A Cloud-Based AutoML Framework for Intelligent Sales Performance Optimization in Salesforce CRM Environments
DOI:
https://doi.org/10.63282/3050-9262.IJAIDSML-V3I2P116Keywords:
Cloud Computing, Automated Machine Learning (AutoML), Salesforce CRM, Sales Performance Optimization, Predictive Analytics, Intelligent CRM Systems, Sales Forecasting, Lead ScoringAbstract
The rapid adoption of cloud-based Customer Relationship Management (CRM) systems has transformed the way organizations manage customer data, sales pipelines, and business analytics. One of the most popular enterprise CRM platforms among such is Salesforce, whose scalable cloud architecture and embedded analytics have made it one of the most popular platforms. Nonetheless, the process of deriving meaningful insights out of great amounts of CRM data demands sophisticated machine learning skills that are unavailable to many organizations. Recently, the AutoML has become a potential solution that makes the creation of predictive models less challenging through the automation of data preprocessing, model selection, hyperparameter optimization, and performance evaluation. This paper presents an intelligent sales performance optimization based on the Salesforce CRM setting cloud-based AutoML framework. The suggested structure will combine Salesforce Sales Cloud data with cloud computing infrastructure and automatic machine learning piping in order to support predictive analytics on a larger scale. The architecture encompasses several functional layers which include data ingestion and integration, data processing and feature engineering, AutoML-based model development, and sales prediction and optimization engine. These elements combine to build predictive intelligence to sales forecasting, lead-score, customer-group, and opportunity-prioritization. The experimental analysis shows that the presented framework is much more successful in forecasting, turning leads into concrete decisions, and making decisions in general than the conventional CRM analytics tools. The cloud computing integration also guarantees scalability and processing the large datasets of CRM in real time and AutoML approaches make the creation of models less complicated. The findings suggest that intelligent CRM analytics with AutoML can promote data-driven sales approach and meaningfully increase the performance of the organization in general.
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