Demographics Analysis

Built end-to-end from raw data using Power Query, Pivot Tables, and interactive slicers to reveal key business patterns.

📊 Case Study: Telecom Demography & Service Dashboard

🔍 Project Background

The telecom industry generates massive amounts of customer and service data. For this project, I worked with artificial telecom data from California, USA, aiming to explore who the customers are, how they use services, and what factors drive churn vs retention.

I wanted to simulate a real-world data analyst task: moving from raw, messy data all the way to a professional, interactive dashboard that delivers insights at a glance.

⚙️ Tools & Process

  • Excel + Power Query → for cleaning and transforming raw data

  • Pivot Tables & Pivot Charts → for aggregating and analyzing key metrics

  • Slicers & Dynamic Titles → for interactivity and user-friendly navigation

  • Custom Dashboard Design → clean layout, professional styling, and intuitive storytelling

The project flow looked like this:

  1. Raw Data Import → Cleaning & Transformation (Power Query)

  2. Pivot Table Setup (customer segments, revenue, churn, usage)

  3. Interactive Elements (filters by age, gender, and status)

  4. Dashboard Layout (separating Demographics from Service Insights)

 

📈 Dashboard Highlights

The dashboard is split into two major sections:

1️⃣ Demography Overview

  • Total Users & Revenue (with YoY growth %)

  • Customer Segments: High/Mid/Low Value

  • Usage Groups: High, Medium, Low

  • Churn Analysis: Stayed vs Joined vs Churned

  • Age & Marital Status breakdowns

  • Top Cities & State-level User Distribution

2️⃣ Service Overview

  • Internet Types: DSL, Cable, Fiber, None

  • Payment Methods: Bank Withdrawal, Credit Card, Mailed Check

  • Subscription Plans: Month-to-Month, 1-Year, 2-Year

  • Premium Tech Support usage

  • Multiple Lines & Unlimited Plan adoption

🌍 Interactivity

  • Filters by Gender, Age Segment, and Customer Status

  • Dynamic visuals update instantly for deeper exploration

🎯 Key Insights Uncovered

  • The majority of users are middle-aged, low-usage, but high-value

  • Fiber Optic is the most popular internet type

  • Bank Withdrawal dominates as the payment method

  • Most customers prefer Month-to-Month plans

  • Retention is relatively strong (67% stayed) despite churn hotspots in some cities

 

🧠 Skills Demonstrated

  • Data Cleaning & Transformation (Power Query)

  • Pivot-based Data Analysis

  • Dashboard Storytelling with Excel

  • Visual & Interactive Design Principles