Propensity Modeling to Identify Behaviors and Attributes of High-Value Customers

Propensity Modeling to Identify Behaviors and Attributes of High-Value Customers
Share:

Download MP3


Similar Tracks

InfoTrust Webinar | Five GA4 Features That Will Improve Your Data Insights InfoTrust
Propensity Score Matching: A Practical Tutorial BERD Education
Designing a Customer-Centric Business Model Harvard Innovation Labs
Michael Johns: Propensity Score Matching: A Non-experimental Approach to Causal... | PyData NYC 2019 PyData
Think Fast, Talk Smart: Communication Techniques Stanford Graduate School of Business
Beyond Propensity: From traditional ML to Uplift Modelling Faculty
InfoTrust Webinar | Measurement: Methods for Reliable Attribution in a Confusing Cookie World InfoTrust
State of Flex Webinar [Dec 2024] Flex Index
3 Ways to Maximise Revenue Post Shopify Plus Migration Webinar ASK BOSCO®
Introduction to Customer Segmentation | 365 Data Science Online Course 365 Data Science
Webinar | Unlocking opportunities: FinOps strategies for MSPs Ternary
Propensity Score Matching econometricsacademy
An Introduction to Product Analytics AstroLabs
Lecture 11 Propensity Score Matching Richard Gallenstein
Predicting Customer Churn: A Case for Churn in Retail & E-Commerce DunnSolutions
Customer Lifetime Value: Models, Metrics and a Multitude of Uses - Brian Bloniarz PyData
Why start using uplift models for more efficient marketing campaigns Data Con LA
A Bayesian Approach to Media Mix Modeling (Michael Johns & Zhenyu Wang) PyMC Developers
Rev 1 "Uplift Modeling for Driving Incremental Revenue by Display Remarketing" - Robert Yi, Wayfair Domino Data Lab
Best Practices For Closing Sales Contracts Faster A Guide For In House Legal Departments In-House Connect