B2B Sales Forecasting (Rimini Street)

Summary

Every quarter, the sales team at Rimini Street must forecast which opportunities will close. Accuracy is critical as these forecasts drive decision-making around prioritization, resource allocation, and compensation. Considering all this information and contextualizing it for forecasting is extremely time consuming for the sales team. This project aims to support the sales team by developing a machine learning model that predicts the outcome of a sale, represented through a dashboard. This dashboard enables the sales team to gain deeper insights into all factors influencing each sale.