Customer Data Analytics
“Customer Data Analytics” looks at understanding the relationship between business value and data analytics, and the different techniques used for analysis, including clustering, classification, segmentation, estimation, prediction, and affinity grouping. These techniques rely on methods such as link analysis, cluster detection, and decision-tree analysis to help develop usable models.
Keywords
Supervised analysis; unsupervised analysis; market basket analysis; memory-based reasoning; clustering; link analysis; decision trees
The Analytics Feedback Loop
Many people often get the false impression that customer data analysis will indubitably result in the creation of value via a customer-centric strategy. But the ...
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