E-Commerce Consumer-Based Behavioral Target Marketing Reports
First Claim
1. A computer-implemented method for predicting purchasing patterns by modeling the interests of consumers in products based on exhibited online shopping activity, comprising the steps of:
- (a) collecting source data from a plurality of sources, wherein said source data includes at least clickstream data and order data for a plurality of customers;
(b) aggregating, via a computing apparatus, said source data into a multi-dimensional, multi-resolutional, de-normalized interaction table;
(c) deriving, via said computing apparatus, at least one materialized, n-dimensional customer score corresponding to at least one of said plurality of customers based on said multi-dimensional, multi-resolutional, de-normalized interaction table;
(d) deriving, via said computing apparatus, at least one run-time, n-dimensional customer score corresponding to said at least one of said plurality of customers from said multi-dimensional, multi-resolutional, de-normalized interaction table; and
(e) producing, via said computing apparatus, an e-commerce report, based on said at least one materialized, n-dimensional customer score and said at least one run-time, n-dimensional customer score, wherein said e-commerce report is used to determine the potential interests of consumers in products being offered online and said e-commerce report is accessible to a user.
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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.
22 Citations
17 Claims
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1. A computer-implemented method for predicting purchasing patterns by modeling the interests of consumers in products based on exhibited online shopping activity, comprising the steps of:
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(a) collecting source data from a plurality of sources, wherein said source data includes at least clickstream data and order data for a plurality of customers; (b) aggregating, via a computing apparatus, said source data into a multi-dimensional, multi-resolutional, de-normalized interaction table; (c) deriving, via said computing apparatus, at least one materialized, n-dimensional customer score corresponding to at least one of said plurality of customers based on said multi-dimensional, multi-resolutional, de-normalized interaction table; (d) deriving, via said computing apparatus, at least one run-time, n-dimensional customer score corresponding to said at least one of said plurality of customers from said multi-dimensional, multi-resolutional, de-normalized interaction table; and (e) producing, via said computing apparatus, an e-commerce report, based on said at least one materialized, n-dimensional customer score and said at least one run-time, n-dimensional customer score, wherein said e-commerce report is used to determine the potential interests of consumers in products being offered online and said e-commerce report is accessible to a user. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A computer software product comprising a non-transitory storage medium, wherein the storage medium contains processor executable instructions that, when executed by a processor, configure a computing apparatus to:
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(a) collect source data from a plurality of sources, wherein said source data includes at least clickstream data and order data for a plurality of customers; (b) aggregate said source data into a multi-dimensional, multi-resolutional, de-normalized interaction table; (c) derive at least one materialized, n-dimensional customer score corresponding to at least one of said plurality of customers based on said multi-dimensional, multi-resolutional, de-normalized interaction table; (d) derive at least one run-time, n-dimensional customer score corresponding to said at least one of said plurality of customers from said multi-dimensional, multi-resolutional, de-normalized interaction table; and (e) produce an e-commerce report, based on said at least one materialized, n-dimensional customer score and said at least one run-time, n-dimensional customer score, wherein said e-commerce report is used to determine the potential interests of consumers in products being offered online and said e-commerce report is accessible to a user. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16)
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17. A computer-implemented method for predicting purchasing patterns by modeling the interests of consumers in products based on exhibited online shopping activity, comprising the steps of:
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(a) aggregating source data from a plurality of sources into a multi-dimensional, multi-resolutional, de-normalized interaction table, wherein said source data includes at least;
order data, clickstream data, product data and customer data ;(b) deriving a plurality of materialized, n-dimensional customer scores corresponding to said customer data from said multi-dimensional, multi-resolutional, de-normalized interaction table; (c) deriving a plurality of run-time, n-dimensional customer scores corresponding to said customer data from multi-dimensional, multi-resolutional, de-normalized interaction table; and (d) producing an e-commerce report, based on said plurality of materialized, n-dimensional customer scores and said plurality of run-time, n-dimensional customer scores, wherein said e-commerce report is used to determine the potential interests of consumers in the products being offered online and said e-commerce report is accessible to a user via a computing device.
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Specification