Receive unstructured customer data from different sources, such as social networks, emails, surveys or phone calls.
Analyze the text with AI Builder's pre-built sentiment analysis model, which allows us to analyze the text in multiple languages and obtain an overall and sentence-by-sentence score indicating the level of positivity, negativity, or neutrality of the text.
Save the results of sentiment analysis to a database or file for further analysis or reporting.
Send alerts or notifications to the appropriate managers or teams when a negative sentiment or opportunity for improvement is detected.
Generate reports or graphs that show the level of customer satisfaction or dissatisfaction and trends over time.
How to create a workflow with Power Automate to analyze sentiments
To create a workflow with sentiment analysis in Power Automate, we need to follow these steps:
Access Power flow instantly.
Choose a trigger for your flow, such seo usa as when an email is received, when a tweet is posted, or when a survey is filled out.
Add an AI Builder action and select the prebuilt sentiment analysis model. This model allows us to analyze text in multiple languages and obtain an overall and sentence-by-sentence score indicating the level of positivity, negativity, or neutrality of the text.
Specify the language and text we want to analyze. We can use the trigger's dynamic content to extract text from the email, tweet, or survey.
Add the actions you want to perform with the results of the sentiment analysis. For example, you can save them in a SQL table, send them by email or Teams, create a task in Planner, or generate a chart in Excel.
Save and test the flow to verify its functionality.
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