{ "_id": "6ad225857af56c173f1205a0", "Type": "Package", "Package": "rfm", "Title": "Recency, Frequency and Monetary Value Analysis", "Version": "0.5.0", "Authors@R": "person(\"Aravind\", \"Hebbali\", email = \"hebbali.aravind@gmail.com\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0001-9220-9669\"))", "Description": "Tools for RFM (recency, frequency and monetary value)\nanalysis. Generate RFM score from both transaction and customer\nlevel data. Visualize the relationship between recency,\nfrequency and monetary value using heatmap, histograms, bar\ncharts and scatter plots. Includes a 'shiny' app for\ninteractive segmentation. References: i. Blattberg R.C., Kim\nBD., Neslin S.A (2008) .", "License": "MIT + file LICENSE", "URL": "https://github.com/rsquaredacademy/rfm,\nhttps://rfm.rsquaredacademy.com/", "BugReports": "https://github.com/rsquaredacademy/rfm/issues", "VignetteBuilder": "knitr", "Encoding": "UTF-8", "LazyData": "true", "RoxygenNote": "7.3.3", "Config/testthat/edition": "3", "Repository": "https://rsquaredacademy.r-universe.dev", "Date/Publication": "2026-10-16 08:21:07 UTC", "RemoteUrl": "https://github.com/rsquaredacademy/rfm", "RemoteRef": "HEAD", "RemoteSha": "869fa0a597d584b116cfb1eb4c6cea48a0513140", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-16 13:13:50 UTC", "User": "root" }, "Author": "Aravind Hebbali [aut, cre] (ORCID:\n)", "Maintainer": "Aravind Hebbali ", "_user": "rsquaredacademy", "_type": "src", "_file": "rfm_0.5.0.tar.gz", "_fileid": "https://r2.ropensci.org/669880afa2aba991258d505bf16e6d572d841fcec625dc9c4679c7b30fd23f7e", "_filesize": 1370753, "_sha256": "669880afa2aba991258d505bf16e6d572d841fcec625dc9c4679c7b30fd23f7e", "_expires": "2027-01-24T13:24:18.000Z", "_created": "2026-10-16T13:13:50.000Z", "_published": "2026-10-16T13:24:21.146Z", "_buildurl": "https://github.com/r-universe/rsquaredacademy/actions/runs/38905776536", "_status": "success", "_host": "GitHub-Actions", "_jobs": [ { "job": 116990608373, "time": 169, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "12048875316" }, { "job": 116990608905, "time": 188, "config": "linux-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "12048850699" }, { "job": 116990608552, "time": 138, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "12049190359" }, { "job": 116990608415, "time": 112, "config": "macos-release-arm64", "r": "4.6.1", "check": "OK", "artifact": "12048024361" }, { "job": 116989033460, "time": 220, "config": "source", "r": "4.6.1", "check": "OK", "artifact": "12048537076" }, { "job": 116990608601, "time": 109, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "12048691885" }, { "job": 116990608588, "time": 119, "config": "windows-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "12048860400" }, { "job": 116990608569, "time": 122, "config": "windows-oldrel-x86_64", "r": "4.5.3", "check": "OK", "artifact": "12048816805" }, { "job": 116990608754, "time": 99, "config": "windows-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "12047409866" } ], "_upstream": "https://github.com/rsquaredacademy/rfm", "_commit": { "id": "869fa0a597d584b116cfb1eb4c6cea48a0513140", "author": "Aravind Hebbali ", "committer": "GitHub ", "message": "Merge pull request #108 from rsquaredacademy/develop\n\nrfm 0.5.0 (on CRAN)", "time": 1792138867 }, "_maintainer": { "name": "Aravind Hebbali", "email": "hebbali.aravind@gmail.com", "login": "aravindhebbali", "twitter": "@rsquaredacademy", "description": "#rstats #economics", "uuid": 8706536, "orcid": "0000-0001-9220-9669" }, "_distro": "resolute", "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 3.2", "role": "Depends" }, { "package": "cli", "role": "Imports" }, { "package": "dplyr", "role": "Imports" }, { "package": "ggplot2", "role": "Imports" }, { "package": "magrittr", "role": "Imports" }, { "package": "RColorBrewer", "role": "Imports" }, { "package": "rlang", "role": "Imports" }, { "package": "scales", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "utils", "role": "Imports" }, { "package": "covr", "role": "Suggests" }, { "package": "DT", "role": "Suggests" }, { "package": "gganimate", "role": "Suggests" }, { "package": "gifski", "role": "Suggests" }, { "package": "kableExtra", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { "package": "plotly", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "rmdformats", "role": "Suggests" }, { "package": "testthat", "version": ">= 