What is Sentiment Analysis of Customer Feedback in Power Automate?

What is Sentiment Analysis of Customer Feedback in Power Automate?

In the past, businesses didn’t pay as much attention to customer feedback, but times have changed. Today, customers are considered the most important part of the market, and their opinions matter more than ever. To improve their business operations, organizations now use various tools to analyze customer feedback. One such tool is Power Automate. When you combine the power of AI with Power Automate for customer analysis, its effectiveness is greatly increased, allowing businesses to gain deeper insights and respond more efficiently to customer needs.

Here in this article, we will discuss in detail the Sentiment Analysis of customer feedback in Power Automate. So if you are looking to grow your career in this field, you can enroll in Power Automate Training. This training is useful for understanding the Sentiment analysis of customer feedback in Power Automate. So let’s begin by discussing what is Sentiment Analysis.

What is Sentiment Analysis?

Sentiment Analysis is a method of using technology that can find out the emotions behind the text. Also, this can help understand whether the writer’s emotions are positive, negative or neutral. Businesses can use these techniques and benefit. Because this technique will help them understand how people feel about their products, services or brand.

How to Implement Sentiment Analysis in Power Automate? Also

Here we have discussed the guide for Implementing Sentiment Analysis in Power Automate. So if you have gained Power Automate Certification then you will be able to implement this in your organization:

1. Triggering the Flow:

The first step in any Power Automate workflow is the trigger. This is the event that kicks off the whole automation process. For analyzing customer feedback with sentiment analysis, the trigger depends on where the feedback comes from. For example, it could be "When a new email arrives" for email feedback, "When a new response is submitted" for Microsoft Forms, "When a new post is created" for social media platforms, or "When a row is added" for Dataverse tables. The trigger is important because it ensures the flow starts as soon as new feedback is available, setting everything in motion for analysis.

2. Connecting to AI Builder:

Once the trigger is activated, the next step is to connect Power Automate to AI Builder's sentiment analysis feature. This is done by adding the "Predict" action from the AI Builder connector in your flow. The AI Builder connector is the bridge that connects Power Automate to the pre-trained AI models from AI Builder. When you add the "Predict" action, you’ll select the "Sentiment analysis" model. If you haven’t already set up the model, you can easily create it. This connection ensures that the feedback data gathered by the trigger is sent to AI Builder for sentiment analysis, helping you get accurate results.

3. Providing Input Text:

After the connection to AI Builder is made, the next step is to provide the text that will be analyzed. This means selecting the right dynamic content from the trigger that contains the customer feedback. For example, if the trigger is "When a new email arrives," you would choose the "Body" of the email. If you're using a Microsoft Forms trigger, you would select the customer’s response. This text is then sent to AI Builder for sentiment analysis, ensuring that the right feedback is being analyzed to understand customer emotions.

4. Analyzing the Results:

Once the text is provided, AI Builder processes it and returns a sentiment classification and a confidence score. The classification tells you whether the sentiment is positive, negative, or neutral, giving you an idea of the emotional tone of the feedback. The confidence score shows how sure the model is about its classification, giving you a sense of how reliable the result is. These results are then available for use in your Power Automate flow, so you can take action based on the sentiment analysis. For example, you could save the sentiment and confidence score in a database, use them to send notifications, or trigger specific actions depending on the sentiment.

5. Taking Action Based on Sentiment:

The final step is using the sentiment results to take action. Based on whether the feedback is positive, negative, or neutral, the flow can trigger different tasks to address customer needs. For negative sentiment, actions could include creating a case in a CRM system, notifying a support team, or sending an apology email. For positive sentiment, you might send a thank-you email, share the feedback on social media, or add the customer to a loyalty program.

Apart from this, if you have taken the Blue Prism Course, you can easily understand the Power Automate skills. Also, this course can help you break down complex tasks into sequential steps.

Conclusion:

From the above discussion, it can be said that when you leverage the power of sentiment analysis in Power Automate, businesses can gain valuable insights. Also, they can improve customer experience and increase business growth. Because all of these things are necessary for the smooth running of the business. When you integrate Power Automate with AI Builder, this may enable you to automate the process of extracting sentiment from customer feedback.