Targeted Advertising and Inventory Optimization Improvements Utilizing User Location and Selection Data

Abstract

A Targeted Advertising and Inventory Optimization Improvement system utilizing user location and selection data to generate targeted advertisements and store layout optimizations. The targeted advertising is generated based on user location and item selection data as a user navigates a store along a predetermined route. The inventory optimization are generated user location and selection data to determine optimal inventory placement along a predetermined route,

We claim the following: 
     
         1 . A targeted advertising system using data collected from multiple user visits to a store, comprising:
 a location tracking system that monitors a user's location within the store;   an item selection system that allows users to select items for purchase that are located within the store at known locations;   a route planning system that plans routes through the store based on the selected items;   a data collection system that collects data on user visits to the store, including the locations visited by the user and the items selected for purchase;   a data analysis system that processes the collected data to determine products associated with locations that the user visits at the store but does not purchase any items from; and   an advertising system that uses the determined products to select advertisements to present to the user.   
     
     
         2 . The targeted advertising system of  claim 1 , further comprising a data storage system that stores the collected data on user visits to the store, including the locations visited by the user and the items selected for purchase. 
     
     
         3 . The targeted advertising system of  claim 1 , wherein the data analysis system utilizes machine learning algorithms to process the collected data and identify patterns in user behavior within the store. 
     
     
         4 . The targeted advertising system of  claim 1 , wherein the advertising system presents the selected advertisements to the user via a mobile device or in-store display. 
     
     
         5 . The targeted advertising system of  claim 1 , wherein the route planning system utilizes information on the layout of the store and the characteristics of the selected items to generate an optimized route for the user to follow during their visit to the store. 
     
     
         6 . A method for targeted advertising to promote products to users based on their previous visits to a store, comprising:
 monitoring a user's location within the store during each visit using a location tracking system;   allowing users to select items for purchase that are located within the store at known locations using an item selection system;   collecting data on the items selected by the user during each visit using a data collection system;   analyzing the collected data to determine the locations in the store that the user frequently visits, but does not purchase any items from, using a data analysis system;   generating targeted advertisements promoting products associated with the determined locations to the user for subsequent visits to the store using a targeted advertising generation system;   planning routes through the store for users' subsequent visits to the store based on the characteristics of the items on the user's list, wherein the planned route includes the determined locations for which the user has not previously purchased any items, using a route planning system.   
     
     
         7 . The method of  claim 6 , wherein the data analysis system further analyzes the collected data to determine the times of day or days of the week when the user visits the determined locations but does not make purchases. 
     
     
         8 . The method of  claim 6 , wherein the item selection system suggests alternative items to the user based on the determined locations for which the user has not previously purchased any items. 
     
     
         9 . The method of  claim 6 , wherein the route planning system further plans the route through the store to increase or decrease the amount time required to visit the determined locations for which the user has not previously purchased any items. 
     
     
         10 . A store layout optimization system comprising:
 a customer history data input module configured to receive customer history data relating to a plurality of customers to a store, the customer history data comprising customer item selection data and customer tracked location data;   a store layout data input module configured to receive store layout data comprising data relating to a current physical layout of said store;   an item data input module configured to receive item data comprising data relating to a location of an item for sale within said store;   a planogram optimization module configured to optimize a store layout based on the customer history data, the store layout data, and the item data, wherein the planogram optimization module generates one of an optimized store layout for said store and recommended stock quantities for items based on the received data.   
     
     
         11 . The system of  claim 10 , wherein the optimization module determines the optimal placement of items on store shelves based on the analysis of customer history data and item data. 
     
     
         12 . The system of  claim 10 , further comprising a recommendation module that generates recommendations for stock quantities of items based on the analysis of customer history data and item data. 
     
     
         13 . The system of  claim 12 , further comprising a planned purchase order module that generates a recommended order quantity and frequency of stocked items based on the analysis of customer history data and item data. 
     
     
         14 . The method of  claim 6 , further comprising analyzing customer purchase data to identify popular product combinations, and optimizing the store layout to promote sales of those popular product combinations. 
     
     
         15 . A method for optimizing a store layout comprising:
 receiving customer history data relating to a plurality of customers to a store, the customer history data comprising customer item selection data and customer tracked location data;   receiving store layout data comprising data relating to a current physical layout of said store;   receiving item data comprising data relating to a location of an item for sale within said store;   analyzing the received customer history data, store layout data, and item data to optimize the store layout;   generating an optimized store layout or recommended stock quantities for items based on the analysis of the received data.   
     
     
         16 . The method of  claim 15 , wherein optimizing the store layout includes determining the optimal placement of items on store shelves based on the analysis of customer history data and item data. 
     
     
         17 . The method of  claim 15 , further comprising generating recommendations for stock quantities of items based on the analysis of customer history data and item data. 
     
     
         18 . The method of  claim 15 , further comprising analyzing customer purchase data to identify popular product combinations, and optimizing the store layout to promote sales of those popular product combinations. 
     
     
         19 . The method of  claim 15 , further comprising generating recommendations for stock purchase order quantities and frequencies of items based on the analysis of customer history data and item data.