Proficiency-based profiling systems and methods

• US 10,332,137 B2
• Filed: 11/11/2016
• Issued: 06/25/2019
• Est. Priority Date: 11/11/2016
• Status: Active Grant

• Current Assignee: Qwalify Inc.
• Original Assignee: Qwalify Inc.
• Inventors: Noelting, Philippe, Abramovitch, Avery
• Primary Examiner(s): Mansfield, Thomas L
• Assistant Examiner(s): Holzmacher, Derick J
• Application Number:
  US15/349,764
• Publication Number:
  US 20180137527A1
• Time in Patent Office: 956 Days
• Field of Search: 705 714
• CPC Class Codes: G06Q 30/0203 Market surveys; Market polls
• CPC Class Codes: G06Q 30/0204 Market segmentation

Abstract

Systems and methods that provide proficiency-based profiling and matching are provided herein. An example method includes providing a series of questions to a plurality of individuals related to a plurality of segments using data reference structures generated from subject matter information, receiving answers to a series of questions from the plurality of individuals, the answers being indicative of a proficiency level of an individual, building a profile for each of the plurality of individuals using the elicited information based on one or more unique subject matter domains.

Claims

1. A computer-implemented method performed by at least one processor for generating an automated profile of a user, the method comprising:

receiving, via a data reference structuring server, descriptive information about an entity from a plurality of data sources, the descriptive information about the entity comprising information about

products and services provided to customers of the entity; and

at least one of;

(i) goals of the entity or (ii) opportunities available at the entity;

executing, via the data reference structuring server, parsing logic to generate an entity knowledge base for the entity from the descriptive information of the entity;

establishing, via the data reference structuring server, a plurality of segments for the entity based on parsing keywords or topics in the entity knowledge base, the plurality of segments relating to unique subject matter domains of the entity;

providing, via a distribution logic server, a plurality of individuals with an electronic first survey, the first survey comprising a plurality of questions directed to eliciting information that allows for placement of each of the plurality of individuals into one or more of the plurality of segments for the entity;

segmenting, via a segmentation structuring server, the plurality of individuals into one or more of the plurality of segments based on electronic evaluation of each individual'"'"'s answers to the questions in the first survey;

for each of the plurality of segments, electronically eliciting, via the data referencing structuring server, information from a plurality of individuals in that segment using a series of questions including behavioral and proficiency questions in a second survey electronically generated from data reference structures, wherein the data reference structures comprise a framework that catalogs at least one of product data, market data and reactionary data related to each segment of the entity;

receiving, via a contribution analysis and reference server, at least one answer to the elicited information from at least one individual of the plurality of individuals, the received answer to the series of questions being indicative of a proficiency level of an individual and behavioral characteristics of the individual;

automatically constructing, via the data reference structuring server, the series of questions from the data reference structures;

providing, via an engagement generation server, the series of questions from the second survey to the plurality of individuals according to a schedule, wherein the schedule is based on any of time between questions and quantity of questions in the second survey;

automatically updating, via the data reference structuring server, the data reference structures using contributions to the series of questions;

refining, via the data reference structuring server, the data reference structures through use of machine learning that uses answers to the elicited information from the plurality of individuals, as well as feedback from the entity;

building, via a segmentation assignment server, a profile for each of the plurality of individuals using the answers to the first survey, answers to the elicited information, and a participation level of the individual based on a number of questions from the second survey for which answers were submitted; and

updating, via the segmentation assignment server, the profile for each of the plurality of individuals based on subsequent answers received from each individual to questions in the second survey, or questions from a third survey.

2. The method according to claim 1, further comprising generating the data reference structures by:

parsing the descriptive information obtained from the plurality of data sources for keywords, key phrases, or data instances related to the data reference structures that are indicative of the unique subject matter domains;

applying data filters to the keywords; and

classifying and normalizing the filtered keywords.

3. The method according to claim 1, further comprising assigning the data reference structures to the unique subject matter domains.

4. The method according to claim 1, further comprising:

creating one or more discussion board groups on an electronic medium, each discussion board group being associated with one of the unique subject matter domains.

5. The method according to claim 4, further comprising presenting a series of proficiency questions in the one or more discussion board groups, the series of proficiency questions selected based on the unique subject matter domains.

6. The method according to claim 1, further comprising calculating an authority level for each of the plurality of individuals based on the answers to the series of proficiency questions.

7. The method according to claim 1, further comprising executing engagement logic to increase engagement in responding to the series of proficiency questions when participation of the plurality of individuals falls below an engagement threshold value.

8. The method according to claim 1, further comprising:

establishing candidacy reference structures that comprise departments for the entity; and

determining when goal parameters are present for each of the candidacy reference structures.

