Behavioral Analytics In Multi-Channel Retail: Network Infrastructure Implications

Abstract

Behavioral Analysis is becoming more important in Multi-channel retail, not just for on-line shops, but also for off-line environments. The implication of such analytics is the provision of a "Personal Shopper" service for all customers, which requires a considerable amount of knowledge. Know-how is required for designing, deploying, monitoring and maintaining the shop floor infrastructure, which is also capable to deliver contextual content to mobile devices. By now, location-based services in the physical world are attracting attention. The importance of adding Value-Added Services to the physical retail environment is also well acknowledged. However, in order to accomplish such services, it is required to master the considerable amount of data how people or groups behave in the store area over time. Such data is needed not just for business operations, but also to optimize the shop floor intrusion of the network infrastructure. The need to have High-Precision Indoor Location available as a Utility Service is not yet clearly reflected in the design of the indoor networks. The most prominent are Wireless Local Area Networks; however also, Optical Networks using Visible Light [1]Communication technologies are found capable of indoor location and behavioral analytics. In this paper, we discuss implications on the indoor network infrastructure and propose an approach to such a network design and optimization. We are proposing a high-precision indoor location design in which locators are used to pre-process the raw signal information required for HPIL-based behavioral analysis. Locators are preferring Visible Light Communication supported basic service sets in combination with WLAN or Optical Wireless Hybrid Networks in the Off-Line Model approach. OWHNs based on Mobile Relays are focusing customers in the shop area- or item/service-specific hotspots.