Customer Segmentation Using RFM Analysis

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Empirical analysis demonstrates customer segmentation via RFM quantiles in retail records, highlighting behavioral insights for targeted marketing.

Quantile-based segmentation categorizes retail customers into distinct behavioural groups using compound recency, frequency, and monetary value scores.
RFM analysis on retail transaction logs applies four quantiles across each metric, structuring customer segmentation into interpretable behavioral profiles.
Integration with XGBClassifier and CatBoostClassifier frameworks enables predictive analytics, supporting tailored customer relationship management strategies.

Madhiraju et al. (2024) studied this question.

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Empirical analysis demonstrates customer segmentation via RFM quantiles in retail records, highlighting behavioral insights for targeted marketing.