为现场销售队伍规划盈利路线：销售分析与数学优化的统一视角
Planning profitable tours for field sales forces: A unified view on sales analytics and mathematical optimization
AI总结：
本文将盈利销售代表路线问题形式化为多周期团队定向问题，统一了客户评分与路线规划，并基于零售业真实数据揭示了数据可用性对模型选择的影响及数据获取的优化方向。
摘要：
现场销售队伍在直接营销中发挥着重要作用，特别是对于在企业对企业背景下提供复杂产品、服务或解决方案的公司而言。销售代表在运营规划中的一项关键任务是在接下来的几天内选择最有潜力的客户进行拜访。在运营层面上，销售代表的一项关键任务是在接下来的几天内选择最有潜力的客户进行拜访。针对这一客户选择阶段，存在多种差异很大的评分方法来预测或近似预期的客户响应。然而，对于现场销售队伍而言，最终的客户选择与路线规划决策密切相关。为此，我们将盈利销售代表路线问题的变体形式化为一个多周期团队定向问题，从而为客户评分和路线规划阶段提供统一视角。在基于零售业真实实例的广泛计算研究中，我们系统地考察了评分方法提供的聚合水平和信息内容的影响，以及所提出模型对预测误差的敏感性。我们表明，客户评分和路线规划变体的选择取决于可用数据。此外，我们明确了在数据获取和评分阶段应在何处投入精力，以获得更好的运营路线。
英文摘要：
Field sales forces play an important role in direct marketing, especially for companies offering complex products, services, or solutions in the business-to-business context. A key task of sales representatives in operational planning is to select the most promising customers to visit within the next days. On an operative horizon, a key task for sales representatives is to select the most promising customers to visit within the next days. A strongly varying set of scoring methods predicting or approximating the expected response exists for this customer selection phase. However, in the case of field sales forces, the final customer selection is strongly interrelated to the tour planning decisions. To this end, we formalize variants of the profitable sales representatives tour problem as a multi-period team orienteering problem, thereby providing a unified view on the customer scoring and the tour planning phase. In an extensive computational study on real-world instances from the retail industry, we systematically examine the impact of the aggregation level and the content of information provided by a scoring method and the sensitivity of the proposed models concerning prediction errors. We show that the selection of a customer scoring and tour planning variant depends on the available data. Furthermore, we work out where to put effort in the data acquisition and scoring phase to get better operational tours.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
