Adaptive Marketing Using Insight Driven Customer Interaction
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Abstract
A system and method for adaptive marketing using insight driven customer interaction. The invention uses a closed-loop process for developing insight that may be used to refine further customer interactions. Results of a first customer interaction such as a marketing campaign are stored in a database. The results may be used to retrain predictive models and gain new insights regarding how customers are responding to marketing campaigns. The insights may be used to refine the offers delivered to customers or to extend additional offers in an effort to increase the likelihood that customers will redeem the offers. After each marketing campaign, the results are stored in the database. New and/or modified offers are created based on insights provided by the results of past campaigns. This process may be repeated such that subsequent campaigns are based on insights generated by the predictive models. The insight enables businesses to better target customers with better offers. These offers can be delivered through ensuing marketing campaigns or, through any form of interaction that the business has with the targeted customers.
93 Citations
88 Claims
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1-68. -68. (canceled)
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69. A method for performing marketing activities, comprising:
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providing a system comprising a memory to store instructions, a processor having a plurality of software modules, and a database embodied on computer-readable medium to store customer data for a plurality of customers, wherein the software modules access the instructions stored in the memory and the customer data stored in the database, and wherein the plurality of software modules comprise a customer data extracting software module and a marketing campaign defining module; and executing the instructions by the processor to perform; extracting the customer data from the database by the customer data extracting software module; defining a targeted marketing campaign by the marketing campaign defining module, the targeted marketing campaign comprising a targeted marketing offer, a targeted interaction channel, and a targeted set of customers most likely to accept the targeted marketing offer via the targeted interaction channel, wherein the defining further comprises; segmenting a sample set of the customers into a plurality of customer segments; describing each of the plurality of customer segments with lift values indicating a likelihood of positive response by a selected customer segment to a selected marketing offer; selecting, based on the lift values, a prospect set from the customer segments for potential inclusion in a selected marketing campaign; assessing with a predictive model a likelihood of acceptance of each customer in the selected prospect set of the selected marketing offer; scoring each customer in the selected prospect set with a customer score indicating the likelihood of acceptance; selecting the targeted set of customers based on the scoring; and executing the targeted marketing campaign by offering the targeted marketing offer to the targeted set of the customers via the targeted interaction channel. - View Dependent Claims (70, 71, 72, 73, 74, 75)
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76. A system, comprising:
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a processor; and a memory storing instructions operable with the processor for performing marketing activities, the instructions structured throughout a plurality of modules, said modules comprising; a customer data extracting module configured to extract customer data from a database; a marketing campaign defining module configured to define a targeted marketing campaign comprising a targeted marketing offer, a targeted interaction channel, and a targeted set of customers most likely to respond to the targeted marketing offer via the targeted interaction channel; a segmenting module configured to segment a sample set of the customers into a plurality of customer segments; a segment description module configured to describe each of the plurality of customer segments with lift values indicating a likelihood of positive response by a selected customer segment to a selected marketing offer; a prospect set selecting module configured to select, based on the lift values, a prospect set from the plurality of customer segments for potential inclusion in a selected marketing campaign; a predictive model module configured to assess a likelihood of acceptance of each customer in the selected prospect set of the selected marketing offer; and a prospect set scoring module configured to score each customer in the selected prospect set with a customer score indicating the likelihood of acceptance; and a customer selection module configured to select the targeted set of customers based on the customer score; and an execution module configured to execute the targeted marketing campaign by offering the targeted marketing offer to the targeted set of the customers via the targeted interaction channel. - View Dependent Claims (77, 78, 79, 80, 81, 82, 83)
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84. A computer program embodied on a computer readable medium for performing marketing activities, wherein the computer program instructs a processor to perform a method comprising:
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accessing instructions for a plurality of software modules stored in a memory, wherein the plurality of software modules comprise a customer data extracting software module and a marketing campaign defining module; accessing customer data stored in a database for a plurality of customers; and executing, by the processor, the instructions to perform; extracting the customer data from the database by the customer data extracting software module; defining a targeted marketing campaign by the marketing campaign defining module, the targeted marketing campaign comprising a targeted marketing offer, a targeted interaction channel, and a targeted set of customers most likely to accept the targeted marketing offer via the targeted interaction channel, wherein the defining further comprises; segmenting a sample set of the customers into a plurality of customer segments; describing each of the plurality of customer segments with lift values indicating a likelihood of positive response by a selected customer segment to a selected marketing offer; selecting, based on the lift values, a prospect set from the customer segments for potential inclusion in a selected marketing campaign; assessing with a predictive model a likelihood of acceptance of each customer in the selected prospect set of the selected marketing offer; scoring each customer in the selected prospect set with a customer score indicating the likelihood of acceptance; and selecting the targeted set of customers based on the scoring; and executing the targeted marketing campaign by offering the targeted marketing offer to the targeted set of the customers via the targeted interaction channel. - View Dependent Claims (85, 86, 87, 88)
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Specification