公开(公告)号：US20240144356A1

公开(公告)日：2024-05-02

申请号：US17981252

申请日：2022-11-04

申请人： WEVO, INC.

发明人： Dustin Garvey ,  Shannon Walsh ,  Frank Chiang ,  Janet Muto ,  Nitzan Shaer ,  Charlie Hoang ,  Hannah Sieber ,  Nick Montaquila ,  Jessica Yau ,  Joseph Gibson ,  Mary McMurray ,  Laurie Delaney ,  Andrea Paola Aguilera García ,  Alexa Stewart

IPC分类号： G06Q30/06 ,  G06Q30/02

CPC分类号： G06Q30/0641 ,  G06Q30/0201 ,  G06Q30/0203

摘要： Techniques are described herein for selecting, curating, normalizing, enriching, and synthesizing the results of user experience (UX) tests. In some embodiments, a system receives input defining or modifying a theme schema for classifying results of user experience tests. Responsive to receiving the input, the system trains a themer model based at least in part on example classifications in a training dataset, where the classifications map results to themes within the theme schema. When a new set of results for a user experience test is received, the trained machine learning model may generate a set of predicted themes to classify the test results. The output of the model may be used to render user interfaces and/or trigger other actions directed to optimizing a product's design.

公开(公告)号：US11972442B1

公开(公告)日：2024-04-30

申请号：US18111444

申请日：2023-02-17

申请人： Wevo, Inc.

发明人： Dustin Garvey ,  Shannon Walsh ,  Frank Chiang ,  Janet Muto ,  Nitzan Shaer ,  Hannah Sieber ,  Charlie Hoang ,  Alexa Stewart ,  Keith Horvath ,  Marshall McCready ,  Laurie Delaney ,  Jon Andrews

IPC分类号： G06Q30/018 ,  G06F9/451

CPC分类号： G06Q30/0185 ,  G06F9/451

摘要： Techniques and embodiments are described herein for detecting and mitigating fraudulent activity within user experience (UX) test applications. In some embodiments, a system applies a set of rules and/or machine learning (ML) models to each respondent of an online survey or UX test. Different ML models may be trained to learn domain-specific patterns indicative of fraudulent activity. The system may then select the ML models based on attributes of the UX test and/or respondent. The selected rules and/or ML models may generate a probabilistic score representing a likelihood that the respondent is currently engaging in or will engage in fraudulent activity with respect to a UX test. If the score exceeds a threshold, then the system may take action to mitigate the fraudulent activity, such as triggering the removal of the user from an accepted respondent pool, halting further engagement between the respondent and the UX test, and generating alerts.

公开(公告)号：US20240281837A1

公开(公告)日：2024-08-22

申请号：US18111441

申请日：2023-02-17

申请人： Wevo, Inc.

发明人： Jon Andrews ,  Charlie Hoang ,  Dustin Garvey ,  Frank Chiang ,  Hannah Sieber ,  Keith Horvath ,  Mary McMurray ,  Nitzan Shaer ,  Shannon Walsh

IPC分类号： G06Q30/0203

CPC分类号： G06Q30/0203

摘要： Techniques and embodiments described herein include a scalable system for integrating panel-based research with user experience (UX) testing tools, such as online survey applications. The techniques provide for the parallelization of a single request across multiple panel providers. The parallelization across multiple panel providers may occur transparently to users, including the designers of UX testing tools and methodologies, without requiring any complex modifications of the underlying source code. The parallelization may further significantly reduce request processing speeds within the system. Additionally or alternatively, the techniques provide for runtime adjustments of configurations to adjust rates at which respondents with varying attributes are fielded. As a result, qualified UX test respondents may be fielded much more quickly, increasing system scalability by allowing the system to process more requests within a given timeframe.

公开(公告)号：US20240144297A1

公开(公告)日：2024-05-02

申请号：US17979231

申请日：2022-11-02

申请人： WEVO, INC.

