Dynamic sentiment-based mapping of user journeys

Patent metadata

Field	Value
Publication number	US-11113721-B2
Application number	US-201715659511-A
Country	US
Kind code	B2
Filing date	Jul 25, 2017
Priority date	Jul 25, 2017
Publication date	Sep 7, 2021
Grant date	Sep 7, 2021

Abstract

The present disclosure covers systems and methods for collecting and analyzing analytics data for a plurality of online user interactions and aggregating the analytics data to determine sentiment scores and generate a presentation of a path of interactions. For example, the systems and methods analyze the analytics data to identify attributes of the online user interactions and determine, based on the identified attributes, a sentiment score for each of the plurality of online user interactions. In addition, the systems and methods aggregate the plurality of online user online user interactions to identify an interaction path commonly experienced by the users of the interactions. Further, the systems and methods generate and provide an interactive presentation including a visualization of the interaction path and associated ranges of sentiment scores associated with types of online user interactions that make up the interaction path.

First claim

What is claimed is:

1. In a digital medium environment for collecting and analyzing analytics data, a computer-implemented method for aggregating interaction information and presenting a user journey comprising:
collecting, by a server device, analytics data for a plurality of online user interactions for a plurality of users with respect to an online entity;
analyzing the analytics data to identify attributes of the plurality of online user interactions;
determining sentiment scores for each of the plurality of online user interactions based on the identified attributes of the plurality of user interactions, each sentiment score indicating a measurement of sentiment of a user of the plurality of users associated with an online user interaction;
aggregating the plurality of online user interactions to identify an interaction path comprising a plurality of different types of online user interactions experienced by a threshold number of the plurality of users associated with a target metric;
aggregating the sentiment scores for each type of online user interaction of the plurality of different types of online user interactions to generate a general sentiment score indicating a measurement of sentiment of users who experienced a corresponding type of online user interaction;
generating an interactive presentation comprising a visualization of the interaction path, the visualization of the interaction path comprising:
a sequence of interaction icons representing the different types of online user interactions;
sentiment icons indicating a range of the determined general sentiment scores for the respective different types of online user interactions in the interaction path, wherein the range of the determined general sentiment scores comprises a lowest sentiment score to a highest sentiment score; and
segment icons corresponding to segments of users from the plurality of users, the segments of users comprising subsets of the plurality of users;

generating a sentiment window corresponding to a sentiment icon of the sentiment icons, the sentiment window comprising a notification of an abnormal sentiment icon and description of factors contributing to the abnormality;
providing the sentiment window within the interactive presentation; and
in response to detecting a selection of a segment icon corresponding to a segment of users, modifying the visualization of the interaction path to reflect interactions experienced by the selected segment of users by modifying a size of the sentiment icons to indicate a range of segment sentiment scores for the segment of users for the respective different types of online user interactions in the interaction path.

2. The method of claim 1 , further comprising excluding outliers from the range of determined general sentiment scores and the range of segment sentiment scores.

3. The method of claim 1 , wherein analyzing the analytics data to identify attributes of the plurality of online user interactions comprises identifying predefined signals based on tracked user behavior with respect to the plurality of online user interactions.

4. The method of claim 1 , further comprising, in response to detecting a selection of a segment icon corresponding to a segment of users, further modifying the visualization of the interaction path to reflect interactions experienced by the selected segment of users by:
identifying a segment interaction path reflecting interactions commonly experienced by the selected segment; and
replacing, within the visualization of the interaction path, the sentiment icons with segment sentiment icons corresponding to the segment interaction path.

5. The method of claim 4 , further comprising identifying different sets of attributes for different types of online user interactions of the plurality of online user interactions.

6. The method of claim 1 , wherein analyzing the analytics data to identify attributes comprises, for each of the plurality of online user interactions, identifying two or more of: a length of the online user interaction, a time between the online user interaction and a previous online user interaction for a user, or a time between the online user interaction and a subsequent online user interaction for the user.

7. The method of claim 1 , wherein analyzing the analytics data to identify attributes comprises, for each of the plurality of online user interactions, identifying one or more of: social customer relationship management text, live chat text, survey results, a length of an online user interaction, a time between the online user interaction and a previous online user interaction, a time between the online user interaction and a subsequent online user interaction, an identifier of a previous online user interaction, or an identifier of a subsequent online user interaction.

8. The method of claim 1 , further comprising:
receiving a user input identifying a number of types of online user interactions to include within the interaction path; and
limiting a number of the interaction icons in the visualization of the interaction path based on the number of types of online user interactions identified by the user input.

9. The method of claim 1 , wherein the interactive presentation further comprises a digital asset corresponding to a type of online user interaction within the interaction path.

10. The method of claim 9 , wherein the visualization of the interaction path comprises an asset icon corresponding to the digital asset, and wherein the method further comprises, in response to detecting a user selection of the asset icon on a client device, providing the digital asset to the client device.

11. The method of claim 1 , wherein the visualization of the interaction path further comprises an indicator of a communication channel over which the corresponding type of online user interaction occurred for each of the interaction icons.

12. In a digital medium environment for collecting and analyzing analytics data, a computer-implemented method for aggregating interaction information and presenting a user journey comprising:
collecting, by a server device, analytics data for a plurality of online user interactions for a plurality of users with respect to an online entity;
analyzing the analytics data to identify attributes of the plurality of online user interactions;
determining sentiment scores for each of the plurality of online user interactions based on the identified attributes of the plurality of user interactions, each sentiment score indicating a measurement of sentiment of a user of the plurality of users associated with an online user interaction;
aggregating the plurality of online user interactions to identify an interaction path comprising a plurality of different types of online user interactions experienced by a threshold number of the plurality of users associated with a target metric;
generating an interactive presentation comprising a visualization of the interaction path, the visualization of the interaction path comprising:
a sequence of interaction icons representing the types of online user interactions; and
sentiment icons indicating a range of determined general sentiment scores for the types of online user interactions, wherein the range of the determined general sentiment scores comprises a lowest sentiment score to a highest sentiment score; and
segment icons corresponding to segments of users from the plurality of users, the segments of users comprising subsets of the plurality of users;

generate a sentiment window corresponding to a sentiment icon of the sentiment icons, the sentiment window comprising a notification of an abnormal sentiment icon and description of f

Assignees

• Adobe Inc

Inventors

• George William Brandon
• Walker Jordan
• Gaines Benjamin R

Classifications

• H04L67/535

  Tracking the activity of the user (network monitoring arrangements H04L43/00; recording of computer activity G06F11/34) · CPC title

• G06Q30/016

  After-sales · CPC title

• G06Q30/0246 Primary

  Traffic · CPC title

• G06Q30/0253

  During e-commerce, i.e. online transactions · CPC title

• G06N20/00

  Machine learning · CPC title