# Using clustering of rankings to explain brand preferences with personality and socio-demographic variables

## TL;DR

This study explores how consumer preferences for brands can be segmented into groups using background variables, examining the roles of personality and socio-demographics, with mixed results across different samples.

## Contribution

It investigates the effectiveness of clustering preferences and relating background variables to consumer segments, highlighting the limited and inconsistent role of personality variables.

## Key findings

- Personality variables contributed significantly in one sample.
- Results were not replicated in a more heterogeneous sample.
- Socio-demographic variables showed limited contribution.

## Abstract

The primary aim of market segmentation is to identify relevant groups of consumers that can be addressed efficiently by marketing or advertising campaigns. This paper addresses the issue whether consumer groups can be identified from background variables that are not brand-related and how much personality vs. socio-demographic variables contribute to the identification of consumer clusters. This is done by clustering aggregated preferences for 25 brands across 5 different product categories, and by relating socio-demographic and personality variables to the clusters using logistic regression and random forests over a range of different numbers of clusters. Results indicate that some personality variables contribute significantly to the identification of consumer groups in one sample. However, these results were not replicated on a second sample that was more heterogeneous in terms of socio-demographic characteristics and not representative of the brands' target audience.