Augmenting a Contact Form
Augmenting a Contact Form
Adding sentiment analysis to contact form in monday.com
Adding sentiment analysis to contact form in monday.com
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.

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.

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.

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:

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.

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

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

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.

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:

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

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.