Purchase-Based Customer Segmentation Analysis
Краткое
Freelancer Client is hiring: Purchase-Based Customer Segmentation Analysis.
Location: Remote
I have a complete purchase-history dataset ready to go and I want to turn it into actionable customer segments. The single objective is clear: identify distinct target customer groups so I can market to them more effectively.
Which customers are truly high-value
You’re free to choose the right statistical or machine-learning approach—RFM scoring, K-means, hierarchical clustering, or a hybrid model—as long as it fits the data. I’ll supply the raw CSV and a short data dictionary; you return:
Skills: Python, Statistics, R Programming Language, Statistical Analysis, Data Science, Data Analytics, Data Visualization, Data Analysis
Budget: $12500–$37500 USD
Source: Freelancer Client via Remote / Online. Apply on the source website.
Оригинал
I have a complete purchase-history dataset ready to go and I want to turn it into actionable customer segments. The single objective is clear: identify distinct target customer groups so I can market to them more effectively.
The analysis must surface three core insights:
• Which customers are truly high-value
• Who buys most frequently
• Who shows signs of churning
You’re free to choose the right statistical or machine-learning approach—RFM scoring, K-means, hierarchical clustering, or a hybrid model—as long as it fits the data. I’ll supply the raw CSV and a short data dictionary; you return:
1. A cleaned, well-documented dataset with the segment labels appended
2. A concise notebook or script (Python, R, or SQL-based) that reproduces the segmentation step-by-step
3. Visual summaries—charts or dashboards—that make the three insights immediately clear
4. A brief write-up on how to act on each segment
Accuracy, reproducibility, and clear explanations matter more to me than fancy visuals, so keep the code readable and the recommendations practical.
Локация & Details
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