Customer Satisfaction Analytics: Driving Loyalty Through Data Insights
Project Overview
Developed a comprehensive customer satisfaction analysis for OmniRetail, a U.S.-based electronics and smart home retailer, examining 120 customers across demographics, satisfaction factors, and loyalty patterns. This analysis helped identify key drivers of customer satisfaction and provided strategic recommendations to improve retention and engagement. The project earned a Top 5 placement in the Onyx Data Challenge July 2025.
Problem Statement
OmniRetail faced declining customer loyalty and inconsistent satisfaction scores across different regions and demographic segments. With a 57.50% repeat customer rate and average satisfaction score of 5.35/10, the company struggled to understand what drove customer satisfaction and loyalty. Without structured insights into satisfaction drivers, OmniRetail couldn't effectively optimize customer engagement strategies or reduce churn in underperforming segments.
Goal
Identify high and low satisfaction customer segments, analyze loyalty patterns across demographics, evaluate the impact of various satisfaction factors, and provide actionable recommendations to improve customer retention and overall satisfaction scores.
My Analytical Approach:
Customer Segmentation: Analyzed 120 customers by age groups, gender, purchase history, and geographic distribution across U.S. cities.
Satisfaction Factor Analysis: Examined nine key satisfaction drivers including brand reputation, customer service, delivery speed, ease of use, features, packaging, price, product quality, and support availability.
Loyalty Pattern Recognition: Investigated customer loyalty levels (Low: 37.50%, Medium: 31.67%, High: 30.83%) across different demographic segments.
Support Impact Assessment: Analyzed the correlation between customer support contact (46.67% contacted support) and satisfaction ratings.
Geographic Analysis: Mapped satisfaction and loyalty trends across different U.S. regions to identify location-specific patterns.
Key Challenges & Solutions:
Multi-dimensional Analysis: Managed complex relationships between satisfaction factors, demographics, and loyalty by creating correlation matrices and segmentation models.
Age-Based Insights: Discovered that the 35-44 age group represented the most loyal segment, requiring targeted strategies for other age groups.
Satisfaction Score Distribution: Addressed the challenge of low overall satisfaction (5.35/10) by identifying specific factors contributing to poor ratings.
Regional Variations: Handled geographic disparities in satisfaction by developing location-specific recommendations.
Key Insights & Recommendations:
Age Group Optimization: The 35-44 age segment showed highest loyalty, suggesting need for targeted retention strategies for younger and older demographics.
Gender-Based Patterns: With 55% female customers but varied satisfaction across factors, gender-specific engagement strategies could improve overall scores.
Support Effectiveness: 46.67% support contact rate indicates potential service issues requiring immediate attention to improve satisfaction.
Factor Prioritization: Identified packaging, product quality, and customer service as key areas needing improvement based on satisfaction factor analysis.
Regional Strategy: Geographic analysis revealed opportunities for location-specific improvements in customer experience.
Business Impact
This analysis enables OmniRetail to implement targeted customer experience improvements, potentially increasing the current 57.50% repeat customer rate and improving the 5.35/10 average satisfaction score. The insights support strategic decision-making for customer retention programs, regional optimization, and satisfaction factor improvements. Recognition as a Top 5 solution in the Onyx Data Challenge validates the analytical approach and business value delivered.