Causal Predictive Optimization and Generation for Business AI
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Abstract (arXiv)
The sales process involves sales functions converting leads or opportunities to customers and selling more products to existing customers. The optimization of the sales process thus is key to success of any B2B business. In this work, we introduce a principled approach to sales optimization and business AI, namely the Causal Predictive Optimization and Generation, which includes three layers: 1) prediction layer with causal ML 2) optimization layer with constraint optimization and contextual bandit 3) serving layer with Generative AI and feedback-loop for system enhancement. We detail the implementation and deployment of the system in LinkedIn, showcasing significant wins over legacy systems and sharing learning and insight broadly applicable to this field.
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References · 5
- 2017Meta-learners for Estimating Heterogeneous Treatment Effects using Machine Learningcited by 478
- 2015Recursive Partitioning for Heterogeneous Causal Effectscited by 255
- 2022Sample-Then-Optimize Batch Neural Thompson Samplingcited by 25
- 2023Neural Contextual Bandits for Personalized Recommendationcited by 10
- 2024Ads Supply Personalization via Doubly Robust Learningcited by 2
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