information, intelligence and technology. Yet, unfortunately, statistics show that most companies attempting such a transformation are investing a disproportionate amount in technology and are ignoring the rest.
A typical CRM corporate investment consists of purchasing either a call center or a sales force automation application, which is driven by a data mart. While these data marts contain the proper customer data to drive the particular application, they are not open and accessible to other organizations and are not adequate for providing an enterprisewide view of each customer relationship.
The finance department, another primary user of a customer-centric data warehouse, however, will be interested in accessing data measuring the profitability of each customer, while the marketing department is interested in determining upsell and cross-sell opportunities.
Large financial service institutions, including Citibank, First Union Bank and Bank of Montreal, have developed enterprise data warehouses. These databases contain detailed information and are able to support several different analytical applications.
However, because they must support such a variety of applications with diverse requirements, they are also unable to provide a complete, enterprisewide view of each customer relationship. And even though they contain voluminous data, the majority of the data warehouses do not contain any of the intelligence needed to determine metrics such as future profitability and propensity to purchase a particular product through a specific channel. So the real question is what should a customer-centric data warehouse include?
Customer data. At the individual, household and account levels, customer data must be included to determine demographic, lifestyle needs and life-stage information, etc.
Transactional data. Information such as transaction frequency, transaction types, cost per transaction and channels through which these transactions are executed will help better understand a customer’s behavior and current and future profitability.
Product usage data. To identify the breadth and depth of each customer’s relationship with the company and to identify future sales opportunities, the data warehouse must include data describing the products each customer and household owns throughout the institution.
Contact and campaign data. The data warehouse must include all outbound contacts made with a particular customer and/or household through any of the available channels, whether it’s through inbound contacts made by each customer, the results of marketing campaigns or summaries of data from other channel databases.
Customer intelligence. The results of analyzing collected data include the collective intelligence the firm has about each customer.
Armed with this type of information and intelligence, the company can start answering these questions:
• How has the customer’s behavior toward the company changed since the customer was acquired?
• What products could/should the customer own?
• Which channels does the customer use most and for what types of transactions?
• What channels should a customer be encouraged to use?
• How should interactions through these channels be coordinated to enhance the customer’s experience?
• Which customers will be directed to self-service channels?
• What types of transactions will a customer be allowed to perform?
• Should any products be offered only through the Web site?
• How much does it cost to service each customer’s transaction?
A customer-centric data warehouse will not only enable the company to better manage each customer relationship, but it will indirectly empower the customer to manage their relationship with the institution.
Organizations must continually collect the data necessary to address the questions above. In this way, the warehouse contains the necessary data to manage each and every customer relationship, with all departments becoming stakeholders to its success.
Evangelos Simoudis is founder and president
of Customer Analytics Inc., Boston.