Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Zhao, Liyang, Seton, Olurotimi, Reddivari, Himadeep Reddy, Jena, Suvendu, Zhao, Shadow, Kumar, Rachit, Wei, Changshuai
Format: Preprint
Veröffentlicht: 2025
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2505.09847
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866915295981993984
author Zhao, Liyang
Seton, Olurotimi
Reddivari, Himadeep Reddy
Jena, Suvendu
Zhao, Shadow
Kumar, Rachit
Wei, Changshuai
author_facet Zhao, Liyang
Seton, Olurotimi
Reddivari, Himadeep Reddy
Jena, Suvendu
Zhao, Shadow
Kumar, Rachit
Wei, Changshuai
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2505_09847
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Causal Predictive Optimization and Generation for Business AI
Zhao, Liyang
Seton, Olurotimi
Reddivari, Himadeep Reddy
Jena, Suvendu
Zhao, Shadow
Kumar, Rachit
Wei, Changshuai
Machine Learning
Artificial Intelligence
Information Retrieval
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.
title Causal Predictive Optimization and Generation for Business AI
topic Machine Learning
Artificial Intelligence
Information Retrieval
url https://arxiv.org/abs/2505.09847