IRSIJun 18, 2015

Analyzing Web Behavior in Indoor Retail Spaces

arXiv:1506.05628v123 citations
Originality Synthesis-oriented
AI Analysis

This work provides insights into indoor consumer behavior for retail and marketing applications, but it is incremental as it applies existing methods to a new dataset.

The researchers analyzed 18 million Wi-Fi access logs from a shopping mall to study the link between physical retail behavior and web activity, finding that 60% of users browse the web and physical context slightly influences web content.

We analyze 18 million rows of Wi-Fi access logs collected over a one year period from over 120,000 anonymized users at an inner-city shopping mall. The anonymized dataset gathered from an opt-in system provides users' approximate physical location, as well as Web browsing and some search history. Such data provides a unique opportunity to analyze the interaction between people's behavior in physical retail spaces and their Web behavior, serving as a proxy to their information needs. We find: (1) the use of Wi-Fi network maps the opening hours of the mall; (2) there is a weekly periodicity in users' visits to the mall; (3) around 60% of registered Wi-Fi users actively browse the Web and around 10% of them use Wi-Fi for accessing Web search engines; (4) people are likely to spend a relatively constant amount of time browsing the Web while their visiting duration may vary; (5) people tend to visit similar mall locations and Web content during their repeated visits to the mall; (6) the physical spatial context has a small but significant influence on the Web content that indoor users browse; (7) accompanying users tend to access resources from the same Web domains.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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