In today’s digital world, businesses receive customer feedback from multiple channels—emails, social media, surveys, and support tickets. Understanding customer sentiment is crucial for improving services, enhancing customer experience, and making informed business decisions.
Microsoft AI Builder and Power Automate enable businesses to automate sentiment analysis by categorizing feedback as positive, neutral, or negative—helping teams respond proactively and improve customer satisfaction.
1. What is Sentiment Analysis?
Sentiment analysis is an AI-powered process that determines the emotional tone of text-based data, such as:
Customer feedback and surveys
Social media posts and reviews
Support tickets and emails
Product comments and chatbot interactions
By using AI Builder’s prebuilt Sentiment Analysis model, businesses can automate responses, trigger workflows, and gain insights from feedback data.
Example: A company receives a negative review on Twitter. Power Automate detects it and triggers an alert to the customer support team for immediate follow-up.
2. How AI Builder and Power Automate Work Together for Sentiment Analysis
AI Builder provides a prebuilt Sentiment Analysis model that can be integrated into Power Automate workflows. This allows businesses to analyze text automatically and take actions based on sentiment scores.
Benefits of AI Builder Sentiment Analysis
- Automates sentiment detection across emails, forms, and social media.
- Categorizes customer feedback into positive, negative, or neutral.
- Triggers workflows for customer engagement or escalation.
- Improves response time by directing feedback to the right teams.
Example: A customer submits a support ticket with negative feedback. AI Builder automatically flags it, and Power Automate notifies a manager for immediate resolution.
3. Step-by-Step: Using AI Builder for Sentiment Analysis in Power Automate
Step 1: Set Up an AI Builder Sentiment Analysis Model
1️⃣ Open Power Apps and go to AI Builder.
2️⃣ Select “Sentiment Analysis” under Prebuilt AI models.
3️⃣ Click Use in Power Automate to start building an automated workflow.
Step 2: Create a Power Automate Flow
1️⃣ Open Power Automate and create a new Automated Cloud Flow.
2️⃣ Choose a trigger, such as:
- “When a new email arrives” (Outlook)
- “When a new response is submitted” (Microsoft Forms)
- “When a tweet is posted” (Twitter)
3️⃣ Add an AI Builder action: Analyze sentiment in text.
4️⃣ Map the text input (e.g., email body, survey response, or tweet content).
Step 3: Define Sentiment-Based Actions
1️⃣ Add a Condition Control to check sentiment analysis results.
2️⃣ Set up different actions based on sentiment:
- Positive Feedback: Send a “Thank You” email.
- Neutral Feedback: Store data for analysis.
- Negative Feedback: Trigger an alert for the support team.
Example: If a negative sentiment is detected in an email, Power Automate automatically creates a high-priority task in Microsoft Teams for follow-up.
Step 4: Store and Monitor Sentiment Data
1️⃣ Save sentiment results in SharePoint, Dataverse, or Excel for reporting.
2️⃣ Use Power BI to analyze trends and insights over time.
3️⃣ Create real-time dashboards to track customer sentiment patterns.
Example: A marketing team tracks brand sentiment trends on social media and adjusts strategies accordingly.
4. Real-World Use Cases of AI Builder Sentiment Analysis
Customer Support
Challenge: Identifying urgent support tickets from a large volume of inquiries.
Solution: AI Builder flags negative emails, and Power Automate escalates urgent cases to managers.
Social Media Monitoring
Challenge: Responding quickly to negative brand mentions.
Solution: AI Builder analyzes tweets, and Power Automate notifies social media managers for quick engagement.
Employee Feedback Analysis
Challenge: Understanding employee satisfaction in surveys.
Solution: AI Builder categorizes survey responses, helping HR teams identify areas for improvement.
5. The Future of AI-Powered Sentiment Analysis
Upcoming Trends:
More Accurate AI Models – Advanced NLP (Natural Language Processing) for better sentiment detection.
Voice Sentiment Analysis – AI detecting sentiment in audio conversations.
Real-Time AI Feedback – Instant customer sentiment responses through AI chatbots.
Deeper CRM Integration – AI-driven insights directly into Dynamics 365, Salesforce, or other CRMs.
Businesses that embrace AI-driven sentiment analysis will improve customer relationships, brand reputation, and decision-making.