# US 2021/0241289 A1 · Mitigating user dissatisfaction related to a product

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- Number: US 2021/0241289 A1
- Document ID: US20210241289A1
- Status: Published application
- Kind: A1
- Application number: 16/782,420
- Filed: 2020-02-05
- Published: 2021-08-05
- Earliest claimed: 2020-02-05
- Assignees: International Business Machines Corporation
- Applicants: International Business Machines Corporation
- Inventors: Sujoy Roy; Radha Mohan De
- Web page: https://patentgrep.com/patent/US20210241289A1

## CPC

- G06Q 30/016: After-sales
- G06N 20/00: Machine learning
- G06Q 10/40: Business processes related to social networking or social networking services
- G06Q 30/0282: Rating or review of business operators or products
- H04L 67/12: specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
- H04L 67/306: User profiles
- H04L 67/535: {Tracking the activity of the user (network monitoring arrangements H04L43/00; recording of computer activity G06F11/34)}
- G16Y 10/75: Information technology; Communication
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M)
- G16Y: INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]

## Abstract

Provided is a method, computer program product, and system for mitigating user dissatisfaction with a product. A processor may collect a first set of user interaction data and a first set of user sentiment data related to the product. The processor may generate a user profile for the user, including a satisfaction threshold for using the product based in part on the first set of user interaction data and the first set of user sentiment data. The processor may monitor a second set of user interaction data and a second set of user sentiment data. The processor may compare the second set of user interaction data and the second set of user sentiment data to the satisfaction threshold and determine that the user is experiencing dissatisfaction with the product when the satisfaction threshold has been exceeded. In response, the processor may output an action to reduce dissatisfaction of the user.

## Claims

### Claim 1

A computer-implemented method comprising:
collecting a first set of user interaction data related to a product from a device on a network and a first set of user sentiment data related to the product from a communication channel, wherein the user interaction data and user sentiment data is specific to a user;
generating a user profile for the user, wherein the user profile includes a satisfaction threshold for using the product based in part on the first set of user interaction data and the first set of user sentiment data;
monitoring a second set of user interaction data related to the product from the device on the network and a second set of user sentiment data from the communication channel;
comparing the second set of user interaction data and the second set of user sentiment data to the satisfaction threshold;
determining that the user is experiencing dissatisfaction with the product when the satisfaction threshold has been exceeded; and
in response to the satisfaction threshold being exceeded, outputting an action to reduce dissatisfaction of the user.

### Claim 2 (depends on 1)

The computer-implemented method of claim 1, wherein the action is selected from the group consisting of:
arranging a customer service appointment;
sending a root cause analysis report related to the dissatisfaction experienced by the user with the product;
sending a complimentary offer for one or more other products;
transmit a firmware or software update to the product to fix/mitigate the problem; and
offering guidance to assist the user with using the product.

### Claim 3 (depends on 1)

The computer-implemented method of claim 1, wherein the action is outputted to the user via contact information associated with the user profile.

### Claim 4 (depends on 1)

The computer-implemented method of claim 1, wherein the satisfaction threshold is generated by:
analyzing, using machine learning, the first set of user interaction data to determine an initial usage pattern of the user related to the product;
analyzing, using natural language understanding, the first set of user sentiment data to determine an initial feeling the user has related to the product; and
generating, using machine learning, the satisfaction threshold by utilizing a scoring model for the analyzed first set of user interaction data and the analyzed first set of user sentiment data.

### Claim 5 (depends on 1)

The computer-implemented method of claim 1, further comprising:
analyzing, using machine learning, historical user interaction data and historical user sentiment data in response to historical actions outputted to reduce dissatisfaction with the product to a plurality of users;
correlating historical success rates for a set of historical actions that have successfully reduced dissatisfaction with the product for the plurality of users; and
implementing one of the set of historical actions when outputting the action to reduce dissatisfaction of the user.

### Claim 6 (depends on 1)

The computer-implemented method of claim 1, wherein the communication channel is selected from the group of:
a social media website;
a service provider website;
a product manufacturer website; and
a customer service telecommunications line.

### Claim 7 (depends on 1)

The computer-implemented method of claim 1, wherein the device is an Internet of Things (IoT) device, and wherein the network is an IoT network.

### Claim 8 (depends on 1)

The computer-implemented method of claim 1, wherein the product is an IoT device.

### Claim 9 (depends on 1)

The computer-implemented method of claim 1, wherein the product is an application accessible by one or more IoT devices.

