TUTORIAL: Big Data & Social MDM - Leveraging 1st & 3rd Party Data to Derive Behavioral Insights
CEO & Co-Founder, LumenData
MDM systems are best at creating a unique, accurate, known view of the customer. In a B2C setting, this includes household information, products owned, purchase history and so on. Most leading edge organizations have a master data strategy and system in place or are planning on deploying one. One of the new emerging (and additional) benefits of these systems is to derive insights into consumer behavior. In order to do so, master data - or sometimes what is known as “1st party data” - must be combined with ambient data, and then predictive models applied to it. “Ambient data” includes source data (referring URL, device types, IP address, geo location) combined with “3rd party data” sources that can then offer great insight into consumer behaviors and propensities.
This tutorial discusses some of these techniques in the context of a specific customer case study for whom these models and techniques were developed. Topics include:
- Identifying & governing which Big Data/ambient data sources help comprise the “longitudinal” customer view
- Understanding how to map ambient data sources to 1st party MDM data
- Accommodating & addressing customer concerns of privacy & security when blending 1st & 3rd party data