发明人： Dustin Garvey ,  Shannon Walsh ,  Frank Chiang ,  Janet Muto ,  Nitzan Shaer ,  Charlie Hoang ,  Hannah Sieber ,  Nick Montaquila ,  Jessica Yau ,  Joseph Gibson ,  Mary McMurray ,  Laurie Delaney ,  Andrea Paola Aguilera García, I ,  Alexa Stewart

IPC分类号： G06Q30/02

CPC分类号： G06Q30/0201 ,  G06Q30/0203

摘要： Techniques are described herein for selecting, curating, normalizing, enriching, and synthesizing the results of user experience (UX) tests. In some embodiments, a system receives input defining or modifying a theme schema for classifying results of user experience tests. Responsive to receiving the input, the system trains a themer model based at least in part on example classifications in a training dataset, where the classifications map results to themes within the theme schema. When a new set of results for a user experience test is received, the trained machine learning model may generate a set of predicted themes to classify the test results. The output of the model may be used to render user interfaces and/or trigger other actions directed to optimizing a product's design.

公开(公告)号：US11836591B1

公开(公告)日：2023-12-05

申请号：US17981243

申请日：2022-11-04

申请人： WEVO, INC.

发明人： Dustin Garvey ,  Shannon Walsh ,  Nitzan Shaer ,  Janet Muto ,  Jon Andrews ,  Frank Chiang ,  Alexa Stewart ,  Hannah Sieber ,  Charlie Hoang ,  Rick Alarcon Sisniegas ,  Alexander Barza

IPC分类号： G06N20/20

CPC分类号： G06N20/20

摘要： Techniques are described herein for selecting, curating, normalizing, enriching, and synthesizing the results of user experience tests. In some embodiments, a system identifies a qualitative element within a result set for a user experience test. The system then selects a machine learning model to apply based on one or more attributes associated with the user experience test and generates a predicted visibility, quality, and/or relevance for the qualitative element. Based on the prediction, the system generates a user interface that curates a set of results of the user experience test.

公开(公告)号：US11748248B1

公开(公告)日：2023-09-05

申请号：US17981249

申请日：2022-11-04

申请人： WEVO, INC.

发明人： Dustin Garvey ,  Shannon Walsh ,  Frank Chiang ,  Janet Muto ,  Nitzan Shaer ,  Charlie Hoang ,  Hannah Sieber ,  Nick Montaquila ,  Jessica Yau ,  Joseph Gibson ,  Mary McMurray ,  Laurie Delaney ,  Andrea Paola Aguilera García ,  Alexa Stewart

IPC分类号： G06F9/44 ,  G06F11/36

CPC分类号： G06F11/3692

摘要： Techniques are described herein for selecting, curating, normalizing, enriching, and synthesizing the results of user experience (UX) tests. In some embodiments, a system identifies a set of expectation elements associated with one or more UX tests. An expectation element may specify, using unstructured data that does not conform to a schema, an expectation for a user experience and a respective outcome for the user experience. A themer model may generate predictions that map the respective expectation elements to a theme from a theme schema, which may include a plurality of themes. A selector model may generate selection scores for the expectation elements. The predicted themes and selection scores may be used to render user interfaces and/or trigger other actions directed to optimizing a product's design.

公开(公告)号：US20240354789A1

公开(公告)日：2024-10-24

申请号：US18306030

申请日：2023-04-24

申请人： Wevo, Inc.

发明人： Dustin Garvey ,  Janet Muto ,  Nitzan Shaer ,  Shannon Walsh ,  Alexa Stewart ,  Andrea Paola Aguilera García ,  Kim Coccoluto ,  Sara Peters ,  Ruthie McCready ,  Kelly Lyons ,  Melany Carvalho ,  Everett Granger ,  Julia McCarthy ,  Frank Chiang ,  Alexander Barza ,  Hannah Sieber

IPC分类号： G06Q30/0203 ,  G06N20/00

CPC分类号： G06Q30/0203 ,  G06N20/00

摘要： Techniques are described for producing machine-generating findings associated with user experiences with products and/or services. In some embodiments, a finding generator receives a set of user experience test results, generates a set of permutations of user attribute values, and, for each permutation, determines distributions of quantitative values that measure one or more facets of the user experience with a product or service for users that have the user attribute values and users that do not. Based on a comparison of the distributions, the finding generator identifies a subset of permutations to retain, generates segments of user experience test results based on the permutations, and generates findings summaries based on the results included in each segment. The findings may be presented to an analyst and or consumed by downstream application to perform actions directed at improving the design of the product or service.

