Select “Yes” to [stop this Zap step](https://help.zapier.com/hc/en-us/articles/20505304170637-Review-Zap-run-statuses#h_01HD20969HPZ01ENM30NQR79X5) if the app returns an error and enable automatic authentication refresh. Select “No” to run the Zap step regardless of errors. Learn more about [API Request action error handling](https://help.zapier.com/hc/en-us/articles/12899473501453#h_01JKRBY68EDXBB1V817DSTRZ0N).

Requests can only be made to domains associated by this application. Read more about [API Request Setup](https://help.zapier.com/hc/en-us/articles/12899607716493).

Any parameters added to a URL will be URL-encoded and appended to the request URL to pass additional data to the API request.

These headers and values will be applied to the request in addition to any headers created as part of authentication. Authentication headers are added automatically.

Zapier will pass this along raw. If you would like to provide complex JSON, try a "Code by Zapier" step to build the structure and pass it along here. For example, `{"foo": "bar"}` is perfectly valid.

Google Forms is an easy way to collect data from the web with a simple UI and powerful editor. Works hand-in-hand with Google Sheets!

Google Forms

Instantly build dynamic interfaces that connect to Zaps and a data source (like Tables). Interfaces gives you a drag-and-drop way to build visual workflows for any business process, without writing code.

Zapier Interfaces

Here you can put a direct reference to the text. This could be a url to a Tweet, an identifier of an online survey, or a link to a reddit thread.

Enter the source of the text. This field can help you later to identify where a certain detection was made. Common examples of sources would be "Twitter", or "Facebook" for social media analysis, "Personal Email" when analysing your email, or "Survey Campaign X" for a specific survey that you run online.

Enter the author of the text that you are sending for analysis. Examples would be an email address, a Twitter account, or any other identifier that helps you to know who wrote the text.

Select the Deeper that you want to use to evaluate the text document.

Enter the text that you want to evaluate with the Deeper.

Enter the author of the text. Examples would be an email address, a Twitter account, or any other identifier that helps you to know who wrote the text.

Enter the source of the text. Common examples of sources would be "Twitter", or "Facebook" for social media data, or the name of a specific survey that you are running online.

Enter a reference that helps you to uniquely identify the text. This could be the url of a Tweet, an identifier of an online survey response, or a link to a reddit post.

Chose the analysis that you want to add your text document to.

Enter the text that you want to add to your analysis.

Enter the date of creation of the text content.

Enter the NPS evaluation of your customer, if applicable.

Enter the CSAT evaluation of your customer, if applicable.

Enter an identifier that allows you to uniquely identify the text within the app that it originates from.
For example, if you analyze surveys, this could be the response_id.

Enter the name the categorical metadata columns.
Categorical metadata is any type of metadata that is not numerical and, therefore, has no intrinsic ordering to it. Examples would be country, gender or job position. You will be able to apply a multi-select filter to this metadata.

Enter the values of the categorical metadata columns. Ensure the order is the same as in the names of the columns.

Enter the name the numerical metadata columns. Numerical metadata must consist of numbers. Examples would be age or    price. You will be able to apply a range filter to this metadata.

Enter the values of the numerical metadata columns. Ensure the order is the same as in the names of the columns.

A tag helping you in identifying the newly created model in Deep Talk.

The Project in which the clustering analysis should run.

The name of the column containing your text data.

Name of the column containing the date when the texts were created. You may leave this blank.

Deep Talk is a no code AI platform to get value from your unstructured text data.

Deep Talk

When you have a Google Form, whose responses you would like to analyze in Deep Talk, you can use this handy integration to take care of the data import for you. Once active, every newly submitted form will be added automatically to your analysis in Deep Talk. This easily keeps your analysis up-to-date without you having to manually import the data.

Deep Talk + Google Forms

Add new Google Forms responses to an analysis in Deep Talk

Supported triggers and actions

New Form Response

API Request (Beta)

Add Text Document to Analysis

New or Updated Form Response

Evaluate Text Document With Deeper

About Deep Talk

Related categories

About Google Forms

Related categories

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