Nigerian Retail Customer Spending Analysis

30,000 records from a Nigerian retail and e-commerce customer segmentation dataset are analyzed for spending patterns. The EDA project by shiragraiver explores predicting total customer spending from key numerical variables. The dataset was last updated on Hugging Face in March 2026.

Use Cases

• Predict customer total_spending using key numerical_variables like purchase frequency or basket size.
• Segment customers into groups based on spending patterns and transaction features.
• Analyze correlations between customer demographics and purchase behavior for targeted marketing.
• Identify important patterns in retail transaction data to inform inventory or pricing strategies.

Strengths

• Contains 30,000 records suitable for analysis.
• Focuses on predicting a specific target variable: customer total spending.

Limitations

• Specific column names and data types are unknown.
• Sample data and original source details are unavailable for validation.
• Potential for geographic bias, limited to Nigerian retail context.

Provenance

Source

Original source not specified; dataset hosted by shiragraiver on Hugging Face.

Collection Method

Method of collection unknown; used for an Exploratory Data Analysis project.

Freshness

Last updated March 2026.

Geography

Nigeria