I-Corps: Business Analytics for Large Scale Intelligence

I-Corps：大规模智能业务分析

• 批准号: 1530914
• 负责人: Yung-Hsiang Lu
• 金额: $ 5万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-04-15 至 2016-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1530914&HistoricalAwards=false
• 关键词: Corps; Business; Analytics; Large; Scale

For the last 20 years, traditional "brick-and-mortar" stores have been trying to find strategies to compete with on-line store in understanding customers' behaviors and preferences. An on-line store can easily create personalized advertisements, based on what a customer has purchased and seen. In contrast, traditional stores do not have such information and cannot provide personalized experience attracting customers into the stores and encouraging customers to buy after they are in the stores. Understanding customers' needs are currently met by surveys, focus groups, in-store observers, sales records, and market trends. Surveys and focus groups are costly and disrupt customers' buying process. In-store observers are labor-intensive and cannot record many customers' activities at once. Sales records show what has been sold, without any information about why customers do or do not purchase products. This research team has created the Business Analytics for Large-Scale Intelligence (BALSI) system that allows retailers to make real time, dynamic, and personalized advertisements and promotions to attract customers into the stores.The BALSI system uses visual analysis of video stream from in-store camera systems to observe a shopper's behavior, movement, gaze and other actions. From such data, information can be mined to help the retailer better attract, retain, and satisfy customers. BALSI's software solution analyzes the videos captured in stores without interfering with the customers and does not require any additional employees. The software will analyze the characteristics of customers to presents trends and patterns to the clients and to create dynamic advertisements to attract the customers into stores. Inside the store, the software can adaptively try to increase the likelihood of a purchase by a shopper. BALSI's software also augments human sales people by alerting a store associate to help a customer that appears to be looking for something. The technology does not recognize faces and offers better privacy protection when compared with technologies that attempt do similar things within the retail area by tracking the signals coming from a customer's phone.

过去 20 年来，传统的“实体”商店一直在努力寻找策略，在了解顾客的行为和偏好方面与网上商店竞争。在线商店可以根据客户购买和看到的内容轻松创建个性化广告。相比之下，传统商店没有这些信息，无法提供吸引顾客进店并鼓励顾客到店后购买的个性化体验。目前，了解客户的需求是通过调查、焦点小组、店内观察员、销售记录和市场趋势来满足的。调查和焦点小组的成本很高，而且会扰乱客户的购买过程。店内观察员属于劳动密集型工作，无法同时记录许多顾客的活动。销售记录显示已售出的商品，但没有任何有关客户购买或不购买产品的原因的信息。 该研究团队创建了大规模智能商业分析 (BALSI) 系统，允许零售商制作实时、动态和个性化的广告和促销活动，以吸引顾客进入商店。BALSI 系统使用店内摄像系统的视频流的视觉分析来观察购物者的行为、动作、目光和其他动作。从这些数据中，可以挖掘信息来帮助零售商更好地吸引、保留和满足客户。 BALSI 的软件解决方案可以分析商店中捕获的视频，而不会干扰顾客，也不需要任何额外的员工。该软件将分析顾客的特征，向顾客展示趋势和模式，并创建动态广告来吸引顾客进入商店。在商店内，该软件可以自适应地尝试增加购物者购买的可能性。 BALSI 的软件还可以提醒店员帮助似乎正在寻找商品的顾客，从而增强销售人员的能力。与试图通过跟踪来自客户手机的信号在零售区域内执行类似操作的技术相比，该技术无法识别面孔，并且提供更好的隐私保护。