Automate Sentiment Analysis of New Airtable Records Using MonkeyLearn
Automatically analyze the sentiment of new records in your Airtable base using MonkeyLearn's machine learning models. This workflow helps you gain insights into customer feedback by classifying sentiments as positive or negative.
This workflow triggers whenever a new record is added to a specified Airtable base. It extracts the 'Reasons' field from the record and sends it to MonkeyLearn for sentiment analysis. The resulting sentiment classification is then updated back into the Airtable record, allowing for seamless tracking and analysis of customer feedback.
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How to import this workflow into Make
- 1Purchase or download the workflow to get the Make blueprint JSON file.
- 2In Make, create a new scenario, click the three-dots menu, and choose "Import Blueprint".
- 3Reconnect each module to your own app connections when prompted.
- 4Run the scenario once to verify it, then set your schedule and turn it on.
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