公开(公告)号：US12079585B1

公开(公告)日：2024-09-03

申请号：US18306028

申请日：2023-04-24

申请人： Wevo, Inc.

发明人： Dustin Garvey ,  Janet Muto ,  Nitzan Shaer ,  Shannon Walsh ,  Alexa Stewart ,  Andrea Paola Aguilera Garcia ,  Kim Coccoluto ,  Sara Peters ,  Ruthie McCready ,  Kelly Lyons ,  Melany Carvalho ,  Everett Granger ,  Julia McCarthy ,  Frank Chiang ,  Alexander Barza ,  Hannah Sieber

IPC分类号： G06F40/40

CPC分类号： G06F40/40

摘要： Techniques are described herein for producing machine-generated findings given a set of user experience test results. In some embodiments, the system generates the findings using an artificial intelligence and machine learning engine. The findings may highlight areas that are predicted to provide the most insight into optimizing a product's design. A finding may be generated based on all or a subset of the test result elements, including qualitative and/or quantitative data contained therein. A finding may summarize a subset of the UX test results that are interrelated. A finding may link a summary to one or more references extracted from the set of test results to show support for the machine-generated insights in the underlying raw test data. Machine-generated findings reports may provide near instantaneous guidance for optimizing product designs while removing extraneous information from a vast quantity of raw test result data.

公开(公告)号：US20240144107A1

公开(公告)日：2024-05-02

申请号：US17979230

申请日：2022-11-02

申请人： WEVO, INC.

发明人： Dustin Garvey ,  Shannon Walsh ,  Frank Chiang ,  Janet Muto ,  Nitzan Shaer ,  Charlie Hoang ,  Hannah Sieber ,  Nick Montaquila ,  Jessica Yau ,  Joseph Gibson ,  Mary McMurray ,  Laurie Delaney ,  Andrea Paola Aguilera García, I ,  Alexa Stewart

IPC分类号： G06N20/20 ,  G06F9/451

CPC分类号： G06N20/20 ,  G06F9/451

摘要： Techniques are described herein for selecting, curating, normalizing, enriching, and synthesizing the results of user experience (UX) tests. In some embodiments, a system identifies a set of expectation elements associated with one or more UX tests. An expectation element may specify, using unstructured data that does not conform to a schema, an expectation for a user experience and a respective outcome for the user experience. A themer model may generate predictions that map the respective expectation elements to a theme from a theme schema, which may include a plurality of themes. A selector model may generate selection scores for the expectation elements. The predicted themes and selection scores may be used to render user interfaces and/or trigger other actions directed to optimizing a product's design.

公开(公告)号：US20240118993A1

公开(公告)日：2024-04-11

申请号：US17963760

申请日：2022-10-11

申请人： WEVO, INC.

发明人： Dustin Garvey ,  Shannon Walsh ,  Nitzan Shaer ,  Janet Muto ,  Jon Andrews ,  Frank Chiang ,  Alexa Stewart ,  Hannah Sieber ,  Charlie Hoang ,  Rick Alarcon Sisniegas ,  Alexander Barza

IPC分类号： G06F11/36 ,  G06N20/20

CPC分类号： G06F11/3664 ,  G06F11/3692 ,  G06N20/20

摘要： Techniques are described herein for selecting, curating, normalizing, enriching, and synthesizing the results of user experience tests. In some embodiments, a system identifies a qualitative element within a result set for a user experience test. The system then selects a machine learning model to apply based on one or more attributes associated with the user experience test and generates a predicted visibility, quality, and/or relevance for the qualitative element. Based on the prediction, the system generates a user interface that curates a set of results of the user experience test.