I can help you conduct customer segmentation using Python

Why Hire Me?

I specialize in Python-based customer segmentation that translates directly into marketing performance. My approach combines domain understanding with machine learning to uncover distinct, usable customer groups.

What I Offer:

• 7+ years of experience in clustering, RFM segmentation, and behavioral analytics

• Expert in Python libraries like pandas, scikit-learn, matplotlib, seaborn

• Proficiency in advanced clustering algorithms: K-means, DBSCAN, Agglomerative

• Reports include clearly visualized segments and targeted action plans

• Industry experience across e-commerce, fintech, edtech, and B2B services

What I Need to Start Your Project

To perform effective segmentation using Python, I will require:

1) Objective & Scope

• Specific marketing or business goals driving segmentation

• Expected use of segments (e.g., personalized campaigns, retention, product design)

2) Dataset Details

• Raw or cleaned customer data (CSV, Excel, SQL) with relevant variables

• Variable types: demographics, transactions, engagement, loyalty indicators

• Clarification on missing values or outlier handling if applicable

3) Preferred Segmentation Approach

• Preference for K-means, hierarchical clustering, DBSCAN, or hybrid models

• Mention if RFM or rule-based segmentation is to be included

• Any need for supervised segmentation (e.g., classification afterward)

4) Key Metrics and Business Variables

• KPIs tied to customer value: frequency, recency, spend, churn probability

• Fields that should influence clustering vs fields used only for interpretation

5) Reporting and Delivery Format

• Expected format of report: PDF, PPT, Markdown, or Jupyter Notebook

• Any visuals required (e.g., dendrogram, elbow curve, segment profile heatmap)

6) Technical and Access Requirements

• Data access method: file upload, cloud link, API

• Any restrictions on data sharing, NDA, or confidentiality preferences

• Whether Python execution needs to be shown or handed over as script

7) Timeline & Collaboration Preferences

• Delivery deadline and any interim milestones

• Frequency of check-ins, review calls, or demo sessions

• Platform preferred for communication: email, WhatsApp, Zoom, etc.

8) Post-Project Support

• Whether handholding or explanation of code is expected

• Future use cases or repeat analyses to be kept in mind while designing output