Customer journey prediction and resolution

• US 9,092,801 B2
• Filed: 08/30/2012
• Issued: 07/28/2015
• Est. Priority Date: 09/23/2011
• Status: Active Grant

• Current Assignee: [24]7.ai, Inc.
• Original Assignee: 24/7 Customer Incorporated
• Inventors: Chang, Andrew, Kannan, Pallipuram V.
• Primary Examiner(s): Wong, Lut
• Application Number:
  US13/599,974
• Publication Number:
  US 20130080362A1
• Time in Patent Office: 1,062 Days
• Field of Search: 706/21, 705/14.53
• US Class Current: 1/1
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: H04L 67/306 User profiles
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34

Abstract

Customer journey prediction and resolution is accomplished via a predictive model in which each user is mapped onto all available user journey information corresponding to a specific business. The predictive model is analyzed to understand the characteristics, preferences, and lowest effort resolution for the user related to the services that are subscribed to by the user. The predictive model is analyzed to predict the service or collection of services for each user. Embodiments interact with, provide and receive information from, and react to and/or deliver action to the customer across channels and across services. All customer and system behavior, data, and action is tracked and coordinated and leveraged for continuous feedback and performance improvement.

Claims

1. A computer implemented method for customer journey resolution and prediction, comprising:

a processor interacting with users across multiple channels, either sequentially or simultaneously, and fetching data related to services capable of being offered to said users;

mapping with a processor to one or more predetermined customer journeys, said mapping applying both of user profiles depicting demographics to which the user belongs, a location of the user, services used by the user in the past, and services the user is currently using, and a catalog of available and possible customer journeys corresponding to each user and/or user segment or type,

wherein a customer journey includes one or more goals and an action plan related to customer engagement with a brand; and

offering services and resolutions via an execution channel to the user based on a determined customer journey, user intent, and user models for characterizing or predicting user behavior across multiple channels.

2. The method of claim 1, said mapping comprising:

when a user interacts with a service, analyzing with a processor an arbitrary combination of a user'"'"'s profile, the user'"'"'s current behavior, results of the user'"'"'s behavior and user interactions, the user'"'"'s recent history, and actual and possible customer journeys available from said catalog to map a customer journey; and

predicting with a processor services for said user by applying a user model for predicting user behavior that is based on at least information comprising any of user interaction across the multiple channels, customer journeys mapped, and execution channels used;

user behavior related to any of current services being consumed, execution channel state information, and user information relevant to delivered services; and

generic algorithm models for learning and optimization using any of neural network based models and statistical optimization models.

3. The method of claim 2, said offering further comprising any of:

guiding said user through steps involved in determined customer journeys;

determining, dictating, and directing the steps available to the user;

supporting the user'"'"'s choice of steps;

combining an arbitrary combination of guidance, determination, direction, and support to the user.

4. The method of claim 1, said execution channel comprising:

a channel for interaction between a user and a system for any of delivery of services and resolution of conflict.

5. The method of claim 4, said execution channel comprising any of:

a mobile platform, Web platform, and communication tools comprising any of chat/email/SMS, Interactive Voice Response (IVR), and social media.

6. The method of claim 1, further comprising:

automatically checking and updating said user regarding status of services and channels that said user is accessing or to which said user is subscribing, either sequentially or in parallel.

7. The method of claim 1, further comprising:

performing automatic self optimization, wherein said automatic self optimization comprises any of preset time intervals, continuous and ongoing self optimization, and instantaneous self optimization.

8. The method of claim 1, said mapping further comprising:

mapping tracking, operations, and execution onto multi-channel interactions performed by the user; and

predicting services that match customer journeys and user behavior.

9. The method of claim 1, said mapping further comprising:

performing customer journey mapping and analysis, wherein said customer journey relates to a sales or service based scenario.

10. The method of claim 9, wherein said customer journey includes

a preferred and designed path that user is intended to take, wherein said path comprises any of a literal path, a virtual path, or a combination of literal and virtual path components.

11. The method of claim 10, further comprising:

mapping to said preferred path, alternate paths, and unintended paths; and

predicting said user'"'"'s goals to identify when and how to deliver key information and actions and services to the user.

12. The method of claim 1, further comprising:

upon reception of a trigger/event from the user, checking if the user has access to any services offered;

wherein said trigger/event is initiated by the user or based on information obtained by the user, said information comprising any of a location of a user, movement of a user, and interaction at a service end point.

13. The method of claim 1, further comprising:

providing a unique id corresponding to a user to identify whether the user has access to various services;

wherein if the user is identified as having access to multiple services, all of said services are linked together and said processor predicts a user model.

14. The method of claim 1, further comprising:

selecting with a processor services related to the user'"'"'s identified preferences and interests;

wherein the selected services are delivered to the user through said execution channel.

15. An apparatus for customer journey resolution and prediction, comprising:

a processor for interacting with users across multiple channels, either sequentially or simultaneously, and fetching data related to services capable of being offered to said users;

said processor mapping to one or more predetermined customer journeys, said mapping applying both of user profiles depicting demographics to which the user belongs, a location of the user, services used by the user in the past, and services the user is currently using, and a catalog of available and possible customer journeys corresponding to each user and/or user segment or type,

wherein a customer journey includes one or more goals and an action plan related to customer engagement with a brand; and

an execution channel for offering services and resolutions to the user based on any of a determined customer journey, user intent, and user models for characterizing or predicting user behavior across multiple channels.

16. The apparatus of claim 15, further comprising:

when a user interacts with a service, said processor analyzing an arbitrary combination of a user'"'"'s profile, the user'"'"'s current behavior, results of the user'"'"'s behavior and user interactions, the user'"'"'s recent history, and actual and possible customer journeys available from said catalog to map a customer journey; and

said processor predicting services for said user by applying a user model for predicting user behavior that is based on at least a hierarchy of information comprising user lifecycle information comprising any of user interaction across the multiple channels, customer journeys mapped, and execution channels used;

user behavior related to any of current services being consumed, execution channel state information, and user information relevant to delivered services; and

generic algorithm models for learning and optimization using any of neural network based models and statistical optimization models.

17. The apparatus of claim 16, said offering further comprising any of:

guiding said user through steps involved in determined customer journeys;

determining, dictating, and directing the steps available to the user;

supporting the user'"'"'s choice of steps;

combining an arbitrary combination of guidance, determination, direction, and support to the user.