3.0.0", "role": "Suggests" }, { "package": "treemapify", "role": "Suggests" }, { "package": "vdiffr", "role": "Suggests" }, { "package": "xplorerr", "role": "Suggests" } ], "_owner": "rsquaredacademy", "_selfowned": true, "_usedby": 0, "_updates": [ { "week": "2026-18", "n": 1 }, { "week": "2026-42", "n": 1 } ], "_tags": [ { "name": "v0.4.0", "date": "2026-04-30" }, { "name": "v0.5.0", "date": "2026-10-15" } ], "_topics": [ "customer-analytics", "customer-segmentation", "rfm-analysis", "segmentation" ], "_stars": 69, "_contributors": [ { "user": "aravindhebbali", "count": 446, "uuid": 8706536 }, { "user": "framartin", "count": 2, "uuid": 1850174 } ], "_userbio": { "uuid": 23705610, "type": "organization", "name": "Rsquared Academy", "followers": 25 }, "_downloads": { "count": 1076, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/rfm" }, "_mentions": 1, "_devurl": "https://github.com/rsquaredacademy/rfm", "_pkgdown": "https://rfm.rsquaredacademy.com/", "_searchresults": 119, "_rbuild": "4.6.1", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/manual.pdf", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md", "extra/rfm.html", "LICENSE" ], "_homeurl": "https://github.com/rsquaredacademy/rfm", "_realowner": "rsquaredacademy", "_cranurl": true, "_releases": [ { "version": "0.1.0", "date": "2018-04-09" }, { "version": "0.2.0", "date": "2019-01-14" }, { "version": "0.2.1", "date": "2020-04-23" }, { "version": "0.2.2", "date": "2020-07-21" }, { "version": "0.3.0", "date": "2024-02-26" }, { "version": "0.4.0", "date": "2026-04-30" }, { "version": "0.5.0", "date": "2026-10-16" } ], "_exports": [ "rfm_bar_chart", "rfm_barchart_data", "rfm_create_report", "rfm_fm_plot", "rfm_heatmap", "rfm_heatmap_data", "rfm_histograms", "rfm_launch_app", "rfm_order_dist", "rfm_plot_bar_chart", "rfm_plot_heatmap", "rfm_plot_histogram", "rfm_plot_median_frequency", "rfm_plot_median_monetary", "rfm_plot_median_recency", "rfm_plot_order_dist", "rfm_plot_revenue_dist", "rfm_plot_segment", "rfm_plot_segment_scatter", "rfm_plot_segment_summary", "rfm_rf_plot", "rfm_rm_plot", "rfm_segment", "rfm_segment_summary", "rfm_table_customer", "rfm_table_customer_2", "rfm_table_order" ], "_datasets": [ { "name": "rfm_data_customer", "title": "RFM customer data", "object": "rfm_data_customer", "class": [ "data.frame" ], "fields": [ "customer_id", "revenue", "most_recent_visit", "number_of_orders", "recency_days", "first_name", "last_name", "email" ], "rows": 39999, "table": true, "tojson": true }, { "name": "rfm_data_orders", "title": "RFM transaction data", "object": "rfm_data_orders", "class": [ "data.frame" ], "fields": [ "customer_id", "order_date", "revenue", "first_name", "last_name", "email" ], "rows": 4906, "table": true, "tojson": true } ], "_help": [ { "page": "rfm_barchart_data", "title": "Bar chart data", "topics": [ "rfm_barchart_data" ] }, { "page": "rfm_create_report", "title": "RFM report", "topics": [ "rfm_create_report" ] }, { "page": "rfm_data_customer", "title": "RFM customer data", "topics": [ "rfm_data_customer" ] }, { "page": "rfm_data_orders", "title": "RFM transaction data", "topics": [ "rfm_data_orders" ] }, { "page": "rfm_heatmap_data", "title": "Heatmap data", "topics": [ "rfm_heatmap_data" ] }, { "page": "rfm_launch_app", "title": "Launch shiny app", "topics": [ "rfm_launch_app" ] }, { "page": "rfm_plot_bar_chart", "title": "RFM bar chart", "topics": [ "rfm_bar_chart", "rfm_plot_bar_chart" ] }, { "page": "rfm_plot_heatmap", "title": "RFM heatmap", "topics": [ "rfm_heatmap", "rfm_plot_heatmap" ] }, { "page": "rfm_plot_histogram", "title": "RFM histograms", "topics": [ "rfm_histograms", "rfm_plot_histogram" ] }, { "page": "rfm_plot_median_recency", "title": "Median plots", "topics": [ "rfm_plot_median_frequency", "rfm_plot_median_monetary", "rfm_plot_median_recency" ] }, { "page": "rfm_plot_order_dist", "title": "Customers by orders", "topics": [ "rfm_order_dist", "rfm_plot_order_dist" ] }, { "page": "rfm_plot_revenue_dist", "title": "Revenue distribution", "topics": [ "rfm_plot_revenue_dist" ] }, { "page": "rfm_plot_segment", "title": "RFM Segmentation Plot", "topics": [ "rfm_plot_segment" ] }, { "page": "rfm_plot_segment_scatter", "title": "Segment Scatter Plots", "topics": [ "rfm_plot_segment_scatter" ] }, { "page": "rfm_plot_segment_summary", "title": "Visulaize