I can help you conduct customer segmentation using R

Why Hire Me?

📱Click to Connect on Whatsapp to Discuss Your Project

I bring 7+ years of experience in data analysis with expertise in R-based customer segmentation for marketing, CRM, and product teams. My approach goes beyond just clustering; I deliver business-relevant segments supported by actionable insights.

What I Offer:

• Hands-on experience with K-means, hierarchical clustering, DBSCAN, and RFM segmentation

• Expertise in using R libraries like dplyr, cluster, ggplot2, and factoextra

• Domain adaptability across retail, finance, edtech, and services

• Visual and narrative clarity in final segmentation reports

• Ability to link segments to KPIs like retention, CLV, and campaign ROI

What I Need to Start Your Project

To execute precise and insightful customer segmentation in R, I require the following details:

1) Project Goals and Context

• Your business objectives for segmentation (e.g., campaign targeting, loyalty analysis)

• Desired outcomes such as increased ROI, improved personalization, or segment profiling

2) Dataset Details

• A sample or full dataset including customer demographics, transaction history, engagement data

• Data format (CSV, Excel, database access)

• Any labels or pre-tagged customer attributes

3) Preferred Segmentation Logic

• Type of segmentation: K-means, RFM, hierarchical, or other

• Any specific clustering technique or distance metric preference

• Whether segmentation should be based on behavioral, demographic, or hybrid variables

4) Data Preprocessing Requirements

• Information on missing values, outliers, or scaling needs

• Specific filters or data inclusion/exclusion logic to apply

5) Report and Visualization Expectations

• Format: PDF, Word report, R Markdown, or Jupyter Notebook

• Required plots: cluster plots, elbow method, dendrograms, heatmaps

6) KPIs and Business Use

• Metrics to be extracted per cluster (e.g., average order value, frequency)

• How you plan to use the output (e.g., targeting, dashboard, campaign)

7) Timeline and Communication

• Final delivery date

• Frequency of status updates

• Preferred communication platform (email, Zoom, WhatsApp)

8) Access and Tools Setup

• Data transfer method (email, Google Drive, secure link)

• Access to R setup on your system (if needed for deployment or demo)

9) Security and Confidentiality

• Data privacy concerns or NDA requirements

• Handling of customer-sensitive variables

10) Support and Handoff

• Need for handholding or future revisions

• Whether training or documentation is expected after delivery