{"id":20608915,"url":"https://github.com/tpunt/shopper","last_synced_at":"2025-03-06T17:41:24.019Z","repository":{"id":77845209,"uuid":"46755653","full_name":"tpunt/shopper","owner":"tpunt","description":"Arbitrating new store opening locations based on business intelligence acquired from customers","archived":false,"fork":false,"pushed_at":"2015-12-07T21:12:56.000Z","size":74,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-01-17T03:13:48.549Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Elixir","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/tpunt.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}},"created_at":"2015-11-23T23:59:32.000Z","updated_at":"2019-05-17T08:50:40.000Z","dependencies_parsed_at":"2023-03-14T12:45:39.982Z","dependency_job_id":null,"html_url":"https://github.com/tpunt/shopper","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/tpunt%2Fshopper","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tpunt%2Fshopper/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tpunt%2Fshopper/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tpunt%2Fshopper/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/tpunt","download_url":"https://codeload.github.com/tpunt/shopper/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":242256412,"owners_count":20097972,"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":"2024-11-16T10:12:13.518Z","updated_at":"2025-03-06T17:41:23.985Z","avatar_url":"https://github.com/tpunt.png","language":"Elixir","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Shopper\n\nContents:\n - [Overview](#overview)\n - [Introduction](#introduction)\n - [Application Features](#application-features)\n\n## Overview\n\nThis application is the server application for mine and\n[Liam Mann](https://github.com/liammann)'s **Shopper** application.\n\nShopper visualises the spatial distribution of a company’s stores and their\nvisiting customer base to provide further business intelligence for arbitrating\nnew store locations.\n\nLink to client application: to be open sourced...\n\n## Introduction\n\nThe aim of this project is to provide a generic solution that companies can\nutilise to analyse the shopping location patterns of their customer base. This\nis based on the requirement for companies to intelligently select new store\nlocations based on which areas will most likely yield the most revenue and\ntherefore increase their return on investment.\n\nTo achieve this, company store locations will be plotted on a map, along with\ncustomer locations from the company’s sales history database. Lines will\nvisually represent the direct route from customer residence to store locations,\nwith a time lapse animation. These timeframes will either be over set periods\nof time e.g. month by month, or from the opening of new stores in the area to\ndisplay fluctuations in customer store choices.\n\nThis will enable for the following facets to be inspected:\n - Where the general grouping of the customer base is\n - How far customers travel to their selected store\n - How successful a new store opening was\n - Which stores are being used less and whether there’s a correlation to the\n distance of the customer base. (This can then be used to indicate problems\n   such as; questionable quality of the store, quantity of the products\n   stocked, or other competitor’s stores in the area.)\n\n## Application Features\n\nThe following features are provided by the client application:\n - Visualise spatial distribution of customers to the stores they visit\n - Get the mean and median distances customers travel to any given store\n - Customer visit history can be viewed from a given time scale, as well as\n from break points in the history according to new store openings\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftpunt%2Fshopper","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftpunt%2Fshopper","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftpunt%2Fshopper/lists"}