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UID:pretalx-cfp-KS7JJN@nyc2023.pydata.org
DTSTART;TZID=America/New_York:20231103T141500
DTEND;TZID=America/New_York:20231103T145500
DESCRIPTION:The Customer Lifetime Value(CLV) model is one of the major tech
 niques of customer analytics and it helps companies to identify who valuab
 le customers are. A high CLV indicates customers who deserve more marketin
 g resources. If the company overlooks CLV\, it might invest more in short-
 term customers who buy just once.\n\nTo predict future CLV\, we encounter 
 sub-problems like forecasting the time until a customer's next purchase (
 “Buy Till You Die” modeling) and the probability of a customer's churn
  (Survival Analysis). \n\nRecently\, PyMC-Marketing was released and\, it'
 s becoming more feasible to implement these models with the Bayesian appro
 ach.\n\nIn this talk\, I will show the key concepts of CLV prediction\, it
 s demonstration using Pymc-marketing\, and practical tips.
DTSTAMP:20250709T214333Z
LOCATION:Winter Garden (Room 5412)
SUMMARY:Customer Lifetime Value Prediction with PyMC Marketing - Hajime Tak
 eda
URL:https://nyc2023.pydata.org/cfp/talk/KS7JJN/
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