Europe/Paris
WorkJanuary 1, 2020

Multi-Brand Cannibalization Analysis: Optimizing Global Customer Value

BI & Analytics
Source: Multi-brand retail group - Customer cannibalization analysis (GCP, Python, Terraform, Airflow) Context:
  • Cross-brand customer cannibalization and complementarity analysis across multiple retail brands within the same group
  • Implementation of strategies to optimize global customer value
  • Mutual customer data enrichment between brands
Technologies:
  • Cloud: GCP
  • Data Warehouse: BigQuery
  • Languages: Python, SQL
  • Orchestration: Airflow
Key Analyses:
  • Cannibalization vs. complementarity analysis between brands
  • Customer Lifetime Value (CLV) analysis: single-brand vs multi-brand customers
  • Cohort analysis: tracking customers before/after starting to shop second brand
  • Revenue attribution modeling
Results:
  • Multi-brand customers have 2.5x higher CLV than single-brand
  • Measurable impact on revenue and brand profitability
  • Cross-brand customers: 15% of customers but 30% of revenue
  • Online growth is 60% new customers, 40% migrated from stores (not pure cannibalization)

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