Abstract
As a result of significantly growing competition from online-only retailers, physical store retailers have resorted to measures such as discount coupons, online price matching, sale events, and a seamless omnichannel customer experience. One important, often overlooked method is <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">partner-marketing</i> , where a retailer promotes products or services offered by other merchants. The main challenge in partner-marketing is finding partners, i.e., determining whom a retailer should choose as partners among many choices. In this paper, we discuss how a retailer can make use of rich information from mobile and geo-social media to find potential partners in a geographic region. The explosion of mobile and geo-social media in recent years has led to increasing insights about consumers' footprints—which shops they visit, where they travel, and where they live and work. In addition, geo-social data also reveals which regional merchants are popular and why. We propose a series of partner-finding techniques that leverage geo-social data at increasing granularity and discuss analytics to rank potential partners. We present compelling business case studies using real data from Foursquare, a social networking website. We also discuss how retailers can combine geo-social data with traditional data such as demographics, weather information, and their own marketing databases to personalize partner-marketing.
Published Version
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