Predictive recommendation engine
US-2016127010-A1 · May 5, 2016 · US
US2016292703A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2016292703-A1 |
| Application number | US-201615085260-A |
| Country | US |
| Kind code | A1 |
| Filing date | Mar 30, 2016 |
| Priority date | Mar 30, 2015 |
| Publication date | Oct 6, 2016 |
| Grant date | — |
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Provided herein are methodologies, systems, and devices for simulating the performance of products a within a display area of a retail store. Data relating to a product's attributes, location within a display area, and historical performance can be used to create a model that can predict the impact on sales that will result from moving particular items from one location in a display area to another location. Once created, this model can predict a product's performance at various locations and assist in optimizing product placement within a display area. A GUI of an electronic device can display a virtual display area that allows a user to create various product placement scenarios. The model may also display product placement recommendations based on the predicted performance values of various products at different locations within a display area.
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What is claimed is: 1 . A method of simulating product performance based on physical and economic attributes associated with a product and a product display area in a retail location, the method comprising: receiving, in an electronic computer-readable format, product attribute data corresponding to physical and economic attributes of a product, product location data representing a first physical location of the product within a display area of a store, and historical product performance data; creating a model of the product at the first physical location based on the product attribute data and the historic data; simulating product performance for the product using the model to generate a predicted performance value for the product at a second physical location within the display area of the store; and transmitting instructions to render the simulation of the product performance in a graphical user interface, and depicting within the graphical user interface, the predicted performance value. 2 . The method of claim 1 , wherein the product attribute data is representative of product shelf volume, product price, product size, product weight, product shape, product shelf life, product brand, product seasonality, product marketing, product market share, or product brand contribution to category sales. 3 . The method of claim 1 , wherein the historical product performance data is representative of sales, units sold, or profit margin for the product at each location within the display area. 4 . The method of claim 1 , wherein the graphical user interface is further programmed to display a virtual display area including a graphical indicator of at least one product at a first location within the virtual display area. 5 . The method of claim 4 , further comprising receiving, via the graphical user interface, user input relocating the at least one product from the first location to a second location within the virtual display area, the graphical user interface further programmed to display the at least one product at the second location within the virtual display area. 6 . The method of claim 5 , wherein the user input includes a drag-and-drop command performed via a pointing device of the electronic display device. 7 . The method of claim 5 , further comprising generating, with a processor of the performance prediction system, a predicted change in product performance between the first location and the second location by calculating a difference between a predicted performance value at the second location and a predicted performance value at the first location. 8 . The method of claim 7 , the graphical user interface further programmed to display an indication of the predicted change in product performance between the first location and the second location. 9 . The method of claim 7 , further comprising generating, with a processor of the performance prediction system, a predicted change in sales, units sold, or profit margin for a product category in response to relocating a product within the product category from a first location to a second location. 10 . The method of claim 7 , wherein relocating a first product from a first location to a second location displaces a second product from the second location to a third location, the method further comprising generating, with a processor of the performance prediction system, a predicted change in product performance of the second product between the second location and the third location. 11 . The method of claim 7 , further comprising generating, with a processor of the performance prediction system, an optimum placement of the at least one product within the display area based on the predicted change in product performance. 12 . A system of simulating product performance based on physical and economic attributes associated with a product and a product display area in a retail location, the system comprising: one or more servers programmed to: receive, in an electronic computer-readable format, product attribute data corresponding to physical and economic attributes of a product, product location data representing a first physical location of the product within a display area of a store, and historical product performance data; create a model of the product at the first physical location based on the product attribute data and the historic data; simulate product performance for the product using the model to generate a predicted performance value for the product at a second physical location within the display area of the store; and transmit instructions to render the simulation of the product performance in a graphical user interface, and depicting within the graphical user interface, the predicted performance value. 13 . The system of claim 12 , wherein the product attribute data is representative of product shelf volume, product price, product size, product weight, product shape, product shelf life, product brand, product seasonality, product marketing, product market share, or product brand contribution to category sales. 14 . The system of claim 12 , wherein the historical product performance data is representative of sales, units sold, or profit margin for the product at each location within the display area. 15 . The system of claim 12 , wherein the graphical user interface is further programmed to display a virtual display area including a graphical indicator of at least one product at a first location within the virtual display area. 16 . The system of claim 15 , wherein the one or more servers are further programmed to receive via the graphical user interface, user input relocating the at least one product from the first location to a second location within the virtual display area, the graphical user interface further programmed to display the at least one product at the second location within the virtual display area. 17 . The system of claim 16 , wherein the user input includes a drag-and-drop command performed via a pointing device of the electronic display device. 18 . The system of claim 16 , wherein the one or more servers are further programmed to generate a predicted change in product performance between the first location and the second location by calculating a difference between a predicted performance value at the second location and a predicted performance value at the first location. 19 . The system of claim 18 , wherein the graphical user interface is further programmed to display an indication of the predicted change in product performance between the first location and the second location. 20 . The system of claim 18 , wherein the one or more servers are further programmed to generate a predicted change in sales, units sold, or profit margin for a product category in response to relocating a product within the product category from a first location to a second location. 21 . The system of claim 18 , wherein relocating a first product from a first location to a second location displaces a second product from the second location to a third location, the one or more servers further programmed to generate a predicted change in product performance of the second product between the second location and the third location. 22 . The system of claim 18 , wherein the one or more servers are further programmed to generate an optimum placement of the at least one product within the display area based on the predicted change in product performance. 23 . A non-
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