9. The method according to claim 1, further comprising determining a contribution level for each of the plurality of individuals based on the elicited information, wherein the contribution level is based on open-ended information provided by the plurality of individuals.

10. A system for automated profiling of an individual by an entity, the system comprising:

a data reference structuring server that;

executes data intake logic to receive descriptive information about an entity from a plurality of data sources, the descriptive information about the entity comprising information about;

products and services provided to customers of the entity; and

at least of (i) goals of the entity or (ii) opportunities available at the entity;

executes parsing logic to convert the descriptive information about the entity into an entity knowledge base of information,

wherein the parsing logic further generates data reference structures by;

tuning data filters to parse for words or phrases indicative of goals or requirements of the entity;

parsing the entity knowledge base using the tuned data filters; and

employing object classification and normalization logic to generate the data reference structures from the parsed and filtered descriptive information about the entity,

 

wherein the data reference structures provide a framework that catalogs product, market, and reactionary data about the entity;

generates a series of questions based on the data reference structures;

assesses a degree of alignment between the generated series of questions and at least one of;

the automatically generated data reference structures, or

the goals or requirements of the entity; and

updates the entity knowledge base and the data reference structures in response to electronically received answers to the series of questions, to refine subsequent questions generated;

a data association logic server that;

executes segmentation distribution logic to create segmentation schemas for delivering the series of questions to a plurality of individuals, the segmentation schemas created based at least in part on the generated data reference structures;

a segmentation structuring server that;

creates nomenclature for each segment of the entity and constructs tags that can be applied to each individual from the plurality of individuals that electronically submits an answer to at least one question of the series of questions electronically delivered to the plurality of individuals,

the tags generated at least in part on the data reference structures;

an engagement generation server that;

executes distribution logic received from a distribution logic server to

schedule the series of questions generated by the data reference structuring server for electronic delivery to the plurality of individuals,

where timing of the schedule is set to drive maximum engagement by the plurality of individuals with the series of questions to elicit maximally useful information for the entity;

where the schedule further comprises;

 

a list of the plurality of individuals to electronically receive the series of questions; and

 

topics for the series of questions electronically delivered to the plurality of individuals; and

organize and distribute collected answers from the plurality of individuals to the series of questions;

the distribution logic server that;

creates or identifies target segments to receive the series of questions electronically generated;

schedules publishing to an electronic medium of the series of questions from the engagement generation server; and

executes engagement trend logic to examine a participation level by the plurality of individuals in submitting answers to the series of questions, to determine which questions of the series of questions are answered more frequently by the plurality of individuals;

a contribution analysis and reference server, that;

electronically receives any answers to the at least one question of the series of questions from the plurality of individuals; and

executes parsing logic to evaluate the received answer from each individual of the plurality of individuals to infer at least one main point of contribution of each individual to the entity; and

a segmentation assignment server that;

automatically builds a user profile for each individual of the plurality of individuals using the received answers to the at least one question of the series of questions and tags associated with the received answers; and

executes profile adaptation logic to selectively adjust or update each user profile as

the data reference structures are updated over time,

the questions generated by the data reference structuring server are updated over time, and

answers are subsequently received from each individual.

11. The system according to claim 10, wherein the distribution logic server further:

creates one or more electronic discussion board groups, each discussion board group associated with one or more segments of the entity; and

publishes the series of questions to the one or more electronic discussion board groups, based on the segments of the entity.

12. The system according to claim 10, wherein the engagement generation server further schedules the series of questions to the plurality of individuals based on a quantity of questions previously delivered to the plurality of individuals.

13. The system according to claim 10, wherein the data reference structures are updated by the data reference structuring server based on the received answers to the series of questions.

14. The system according to claim 10, further comprising a contribution recognition server that utilizes recognition distribution logic and relevance scoring logic to evaluate the received answers from each of the plurality of individuals;

and

updates each user profile with a value recognition component based on results of the recognition distribution logic and the relevance scoring logic.

15. The system according to claim 10, wherein the distribution logic further:

adjusts the schedule of the series of questions in accordance with an engagement threshold, to ensure that the series of questions electronically delivered to the plurality of individuals are of an optimal frequency and type of question to maximize an amount of information collected by the entity.

16. The system according to claim 10, wherein the engagement generation server further executes media selection logic to select relevant media to electronically deliver to the plurality of individuals with each of the series of questions.

17. The system according to claim 10, wherein the engagement generation server further executes media selection logic to receive and evaluate media electronically submitted by an individual of the plurality of individuals, in response to a question of the series of questions.

18. The system according to claim 10, wherein the engagement trend logic is executed separately for each segment of the entity.

19. The system according to claim 10, wherein the engagement trend logic is utilized to update the series of questions or the schedule of the series of questions.

20. The system according to claim 10, wherein at least one user profile is matched to at least one of the goals or requirements of the entity.