Database: Focus on the Future
August 2006
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Today’s data management processes often fail to meet the needs of evolving multitouch, multichannel marketing campaigns. At this summer’s DM Days New York Conference & Expo, Scott Cone, vice president, client group leader for database marketing agency Merkle Inc., discussed the changes and best practices that will optimize the data management process going forward.
Currently, effective multitouch data management and performance measurement doesn’t exist, asserts Cone. In fact, he says, decision criteria such as demographics, model scores and purchase history at the time of the marketing effort rarely are captured. Cone suggests a data management process best suited to meet tomorrow’s challenges creates an individual dialogue with customers and has the following characteristics:
• Specific data plans and processes exist for prospect, customer and market-level data management;
• All touchpoints are coordinated to continually build and validate data for every customer and prospect;
• Central data stores feed an intelligence system, continually updating derived and aggregated data and associated models; and
• Privacy, permission and marketing are managed in a balance that facilitates customer requests and maximizes marketing opportunities.
To reach these goals, data management should be an ongoing process that follows a number of key steps including: data capture, transfer, organization, transformation, storage, analysis and use. Cone notes data capture should include all possible sources and touchpoints in a common data format. That information should include what happened; why it happened; when it happened; and the recommended next steps. Detailed transaction data should then be transferred to a common data store.
During the organization, transformation and storage steps, operational data stores can facilitate marketing, sales and other uses of the data, but marketing needs to drive the creation of content.
Finally, Cone points out that customer analysis and action need to be based on customer life cycle and segmentation metrics. When it comes to marketing program assessment, he stresses that the focus should be on program and customer metrics rather than campaign metrics.
—Irene Cherkassky
Currently, effective multitouch data management and performance measurement doesn’t exist, asserts Cone. In fact, he says, decision criteria such as demographics, model scores and purchase history at the time of the marketing effort rarely are captured. Cone suggests a data management process best suited to meet tomorrow’s challenges creates an individual dialogue with customers and has the following characteristics:
• Specific data plans and processes exist for prospect, customer and market-level data management;
• All touchpoints are coordinated to continually build and validate data for every customer and prospect;
• Central data stores feed an intelligence system, continually updating derived and aggregated data and associated models; and
• Privacy, permission and marketing are managed in a balance that facilitates customer requests and maximizes marketing opportunities.
To reach these goals, data management should be an ongoing process that follows a number of key steps including: data capture, transfer, organization, transformation, storage, analysis and use. Cone notes data capture should include all possible sources and touchpoints in a common data format. That information should include what happened; why it happened; when it happened; and the recommended next steps. Detailed transaction data should then be transferred to a common data store.
During the organization, transformation and storage steps, operational data stores can facilitate marketing, sales and other uses of the data, but marketing needs to drive the creation of content.
Finally, Cone points out that customer analysis and action need to be based on customer life cycle and segmentation metrics. When it comes to marketing program assessment, he stresses that the focus should be on program and customer metrics rather than campaign metrics.
—Irene Cherkassky
Companies Mentioned:
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The Business of Database Marketing