### Claim 10

A system comprising:
a network;
a communication channel;
a processor; and
a computer-readable storage medium communicatively coupled to the processor and storing program instructions which, when executed by the processor, cause the processor to perform a method comprising:
collecting a first set of user interaction data related to a product from a device on the network and a first set of user sentiment data related to the product from the communication channel, wherein the user interaction data and user sentiment data is specific to a user;
generating a user profile for the user, wherein the user profile includes a satisfaction threshold for using the product based in part on the first set of user interaction data and the first set of user sentiment data;
monitoring a second set of user interaction data related to the product from the device on the network and a second set of user sentiment data from the communication channel;
comparing the second set of user interaction data and the second set of user sentiment data to the satisfaction threshold;
determining that the user is experiencing dissatisfaction with the product when the satisfaction threshold has been exceeded; and
in response to the satisfaction threshold being exceeded, outputting an action to reduce dissatisfaction of the user.

### Claim 11 (depends on 10)

The system of claim 10, wherein the action is selected from the group consisting of:
arranging a customer service appointment;
sending a root cause analysis report related to the dissatisfaction experienced by the user with the product;
sending a complimentary offer for one or more other products;
transmit a firmware or software update to the product to fix/mitigate the problem; and
offering guidance to assist the user with using the product.

### Claim 12 (depends on 10)

The system of claim 10, wherein the action is outputted to the user via contact information associated with the user profile.

### Claim 13 (depends on 10)

The system of claim 10, wherein the satisfaction threshold is generated by:
analyzing, using machine learning, the first set of user interaction data to determine an initial usage pattern of the user related to the product;
analyzing, using natural language understanding, the first set of user sentiment data to determine an initial feeling the user has related to the product; and
generating, using machine learning, the satisfaction threshold by utilizing a scoring model for the analyzed first set of user interaction data and the analyzed first set of user sentiment data.

### Claim 14 (depends on 10)

The system of claim 10, further comprising:
analyzing, using machine learning, historical user interaction data and historical user sentiment data in response to historical actions outputted to reduce dissatisfaction with the product to a plurality of users;
correlating historical success rates for a set of historical actions that have successfully reduced dissatisfaction with the product for the plurality of users; and
implementing one of the set of historical actions when outputting the action to reduce dissatisfaction of the user with the product.

### Claim 15 (depends on 10)

The system of claim 10, wherein the communication channel is selected from the group of:
a social media website;
a service provider website;
a product manufacturer website; and
a customer service telecommunications line.

### Claim 16

A computer program product comprising a computer-readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform a method comprising:
collecting a first set of user interaction data related to a product from a device on a network and a first set of user sentiment data related to the product from a communication channel, wherein the user interaction data and user sentiment data is specific to a user;
generating a user profile for the user, wherein the user profile includes a satisfaction threshold for using the product based in part on the first set of user interaction data and the first set of user sentiment data;
monitoring a second set of user interaction data related to the product from the device on the network and a second set of user sentiment data from the communication channel;
comparing the second set of user interaction data and the second set of user sentiment data to the satisfaction threshold;
determining that the user is experiencing dissatisfaction with the product when the satisfaction threshold has been exceeded; and
in response to the satisfaction threshold being exceeded, outputting an action to reduce dissatisfaction of the user.

### Claim 17 (depends on 16)

The computer program product of claim 16, wherein the action is selected from the group consisting of:
arranging a customer service appointment;
sending a root cause analysis report related to the dissatisfaction experienced by the user with the product;
sending a complimentary offer for one or more other products;
transmit a firmware or software update to the product to fix/mitigate the problem; and
offering guidance to assist the user with using the product.

### Claim 18 (depends on 16)

The computer program product of claim 16, wherein the satisfaction threshold is generated by:
analyzing, using machine learning, the first set of user interaction data to determine an initial usage pattern of the user related to the product;
analyzing, using natural language understanding, the first set of user sentiment data to determine an initial feeling the user has related to the product; and
generating, using machine learning, the satisfaction threshold by utilizing a scoring model for the analyzed first set of user interaction data and the analyzed first set of user sentiment data.

### Claim 19 (depends on 16)

The computer program product of claim 16, further comprising:
analyzing, using machine learning, historical user interaction data and historical user sentiment data in response to historical actions outputted to reduce dissatisfaction with the product to a plurality of users;
correlating historical success rates for a set of historical actions that have successfully reduced dissatisfaction with the product for the plurality of users; and
implementing one of the set of historical actions when outputting the action to reduce dissatisfaction of the user with the product.

### Claim 20 (depends on 16)

The computer program product of claim 16, wherein the communication channel is selected from the group of:
a social media website;
a service provider website;
a product manufacturer website; and
a customer service telecommunications line.