Raw Sales Dataset for RFM Customer Segmentation

30,000 raw retail transactions documenting the purchasing behavior of 100 customers across 5 regions. This Kaggle-hosted dataset provides the raw inputs necessary for calculating Recency, Frequency, and Monetary (RFM) metrics. The data is specifically curated for retail analytics and customer segmentation workflows.

Use Cases

• Calculating Recency, Frequency, and Monetary (RFM) scores for 100 customers
• Analyzing regional sales distribution across the 5 included regions
• Practicing data cleaning and aggregation on raw transaction logs

Strengths

• 30,000 transaction records
• Includes 5 distinct geographic regions
• High transaction-to-customer ratio (300:1)

Limitations

• Small customer sample size of only 100 unique individuals
• Unknown temporal range or currency units
• Lack of column headers or data dictionary in source

Provenance

Geography

5 regions