The Role of Machine Learning in Automating Sales Processes and Customer Support within CRM Systems

In the era of AI, the integration of ML in CRM has significantly transformed how sales automation and customer support is conducted. This includes the use of ML to improve predictive analytics, lead scoring, customer segmentation, and the intelligent automation of sales workflows. Furthermore, it also globalizes that of natural language processing (NLP) and conversational AI in terms of automated customer interaction, optimizing response times and customer satisfaction. The contributions of advanced ML models such as deep learning and reinforcement learning toward sales forecasting, churn prediction, and personalized recommendation systems are examined. It also talks about how anomaly detection is used for fraudulent activity detection and how AI-powered chatbots minimize human intervention. By reviewing existing frameworks, issues such as data privacy, model interpretability, and system integration are attained. This study contributes to our understanding of how ML-driven automation in CRM system is being adopted by enterprises and provide recommendations for how to improve such adoption.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-06
DOI
https://doi.org/10.5281/zenodo.15597591
Primary Topic
Customer churn and segmentation
Type
article
Field-Weighted Citation Impact
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article

The Role of Machine Learning in Automating Sales Processes and Customer Support within CRM Systems

Zenodo (CERN European Organization for Nuclear Research)
Customer churn and segmentation
article

The Role of Machine Learning in Automating Sales Processes and Customer Support within CRM Systems

article en

Abstract

In the era of AI, the integration of ML in CRM has significantly transformed how sales automation and customer support is conducted. This includes the use of ML to improve predictive analytics, lead scoring, customer segmentation, and the intelligent automation of sales workflows. Furthermore, it also globalizes that of natural language processing (NLP) and conversational AI in terms of automated customer interaction, optimizing response times and customer satisfaction. The contributions of advanced ML models such as deep learning and reinforcement learning toward sales forecasting, churn prediction, and personalized recommendation systems are examined. It also talks about how anomaly detection is used for fraudulent activity detection and how AI-powered chatbots minimize human intervention. By reviewing existing frameworks, issues such as data privacy, model interpretability, and system integration are attained. This study contributes to our understanding of how ML-driven automation in CRM system is being adopted by enterprises and provide recommendations for how to improve such adoption.

Zenodo (CERN European Organization for Nuclear Research)
Greatbatch (United States) (US)
Openalex Percentile: Top 48%
Customer churn and segmentation
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The Role of Machine Learning in Automating Sales Processes and Customer Support within CRM Systems · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS