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Enhancing Marketing Strategies of Durable Private Label Products Through Customer Segmentation
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| 3.76 MB | Adobe PDF |
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Orientador(es)
Resumo(s)
The retail and private label (PL) industry is experiencing dynamic changes driven by evolving
consumer behaviors and increased competition. Retailers are now leveraging advanced data
analytics to understand customer preferences, leading to more effective segmentation and
targeted marketing strategies. In this context, durable PL products have emerged as a key area
of focus, offering retailers opportunities for differentiation and customer loyalty. This study
delves into customer segmentation in the context of durable PL products in a German discount
retail setting. Utilizing real retail data, it applies K-Means clustering to identify three distinct
customer segments with unique purchasing behaviors and preferences regarding a durable PL
in the do-it-yourself (DIY) and tool categories. These segments, named "Durable Bargain
Hunters & New Customers," "Regular Grocery Shoppers", and "Loyal DIY Fans", provide
insights for personalized marketing strategies. The study explores the characteristics of these
clusters, examines their purchasing patterns, and proposes actionable marketing
recommendations. This study contributes to the understudied research area of durable PL
marketing and offers practical applications in customer segmentation and data-driven
marketing strategies in the retail sector. The findings are particularly relevant for retailers
aiming to enhance their marketing strategies for PL products through targeted customer
engagement and segmentation using machine learning approaches.
Descrição
Project Work presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Marketing Intelligence
Palavras-chave
Customer Segmentation Private Label Marketing Durable Private Labels Cluster Analysis Personalized Marketing SDG 8 - Decent work and economic growth SDG 9 - Industry, innovation and infrastructure