论文标题
客户网络：用于预测新客户的交互式模型
Client Network: An Interactive Model for Predicting New Clients
论文作者
论文摘要
随着公司旨在扩大其市场基础，了解潜在客户变得越来越重要。传统方法通常会孤立地对待每个客户，要么研究其互动或与现有客户的相似之处。我们建议客户网络，该网络考虑了整个客户端生态系统，以通过复杂的网络分析来预测目标客户的销售销售成功。它结合了一种新颖的排名算法与数据可视化和导航。基于公司与客户之间的历史互动数据，客户网络利用组织连接来定位前瞻性客户的最佳途径。用户界面支持探索客户端生态系统并执行销售必需的任务。我们的实验和用户访谈展示了客户网络的有效性及其在支持卖家日常任务方面的成功。
Understanding prospective clients becomes increasingly important as companies aim to enlarge their market bases. Traditional approaches typically treat each client in isolation, either studying its interactions or similarities with existing clients. We propose the Client Network, which considers the entire client ecosystem to predict the success of sale pitches for targeted clients by complex network analysis. It combines a novel ranking algorithm with data visualization and navigation. Based on historical interaction data between companies and clients, the Client Network leverages organizational connectivity to locate the optimal paths to prospective clients. The user interface supports exploring the client ecosystem and performing sales-essential tasks. Our experiments and user interviews demonstrate the effectiveness of the Client Network and its success in supporting sellers' day-to-day tasks.
