Adaptation and resilience in retail: Exploring consumer clusters in the new normal

Purpose

This research delves into the diverse responses of individuals to the challenges of the COVID-19 pandemic and subsequent shopping behaviour.

Design

Based on the K-means clustering algorithm, a comprehensive analysis of survey data identifies distinct consumer clusters based on their adaptive capacities, resilience, and shopping preferences. The study encompasses a broad demographic spectrum, examining various aspects such as age, urban or rural residence, education, household size, and income.

Findings

The findings identify several clusters of consumers showing specific behaviour during the COVID-19 pandemic and their subsequent shopping behaviours, unveiling distinct profiles of adaptation, resilience, and shopping preferences. The K-means clustering algorithm allows the identification of four distinct consumer clusters.

Implications

The results have significant implications for understanding consumer behaviour, tailoring marketing strategies, and shaping the future of retail under the New Normal. Each cluster's characteristics provide valuable insights for businesses to align strategies with evolving consumer needs, considering both demographic factors and shopping preferences.

Originality

The research contributes to the understanding of consumer behaviour during times of crisis, providing relevant insights from a theoretical perspective based on the K-means clustering algorithm.