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Traditional approaches to predicting CLV (Customer Lifetime Value), like EP/NBD, continue to be effective many years after their initial formulation. In fact, attempts to improve on traditional methods using advanced ML techniques have been minimally effective. We explored combining an ML approach with the use of additional (non-transactional) data and have found early results to be quite promising. We’ve summarized our results in a blog post[1] and a more detailed paper[2].
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