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Oracle Retail Customer Segmentation

Improve Personalization with Advanced Customer Segmentation Strategies

Increase the accuracy of retail merchandise and sales plans by effectively identifying, grouping, and targeting customers by channel using multiple methods, including category purchase behavior, demographics, and transaction data. Drive customer-centricity and equip your data science teams with advanced retail science models and tools to enhance localized assortments, targeted offers, and personalized shopping experiences.

Review customer distribution across attributes.


Create an Unbiased View of Core Customers

Create an Unbiased View of Core Customers

  • Enable localized assortments, targeted offers, and personalized shopping experiences
  • Leverage multiple segmentation approaches, including demographics, customer value (RFM), and purchase behavior
  • Identify the key attributes related to each customer segment
  • Predict how customer shopping patterns evolve over time
  • Seamlessly integrate with planning, pricing, offer optimization, and customer engagement solutions

Related Solutions

  • Oracle Retail Advanced Clustering

    Evaluate sales performance, customer penetration, and market share across stores, geographies and markets to plan and compete in an evolving landscape of pure play, general merchants, and traditional competitors.

  • Oracle Retail Attribute Extraction

    Remove data quality issues from the equation with machine-learning to enable attribute extraction.

  • Oracle Retail Affinity Analysis

    Gain actionable insight into your shoppers' behavior across channels and maximize the potential of your data through persona-based workflows and dashboards. Affinity analysis identifies similarities, halo, and cannibalization effects, and shows how store clusters perform relative to each other.


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