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School of Geography

Amanda Otley Amanda Otley

Contact details


School of Geography
University of Leeds
University Road
Leeds LS2 9JT   UK

Email:
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Project title

Generating a Leeds Geodemographic Classification: Applications in Policy, Commerce and Health

Project overview

Geodemographic classifications are commonly generated using national level data, predominantly from the decadal UK census, or generalised from national sample surveys. Given that regions and cities differ from one another in structure, governance, social norms and behaviours, there are societal, policy and commercial needs for city specific geodemographics. Moreover, in an age of ‘the big data revolution’ increasing volumes of real time data are emerging which could transform city-specific geodemographic segmentation, providing more granular classifications based on local demographic, compositional, behavioural and attitudinal insights available from local level data sources.

To date there are no examples of geodemographic classifications, accounting for attitudinal and transactional behaviours, built at a sub-national level. This project seeks to link academic, commercial and local authority datasets related to the city of Leeds to demonstrate the potential benefits of city specific geodemographics.

Aim: Create and apply a custom built geodemographic classification for Leeds at a household and small area level.

Objectives and approach:

(1) Generate a data driven Leeds specific geodemographic classification. This will involve integration of data sources and the application of the most appropriate and forward-thinking methods to generate a robust segmentation for wider application.

(2) Apply this classification to a range of case study applications to assess potential benefits and uplift relative to generic geodemographic systems. Case studies to be applied to a range of topical research areas for example; health, fuel poverty, employment opportunities, direct marketing and retail demand.

Supervisors

Dr Michelle Morris, Dr Andy Newing, Professor Mark Birkin

Cluster & research affiliations

Centre for Spatial Analysis and Policy

Funding

ESRC White Rose DTC studentship

Brief CV

Qualifications

  • Mathematics BSc
  • Geographical Information Systems MSc
  •  4.5 years of experience working as a Data Analyst/Data Scientist in digital marketing and market research environments matching emerging research to commercial problems and developing innovative cutting-edge data solutions.
  • Current Vice President of Leeds University Data Science Society.