Design considerations for multi-stakeholder display analytics

Abstract

Measuring viewer interactions through detailed analytics will be crucial to improving the overall performance of future open display networks. However, in contrast to traditional sign and web analytics systems, such display networks are likely to feature multiple stakeholders each with the ability to collect a subset of the required analytics information. Combining analytics data from multiple stakeholders could lead to new insights, but stakeholders may have limited willingness to share information due to privacy concerns or commercial sensitivities. In this paper, we make the case for the synthesis of analytics data in display networks, present design considerations for future architectures designed to enable the sharing of display analytics information, and consider how such systems might be implemented.

Scheduling Content in Pervasive Display Systems

“…While traditional display networks have operated as largely closed systems (managed by a single organisation), there has been increasing interest in stimulating innovation by creating "open display networks" that can accommodate content and control from multiple sources [26]. Such networks are characterised by open APIs and software components that enable developers to create new signage applications [26,83], techniques for enabling content ingestion from multiple sources [21], and recognition of the complex set of stakeholders that exist in such networks [4,21,63,89]. In [26] the authors provide three example scenarios of potential applications for open display networks:…”

“…The problem is compounded by the diverse set of stakeholders involved. Prior research has identified four stakeholders in typical public display deployments: display owners, space owners, content providers, and viewers [4,21,63,89]. In traditional display systems many of these stakeholders are represented by a single organisation (e.g.…”

“…Contemporary scheduling systems use essentially fixed schedules with, in advanced systems, some minimal tailoring of content or scheduling decisions based on the presence of viewers in particular demographic categories as identified by video analytics [46]. However, recent research [63] suggests that there are opportunities to combine much richer sets of analytics data to drive scheduling decisions. For example, combining analytics of human movements through a shopping mall with signage analytics could enable multiple new types of scheduling including selecting content items specifically to influence mobility patterns -perhaps to guide viewers to specific stores with sales events or to slow down or re-route viewers for safety reasons.…”