Mobile device based inventory management and sales trends analysis in a retail environment

Abstract

A method for calculating sales trend of a product at a store shelf based on crowdsourcing, includes receiving, by a retail store server, availability data of a product measured on a shelf in the retail store from a portable device, where the availability data is in the form of a picture acquired of the product on the shelf, identifying products on the shelf using tags attached to the shelves, calculating sales velocity and sales trends of the product from the identified products, and transmitting the sales velocity and sales trend of the product to one or more third parties' systems in a supply chain of said retail store. Products and their locations on retail store shelves have been cataloged in a product database.

What is claimed is: 
     
         1 . A method for calculating sales trend of a product at a store shelf based on crowdsourcing, comprising the steps of:
 receiving, by a retail store server, availability data of a product measured on a shelf in the retail store from a portable device, wherein the availability data is in the form of a picture acquired of the product on the shelf;   identifying products on the shelf using tags attached to the shelves;   calculating sales velocity and sales trends of the product from the identified products; and   transmitting the sales velocity and sales trend of the product to one or more third parties' systems in a supply chain of said retail store,   wherein products and their locations on retail store shelves have been cataloged in a product database.   
     
     
         2 . The method of  claim 1 , further comprising triggering a warning message if the retail store shelf is empty. 
     
     
         3 . The method of  claim 1 , wherein identifying products on the shelf using tags comprises the steps of:
 identifying the tags on the shelves using tag template information and information regarding a distribution of tags on the retail store shelves that is read from a tag database;   mapping the identified tags to a shelf and its corresponding assortment of items;   identifying products in the picture by reading product templates related to the identified tags from the product database; and   transmitting a list of identified products and their quantities to the server.   
     
     
         4 . The method of  claim 3 , wherein identifying the tags is performed by a first image processing application, and identifying products in the picture is performed by a second image processing application. 
     
     
         5 . The method of  claim 3 , further comprising filtering the results of identified products based on product dimensions, to eliminate false positives. 
     
     
         6 . The method of  claim 1 , wherein calculating sales velocity and sales trends of the product comprises the steps of:
 receiving for each product p a timestamp t and a number of items n of product p on the retail store shelf, where the product information is organized as pairs p(t, n);   ordering product pairs p(t, n) according to the timestamp t to generate an ordered sequence;   calculating a least square line fit for the sequence to estimate a sales' velocity; and   comparing changes in a slope of the fitted line to determine a change in the sale's velocity over time.   
     
     
         7 . A method for minimizing a products out-of-the-shelf time based on data collected by mobile applications, comprising the steps of:
 receiving, by a retail store server, data acquired by a mobile application regarding a number of missing product items on a shelf in the retail store;   calculating the product's turnover;   receiving, by the retail store server, a request for an optimized replenishment route;   generating an optimized replenishment route from the products' turnover calculation that minimizes out-of-the-shelf occurrences; and   transmitting the optimized replenishment route to the mobile application for display to a user.   
     
     
         8 . The method of  claim 7 , wherein the product's turnover is calculated by a first sales trend calculation application. 
     
     
         9 . The method of  claim 7 , further comprising updating demand forecasts of the reported missing product items in a product localization and turnover database. 
     
     
         10 . The method of  claim 7 , wherein the optimized replenishment route is calculated by a second sales trend calculation application. 
     
     
         11 . The method of  claim 7 , wherein the data of number of missing product items on a shelf acquired by the mobile application is in the form of a picture,
 wherein products and their locations on retail store shelves have been cataloged in a product database, and   wherein the method further comprises identifying products on the shelf using tags attached to the shelves.   
     
     
         12 . The method of  claim 11 , wherein identifying products on the shelf using tags comprises the steps of:
 identifying the tags on the shelves using tag template information and information regarding a distribution of tags on the retail store shelves that is read from a tag database;   mapping the identified tags to a shelf and its corresponding assortment of items;   identifying products in the picture by reading product templates related to the identified tags from the product database; and   transmitting a list of identified products and their quantities to the server.   
     
     
         13 . The method of  claim 12 , wherein identifying the tags is performed by a first image processing application, and identifying products in the picture is performed by a second image processing application. 
     
     
         14 . The method of  claim 12 , further comprising filtering the results of identified products based on product dimensions, to eliminate false positives.