Customer Analytics

Project Overview
This project was completed as part of the Google Data Analytics Professional Certificate Capstone. The objective was to uncover actionable insights from a global retail dataset to support customer retention, reduce churn, and identify opportunities for business growth.

Using Tableau for visualization and SQL-style thinking for calculated fields and segmentation logic, I analyzed customer behavior over time, across regions, and by segment.

The insights led to data-driven recommendations aimed at optimizing customer value and strengthening performance in underperforming segments.

Problem Statement
While customer retention had improved, the company relied heavily on a few high-value customers for most of its revenue. In addition, several customer segments and regions showed signs of low engagement and poor retention.

Proposed Solution
Analyze customer behavior using key performance indicators (KPIs) such as:

Customer Lifetime Value (CLV)
Average Order Value (AOV)
Monthly Active Customers (MAC)
Monthly Customer Acquisition (MCA)
Churn and Retention Rates

These metrics help reveal who the most valuable customers are, why others churn, and how segment and region affect engagement. Recommendations would be based on these findings.

Tools & Techniques Used
Tableau Public: For building dynamic dashboards and calculated fields
Data Cleaning: Removing duplicates and handling missing values
Time-Based Segmentation: Grouping customer data by year and month
Cohort Analysis: Using time-of-first-order logic to track retention
Calculated Metrics: CLV, AOV, churn rate, customer frequency, customer lifetime
Data Visualization: To present customer trends and segment comparisons
PowerPoint: For compiling the final presentation and telling the story visually

🔎 Key Findings
A small group of high-value customers (e.g., Tom Ashbrook) contributes a disproportionately large share of revenue

Customer retention improved steadily over time, reaching 74.77% by 2016

Churn rates declined to nearly 0% in the final year, showing stronger engagement over time

The Consumer segment dominated the customer base (51%), while Home Office was underperforming

Emerging markets like Nigeria, Turkey, and Brazil showed moderate customer numbers and represent untapped growth areas

📌 Recommendations
Retain High-Value Customers
Implement loyalty programs and personalized offers to retain customers who deliver outsized value.

Engage Underperforming Segments
Tailor marketing and product strategies for segments like "Home Office" to improve adoption.

Expand in Emerging Markets
Localize acquisition strategies in growing regions like Nigeria and Brazil to unlock market potential.

What I Learned
This project sharpened my ability to:

Translate raw data into strategic insights

Design dashboards that tell a story, not just show numbers

Ask the right business questions and answer them with data

Think critically about customer behavior and revenue drivers

Apply Google’s DA framework (Ask → Prepare → Process → Analyze → Share → Act) in a real-world setting

Role & Contribution

Role: Data Analyst
Contribution: End-to-end ownership — from data cleaning and transformation, to analysis, visualization, insights, and storytelling.

Tags / Skills
Tableau • Customer Analytics • Data Visualization • Churn Analysis • CLV • Data Storytelling • PowerPoint • Segment Analysis • Emerging Markets • Capstone Project