Customer image tags (TAGs) are developed by analyzing customer interaction and behavioral data using big data techniques to outline distinct customer characteristics. These tags include demographic, purchasing behavior, and marketing response data. A key advantage is transforming raw data into structured, actionable "data language" and providing richer, dynamic profiles, essential for the "Retail 4.0" era. They enable precise marketing and improved customer service by understanding individual preferences. Applications involve customer segmentation (value, behavior), product prediction, and churn analysis, often utilizing models like RFM (Recency, Frequency, Monetary). Dashboard tools facilitate comparative analysis of customer groups, contribution, acquisition channels, and marketing campaign responses. The ability to leverage AI for data analysis is also emphasized as a significant competitive advantage.

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