Today, the organizations advertise and sell their products online and offline but they face the issue of managing their sales and inventory. A crucial part of their businesses is maintaining relationships with their customers, preventing them from churning out, track decreasing brand loyalty and taking steps to prevent it, and increasing profitability. This paper focuses on efficiently automating the sales processes and making a more accurate system for improving customer retention and extension, than previous software’s. An extensive research done on existing systems gave us an insight into their shortcomings which this system attempts to overcome by using predictive analytics. Using decision trees and random forests in machine learning, the accuracy of the algorithm improves over time to give us better results progressively. The implementation of this system has resulted in better resource utilization, increased responsiveness and accurate forecasting of customer behaviour. This system has been implemented to seamlessly integrate with any ERP system for efficient stock management and an Android application to track the employees and keep them updated with their tasks.

Salesforce automation classification predictive analytics