Summary
This case study outlines the implementation of a lead scoring system for Wholesales Flights, a travel agency specializing in premium class airfare. The objective was to address stagnant conversion rates despite previous efforts in training, user experience improvements, and marketing. The solution involved revamping the management process by utilizing machine learning to predict which users were likely to respond positively to calls from travel managers. By analyzing user requests and behaviors, the system prioritized leads based on their likelihood to convert, thus enhancing the efficiency of the sales process. The technology stack included Python, MySQL, and machine learning algorithms such as gradient boosting. As a result of this implementation, Wholesales Flights experienced a 17% increase in sales growth, demonstrating the effectiveness of the lead scoring system in improving conversion rates and optimizing resource allocation among travel managers.
