Analytical E-Commerce Processing System And Methods
First Claim
1. A method of producing an e-commerce report comprisingproviding a user interface, the user interface configured to allow a user to customize an e-commerce report;
- providing a model in the form of an aggregate set of at least one affinity score from a plurality of information, the plurality of information comprising information selected from a group consisting of information on products at varying resolutions, information on potential customers, and information on events at various times;
generating a run-time set of affinity scores by extrapolation from at least one of the aggregate set;
calculating a buying probability from at least one of the run-time set of affinity scores; and
producing an e-commerce report from the buying probability.
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Abstract
A system and methods which enable modeling of end consumer interests based on online activity and producing e-commerce reports is described. The method includes scoring and classifying interests and preferences of consumers in relation to various items being offered as function of time and utilizing such scores to predict purchasing activity and revenue yield for n-dimensional combinations of interest for generation of consumer lists for target marketing and merchandising. The method also includes converse modeling of the performance and behavioral profile of items offered as a function of consumer activity. This Abstract is provided for the sole purpose of complying with the rules that allow a reader to quickly ascertain the subject matter of the disclosure contained herein. This Abstract is submitted with the explicit understanding that it will not be used to interpret or to limit the scope or the meaning of the claims.
144 Citations
25 Claims
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1. A method of producing an e-commerce report comprising
providing a user interface, the user interface configured to allow a user to customize an e-commerce report; -
providing a model in the form of an aggregate set of at least one affinity score from a plurality of information, the plurality of information comprising information selected from a group consisting of information on products at varying resolutions, information on potential customers, and information on events at various times; generating a run-time set of affinity scores by extrapolation from at least one of the aggregate set; calculating a buying probability from at least one of the run-time set of affinity scores; and producing an e-commerce report from the buying probability. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A computing apparatus comprising:
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a processor; a memory communicating with the processor; and a storage medium, the storage medium comprising a set of processor executable instructions that, when executed by the processor configure the computing apparatus to; provide a user interface, the user interface configured to allow a user to customize an e-commerce report; provide a model in the form of an aggregate set of at least one affinity score from a plurality of information, the plurality of information comprising information selected from a group consisting of information on products at varying resolutions, information on potential customers, and information on events at various times; generate a run-time set of affinity scores by extrapolation from at least one of the aggregate set; calculating a buying probability from at least one of the run-time set of affinity scores; and produce an e-commerce report from the buying probability. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16)
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17. A computer software product comprising:
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a storage medium comprising a set of processor executable instructions that, when executed by a processor configure a computing apparatus to; provide a user interface, the user interface configured to allow a user to customize an e-commerce report; provide a model in the form of an aggregate set of at least one affinity score from a plurality of information, the plurality of information comprising information selected from a group consisting of information on products at varying resolutions, information on potential customers, and information on events at various times; generate a run-time set of affinity scores by extrapolation from at least one the aggregate set; calculating a buying probability from at least one of the run-time set of affinity scores; and produce an e-commerce report from the buying probability. - View Dependent Claims (18, 19, 20, 21, 22, 23, 24, 25)
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Specification