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Augmenting a Contact Form

Adding sentiment analysis to contact form in monday.com

· monday,sentiment,text analysis,NLP,customer feedback

In this example we will add sentiment analysis to existing Contact Form template in Monday.com. Contact Form template consists of a main view with a list of task that are created per each submitted message and a form that can be shared on a website or via URL.

Here is the video of how it works and below you will find a step-by-step instruction.

Once the form is filled with information like name, phone, email and comments, it is converted into a task in Monday.com board giving your the overview of the contacts. What we will do here is add an extra dimension to the message by adding sentiment analysis.

a screenshot of Contact Us form template from Monday.com

To analyse a sentiment we will need to create a Text Analysis model and add it to a workflow. We will focus on analysing for negative sentiment because we want to tackle issues right away.

A screenshot of Bitskout Text Analysis model creation with selected Negative Sentiment check

Once we've integrated the board to the Bitskout, we need to add some extra labels so we can see what it going on with our contacts. First, we've added a Status column and renamed to Sentiment. And we've also added several labels to tells about the sentiment, and one extra label called Validate that will be a trigger.

a Contact Form template from Monday.com with added labels for sentiment analysis from Bitskout

Now the last thing that we need to do is to add Bitskout recipes that analyse the column "Comment". We will do that by going to Integrations and selecting appropriate option:

A bitskout recipe that is analysing a data from a  column

Basically, we need to add the following condition - when the Sentiment column has a status Validated, run a workflow Sentiment verification on a column Comments.

a configured Bitskout recipe for monday.com board with sentiment analysis

And also to simplify our life, we can add an extra automation that sets the Sentiment to Validate once the item is created:

an extra monday.com automation to set Sentiment value to Validate so we can trigger Bitskout workflow

So now let's use the form and test it. Go to the form and fill it with some sample comment.

an example of Monday.com form filled with Hamlets' to be or not to be.

Once the form is submitted, we can see that the sentiment has changed to Validate. Now Bitskout workflow will be invoked to check it.

Once the check is finished, Bitskout workflow will assign a label and write the results into an update.

a monday.com task with Bitskout workflow results for text sentiment checks

Then you can add extra automation that will move the items with Negative Sentiment to a special group with urgent requests that require immediate attention.

The automation will be like this:

a view of another Monday.com automation that will allow moving items to a group after Bitskout sentiment check

This will allow you distribute items based on their sentiment and see what things you need to take care first.

task routing between monday.com groups based on a sentiment check by Bitskout workflow

Using text analysis you uncover different insights or understand feedback better. You can check incoming messages from your customers or your employees allowing you to focus on the issues that matter the most until they'll become a problem.

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