FastFoodFeedback: AI-Driven Analysis of Customer Reviews in Fre…

Walid Benzineb

Data Scientist
Data Analyst
AI Developer
Microsoft Excel
Python

FastFoodFeedback: AI-Driven Analysis of Customer Reviews in French Cities

Project Overview

This project conducts an in-depth analysis of customer reviews for fast food restaurants in three major French cities: Lyon, Marseille, and Paris. The primary goal is to identify key factors influencing customer satisfaction and dissatisfaction, and to develop targeted, cost-effective strategies for improving customer experience in each city.

Table of Contents

Data Collection

Source: Google Reviews
Scope: Fast food restaurants in Lyon, Marseille, and Paris
Sample Size: Lyon : 11892 reviews, marseille : 13053 reviews and paris : 26240 reviews. Total : 51185 reviews.
Data Points: review text, date of review
Ethics: All data was collected in compliance with Google's terms of service

Methodology

Data Collection: Reviews were gathered from Google Reviews using automated data collection techniques.
Data Preprocessing:
Categorization: Reviews were categorized into six main areas:
Analysis:
Visualization:
Strategy Development:

Key Findings

Negative reviews have a more significant impact on business reputation and customer retention than positive ones.
Service and food quality are the top concerns across all three cities, but their relative importance varies.
Each city has unique secondary concerns that require targeted strategies.

City-Specific Analysis

Lyon

Positive Reviews:
Negative Reviews:
Notable: Highest percentage of delivery-related complaints (2.7%) among the three cities.

Marseille

Positive Reviews:
Negative Reviews:
Notable: Highest percentage of cleanliness complaints and showed more price sensitivity (5.6%) than Lyon.

Paris

Positive Reviews:
Negative Reviews:
Notable: Highest price sensitivity and more ambiance-related complaints (4.0%) than other cities.

Improvement Strategies

Lyon

Service Improvement:
Food Quality Consistency:
Delivery Enhancement:

Marseille

Service Excellence:
Cleanliness Initiative:
Value Perception:

Paris

Parisian Service Standards:
Food Quality Perception:
Value Enhancement:

Cross-City Initiatives

Enhanced Customer Feedback System:
Social Media Engagement:
Staff Empowerment:
Menu Optimization:

Implementation Plan

Prioritize issues based on the percentage of complaints in each city.
Implement changes gradually, starting with one or two initiatives at a time.
Regularly review customer feedback and sales data to measure the impact of each initiative.
Adjust strategies based on results and ongoing customer feedback.
Ensure all staff members are well-informed about new initiatives and their role in implementation.
Celebrate successes with staff to maintain motivation and reinforce the importance of improvements.

Conclusion

By focusing on these city-specific concerns and implementing targeted, cost-effective strategies, fast food businesses in Lyon, Marseille, and Paris can work towards reducing negative reviews, enhancing customer satisfaction, and improving their overall reputation and profitability. The key to success lies in consistent application, ongoing monitoring, and a commitment to continuous improvement in response to evolving customer needs and preferences.

Contact Information

Walid Benzineb - benzinebwal@gmail.com
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