I will increase your customer lifetime value with data science
About this Gig
Acquiring a new e-commerce customer costs 5x more than keeping one. If buyers purchase once and never return, your ad spend is bleeding profits. To scale, you MUST increase Customer Lifetime Value (LTV).
Stop guessing why customers leave. Provide your store data (Shopify/WooCommerce, Ecommerce stores CSV exports, SQL), and I will use Data Science to build a proactive retention strategy.
I analyze your transaction history to find your true VIPs, identify who is at risk of churning, and uncover the exact triggers causing them to leave.
What I will do:
RFM Segmentation: Group buyers into VIPs, Loyal, Hibernating, and Lost.
Churn Prediction (ML): Build a Machine Learning model to assign a "Churn Risk %" to every user.
Trigger Analysis: Tell you why they leave (e.g., "No purchase in 30 days").
NLP Review Analysis: Find hidden complaints in thousands of product reviews.
Deliverables for Business Owners:
Fully documented Jupyter Notebooks
Clean datasets with LTV & Churn scores
4-Page Executive PDF Report (Plain English, no confusing math)
Interactive Dashboards (Tableau/PowerBI in Premium Tier)
Stop sending generic discounts to everyone. Target the rig
Programming language:
Python
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R
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SQL
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Colab
My Portfolio
FAQ
Q: What kind of data do I need to provide?
A: Ideally, an export of your customer orders (Customer ID, Order Date, Total Spend, etc.). If you use Shopify, WooCommerce, or Magento, you can simply export the CSV files from your store's admin panel. If you aren't sure what to export, message me before ordering and I will guide you!
Q: What is "Feature Importance" and why does it matter to my store?
A: It tells you why customers are leaving. Instead of just saying "Customer A will churn," the model says "Customer A will churn because they haven't bought in 30 days and only used a discount code once." This gives your marketing team an exact "To-Do List" to save them.

