{"id":27261503,"url":"https://github.com/caesaredia/food-app-user-behavior-analysis","last_synced_at":"2026-04-27T20:32:04.654Z","repository":{"id":287136043,"uuid":"963712048","full_name":"caesaredia/food-app-user-behavior-analysis","owner":"caesaredia","description":"Analyze user behavior and optimize app experience in a food-tech startup through funnel analysis and A/A/B testing. 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By analyzing event logs and user funnel progression, the project uncovers insights to optimize user engagement and improve conversion rates.\n\n# Objectives 🧠\n- Analyze user behavior and engagement across the product funnel\n- Quantify drop-offs between funnel stages\n- Evaluate the effectiveness of UI changes using A/A/B testing\n- Provide data-driven recommendations for UX optimization\n\n# Key Insights 📈 \n- Average of 32.33 events per user\n- Major user drop-off occurs at the OffersScreenAppear stage\n- Only 18.36% of users complete the entire funnel\n- Statistically significant differences found across experimental groups using Chi-squared testing\n\n# Files in This Repository 📚 \n- Raw dataset used for the analysis: [`data/food_app_user_behavior_data.csv`](./data/food_app_user_behavior_data.csv)\n- Main Jupyter Notebook with full analysis: [`data/food_app_user_behavior_analysis.ipynb`](./data/food_app_user_behavior_analysis.ipynb)\n\n# Author\nNabilla Hafsah Caesaredia\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcaesaredia%2Ffood-app-user-behavior-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcaesaredia%2Ffood-app-user-behavior-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcaesaredia%2Ffood-app-user-behavior-analysis/lists"}