Mobile Phones and Outdoor Advertising: Measurable Advertising

Abstract

Television and newspapers sit at the top of many agency marketing plans, while outdoor advertising stays at the bottom. The reason for this is that it's difficult to account for who views a billboard, so there is no way of consistently determining the effectiveness of outdoor advertising. As a result, agencies do not consider the medium and allocate their money elsewhere. To change this situation, one needs to create new credible audience measurements for the outdoor marketing industry. Here we propose a new way of performing audience measurements that combines mobile phone location estimations with information freely available on the Internet. We show that it is possible to estimate the number of people who drive or walk by a given area in Greater Boston from location estimations of a large fraction of mobile phone users in the region. We also infer the preferences for social events of the users by combing their location estimations with Internet listings of social events. This makes it possible to profile areas based on their residents' interests and dynamically change displayed advertising based on those assessments.

Estimating Origin-Destination Flows Using Mobile Phone Location Data

“…At this level, noise is more evident (see Figure 4(b)), but still we can see on average a very good linear relationship between census estimation and our estimation. R 2 = 0.36 in this case, which is however very high compared to the R 2 = 0.10 of the gravity model 6 . The relatively low value of R 2 compared to the county level analysis is partially due to the fact that the relationship seems less linear for cases when the census estimates less than 10 trips from tract to tract.…”

“…mobile phone, smart cards, GPS devices and digital cameras) provide unprecedented digital footprints, telling where people are and when they are there. In former projects, different methodologies for detecting the presence and movement of crowds through their digital footprint (flickr photo, mobile phone logs, smart card record and taxi/bus GPS traces) were developed, see for instance [4]- [6]. This fine grained analysis can potentially make a big leap in terms of understanding the use of space and daily commuting flows for the purposes of urban mobility planning and management.…”

Retail in the Digital City

“…Likewise, other pervasive computing technologies show significant promise. Harnessing these technologies to augment the shopping experience has led to the term pervasive retail being coined, and a number of prototype solutions have been documented in the research literature, see for example (Strohbach & Martin, 2011;Kourouthanassis & Roussos, 2003;Yih et al, 2005;Sellitto et al, 2007;Quercia et al, 2011 …”

Representação, extração e avaliação de interações entre usuários de redes sociais online

“…Quercia et al [2010] desenvolveram uma nova tecnologia que silenciosamente produz informações de atualizações dos usuários para ajudar os adolescentes a cultivar suas relações sociais. Em um trabalho posterior, Quercia et al [2011] propuseram um sistema que combina a localização dos telefones celulares com 3.8 TRABALHOS RELACIONADOS 63 anúncios de eventos em Redes Sociais para criar estimativas do número de pessoas em um determinado local.…”

“…A modelagem, a análise e a visualização do comportamento social são exploradas nos trabalhos de Vinciarelli et al [2009] • Ligações sociais ativadas a partir de dispositivos móveis. As ligações sociais ativadas a partir de smartphones são foco de estudo nos trabalhos de Barkhuus and Tashiro [2010], Quercia et al [2010] e Quercia et al [2011]. O uso de aplicativos que são habilitados em dispositivos móveis, e ativam ligações sociais entre usuários, é analisado nos trabalhos de Lane et al [2010], Anthonysamy et al [2012], Egele et al [2012] e Wang [2012.…”