Metrics, locations, and lift: mobile location analytics and the production of second-order geodemographics

ABSTRACT

This article examines the relationship between location data and geodemographic knowledge by focusing on the role of the third-party mobile location analytics companies that passively capture location data from mobile advertising exchanges to develop new approaches to audience measurement. It argues that in addition to segmentation, a key objective is to calculate the performativity of algorithmically targeted advertising by measuring its capacity to drive foot traffic to particular locations. This is known as measuring audience ‘lift’ and reveals how the value of location data depends on how metrics can be created to prove their ability to influence behaviour. ‘Second-order geodemographics’ is proposed as a concept for theorizing the relationship between location-based classification and measurement and is grounded in a case study of one company to illustrate the ecosystem of mobile location analytics.

KEYWORDS:

• Mobile technology
• surveillance/privacy
• geographic information systems
• mobile marketing
• location data

Disclosure statement

No potential conflict of interest was reported by the author.

Notes on contributor

Harrison Smith is a research associate for the School of Architecture, Planning and Landscape at Newcastle University working with the Global Urban Research Unit (GURU). His research focuses on the economic and cultural impact of location analytics for smart cities and digital economies.

ORCID

Harrison Smith http://orcid.org/0000-0001-8144-5754 

Notes

1 https:// www.placeiq.com/who-we-are/.

2 The extent to which this approach to mapping is entirely new is subject to some scrutiny; for example, Galpin’s (1915) The social anatomy of an agricultural community details an early instance of ecological mapping in Walworth County, Wisconsin, whereby maps were created to measure how far residents had to travel to access particular resources such as a bank, grocery store, or library.

3 Sometimes, marketers also use the term ‘conversion’ to describe audiences that were successfully converted into buyers or some other desired objective. Lift is based on using an experimental or quasi-experimental research designs whereby a portion of users are assigned into a treatment or control group in order to better understand what effect geo-targeted content had on changing behaviour.

4 For a more detailed explanation of the Android’s Advertising API, see: https://developers.google.com/android/reference/com/google/android/gms/ads/identifier/AdvertisingIdClient.

5 See the Interactive Advertising Bureau’s Mobile Location Working Group’s (2016) white paper on collecting and using location data for further details. Retrieved from https://www.iab.com/wp-content/uploads/2016/04/IAB_Mobile-Location-Data-Guide-for-Publishers_Feb2016-Revised.pdf.

6 https:// www.placeiq.com/measurement/.

7 PlaceIQ boasts many partners in their network, including companies that deal in selling purchase history, and TV viewership data. In 2016, PlaceIQ partnered with Nielsen Catalina for measuring the purchase histories, retail visits, and recreational activities of the consumers for the Consumer Package Goods (CPG) market. See https:// www.placeiq.com/partners/ for a list of Place IQ's third party data partners.

8 https:// www.placeiq.com/technology/.

Additional information

Funding

This work was supported by Social Sciences and Humanities Research Council of Canada [grant number 752-2014-2618].