{"id":16228404,"url":"https://github.com/mrsaeeddev/customer-segmentation-using-rfm-matrix-technique-and-k-means-algorithm","last_synced_at":"2025-04-08T04:44:23.018Z","repository":{"id":123096947,"uuid":"168809440","full_name":"mrsaeeddev/customer-segmentation-using-rfm-matrix-technique-and-k-means-algorithm","owner":"mrsaeeddev","description":null,"archived":false,"fork":false,"pushed_at":"2019-12-04T06:27:08.000Z","size":31099,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-03-24T22:34:30.660Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"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/mrsaeeddev.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}},"created_at":"2019-02-02T08:05:56.000Z","updated_at":"2019-12-04T06:27:36.000Z","dependencies_parsed_at":null,"dependency_job_id":"efd0a596-a620-4d0b-b7e2-08a6a2c34296","html_url":"https://github.com/mrsaeeddev/customer-segmentation-using-rfm-matrix-technique-and-k-means-algorithm","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mrsaeeddev%2Fcustomer-segmentation-using-rfm-matrix-technique-and-k-means-algorithm","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mrsaeeddev%2Fcustomer-segmentation-using-rfm-matrix-technique-and-k-means-algorithm/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mrsaeeddev%2Fcustomer-segmentation-using-rfm-matrix-technique-and-k-means-algorithm/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mrsaeeddev%2Fcustomer-segmentation-using-rfm-matrix-technique-and-k-means-algorithm/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mrsaeeddev","download_url":"https://codeload.github.com/mrsaeeddev/customer-segmentation-using-rfm-matrix-technique-and-k-means-algorithm/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247779796,"owners_count":20994572,"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":[],"created_at":"2024-10-10T12:55:14.862Z","updated_at":"2025-04-08T04:44:22.998Z","avatar_url":"https://github.com/mrsaeeddev.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Customer Segmentation Using RFM Matrix Technique and K Means Algorithm\n## Analysis of E-commerce data of different countries in order to understand the need of markets and customer segmentation in order to identify best customers\n\n## Dataset:\n\nTypically e-commerce data sets are proprietary and consequently hard to find among publicly\navailable data. However, The UCI Machine Learning Repository has made this data set containing\nactual transactions from 2010 and 2011. The data set is maintained on their site, where it can be\nfound by the title \"Online Retail\".\n\nThis is a transnational data set which contains all the transactions occurring between 01/12/2010\nand 09/12/2011 for a UK-based and registered non-store online retail. The company mainly sells\nunique all-occasion gifts. Many customers of the company are wholesalers.\n\n## Approach :\n\nIn this dataset, I performed Exploratory Data Analysis(EDA) on dataset by which I visualized different parameters of dataset. \nThen, I used RFM Matrix technique and K Means Algorithm to identify the best customers.\n\n## Results :\n\nThis method can be used by vendors to identify best potential customers which may \nbe helpful for them to target customers for promotions and marketing compaigns.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmrsaeeddev%2Fcustomer-segmentation-using-rfm-matrix-technique-and-k-means-algorithm","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmrsaeeddev%2Fcustomer-segmentation-using-rfm-matrix-technique-and-k-means-algorithm","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmrsaeeddev%2Fcustomer-segmentation-using-rfm-matrix-technique-and-k-means-algorithm/lists"}