Systems and methods of data mining to customize software trial demonstrations
First Claim
Patent Images
1. A computer implemented system applied to customizing a demonstration of a software suite with numerous features and deployments, the computer implemented system including:
- a processor, memory coupled to the processor, and program instructions stored in the memory that implement a method comprising;
obtaining from at least one of a user profile and a social profile user attributes for a demonstration candidate, including the demonstration candidate'"'"'s role within a company;
obtaining interest attributes extracted from the demonstration candidate'"'"'s browsing history or social media feed that indicate personal interest of the demonstration candidate in business entities that use the software suite;
using at least some of the user attributes of the demonstration candidate to select a subset of features of the software suite to guide the demonstration candidate through during a software demonstration, to include;
accessing and automatically applying at least one trained classifier rule set that maps the user attributes to subsets of features to select based on parameters of the trained classifier;
using at least some of the interest attributes of the demonstration candidate to select one or more software usage stories describing successful implementation of the software suite by the business entities determined to be of personal interest to the demonstration candidate to profile during the software demonstration;
customizing the software demonstration for the demonstration candidate with the selected subset of software features and the software usage stories; and
at least initializing presentation across a display screen of the software demonstration to the demonstration candidate.
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Accused Products
Abstract
The technology disclosed describes systems and methods for delivering software trial demonstrations that are customized, with features identified as interesting to a software demonstration candidate, by mining biographical and behavioral data of the candidate. The technology further discloses systems and methods for the customization of trial demonstrations with software usage stories that reflect a software demonstration candidate'"'"'s interests, identified by analyzing mined biographical and behavioral data about the candidate.
178 Citations
24 Claims
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1. A computer implemented system applied to customizing a demonstration of a software suite with numerous features and deployments, the computer implemented system including:
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a processor, memory coupled to the processor, and program instructions stored in the memory that implement a method comprising; obtaining from at least one of a user profile and a social profile user attributes for a demonstration candidate, including the demonstration candidate'"'"'s role within a company; obtaining interest attributes extracted from the demonstration candidate'"'"'s browsing history or social media feed that indicate personal interest of the demonstration candidate in business entities that use the software suite; using at least some of the user attributes of the demonstration candidate to select a subset of features of the software suite to guide the demonstration candidate through during a software demonstration, to include; accessing and automatically applying at least one trained classifier rule set that maps the user attributes to subsets of features to select based on parameters of the trained classifier; using at least some of the interest attributes of the demonstration candidate to select one or more software usage stories describing successful implementation of the software suite by the business entities determined to be of personal interest to the demonstration candidate to profile during the software demonstration; customizing the software demonstration for the demonstration candidate with the selected subset of software features and the software usage stories; and at least initializing presentation across a display screen of the software demonstration to the demonstration candidate. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 23)
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11. A method of customizing a demonstration of a software suite with numerous features and deployments, the method including:
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obtaining from at least one of a user profile and a social profile user attributes for a demonstration candidate, including the demonstration candidate'"'"'s role within a company and the company'"'"'s business segment; obtaining interest attributes extracted from the demonstration candidate'"'"'s browsing history or social media feed that indicate personal interest of the demonstration candidate in business entities that use the software suite; using at least some of the user attributes of the demonstration candidate to select a subset of features of the software suite to guide the demonstration candidate through during a software demonstration, to include; accessing and automatically applying at least one trained classifier rule set that maps the user attributes to subsets of features to select based on parameters of the trained classifier; using at least some of the interest attributes of the demonstration candidate to select one or more software usage stories describing successful implementation of the software suite by the business entities determined to be of personal interest to the demonstration candidate to profile during the software demonstration; customizing the software demonstration for the demonstration candidate with the selected subset of software features and the software usage stories; and at least initializing presentation across a display screen of the software demonstration to the demonstration candidate. - View Dependent Claims (12, 13, 14, 24)
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15. A method of training a classifier to customize a software demonstration for a demonstration candidate with a selected subset of software features and one or more software usage stories, the method including:
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for a test set of data, accessing user attribute and interest attribute data obtained from at least one of a user profile and a social profile for demonstration users of a software application; for the test set, accessing at least user dwell times during use of particular features and viewing of particular software usage stories for the demonstration users; using at least the user attribute and interest attribute data as independent variables and at least the user dwell times as dependent variables, training the classifier to select for demonstration candidates a subset of features of the software application and to select one or more software usage stories describing successful implementation of a software suite by business entities determined to be of personal interest to the demonstration candidate and producing classifier parameters that implement the trained classifier; storing the classifier parameters for later use in customizing a software demonstration for demonstration candidates with the selected subset of software features and the software usage stories; and at least initializing presentation across a display screen of the software demonstration to at least one of the demonstration candidates. - View Dependent Claims (16, 17)
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18. A non-transitory computer readable storage medium that stores program instructions that implement a method of customizing a demonstration of a software suite with numerous features and deployments, which implementation includes:
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obtaining from at least one of a user profile and a social profile user attributes for a demonstration candidate, including the demonstration candidate'"'"'s role within a company and the company'"'"'s business segment; obtaining interest attributes extracted from the demonstration candidate'"'"'s browsing history or social media feed that indicate personal interest of the demonstration candidate in business entities that use the software suite; using at least some of the user attributes of the demonstration candidate to select a subset of features of the software suite to guide the demonstration candidate through during a software demonstration, to include; accessing and automatically applying at least one trained classifier rule set that maps the user attributes to subsets of features to select based on parameters of the trained classifier; using at least some of the interest attributes of the demonstration candidate to select one or more software usage stories describing successful implementation of the software suite by the business entities determined to be of personal interest to the demonstration candidate to profile during the software demonstration; customizing the software demonstration for the demonstration candidate with the selected subset of software features and the software usage stories; and at least initializing presentation across a display screen of the software demonstration to the demonstration candidate. - View Dependent Claims (19, 20, 21, 22)
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Specification