In the previous blog post, we've shown how to create a sentiment analysis dashboard for customer communications. If you track customer emails and analyze their sentiment, you can seriously improve your support function which ultimately will affect your NPS score in a positive. This in turn will lead to more sales.
Additionally, sentiment analysis can be used on an individual level by sales reps when they work on a deal. Your sales reps also need tools to tackle potential deal delays or early warnings of customer churn.
There is a great template shared by Monday.com team Alex Goya that he used for his sales reps and we will augment it with sentiment analysis using Bitskout workflow.
Here is the video with the description below:
First of all, you can find the template at monday.com story from Alex Goya. There is also a video webinar where Alex goes through the template and how he then compiles all his team pipelines into an overview.
So let's use the template and add it to our workspace:
As you can see from the screenshot above we've added a new status column called "Comms Sentiment" and added several labels like this:
Then, we need to configure several integrations. As Alex explains in the video, if you add Gmail integration and configure the recipe to update the task, all communications with the customer will be recorded on the board. This is precisely what we are looking for:
The marked column name("Email") is responsible for sorting between tasks. As it contains the email address of the lead, every email where this lead is a sender will be reflected as an update in the corresponding row.
Then, we add a Bitskout recipe that will analyse each email for Sentiment:
In this case we use a "Positive Sentiment Text Analysis" workflow to test for sentiment. It will set the label to "Not positive" when the email communication will be anything but not positive (e.g. neutral, negative or mixed). You can change it to make it more clearer by reverting the check to "Negative Sentiment Check" like this:
And now let's send some test emails to see how it works. Once the emails are received, we see the change in the Comms Sentiment label:
If we take a look inside, we can see what was the sentiment values in the last check:
We've used the Negative sentiment check and it resulted in mostly neutral. According to our setup, this is considered not negative, therefore, we set the label as positive.
This small addition will allow your sales reps track communication sentiment to understand the dynamics of conversation and, if required, take action to revert it before it is too late.