Planning profitable tours for field sales forces: A unified view on sales analytics and mathematical optimization

A key task of sales representatives in operational planning is to select the most profitable customers visit within next few days. strongly varying set scoring methods predicting or approximating expected response exists for this customer selection phase. However, case field forces, final interrelated with tour decisions. To end, we formalize variants problem as a multi-period team orienteering problem, thereby providing unified view on and In an extensive computational study real-world instances from retail industry, systematically examine impact aggregation level content information provided by method sensitivity proposed models concerning prediction errors. We show that variant depends available data. Furthermore, work out where put effort data acquisition phase get better tours.