Abstract: A system for automatically addressing detected conditions within the retail store is provided. The system may include at least one processor configured to receive a plurality of images depicting a plurality of products displayed on a plurality of store shelves; retrieve reference data specifying a desired state of the retail store; use the reference data to detect an indicator of a first service-improvement condition; use the reference data to detect an indicator of a second service-improvement; determine a first product-related task for addressing the first service-improvement condition; determine a second product-related task for addressing the second service-improvement condition; access a database storing information indicative of a first employee and a second employee on duty during a time interval over which the plurality of images was received; and assign the first product-related task to the first employee and assign the second product-related task to the second employee.

Abstract: A system for acquiring images of products in a retail store is disclosed. The system may include at least one first housing configured for location on a retail shelving unit, and at least one image capture device included in the at least one first housing and configured relative to the at least one first housing such that an optical axis of the at least one image capture device is directed toward an opposing retail shelving unit when the at least one first housing is fixedly mounted on the retail shelving unit. The system may further include a second housing configured for location on the retail shelving unit separate from the at least one first housing, the second housing may contain at least one processor configured to control the at least one image capture device and also to control a network interface for communicating with a remote server.

Abstract: A system for identifying products and tracking inventory in a retail store based on analysis of image data is provided. The system may comprise at least one processor configured to receive image data from a plurality of image sensors mounted in a retail store; analyze the image data to estimate a current inventory of at least one product type in the retail store; receive product supply information associated with the at least one product type in the retail store; determine that an online order from a virtual store made during a first time period will be fulfilled by an employee of the retail store during a second time period; determine a predicted inventory of the at least one product type during the second time period; and provide information to the virtual store regarding the predicted inventory of the at least one product type during the second time period.

Abstract: A system for identifying products and tracking inventory in a retail store based on analysis of image data is provided. The system may comprise at least one processor configured to receive image data from a plurality of image sensors mounted in a retail store; analyze the image data to estimate a current inventory of at least one product type in the retail store; receive product supply information associated with the at least one product type in the retail store; determine that an online order from a virtual store made during a first time period will be fulfilled by an employee of the retail store during a second time period; determine a predicted inventory of the at least one product type during the second time period; and provide information to the virtual store regarding the predicted inventory of the at least one product type during the second time period.

Abstract: The present disclosure relates to systems and methods for identifying products in retail stores based on analysis of image data and for automatically generating performance indicators relating to the identified products. In one implementation, the system may include a processor configured to receive a first set of images depicting a first plurality of products associated with single product type displayed on a first shelving unit in a retail store; analyze the first set of images to determine first product turnover data associated with the first shelving unit; receive a second set of images depicting a second plurality of products also associated with the single product type displayed on a second shelving unit in the retail store nonadjacent to the first shelving unit; and analyze the second set of images to determine second product turnover data associated with the second shelving unit.

Abstract: The present disclosure relates to systems and methods for processing images captured in a retail store and automatically addressing detected conditions within the retail store. In one implementation, the system may include a processor configured to receive a plurality of images depicting a plurality of products displayed on a plurality of store shelves; detect in the plurality of images an indicator of a first service-improvement condition relating to the plurality of products; detect in the plurality of images an indicator of a second service-improvement condition relating to the plurality of products; determine a first product-related task for addressing the first service-improvement condition; determine a second product-related task for addressing the second service-improvement condition; and access a database storing information indicative of a first employee and a second employee on duty during a time interval over which the plurality of images was received.

Abstract: The present disclosure relates to systems and methods for identifying products in retail stores based on analysis of image data and for automatically generating performance indicators relating to the identified products. In one implementation, the system may include a processor configured to receive a first set of images depicting a first plurality of products associated with single product type displayed on a first shelving unit in a retail store; analyze the first set of images to determine first product turnover data associated with the first shelving unit; receive a second set of images depicting a second plurality of products also associated with the single product type displayed on a second shelving unit in the retail store nonadjacent to the first shelving unit; and analyze the second set of images to determine second product turnover data associated with the second shelving unit.

Abstract: The present disclosure relates to systems and for identifying products and tracking inventory in a retail store based on analysis of image data. In one implementation, the system may include processor configured to receive image data from a plurality of image sensors mounted in a retail store; analyze the image data to estimate a current inventory of at least one product type in the retail store; receive product supply information associated with the at least one product type in the retail store; determine that an online order from a virtual store made during a first time period will be fulfilled by an employee of the retail store during a second time period; and determine, based on the current inventory estimated by analyzing the image data and the product supply information, a predicted inventory of the at least one product type during the second time period.

Abstract: A framework for customer relationship management includes a first layer to identify platforms for customer interactions and a second layer to identify capabilities of customer interactions. The framework includes a third layer to demonstrate how knowledge about customer preferences and behavior can be brought to bear on customer interactions. The framework has a fourth layer to identify applications of analysis and modeling to customer information. The framework also can include backplanes identifying common services that can be defined and tailored to support capabilities described in the first, second, third and fourth layers.