segment summary", "topics": [ "rfm_plot_segment_summary" ] }, { "page": "rfm_rm_plot", "title": "RFM Scatter plot", "topics": [ "rfm_fm_plot", "rfm_rf_plot", "rfm_rm_plot" ] }, { "page": "rfm_segment", "title": "Segmentation", "topics": [ "rfm_segment" ] }, { "page": "rfm_segment_summary", "title": "Segment summary", "topics": [ "rfm_segment_summary" ] }, { "page": "rfm_table_customer", "title": "RFM table (customer data)", "topics": [ "rfm_table_customer", "rfm_table_customer_2" ] }, { "page": "rfm_table_order", "title": "RFM table (transaction data)", "topics": [ "rfm_table_order" ] } ], "_readme": "https://github.com/rsquaredacademy/rfm/raw/HEAD/README.md", "_rundeps": [ "cli", "cpp11", "dplyr", "farver", "generics", "ggplot2", "glue", "gtable", "isoband", "labeling", "lifecycle", "magrittr", "pillar", "pkgconfig", "R6", "RColorBrewer", "rlang", "S7", "scales", "tibble", "tidyselect", "utf8", "vctrs", "viridisLite", "withr" ], "_vignettes": [ { "source": "rfm-introduction.Rmd", "filename": "rfm-introduction.html", "title": "RFM - Introduction", "author": "Aravind Hebbali", "engine": "knitr::rmarkdown", "headings": [ "Introduction", "Data", "RFM Score", "Segments", "Segmented Customer Data", "Segment Summary", "Segmentation Plot", "Segment Summary Plot", "Revenue Distribution" ], "created": "2023-06-28 11:00:36", "modified": "2024-02-26 11:47:06", "commits": 2 } ], "_score": 6.946208323460156, "_indexed": true, "_nocasepkg": "rfm", "_universes": [ "rsquaredacademy", "aravindhebbali" ], "_previous": "0.4.0", "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.5.0", "date": "2026-10-16T13:16:14.000Z", "distro": "resolute", "commit": "869fa0a597d584b116cfb1eb4c6cea48a0513140", "fileid": "https://r2.ropensci.org/98be07172837d3a994662587f2a263299e8e3b978bf4ca0ac73dd3c614eb541d", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/rsquaredacademy/actions/runs/38905776536" }, { "r": "4.6.1", "os": "linux", "version": "0.5.0", "date": "2026-10-16T13:16:39.000Z", "distro": "resolute", "commit": "869fa0a597d584b116cfb1eb4c6cea48a0513140", "fileid": "https://r2.ropensci.org/298a69d42e0aa8d5f6eac90430a7cb45683e295652ebab3a0f89e017008209a2", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/rsquaredacademy/actions/runs/38905776536" }, { "r": "4.5.3", "os": "mac", "version": "0.5.0", "date": "2026-10-16T13:23:20.000Z", "commit": "869fa0a597d584b116cfb1eb4c6cea48a0513140", "fileid": "https://r2.ropensci.org/4322bf97f6f9fc4f31f9756f2b373dc4bc743354d32de9a4fb3633f81a5ffa5f", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/rsquaredacademy/actions/runs/38905776536" }, { "r": "4.6.1", "os": "mac", "version": "0.5.0", "date": "2026-10-16T13:22:00.000Z", "commit": "869fa0a597d584b116cfb1eb4c6cea48a0513140", "fileid": "https://r2.ropensci.org/6459101e6feec4f19fbc907b832d6e765fc40f1e2d43e3e1dc3bd76e8d8e2472", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/rsquaredacademy/actions/runs/38905776536" }, { "r": "4.6.0", "os": "wasm", "version": "0.5.0", "date": "2026-10-16T13:15:59.000Z", "commit": "869fa0a597d584b116cfb1eb4c6cea48a0513140", "fileid": "https://r2.ropensci.org/336a4a70232407328d35f4969184111b24fa57f22221dff37b7d67a461361d1e", "status": "success", "buildurl": "https://github.com/r-universe/rsquaredacademy/actions/runs/38905776536" }, { "r": "4.7.0", "os": "win", "version": "0.5.0", "date": "2026-10-16T13:15:13.000Z", "commit": "869fa0a597d584b116cfb1eb4c6cea48a0513140", "fileid": "https://r2.ropensci.org/3a1c9353b227e088f092a64cdbb8cd82b52d4bd4f1a38262f125ff14af804326", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/rsquaredacademy/actions/runs/38905776536" }, { "r": "4.5.3", "os": "win", "version": "0.5.0", "date": "2026-10-16T13:15:23.000Z", "commit": "869fa0a597d584b116cfb1eb4c6cea48a0513140", "fileid": "https://r2.ropensci.org/e30cefaf4479e4c07a148c86f905f82ba135f910616ac36fb73f7b0d1c196a4c", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/rsquaredacademy/actions/runs/38905776536" }, { "r": "4.6.1", "os": "win", "version": "0.5.0", "date": "2026-10-16T13:15:08.000Z", "commit": "869fa0a597d584b116cfb1eb4c6cea48a0513140", "fileid": "https://r2.ropensci.org/3c79e380aa23d6ca1cd6fba523ce9a5e30b208f8550261f30191f113b85eb5c0", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/rsquaredacademy/actions/runs/38905776536" } ] }