Techniques for real-time customer preference learning
First Claim
1. A processor-implemented method programmed in a non-transitory processor-readable medium and to execute on a device, which is configured to execute the method, comprising:
- identifying a customer engaging in an interaction with the device;
obtaining predefined rules pertinent to preference determination for preferences of the customer, wherein some of all available preferences for the customer are unavailable based on a specific communication channel used by the customer;
gathering actions of the customer during the interaction;
feeding metrics for the actions to the predefined rules; and
evaluating the predefined rules using the metrics to learn a new preference to assign to the customer or to update an existing preference value for an existing preference based on evaluation of the predefined rules.
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Abstract
Techniques for real-time offer customer preference learning are presented. Local agents on communication channels are equipped with predefined rules that capture actions and behaviors of customers interacting with an enterprise. The metrics associated with these actions and behaviors are plugged into the rules and in some cases combined with known pre-existing preferences for the customers for purposes of evaluating the rules and creating newly learned preferences for the customers. The newly learned preferences are dynamically fed into offer evaluation processing to determine whether to make offers to the customers.
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Citations
20 Claims
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1. A processor-implemented method programmed in a non-transitory processor-readable medium and to execute on a device, which is configured to execute the method, comprising:
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identifying a customer engaging in an interaction with the device; obtaining predefined rules pertinent to preference determination for preferences of the customer, wherein some of all available preferences for the customer are unavailable based on a specific communication channel used by the customer; gathering actions of the customer during the interaction; feeding metrics for the actions to the predefined rules; and evaluating the predefined rules using the metrics to learn a new preference to assign to the customer or to update an existing preference value for an existing preference based on evaluation of the predefined rules. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A processor-implemented method programmed in a non-transitory processor-readable medium and configured to execute on one or more processors, the method comprising:
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receiving a request for preferences tied to a customer interacting with an enterprise; acquiring the preferences from an enterprise preference manager, wherein some of all available preferences for the customer are unavailable based on a specific communication channel used by the customer; delivering the preferences to a client loyalty preference agent interacting with the customer; and receiving updates to the preferences in real time from the client loyalty preference agent based on actions taken by the customer when interacting with the client loyalty preference agent. - View Dependent Claims (15, 16, 17, 18)
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19. A system, comprising:
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a first machine having a client loyalty preference agent implemented in a non-transitory computer-readable storage medium and which processes on the first machine; and a second machine having a preference learning agent implemented in a non-transitory computer-readable storage medium and which processes on the second machine; the client loyalty preference agent configured to interact with a customer that is interacting with an enterprise via the first machine to capture actions taken and selections made by the customer, the client loyalty preference agent also configured to apply the actions and selections to the evaluation of predefined rules to determine when new preferences for the customer are to be made and to determine when updates to existing preferences are to be made, the preference learning agent is configured to receive the new preferences and the updates to the existing preferences and make them available in real time across disparate communication channels of an enterprise dynamically wherein some of all available preferences for the customer are unavailable based on a specific communication channel used by the customer. - View Dependent Claims (20)
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Specification