customer-segmentation-clv-analysis's Introduction

Customer Segmentation & CLV Analysis

Data Jedi Skills: Data Cleaning and Prep
Clustering Charm: K-means Clustering
CLV Magic: Customer Lifetime Value Calculation
Demographic Insights: Demographic Analysis
Visual Magic: Visualization (Seaborn, Matplotlib)

Optimizing Marketing Strategies through Customer Data Analysis

Objectives 🎯

Data Magic: ✨ We'll start by collecting and tidying up customer data, which includes details like customer IDs, gender, age, annual income, and spending score.
Cluster Power: ✨ Using the mighty K-means clustering, we'll group customers with similar characteristics to help tailor marketing strategies.
Valuing Customers: ✨ We'll compute the Customer Lifetime Value (CLV) for each customer. It's all about understanding who's more valuable in the long run.
Demographics Dive: ✨ Let's dive into demographics—age, gender, income, spending habits—to reveal how customer segments differ.
Visual Stories: ✨ Expect beautiful visualizations with Python's Seaborn and Matplotlib to showcase insights on customer segments, demographics, and CLV.
Smart Moves: ✨ Recommendations galore! We'll provide insights to supercharge marketing, from segment focus to budget allocation.

Personalized Campaigns: Get ready to craft laser-targeted marketing campaigns with customer segmentation.
Value-Based Focus: We'll reveal which customer segments bring in the gold based on CLV.
Demographic Gems: Dive deep into demographic insights to understand your customer groups.
Optimized Strategies: Armed with insights, you can now optimize marketing strategies for skyrocketing sales and profit.

Clone Me: Begin by cloning this repository.
Install Goodies: Install necessary dependencies using npm install or pip install.
Run the Magic: Run the project locally using npm start or python app.py.