Customer-Centric Data and Analytics-Readiness

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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 percent 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 for an “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