Automated Analytics Trigger for Customer Feedback Parsing

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Solution Overview

Problem

Enterprises face challenges in efficiently and accurately analyzing solicited customer feedback from numerous interactions, making it difficult to determine which customers to target for feedback and understand their preferences effectively.

Innovation Solution

A system that automatically triggers analytics actions during customer service interactions, parsing feedback into structured data and assigning sentiment categories using a big data application platform, facilitating the recording of feedback into positive, neutral, or negative sentiment pools.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual analysis of customer feedback is performed, then understanding of individual customer preferences can be achieved, but the system cannot handle substantial numbers of customer interactions efficiently

Engineering Contradiction:

Improvefeedback analysis throughputVSAvoidcustomer preference understanding accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent introduces an automated analytics system as an intermediary between customer feedback collection and analysis. This system includes components that automatically detect interaction contexts, trigger relevant analytics actions, capture feedback data, and process it through structured pipelines. The intermediary handles the volume of data processing while preserving analytical depth through automated sentiment analysis and categorization, thus resolving the contradiction between handling substantial numbers of interactions and maintaining understanding accuracy.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent replaces manual mechanical analysis processes with automated computational systems. Instead of human analysts manually reviewing each customer interaction, the system uses automated detection algorithms, triggered analytics actions, and computational processing to analyze feedback at scale. This substitution enables high-throughput processing while maintaining consistent analytical standards through programmed methodologies, addressing the productivity-precision contradiction.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Quantity of substance

If feedback is solicited from all customers, then comprehensive data can be collected, but it becomes difficult to determine which customers should be targeted

Engineering Contradiction:

Improvefeedback data volumeVSAvoidcustomer selection complexity

Core Design Contradiction:

Quantity of substanceVSEase of operation

Solution Approach 1:

The patent implements preliminary action by pre-configuring analytics actions that are automatically triggered based on detected interaction contexts. The system establishes beforehand which types of interactions should generate feedback requests, creating a structured framework that identifies target customers automatically. This preliminary setup eliminates the need for manual determination of which customers to contact, as the system autonomously selects appropriate targets based on pre-defined criteria, thus resolving the contradiction between data volume and selection ease.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system uses feedback mechanisms where analytics actions are automatically triggered based on detected interaction patterns and customer database entries. This creates a closed-loop system where past interaction data informs future feedback solicitation decisions. The automated feedback loop continuously refines customer selection based on accumulated insights, making the process increasingly efficient without manual intervention, addressing the contradiction between comprehensive data collection and operational simplicity.

Inventive Principle:

Principle #23Feedback

3Productivity

If automated systems are used to analyze feedback, then processing efficiency increases, but data accuracy and security may be compromised

Engineering Contradiction:

Improvefeedback processing speedVSAvoidfeedback analysis accuracy

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The patent implements self-service through automated analytics actions that autonomously detect interaction contexts, trigger appropriate analysis routines, capture feedback data, and process it through structured pipelines without requiring continuous human oversight. The system serves itself by maintaining automated workflows that consistently apply analytical standards while preserving data accuracy through programmed validation and structured processing methods, thus resolving the contradiction between processing speed and reliability.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS10636047B2System using automatically triggered analytics for feedback data

Publication Date: 2020.04.28 HARTFORD FIRE INSURANCE CO

AI summary

A customer database system may store historic customer satisfaction information. A CSR terminal may facilitate an interaction between a service representative and a first customer, and a survey platform may: (i) detect that the CSR terminal is currently interacting with the first customer and that the first customer has an entry in the customer database system, and (ii) automatically trigger an analytics action at the CSR terminal. A relational database may receive solicited customer feedback information along with a structured escalation level category entered via the analytics action. The solicited customer feedback information may be parsed into unstructured text, and a big data application platform may: (i) execute an algorithm to assign a sub-category to the first customer interaction based on the unstructured parsed text, and (ii) assign the solicited customer feedback to positive, neutral, and/or negative sentiment pools.