The locative imaginary: Classification, context and relevance in location analytics

Abstract

The location analytics industry has the potential to stimulate critical sociological discussions concerning the credibility of data analytics to enact new spatial classifications and metrics of socio-economic phenomena. Key debates in the sociology of geodemographics are revisited in this article in light of recent developments in algorithmic culture to understand how location analytics impacts the structural contexts of classification and relevance in digital marketing. It situates this within a locative imaginary, where marketers are experimenting with consolidating the epistemes of behavioural targeting, classification and performance evaluation in urban environments through spatial analytics of movement. This opens up future research into the political and cultural economies of relevance in media landscapes and the social shaping of valuable subjects by third-party data brokers and analytics platforms that have become matters of public and regulatory concern.

Big data: The effect of analytics on marketing and business

“…To continue the map analogy, Smith (2020) explores the use of location data and its ability to invest “specific meanings into the social relationship between people and places.” He explains that “geodemographic clustering…allows for the classification of populations through postal codes” (Ibid). The ability to pinpoint user location has existed for at least a decade and allows a business to determine overlap in the location of the group they want to reach with advertisement and where that group exists in key high traffic areas.…”

The algorithmic fix: Location intelligence, placemaking, and predictable futures

“…In some cases, unsupervised machine learning models are deployed to predict 'a likelihood of the respective consumer engaging in behavior associated with a corresponding one of the psychographic segment', since labelling data sets for each segment is not widely available (PlaceIQ, 2019). These automatically generated and cross-referenced profiles are then used to fix various media content for intended audience based on location analytics (Smith, 2019(Smith, , 2020. As the existing market segmentation databases work on the level of households, location intelligence becomes a key for differentiating between different users in any given household with finer detail and granularity (Qualcomm, 2018).…”

“…I build on the existing studies on location intelligence and location analytics (e.g. Barreneche, 2012;Smith, 2019Smith, , 2020Wilken, 2019a) and geodemographic profiling and segmentation (e.g. Burrows and Gane, 2006).…”

Failed hybrids: The death and life of Bluetooth proximity marketing

“…The standards allowed technical systems to span multiple sites of activity, enabled interoperability across heterogeneous settings, and were enforced by the operating systems as (de facto) standard-setting bodies (Bowker & Star, 1999, p. 12). Most importantly, the standards indicated to investors that beacons might finally scale to an industrially viable level—that consumers’ physical mobility could be subject to the same analytics and revenue capture as their web traffic (Smith, 2020; Van Couvering, 2008). But Apple and Google’s rivalry would have consequences for the proximity industry.…”

“…Such lofty ambitions resonate with a wholesale transformation of commercial life that accelerates corporations’ capacity to extract massive amounts of data about consumer activity, online and off (Turow, McGuigan & Maris, 2015; see also Smith 2020). What makes beacons’ story striking though is how short-lived their role in the retail revolution would be.…”