Moving Towards Real-Time Geodemographic Segmentation

MOVING TOWARDS REAL-TIME GEODEMOGRAPHIC SEGMENTATION Dr Alex D Singleton Department of Geography and Centre for Advance Spatial Analysis , University College London www.alex-singleton.com

London Terraces Council Flat Blue Collar Central Districts

SEGMENTATIONS ARE CREATED BY CLUSTER ANALYSIS Area V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 ... Area1 Area2 Area3 Area4 Area5 Area6 Area7 Area8 ...

CLUSTER ANALYSIS Variable 2 Variable 1

CLUSTER ANALYSIS Variable 2 Cluster 1 Cluster 2 Variable 1 Cluster 3

OUTPUT Area Cluster Area1 1 Area2 1 Area3 2 Area4 1 Area5 3 Area6 3 Area7 3 Area8 2 ...

NEED FOR REAL TIME GEODEMOGRAPHICS • Current classifications are created using static data sources. • Rate and scale of current population change is making large surveys (census) increasingly redundant. • Significant hidden value in transactional data • Data is increasingly available in near real time • Application specific (bespoke) classifications have demonstrated utility.

REALTIME GEODEMOGRAPHICS Speciﬁcation Estimation Testing

REALTIME FEEDS OF DATA • Involve integration of large and possibly disparate databases • Common protocol • XML: E.g. UK Neighbourhood Statistics API • Formal • E.g. Doctor registrations; HE Data; Census data • Informal • Is there any value in other non- traditional data sources?

http://www.loopt.com/phones/iphone SOCIAL GPS

http://smalltalkapp.com

http://senseable.mit.edu/

STORE CARDS

What information can be extracted?

ONLINE SPECIFICATION INPUTS • Usability • Expert V Non-Expert Users • Non-Expert Users • Pre selection of variables and weighting for speciﬁc application • Expert Users • Selection of any variable and any weighting

CLUSTERING K=4 • K-Means algorithm: Unstable - initial start conditions effect the results • Measured within sum of squares or R2

CLUSTERING • Alternate algorithms? • PAM (Partitioning around medoids) tries to minimize the sum of distances of the objects to their cluster centers. • CLARA draws multiple samples of the dataset, applies PAM to each sample and returns the best result. • GA (Genetic Algorithm) is inspired by models of biological evolution. Produce results through a breeding procedure.

CLUSTERING or... reﬁne k-means ~99% Similar K=4 K-means result for 41 “OAC variables” K-means result for 26 OAC Principle Components

VISUALISATION

STATE OF THE ART • Slowly moving beyond: • Idea of expert producers • General purpose classifications • There is only one correct representation • Creating classifications which are • Responsive to changes in local populations • Fit for purpose (bespoke classifications) • Open to scrutiny and verifiable by the public

SO WHAT DOES A FUTURE GEODEMOGRAPHIC LOOK LIKE?

Moving Towards Real-Time Geodemographic Segmentation

by Alex Singleton

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