{"id":28419327,"url":"https://github.com/samruddhi3012/rfm-analysis","last_synced_at":"2025-06-27T01:31:33.886Z","repository":{"id":249997838,"uuid":"833188001","full_name":"samruddhi3012/RFM-Analysis","owner":"samruddhi3012","description":"Hi there! In this project I have performed Sales Analysis (RFM Analysis)  using SQL and Tableau.","archived":false,"fork":false,"pushed_at":"2025-05-26T17:46:46.000Z","size":40,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-06-02T22:47:31.512Z","etag":null,"topics":["data-analysis","data-visualization","mssqlserver","rfm-analysis","segmentation","tableau"],"latest_commit_sha":null,"homepage":"","language":null,"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/samruddhi3012.png","metadata":{"files":{"readme":"README.md","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}},"created_at":"2024-07-24T14:24:25.000Z","updated_at":"2025-05-26T17:47:06.000Z","dependencies_parsed_at":"2024-07-24T16:46:41.853Z","dependency_job_id":"0a36c20f-0249-4ef4-9571-85c1c6ef6965","html_url":"https://github.com/samruddhi3012/RFM-Analysis","commit_stats":null,"previous_names":["samruddhi3012/sales-data-analysis","samruddhi3012/sales-rfm-analysis","samruddhi3012/rfm-sales-analysis"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/samruddhi3012/RFM-Analysis","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/samruddhi3012%2FRFM-Analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/samruddhi3012%2FRFM-Analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/samruddhi3012%2FRFM-Analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/samruddhi3012%2FRFM-Analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/samruddhi3012","download_url":"https://codeload.github.com/samruddhi3012/RFM-Analysis/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/samruddhi3012%2FRFM-Analysis/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":262172451,"owners_count":23270009,"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","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":["data-analysis","data-visualization","mssqlserver","rfm-analysis","segmentation","tableau"],"created_at":"2025-06-04T17:16:19.454Z","updated_at":"2025-06-27T01:31:33.873Z","avatar_url":"https://github.com/samruddhi3012.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# RFM Analysis\nRFM (Recency, Frequency, Monetary) sales analysis is a marketing technique used to evaluate and segment customers based on their purchasing behavior. This method helps businesses identify their most valuable customers and tailor marketing strategies accordingly.\n![dead3-1_ohv1o0sljibjk6evwkvg5g](https://github.com/user-attachments/assets/94778fb4-289e-48c6-b062-606dfe06ecb9)\n\n## :round_pushpin: Objectives\nTo identify high-value customers and at-risk churners through data-driven segmentation, enabling targeted marketing and inventory decisions.\n\n## :round_pushpin: Tools and Technologies\n\n* Data Source: [Dataset](https://www.kaggle.com/datasets/kyanyoga/sample-sales-data)\n* Tools: Microsoft SQL Server, Tableau\n* Keywords: **RFM Analysis**, **Segmentation Analysis**, **Data Visualization**, Data Interpretation, Data Manipulation, Tableau Dashboard \n* Concepts: Common Table Expression, Window Functions, GROUP BY clause, Aggregate Functions, Various charts in Tableau\n  \n\u003c!--\n## :round_pushpin: Dashboard\nA sales analysis dashboard is created using Tableau, which is presented as follows: \n--\u003e\n\n## :round_pushpin: Results\nThe key results from the analysis are presented as follows:\n* _**Exploratory Analysis Results**_:\n   1. The company generated total revenue of **$10,032,629**.\n   4. There were **92** unique customers.\n   5. **Classic Cars** and **Vintage Cars** are the highest-selling products.\n   6. According to order status, **92%** of products were shipped, and 2% were canceled.\n   8. Yearly Sales Change:\n      1. Sales increased by **34.32%** from 2003 to 2004.\n      2. Sales dropped by **62.08%** from 2004 to 2005.\n   10. The top 3 revenue-generating countries are the USA, Spain, and France.\n   11. The 4th quarter has the highest product sales, with **38.62%**.\n\n* **_RFM Analysis Results_**:\n\u003cbr\u003e \u0026nbsp;From **customer segmentation**, it was concluded that 15% of customers were loyal, 18% were potential churners, and **22% of customers were lost**.\n\n## :round_pushpin: Description \n1. _**Preliminary Analysis**_\n\u003cbr\u003eConducted a comprehensive analysis to understand key sales metrics:\n   * Total Sales \u0026 Orders: \u003cbr\u003e \u0026nbsp; Analyzed total sales and order count across countries.\n   * Order Frequency \u0026 Unique Customers: \u003cbr\u003e \u0026nbsp; Identified the most frequent ordering country and unique customer count.\n   * Product \u0026 Deal Size Analysis: \u003cbr\u003e \u0026nbsp;Evaluated sales performance of products and various deal sizes.\n   * Order Status Distribution: \u003cbr\u003e \u0026nbsp; Assessed distribution of order statuses.\n   * Top Performance Metrics:\n   * Best selling year and month.\n   * Year-over-year revenue changes.\n   * Highest selling products in peak months and by city/country.\n   * Top revenue-generating countries and cities.\n   * Sales trends by territories, quarters, and yearly product performance.\n   * Yearly sales differences for specific products.\n  \n2. _**RFM Analysis**_\n\u003cbr\u003e Utilized RFM (Recency, Frequency, Monetary) analysis to segment and understand customer behavior:\n   * Best Customers Identification: \u003cbr\u003e \u0026nbsp;Identified top customers based on purchase patterns.\n   * Customer Segmentation: \u003cbr\u003e \u0026nbsp;Grouped customers into segments such as best, loyal, and at-risk customers.\n   * Segment Distribution: \u003cbr\u003e \u0026nbsp;Calculated the percentage of customers in each segment.\n   * Product Combinations: \u003cbr\u003e \u0026nbsp;Analyzed frequently bought together products for bundling opportunities.\n\n### _Thank you for visiting my repository!_\n\n\u003c!--\n# Results\n   * Generated total revenue of $10,032,629.\n   * Total 307 orders were placed.\n   * Orders were placed from 19 different countries.\n   * A total of 92 unique customers\n   * The Classic Cars and Vintage Cars are the highest-selling products.\n   * Medium size is the highest selling deal size.\n   * Accoridng to order status 92% of products were shipped and 2% were canceled.\n   * The Best Selling Year was 2004.\n   * Yearly Sales Change:\n      1. Sales increased by 34.32% from 2003 to 2004.\n      2. Sales dropped by 62.08% from 2004 to 2005.\n   * Best Selling Month was November in 2003 and 2004.\n   * Top Product in Best Month was Classic Cars in 2003 and 2004.\n   * Top 3 Revenue Generating Countries are USA, Spain, and France.\n   * Top 3 Revenue Generating Cities are Madrid, San Rafael, and NYC.\n   * The 4th quarter has the highest product sales, with 38.62%.\n\n   --\u003e\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsamruddhi3012%2Frfm-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsamruddhi3012%2Frfm-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsamruddhi3012%2Frfm-analysis/lists"}