Using response tags to categorize customer feedback into topics is a highly effective practice that will help you easily analyze your survey data.
However, if you’re receiving lots of responses, it will eventually become hard to manually manage the feedback tags.
Fortunately, you can automate the whole process and have your customer responses tagged automatically by integrating a specific service - MonkeyLearn, using our native Zapier integration.
MonkeyLearn is a content analysis service that uses AI and machine learning to identify topics and emotions from text-data and offers a variety of content classifiers.
To set up this workflow you will need:
- A Zapier account: Offers a free subscription, for up to 150 tasks per month.
- A MonkeyLearn account: Offers a free subscription, for up to 300 queries per month.
Once you have your accounts set up you can either use this Zap template or follow the tutorial below and create the Zap from the scratch.
Log in to Zapier, create a new Zap, and choose Retently as your "Trigger" app.
Select “New Survey Response” as your trigger.
Next, you will be asked to select a connected Retently account. If you haven't connected your account yet, then you will be asked to log into Retently.
Your trigger is almost configured. On the next step, you will be asked to pull a sample of data from your Retently account to make sure that everything is configured properly.
Click the "Test trigger" button and wait for Zapier to pull one or more responses from your account.
IMPORTANT: There are a couple of things to keep in mind when pulling the test sample:
- Make sure that you have at least one response in your Retently account, otherwise, Zapier will not be able to find any data to display.
- Keep in mind that it takes about 15 minutes for a received response to be available to external services (including Zapier). This is a system delay, to ensure that your survey respondents have enough time to answer all survey questions and provide text feedback.
If pulled successfully, your survey data will have the following structure:
Next, you have to set up the "Action" app. Search for MonkeyLearn and select it.
As your action, choose “Classify Text”.
Next, you will have to connect your MonkeyLearn account, and Zapier will require your API key.
Find the key in your MonkeyLearn account, by clicking on the profile icon in the top-right corner of the page. You will see the API key field in the small drop-down menu. Click on the key and it will be copied to the clipboard.
Go back to your Zap builder in Zapier and choose the connect new account option. You will be prompted a pop-up window asking to include your MonkeyLearn API key. Paste the key you have just copied.
Moving on, you will have to map the action template. In the Classifier input field choose the "NPS SaaS feedback" classifier option.
In the Text field, input the text feedback sample that was generated when you set up Retently as your "Trigger" app.
Hit Continue and test this step. If the test went successfully, then you should see one or more tags that MonkeyLearn has identified in the results window.
Next, create a new, third, step in your Zap and choose Retently again. This time it will perform as an "Action" app. This time choose “Tag a Survey Response” as the action.
Make sure that the Retently account you have previously connected is listed and hit Continue.
When editing the template, click the "Response ID" field. You will see two options, but the one you need is “New survey response in Retently”.
Find the Response ID property from the list and select it.
Below, in the Response tags field, choose the “Classify text” option.
Then select the All tags property from the list.
Continue and test this last step.
If everything looks ok and no error has been thrown, then you can save and enable the Zap.
How does this Zap work?
The three-step Zap will track your Retently account’s new responses, and whenever a customer leaves a new text-feedback, Zapier will export it to your MonkeyLearn account. MonkeyLearn will automatically analyze the text feedback and will identify one or more tags, that will be then returned to Retently and applied as tags to the customer response.