ESTIMATING SHELF CAPACITY FROM IMAGE DATA TO IMPROVE STORE EXECUTION

1 - 161 . (canceled)

162 . A system for processing images captured in a retail store and automatically determining options for store execution based on shelf capacity, the system comprising:

at least one processor configured to:

receive a set of images captured during a period of time, wherein the set of images depict a first plurality of products from a particular product type displayed on a shelving unit in a retail store;

analyze the set of images to identify a portion of the shelving unit associated with the particular product type;

determine a product capacity for the portion of the shelving unit dedicated to the particular product type, wherein the determined product capacity is greater than a number of the first plurality of products depicted in the set of images;

access stored data about a second plurality of products from the particular product type, wherein each of the second plurality of products is located separately from the shelving unit when the period of time ends;

use the product capacity for the portion of the shelving unit dedicated to the particular product type and the accessed data to generate at least one suggestion for improving store execution; and

provide the at least one suggestion for improving store execution.

163 . The system of claim 162 , wherein the at least one processor is further configured to:

obtain data indicative of a depth of the shelving unit; and

determine the product capacity for the portion of the shelving unit dedicated to the particular product type based on the depth of the shelving unit.

164 . The system of claim 163 , wherein the at least one processor is further configured to:

analyze the set of images to determine at least one dimension of products from the particular product type; and

determine the product capacity for the portion of the shelving unit dedicated to the particular product type based on the depth of the shelving unit and the at least one dimension of products from the particular product type.

165 . The system of claim 64 , wherein the at least one processor is further configured to:

based on the at least one dimension of products from the particular product type, determine a maximum number of products from the particular product type that can be placed in a front row of products associated with the portion of the shelving unit dedicated to the particular product type;

based on the obtained shelf depth, determine a maximum number of products from the particular product type that can be placed behind the front row of products; and

determine the product capacity associated with the portion of the shelving unit dedicated to the particular product type based on the maximum number of products that can be placed in the front row and the maximum number of products that can be placed behind the front row.

166 . A computer program product for processing images captured in a retail store and automatically determining options for store execution based on shelf capacity, the computer program product embodied in a non-transitory computer-readable medium and including instructions for causing at least one processor to execute a method comprising:

receiving a set of images captured during a period of time, wherein the set of images depicts a first plurality of products from a particular product type displayed on a shelving unit in a retail store;

analyzing the set of images to identify a portion of the shelving unit dedicated to the particular product type;

determining a product capacity for the portion of the shelving unit dedicated to the particular product type, wherein the determined product capacity is greater than a number of the first plurality of products depicted in the set of images;

accessing stored data about a second plurality of products from the particular product type, wherein each of the second plurality of products is located separately from the shelving unit when the period of time ends;

using the determined product capacity and the accessed data to generate at least one suggestion for improving store execution; and

providing the at least one suggestion for improving store execution.

167 . The computer program product of claim 166 , wherein the at least one suggestion for improving the store execution includes changing a size of the portion of the at least one store shelf dedicated to products from the particular product type.

168 . The computer program product of claim 166 , wherein the at least one suggestion for improving the store execution includes changing a re-stocking frequency of products from the particular product type at the at least one store shelf.

169 . The computer program product of claim 166 , wherein the at least one suggestion for improving the store execution includes at least one of: changing product assortment for the retail store, changing a product assortment for the shelving unit, changing a position of products in the shelving unit, changing a space dedicated to products from the particular product type, changing a type of shelf of the shelving unit, or changing a spacing between shelves of the shelving unit.

170 . The computer program product of claim 166 , wherein the at least one suggestion for improving the store execution includes at least one of: changing a storage capacity of products from the particular product type in the store's backroom, changing a location of products from the particular product type in the store's backroom, or providing an order recommendation for restocking the store's backroom.

