大数据驱动的快消品终端拜访“云-边”联动决策与优化

Big Data-driven FMCG Terminal Visits"Cloud-side"Based Decision-making and Optimization

随着我国的快消品消费市场快速增长,快消品公司的终端拜访成本显著增加,同时终端拜访场景面临着终端信息的实时获取、动态的决策与客户需求动态响应的问题。提出针对快消品终端拜访问题的“云边联动信息架构”,设计“动态云边联动机制”,同时结合深度强化学习算法优化系统决策。经试验仿真结果表明,有效地减少终端拜访人员的在途里程数。针对快消品终端拜访场景,能有效地提高公司终端拜访人员的服务水平,维系客情关系,从而达到提高销量、提升订单转化率等目的。

With the rapid growth of consumer market of FMCG(Fast moving consumer goods),companys'terminal visit cost have increased significantly.At the same time,the terminal visit scene is faced with the problems of obtaining terminal information in real time,making dynamic decisions and responding to customer demand dynamically.The"dynamic cloud-side linkage information architecture"and"dynamic cloud-side linkage mechanism"for FMCG terminal visit problem is proposed.At the same time,the deep reinforcement learning algorithm is used to optimize the system decision.The simulation results show that it can effectively reduce the traveling mileage of terminal visitors.For the FMCG terminal visit scenario,it can effectively improve the terminal service level of enterprises,maintain customer relationship,so as to achieve the purpose of increasing sales volume and order conversion rate.