Customer-Centric Data and Analytics-Readiness

In the age of holistic personalization, Customer Data Platform (CDP) featuring Customer 360 View is clearly the common goal for many marketing organizations. Development of a customer-centric database requires a comprehensive data roadmap, as a CDP is not just a pool of available data in one place. All data elements must be carefully converted into “descriptors of individual” for each target. Creating a Customer ID system through commercially available services is just the first step.

Further, all data must be “analytics-ready” for effective segmentation, modeling, and targeting. It is common that data scientists often spend over 80% of their valuable time in pre-analytics processing such as data cleansing, categorization, and summarization. Such work should be done “before” any serious analytics project begins, and resultant “Analytics Sandbox” will expedite post-analytics deployment processes, as well. When real-time personalization is the goal, most heavy lifting must be done up front, not at the last second.

Key Takeaways:

• Why marketers need customer-centric data depositories that are analytics-ready
• What modern CDPs must be
• Types of pre-analytics data work for 1:1 targeting and personalization
• Design concept of “Analytics-Sandbox” for advanced analytics
• Creating effective data menu for CDP development
• Data summary guidelines for transaction data
• Data categorization rules for seemingly messy data fields such as product, offer, channel, source, etc.
• How to treat missing data
• Check-list for 3rd-party data procurement