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In many companies, sales leads are prioritized manually by sales people. This takes up a lot of time and is not always accurate, thus leading to spending time on leads that are not likely convert. For a €2 bn revenue company, we tackled this issue by automating the process of lead prioritization to enable the sales team to be more efficient.
The main challenges during the process were developing a fine-tuned set of factors that could influence sales success. In addition, we worked with the client to extract data 30 years of data from their CRM system.
Our model used supervised learning to build a forecasting model, which assists the sales force by suggesting which lead to follow. The prediction model is based on historic data as well as on new upcoming sources of data. Due to our system, the client recorded significant time savings and efficiency gains.