I will run customer segmentation and cluster analysis on your data
Data analytics
Level 1
Has met certain performance criteria and shows strong potential in the marketplace.
About this Gig
Send me your customer or transaction data I'll run a full segmentation analysis, profile each segment, and deliver actionable personas you can use to target marketing, pricing, or product decisions.
What you get:
- Cleaned dataset with cluster assignments
- Cluster profiles: who is in each segment, what makes them distinct
- Visualizations (cluster scatter / heatmap / radar chart)
- Recommended actions per segment
- Code (Python or R) fully commented and runnable
- Written report (1-6 pages depending on tier)
Methods I use:
- K-means and K-medoids
- Hierarchical clustering (Ward, complete, average linkage)
- DBSCAN (for finding natural groupings without specifying k)
- RFM segmentation (for transactional / e-commerce data)
- PCA / t-SNE / UMAP for visualization
- Silhouette and gap-statistic for choosing optimal k
Use cases I deliver:
- E-commerce customer segmentation (RFM + behavioral)
- B2B account tiering
- Subscription cohort analysis
- Marketing audience segmentation for ad targeting
- Product user-segment analysis (PLG)
- Patient / member segmentation for healthcare and insurance
Drop your data + a one-line goal in the order requirements. I'll handle the rest.
Other Data Analytics Services I Offer
FAQ
What is included in the basic package?
(1) 1 method (K-means or RFM); (2) 3–5 segments; (3) Basic profiling (means / counts per cluster); (4) 1-page summary report; (5) Commented code
What is included in the standard package?
(1) 2–3 methods compared (K-means, hierarchical, DBSCAN); (2) Optimal-k diagnostics (elbow, silhouette, gap); (3) Full segment profiles with statistical significance tests; (4) Recommended actions per segment; (5) 3-page report; (6) PCA / t-SNE visualization; (7) Commented code
What is included in the premium package?
(1) Multi-method comparison + ensemble stability check; (2) Feature engineering (RFM scores, behavioral derivatives, lifecycle stage); (3) Full segment profiles + 1-page persona write-up per segment; (4) 6-page report with methodology, results, recommendations; (5) Replication repo.
How much data do I need?
For meaningful clusters, ideally 1,000+ customers / observations. For RFM, 500+ transactions per customer over a window. If your data is smaller, I'll flag it and recommend a simpler approach.
What columns should my data include?
For customer segmentation, anything that describes behavior or attributes — purchase history, demographics, engagement metrics, product usage. For RFM specifically: customer ID, transaction date, transaction amount.
Will my data stay private?
Yes — I never share or reuse client files. NDA available on request. For sensitive data (PII, health), tell me up front and I'll work with hashed identifiers.
What if I don't know how many segments I want?
Standard and Premium include diagnostics (elbow plot, silhouette score, gap statistic) that recommend an optimal k. Basic uses a sensible default (k=4 unless your data clearly clusters differently).
Can you also predict which segment a new customer falls into?
Yes — Premium includes a trained classifier (logistic / random forest) that scores new customers into segments, plus the code to run it on your data.
Do you handle non-customer clustering (e.g. product, region, employee)?
Yes — same methods apply. Just describe what you're segmenting in the order requirements.

