Use Google sentiment analysis on Typeform submissions to automatically categorize feedback and prioritize reaching out to those who need it most.
It can be difficult to gain meaningful insights from large amounts of free-form user entered data. Forms that collect user feedback must be read individually and categorized by hand before any sort of aggregation or analytical work can be done. This has driven companies like Google to create Natural Language Processing tools that can do that sort of categorization automatically.
With the Sentiment Analysis transform, Parabola users the power of Google's NLP tools to create a sentiment and confidence score. Read about Google Sentiment Analysis here.
In this flow, we are using Typeform entries. Typeform is a tool for making interactive and useful forms. Check them out here.
The flow pulls in Typeform form entry data, and then passes the long text fields through the Sentiment Analysis step. The step scores each cell given with a sentiment - positive number for positive sentiment, and negative numbers for negative sentiment. 0 is neutral. Along with that is a confidence score between 0 and 1 (or 0% and 100%). The flow multiplies the sentiment by the confidence to get an adjusted score. That score is sent to a database to keep track of historic numbers, and any score that is too negative is sent to the Customer Success team to handle.
This flow can cut down on hours of work and guesses, and deliver a list of unsatisfied customers each day. Use this flow as a jumping off point to incorporate Sentiment Analysis into your data.