Analytics and ReportingPurpose
1.2. Enable automated sentiment analysis to determine positive, neutral, or negative perceptions across multiple feedback sources.
1.3. Centralize analytics reporting and automate alerts for trends, negative spikes, or notable experiences.
1.4. Automate segmentation of sentiment by service aspects (e.g., staff, equipment, song catalog, ambiance).
1.5. Provide actionable automated insights for management regarding customer satisfaction, enabling rapid operational adjustments.
Trigger Conditions
2.2. Daily or scheduled batch import of feedback data.
2.3. Receipt of specific keywords in feedback indicating unusual service experiences.
2.4. Automated detection of repeated topics, names, or complaints.
2.5. Monthly aggregation of sentiment results for auto-generated reports.
Platform variants
• Feature/Setting: Configure automated review text parsing; use "analyzeSentiment" for feedback sentiment score.
3.2. Microsoft Azure Text Analytics
• Feature/Setting: Configure automated "Sentiment Analysis" function; set API endpoint and API key.
3.3. AWS Comprehend
• Feature/Setting: Use "DetectSentiment" API; automate review batches to send/receive sentiment data.
3.4. IBM Watson Natural Language Understanding
• Feature/Setting: Automate "Sentiment" and "Emotion" feature extraction for imported feedback.
3.5. MonkeyLearn
• Feature/Setting: Create automated workflow with "Sentiment Classifier" API endpoint.
3.6. Repustate
• Feature/Setting: API integration for automated feedback parsing and sentiment scoring.
3.7. Lexalytics Semantria
• Feature/Setting: Automate submission of review text to Semantria API for analytic output.
3.8. MeaningCloud
• Feature/Setting: Automate calls to "Sentiment Analysis" endpoint; set language and model.
3.9. Aylien
• Feature/Setting: Use "Sentiment Analysis" REST API; automate keyword-topic tagging.
3.10. Sentiment140
• Feature/Setting: Automate upload of Twitter data for sentiment scoring via API.
3.11. Clarabridge
• Feature/Setting: Automate ingestion of multi-channel feedback, auto-configure for real-time analytics.
3.12. Zendesk
• Feature/Setting: Automate triggers for ticket reviews; export text to sentiment analysis API.
3.13. Salesforce Service Cloud
• Feature/Setting: Automate workflow for feedback field; auto-send to third-party sentiment analyzer.
3.14. SurveyMonkey
• Feature/Setting: Automated export of open-ended responses to analytics API.
3.15. Sprout Social
• Feature/Setting: Set automation to collect and pass reviews from social mentions to sentiment APIs.
3.16. Hootsuite
• Feature/Setting: Automate monitoring of channels, auto-routing reviews to analysis API.
3.17. Trustpilot
• Feature/Setting: Automate review export with automatic parsing and scoring via integrated APIs.
3.18. Yelp Fusion API
• Feature/Setting: Configure automated fetching of new reviews; route text through sentiment engine.
3.19. Facebook Graph API
• Feature/Setting: Automate pulling reviews from Pages; submit for automated sentiment analysis.
3.20. Slack
• Feature/Setting: Automate notification or posting of analyzed sentiment scores in feedback channels.
Benefits
4.2. Automatedly identifies pain-points and top-praised attributes for data-driven improvements.
4.3. Reduces manual data review, automating all sentiment extraction and aggregation tasks.
4.4. Automation supports immediate actions on negative feedback, protecting reputation.
4.5. Enables data-driven automation for reporting to management, with automated trend visualization.
4.6. Consistency and objectivity in sentiment scoring, automatedly applied across all channels.
4.7. Automator processes streamline compliance by auto-archiving sentiment reports for audits.
4.8. Increases operational agility using automatable dashboards based on up-to-the-minute analysis.
4.9. Cost reduction through automation of repetitive analysis and reporting jobs.
4.10. Automation empowers cross-comparison of sentiment by category, time, location, or staff.