Sentiment Feedback Sentiment Feedback (Genesys Cloud Quality & Performance Management) Section Description Module Context Part of Quality Management → Speech & Text Analytics within Workforce Engagement Management (WEM) Admin Location Admin → Quality → Sentiment Feedback Purpose Allows administrators to correct sentiment classification errors in Speech & Text Analytics by labeling phrases as Positive, Neutral, or Negative , improving automated sentiment detection accuracy Sentiment Feedback is used to improve the machine learning sentiment model that evaluates transcripts produced by Speech & Text Analytics. When the system misinterprets emotional tone in a conversation, administrators can add a phrase and assign the correct sentiment classification. These corrections influence future sentiment analysis results and help improve topic detection, interaction insights, and analytics reporting . Summary Table Attribute Details Feature Area Speech & Text Analytics Primary Function Improve sentiment classification accuracy Data Source Interaction transcripts Supported Channels Voice (transcribed), Chat, Messaging, Email Sentiment Labels Positive / Neutral / Negative Dialect Context Sentiment phrases are tied to a language dialect used by speech analytics models Typical Users Quality administrators, analytics administrators Dependency Speech & Text Analytics must be enabled Study Notes Topic Explanation Sentiment Analysis Automatic classification of emotional tone within conversations Sentiment Feedback Manual correction of sentiment detection errors Phrase-Based Overrides Administrators add phrases that override default sentiment classification Transcript Dependency Sentiment feedback only applies to interactions with transcripts Dialect Awareness Phrases must match the speech analytics dialect model used during transcription Analytics Impact Changes influence future sentiment scoring and analytics dashboards Key concepts: Sentiment feedback improves the accuracy of automated sentiment scoring . Phrases are applied per dialect , ensuring correct language interpretation. Corrections apply to future transcript processing . Sentiment feedback helps refine analytics used for CX insights and coaching . Navigation Task Navigation Open Sentiment Feedback Admin → Quality → Sentiment Feedback Add new sentiment phrase Admin → Quality → Sentiment Feedback → Add Phrase Edit phrase Admin → Quality → Sentiment Feedback → Edit Delete phrase Admin → Quality → Sentiment Feedback → Delete Review transcript sentiment Performance → Workspace → Interactions Configuration Fields (UI Form Fields) Main Page UI Field Description Options / Behavior Phrase List Displays phrases configured for sentiment feedback Read-only Sentiment Label Shows sentiment classification assigned to phrase Positive / Neutral / Negative Dialect Dialect the phrase applies to Example: English – United States Created By User who created phrase entry Read-only Created Date Timestamp of phrase creation Read-only Search Search for phrases in list Text field Add Phrase Opens phrase creation form Button Edit Edit phrase sentiment configuration Button Delete Remove phrase from sentiment list Button Refresh Reload phrase list Button Create/Edit Form UI Field Description Options Phrase Phrase appearing in transcripts Text input Sentiment Sentiment assigned to phrase Positive / Neutral / Negative Dialect Speech analytics dialect model used for phrase interpretation Example options: English – United States / English – United Kingdom / Spanish – Spain / Spanish – Mexico / Portuguese – Brazil Description Optional note describing reason for classification Text input Save Save configuration Button Cancel Discard changes Button Tabs, Toggles, Dropdowns, Action Buttons UI Element Type Item Tabs Sentiment Feedback page Text Fields Phrase, Description Dropdowns Sentiment classification, Dialect Buttons Add Phrase, Save, Cancel, Edit, Delete, Refresh Note: No toggles are documented for Sentiment Feedback in the admin UI. Dependencies Component Purpose Speech & Text Analytics Generates transcripts used for sentiment analysis Interaction Recording Required for voice transcript generation Topics Sentiment can be correlated with topics Programs Topics grouped for analytics programs Topic Miner Detects candidate phrases for sentiment feedback Language Models Dialect-specific transcription models Platform Integration / Related Components Component Relationship Speech & Text Analytics Provides transcript and sentiment analysis engine Topics Sentiment often analyzed alongside topics Programs Topic groups used in analytics dashboards Topic Miner Identifies phrases administrators may classify Interaction Analytics Displays sentiment metrics Integration Examples Integration Description Analytics API Retrieve sentiment metrics for dashboards Notifications API