{"id":32633656,"url":"https://github.com/shru924/ecommerce_customer_behavior_analysis","last_synced_at":"2026-04-11T12:43:58.366Z","repository":{"id":321620475,"uuid":"1086531740","full_name":"Shru924/Ecommerce_Customer_Behavior_Analysis","owner":"Shru924","description":"A machine learning project that analyzes and segments e-commerce customers based on behavior patterns using Python, Random Forest, and data visualization.","archived":false,"fork":false,"pushed_at":"2025-10-30T15:25:53.000Z","size":851,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-10-30T17:25:59.744Z","etag":null,"topics":["customer-segmentation","data-analysis","jupyter-notebook","machine-learning","matplotlib","pandas","python","scikit-learn"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Shru924.png","metadata":{"files":{"readme":"README.md.txt","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2025-10-30T14:46:26.000Z","updated_at":"2025-10-30T15:25:57.000Z","dependencies_parsed_at":"2025-10-30T17:27:35.509Z","dependency_job_id":"ad7c4b4c-8c87-49c0-b280-8efa3539d3cb","html_url":"https://github.com/Shru924/Ecommerce_Customer_Behavior_Analysis","commit_stats":null,"previous_names":["shru924/ecommerce_customer_behavior_analysis"],"tags_count":null,"template":false,"template_full_name":null,"purl":"pkg:github/Shru924/Ecommerce_Customer_Behavior_Analysis","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Shru924%2FEcommerce_Customer_Behavior_Analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Shru924%2FEcommerce_Customer_Behavior_Analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Shru924%2FEcommerce_Customer_Behavior_Analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Shru924%2FEcommerce_Customer_Behavior_Analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Shru924","download_url":"https://codeload.github.com/Shru924/Ecommerce_Customer_Behavior_Analysis/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Shru924%2FEcommerce_Customer_Behavior_Analysis/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":281902498,"owners_count":26581164,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-10-30T02:00:06.501Z","response_time":61,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["customer-segmentation","data-analysis","jupyter-notebook","machine-learning","matplotlib","pandas","python","scikit-learn"],"created_at":"2025-10-30T23:53:57.813Z","updated_at":"2025-10-30T23:54:21.208Z","avatar_url":"https://github.com/Shru924.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 🧠 Ecommerce Customer Behavior Analysis\r\n\r\n### 📘 Project Overview\r\nThis project analyzes customer purchasing patterns in an e-commerce platform and segments customers based on their behavior using machine learning models.\r\n\r\n---\r\n\r\n### ⚙️ Tech Stack\r\n- **Programming Language:** Python  \r\n- **Libraries Used:** Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn  \r\n- **Algorithm:** Random Forest Classifier  \r\n\r\n---\r\n\r\n### 🏁 Key Features\r\n- Cleaned and preprocessed customer data  \r\n- Performed feature encoding and scaling  \r\n- Built a Random Forest model for customer segmentation  \r\n- Visualized customer segment distribution with bar charts  \r\n- Predicted segment for new customer entries  \r\n\r\n---\r\n\r\n### 📊 Results\r\n- Model Accuracy: ~33% (Demo dataset for explanation)  \r\n- Segmented customers into 3 behavioral categories  \r\n\r\n---\r\n\r\n### 💼 Author\r\n**Shruthi Reddy**  \r\nAI \u0026 ML Engineering Student | Aspiring Data Analyst  \r\n📍 Hyderabad, India  \r\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fshru924%2Fecommerce_customer_behavior_analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fshru924%2Fecommerce_customer_behavior_analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fshru924%2Fecommerce_customer_behavior_analysis/lists"}