Hyperlocal Analytics Cosimo Accoto WAS 2011

HyperLocal Analytics

WAS 2011 – Milano 20 Aprile 2011www.webanalyticstrategies.com

Cosimo Accoto Industry Analyst, Book’s Author and Researcher

Research Projects (Prof. Andreina Mandelli) at: BIT (SDA Bocconi – UCLA Los Angeles), DIGITAL MARKETS (USI, University of Italian Switzerland, Lugano)

HYPERLOCAL ANALYTICS

(…when bits come home)

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WAS 2011: Cosimo Accoto

… parleremo di web analyticsnell’iperlocalità

… esplorando concetti e approcci analitici emergenti

… con, infine, esempi di metriche in uso e in divenire


• Il code/space: la transduzione dello spazio“software make space”

• Il continuum ontologico delle hybrid realities“from embodied virtuality to virtual reality”

• L’interfaccia ubiqua e la net locality “space matter”

• in breve: mobile+social+geolocal+augmented

HyperLocality/HyperReality

WAS 2011: Cosimo Accoto Source: Dodge and Kitchin, 2011, p.2; Gordon and de Souza e Silva, 2011; Farman, 2011


• Mobile/Location-based Marketing

• Real-time/Near Real-time DMS (POI)

• Near-field Comm/Short-range Wireless

• Context-aware/Sensory-Inscribed Body

• Mobile Augmented Reality (MAR)

“Location” as marketing enabler



Location-based o Location-sharing services?

Source: Bellavista et alii, 2008; Brimicombe and Li, 2009; Ahson and Ilyad, 2011.

“… to deliver information services to the mobile clients on the move at the right time and right location"


“ … services where the content of those services is tailored to the current or some projected location and context of a mobile user "


Social disclosure of spatial information(neogeography, mapping 2.0, partecipatory gis, voluntereed geo information …)

“Social location sharing is the term I use to describe the various services that require a user to actively share his or her location with a network. This network is a group of people and companies with whom the user has agreed to share that information, as well as a broader network via connected social media platforms. It is the active nature of these services that sets them apart from the other services, which are passive in nature. This active partecipation makes them so intriguing and so compelling for marketers”

Source: Salt, 2011.WAS 2011: Cosimo Accoto


• Geosocial/SocioLocal/Co-proximity marketing• From Social Graphs to Spatial Networks• Spacetemporality >> Malleable Social Networks*• Social Gaming, Gamification Theory• Social Networks + Sensors Networks

• Critical issues: locational privacy, real-time/geodata info, innovation-adoption approach, open api, value to customers, brand ubiquity ??

“Location sharing” as marketing enabler

WAS 2011: Cosimo Accoto Source: * Evans, 2011.


Mapping Location-sharing platforms

Source: adapted from Wikipedia, 2011; Cosimo Accoto, 2011WAS 2011: Cosimo Accoto


• Mobile, In-Apps, QR code Analytics• Location-based Analytics• Location-sharing Analytics• Game & In-game Analytics• Augmented Analytics• Reality Mining




Location-based Analytics a (con)temporary definition

• Location-based analytics measure the timing, quantity, and depth of a location-based engagements.

• By location-based engagements (LBE) we mean how users interact with the places they visit via their mobile handsets.

• These engagements might be in the form of a check-in (the simplest form of an LBE) or a deeper engagement such as posting a photo, leaving a tip, or pushing a check-in notification to Facebook or Twitter”

(Derek Browers, Biz Development at MomentFeed)

Source: D. Browers, Personal Interview, 2011 WAS 2011: Cosimo Accoto


From WA to LBS metrics(checkin-centric approach)

Source: Chung, Lu and Tambay, 2010 WAS 2011: Cosimo Accoto


Social Location Metrics

& Location Intelligence

a) LBS Analytics Features and Dashboards

b) Multi Location-Based Platforms Vendors

c) Academic/Lab Studies and Measurements

… a titolo di esempio dei tre approcci analitici



Source: Aboutfoursquare (Foursquare Analytics, after March 2011) WAS 2011: Cosimo Accoto

(a) Foursquare Analytics

New Dashboard:

• # check-ins (total, average..)

• social reach (shared with twitter, FB)

• time breakdown

• gender / age breakdown

• top/most recent visitors..

• special stats: total days run, # views, # unlock tallies

Previous time period trend


(a) Advanced LBS Metrics ??

Source: Leist, 2011WAS 2011: Cosimo Accoto


(a) Beyond Checkins?

Source: Sietsema, March 2011WAS 2011: Cosimo Accoto


(b) Multi LBS Analytics Platforms

Source: D. Browers, MomentFeed, 2011WAS 2011: Cosimo Accoto

• Checkins Traffic (CT)

• Engagement Score (ES)

• Competitive CT e ES


Source: A. Pallian, Geotoko, after March 2011 WAS 2011: Cosimo Accoto

(b) Multi LBS Analytics Platforms• Checkins Traffic

• Demographics

• New/Returning people to venue


# Day of week Checkins

WAS 2011: Cosimo Accoto Source: A. Pallian, Geotoko, after March 2011

(b) Multi LBS Analytics Platforms

# Time per day Checkins


(b) LB Analytics Platforms

WAS 2011: Cosimo Accoto Source: A. Pallian, Geotoko, after March 2011

• Location Heatmap

• Social Influence of people



(c) Academic/Lab LBS Measurements

“Social networks, instead, have been largely studied from a purely topological perspective, focusing on the structural position of their nodes and on structural mechanisms that describe their evolution”.

(…) A more accurate modelling of these networks requiresthe incorporation of processes mingling social and spatial factors. An interesting possibility is related to gravity models, which have long been used to model connections inspatial networks”

Source: Noulas, Scellato, Lambiote, Mascolo, 2011


Source: Noulas, Scellato, Mascolo, Pontil, 2011WAS 2011: Cosimo Accoto


• Entropy of location

• Inter-checkins time

• Inter-checkins distance

“…an analysis of the geotemporal dynamics of collective user activity on Foursquare and show how checkins provide a means to uncover human daily and weekly patterns, urban neighborhood properties and recurrent transitions between different activities” (p. 1).

• Gravity Models


Source: Cheng, Caverlee, Lee, Sui, 2011 WAS 2011: Cosimo Accoto


• Distance-based Displacement

• Radius of gyration

• Returning probability

“ … we study the wheres and whens of over 22 million checkins across the globe. We study human mobility patterns revealed by these checkins and explore factors that influence this mobility, including social status, sentiment, and geographic constraints.” (p. 1).

• User Social Status/Sentiment


• Santa Clara (California)• 1 topic and 3 full-days

Source: Where 2.0 websiteWAS 2011: Cosimo Accoto


WAS 2011 – Milano 20 Aprile 2011www.webanalyticstrategies.com

Cosimo Accoto

twitter: @cosimoaccotoskype: cosimo.accoto

Industry Analyst, Book’s Author and ResearcherResearch Projects at BIT (SDA Bocconi – UCLA Los Angeles), DIGITAL MARKETS (USI Lugano),


(and… forthcoming)(available)(available)

Business

Hyperlocal Analytics Cosimo Accoto WAS 2011