AI in Sales Call Analytics

In the era of big data, sales predictions are gaining popularity and transitioning towards various types of data analysis to enhance competitiveness in business. In industries where sales calls play a crucial role in reaching out to customers, sales call analytics has become a top priority for organisations. Manual analysis of sales calls is a time-consuming and sometimes inconsistent process. Automating this process and implementing several machine learning algorithms to comprehend unknown information contribute to improving productivity and reducing customer churn. Since data is the most valuable asset in the current market scenario, data security and governance are essential aspects of the analysis. Environmental impact and sustainability are also crucial considerations to incorporate into proposed solutions for a better future. In this chapter, sales call analytics has been explored and developed as a platform-agnostic and data-driven decision-making framework. Call records have been analysed to derive meaningful insights and key performance indicators (KPIs) for informed decision-making. Finally, the sustainable impact of the solution has been discussed. This approach to solutions promotes equality in decision-making without discrimination. Such a framework can be accessible through quality training and assessment services.