171 . The computer program product of claim 166 , wherein the stored data includes sales data indicative of a number of the second plurality of products sold during the period of time, and the method further includes:

analyzing the set of images to estimate a number of products from the particular product type placed on the portion of the shelving unit;

determining a level of product population at the portion of the shelving unit dedicated to the particular product type based on the estimated number of products and the determined product capacity;

identifying changes in the level of product population during the period of time; and

determining the at least one suggestion for improving the store execution based on identified correlations between the sales data and the changes in the level of product population.

172 . The computer program product of claim 171 , wherein the method further includes:

obtaining additional sales data indicative of products from the particular product type sold during a second period of time after the at least one suggestion was implemented; and

determining whether implementing the at least one suggestion resulted in higher sales of the particular product type during the second period of time.

173 . The computer program product of claim 166 , wherein the stored data includes inventory data indicative of a number of the second plurality of products available in at least one storage area associated with the retail store, and the method further includes:

identifying changes in a level of product population at the portion of the shelving unit dedicated to the particular product type during the period of time based on the set of images and the determined product capacity; and

generating the at least one suggestion for improving the store execution based on the changes in the level of product population and the inventory data; and

displaying the at east one suggestion to an employee of the retail store.

174 . The computer program product of claim 166 , wherein the method further includes:

comparing the determined product capacity for the portion of the shelving unit dedicated to the particular product type with a capacity for product facings for the particular product type at the portion of the shelving unit dedicated to the particular product type;

in response to a first result of the comparison, providing a suggestion for changing the capacity for product facings for the particular product type at the portion of the shelving unit dedicated to the particular product type; and

in response to a second result of the comparison, forgoing providing the suggestion

175 . The computer program product of claim 166 , wherein the stored data includes reference data indicative of a number of the second plurality of products available on a shelving unit of at least one other retail store, and the method further includes:

identifying changes in a level of product population at the portion of the shelving unit dedicated to the particular product type during the period of time based on the set of images and the determined product capacity; and

generating and providing the at least one suggestion for improving the store execution based on the changes in a level of product population and the reference data.

176 . The computer program product of claim 166 , wherein the method further includes:

analyzing the set of images to detect changes during the period of time in a number of front facing products placed on the portion of the shelving unit dedicated to the particular product type; and

using the product capacity and the detected changes in the number of front facing products to generate and display the at least one suggestion for improving store execution.

177 . The computer program product of claim 176 , wherein the at least one suggestion includes changing a restocking schedule of products from the particular product type to reduce a time duration where the number of front facing products is less than a threshold.

178 . The computer program product of claim 177 , wherein the method further includes:

obtaining sales data reflective of products from the particular product type sold during a second period of time after the at least one suggestion was implemented; and

determining whether changing the restocking schedule to reduce the time duration where the number of front facing products is less than the threshold resulted in higher sales of the particular product type during the second period of time.

179 . The computer program product of claim 176 , wherein the method further includes:

using the determined product capacity and the detected changes in the number of front facing products to predict a time when the number of front facing products is less than a threshold: and

determining at least one suggestion for restocking the portion of the shelving unit dedicated to the particular product type before the predicted time.

180 . The computer program product of claim 179 , wherein the method further includes:

causing restocking, of the portion of the shelving unit dedicated to the particular product type while the number of front facing products is at a maximum possible number of front facing products associated with the portion of the shelving unit dedicated to the particular product type.

181 . A method for processing images captured in a retail store and automatically determining options for store execution based on shelf capacity, the method comprising:

receiving a set of images captured during a period of time, wherein the set of images depicts a first plurality of products from a particular product type displayed on a shelving unit in a retail store:

analyzing the set of images to identify a portion of the shelving unit dedicated to the particular product type;

determining a product capacity for the portion of the shelving unit dedicated to the particular product type, wherein the determined product capacity is greater than a number of the first plurality of products depicted in the set of images:

accessing stored data about a second plurality of products from the particular product type, wherein each of the second plurality of products is located separately from the shelving unit when the period of time ends;

using the determined product capacity and the accessed data to generate at least one suggestion for improving store execution; and providing the at least one suggestion for improving store execution.

182 - 221 . (canceled)