Developing an open, national-level, small-area geodemographic classification of consumer behaviour
Ákos Balog, Les Dolega, Ron Mahabir, Patrick Ballantyne, Paul WilliamsonPurpose
This study fills a gap in consumer insight by developing an open, national-level small-area geodemographic classification. Existing frameworks overlook localised variations and fail to integrate consumer surveys. Our approach delivers a geodemographic classification of consumer behaviour across England and Wales.
Design/methodology/approach
We integrated the PDV Consumer Lifestyle Survey, 2021 Census and built-environment accessibility metrics. Spatial microsimulation is used to create synthetic populations at the Lower Super Output Area level, aligning individual attributes with PDV data to produce small-area estimates. Eight analytical domains (i.e. household composition, financial resilience, lifestyle, mobility, online engagement, social networks, shopping patterns and socioeconomic status) were derived from a conceptual frame which is then used to define an iterative variable selection. We then apply clustering to demographic and demand variables to derive primary and subclusters of consumer behaviour.
Findings
Four clusters emerged, each with distinct demand and demographic profiles. Affluent professional consumers, budget-conscious young urbanites, family-oriented suburban consumers and traditional rural consumers form the main clusters, and then nine further subclusters are derived. Results underscore how the domains derived from the conceptual framework shape small-area patterns.
Originality/value
Insights can inform targeted policy interventions and retail investment strategies by highlighting the spatial distribution of consumer needs. Opportunities for improving retail centre accessibility, fostering digital inclusion and tailoring product offerings can be derived. This classification lays the groundwork for future methodological advances, such as the use of agent-based modelling to simulate dynamic consumer–retail interactions under varying economic, social and environmental scenarios.