Subscribe to interaction lifecycle events to trigger external analytics processing Conversations API Retrieve transcript data programmatically Example integration workflow: Customer Interaction ↓ Speech Analytics Transcript ↓ Sentiment Analysis ↓ Sentiment Feedback Overrides ↓ Analytics API retrieves results ↓ External dashboard updated Related Topics / Further Reading Topic Description Speech & Text Analytics Core analytics engine Topic Miner Discover phrases in transcripts Topics Phrase detection logic Programs Topic grouping for analytics Evaluation Forms Agent performance scoring Implementation Checklist Task Status Enable Speech & Text Analytics ☐ Confirm transcript generation ☐ Verify correct dialect configuration ☐ Review sentiment accuracy ☐ Identify misclassified phrases ☐ Add sentiment feedback entries ☐ Validate improved sentiment detection ☐ Implementation Guide Step Action Step 1 Enable Speech & Text Analytics Step 2 Confirm transcripts are generated Step 3 Review interactions for sentiment misclassification Step 4 Navigate to Sentiment Feedback Step 5 Click Add Phrase Step 6 Enter phrase and select correct dialect Step 7 Assign sentiment classification Step 8 Save configuration How to Implement Phase Description Analytics Monitoring Monitor sentiment results in transcripts Error Identification Detect incorrect sentiment classification Phrase Feedback Add phrase classification using correct dialect Validation Monitor analytics improvements Workflow Customer Interaction ↓ Interaction Recording ↓ Speech-to-Text Transcription ↓ Speech Analytics Sentiment Engine ↓ Admin Detects Incorrect Sentiment ↓ Sentiment Feedback Phrase Added (Dialect-specific) ↓ Future transcripts classified correctly Architecture Diagram Customer Interaction ↓ Recording Engine ↓ Speech-to-Text Processing ↓ Transcript Storage ↓ Speech & Text Analytics ├ Sentiment Analysis └ Topic Detection ↓ Sentiment Feedback Phrase Overrides ↓ Analytics Dashboard Real Flow Scenarios Scenario 1 – Correcting Positive Sentiment Customer says: "Thank you for resolving my issue" ↓ System labels phrase as Neutral ↓ Admin adds phrase with Positive sentiment ↓ Future interactions labeled Positive Scenario 2 – Detecting Customer Frustration Customer says: "This service is terrible" ↓ Transcript generated ↓ Sentiment engine detects negative tone ↓ Analytics dashboard flags interaction Usage Scenarios Scenario Description Customer satisfaction monitoring Improve sentiment accuracy Product issue detection Identify negative feedback Agent coaching Understand customer reactions CX analytics Track sentiment trends Implementation Examples Example Configuration Support center Add satisfaction phrases Billing queue Label complaint phrases Sales queue Label positive purchase indicators Design Example Inbound Customer Call ↓ Speech Analytics Transcript ↓ Sentiment Classification ↓ Admin Reviews Transcript ↓ Sentiment Feedback Added ↓ Improved Analytics Accuracy Best Practices Practice Reason Add phrases tied to correct dialect Prevent incorrect language interpretation Focus on high-frequency phrases Improve model quickly Review sentiment dashboards regularly Detect classification issues Combine sentiment with topics Improve context understanding Naming Convention Resource Example Phrase Classification Positive_Service_Resolution Phrase Classification Negative_Billing_Issue Naming pattern: _ Security Considerations Control Description Role-based access Restrict configuration to administrators Transcript privacy Protect sensitive conversation data Data retention policies Control transcript storage Encryption Protect stored transcripts Limitations / Constraints Constraint Description Sentiment categories Positive / Neutral / Negative Requires transcripts Speech analytics must be enabled Context sensitivity Phrase sentiment may vary by context Dialect dependence Phrase must match configured dialect Troubleshooting Issue Cause Resolution Sentiment incorrect Phrase not defined Add sentiment feedback Phrase not matching Dialect mismatch Select correct dialect No transcripts available Speech analytics disabled Enable transcription Analytics unchanged Phrase not used in transcripts Verify phrase frequency Interview Cheat Sheet Question Answer What is Sentiment Feedback? Manual correction of sentiment classification Where is it configured? Admin → Quality → Sentiment Feedback What labels exist? Positive, Neutral, Negative What additional parameter is required? Dialect What dependency is required? Speech & Text Analytics Key Takeaways Topic Summary Sentiment Feedback Improves automated sentiment detection Phrase Overrides Admins classify phrases manually Dialect Support Phrases must match speech analytics dialect Speech Analytics Provides transcripts used for analysis Continuous Improvement Feedback improves analytics accuracy Screenshots