McDonald's Review Analysis System

McDonald’s sought a solution to categorize and analyze customer reviews collected from different platforms to understand customer experiences better and improve their service quality.

Executive Summary

Pixelette Technologies developed the McDonald’s Review Analysis System to categorize customer reviews using the ChatGPT API. The categorized data was ingested into Google BigQuery, then imported into a Power BI dashboard for visualization and report creation. The system now enables McDonald’s to automate the review collection and analysis process across various platforms, aiding in quality enhancement through insightful customer feedback.

Project Objective

  • Develop a system to categorize customer reviews efficiently.
  • Ingest categorized data into Google BigQuery for further analysis.
  • Create visualizations and reports through a Power BI dashboard.

Challenges

  • Accurate categorization of diverse customer reviews.
  • Efficient data ingestion and integration between ChatGPT, Google BigQuery, and Power BI.
  • Designing intuitive visualizations that provide actionable insights.

Solutions

  • Utilized ChatGPT API for accurate review categorization based on predefined criteria.
  • Employed Azure Databricks for efficient data ingestion into Google BigQuery.
  • Created insightful visualizations and reports in Power BI to represent customer feedback analysis.

Project Timeline

  • Requirement Gathering and Initial Design
  • Development of Review Categorization System
  • Data Ingestion and Dashboard Creation
  • Client Feedback and Refinements

Team Composition:

  • Project Manager
  • Machine Learning Engineers
  • Backend Developers
  • Data Annotation Team
  • Quality Assurance Engineers

Risk Management:

Identified risks such as data inaccuracies in review categorization and addressed them by fine-tuning the ChatGPT API.

Quantifiable Results

  • Automated the review categorization process, saving significant manual effort.
  • Enabled real-time review analysis through the Power BI dashboard, aiding in quicker decision-making for quality improvement.

Lessons Learned

Effective integration between different tech stacks is crucial for seamless data flow and analysis.

Client Feedback

McDonald’s appreciated the automation in review collection and analysis, and the actionable insights provided through visualizations.

Conclusion

The McDonald’s Review Analysis System successfully streamlined the process of collecting, categorizing, and analyzing customer reviews. The project showcased the potential of leveraging advanced technologies like ChatGPT, Azure Databricks, and Power BI in automating review analysis, providing McDonald’s with valuable insights to enhance their service quality and customer satisfaction.