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Google Cloud Natural Language and Mattermost integration
Save yourself the work of writing custom integrations for Google Cloud Natural Language and Mattermost and use n8n instead. Build adaptable and scalable Analytics, and Communication workflows that work with your technology stack. All within a building experience you will love.
How to connect Google Cloud Natural Language and Mattermost
- Step 1: Create a new workflow
- Step 2: Add and configure nodes
- Step 3: Connect
- Step 4: Customize and extend your integration
- Step 5: Test and activate your workflow
Step 1: Create a new workflow and add the first step
In n8n, click the "Add workflow" button in the Workflows tab to create a new workflow. Add the starting point – a trigger on when your workflow should run: an app event, a schedule, a webhook call, another workflow, an AI chat, or a manual trigger. Sometimes, the HTTP Request node might already serve as your starting point.
Step 2: Add and configure Google Cloud Natural Language and Mattermost nodes
You can find Google Cloud Natural Language and Mattermost in the nodes panel. Drag them onto your workflow canvas, selecting their actions. Click each node, choose a credential, and authenticate to grant n8n access. Configure Google Cloud Natural Language and Mattermost nodes one by one: input data on the left, parameters in the middle, and output data on the right.
Step 3: Connect Google Cloud Natural Language and Mattermost
A connection establishes a link between Google Cloud Natural Language and Mattermost (or vice versa) to route data through the workflow. Data flows from the output of one node to the input of another. You can have single or multiple connections for each node.
Step 4: Customize and extend your Google Cloud Natural Language and Mattermost integration
Use n8n's core nodes such as If, Split Out, Merge, and others to transform and manipulate data. Write custom JavaScript or Python in the Code node and run it as a step in your workflow. Connect Google Cloud Natural Language and Mattermost with any of n8n’s 1000+ integrations, and incorporate advanced AI logic into your workflows.
Step 5: Test and activate your Google Cloud Natural Language and Mattermost workflow
Save and run the workflow to see if everything works as expected. Based on your configuration, data should flow from Google Cloud Natural Language to Mattermost or vice versa. Easily debug your workflow: you can check past executions to isolate and fix the mistake. Once you've tested everything, make sure to save your workflow and activate it.
Analyze feedback and send a message on Mattermost
This workflow analyzes the sentiments of the feedback provided by users and sends them to a Mattermost channel.
Typeform Trigger node: Whenever a user submits a response to the Typeform, the Typeform Trigger node will trigger the workflow. The node returns the response that the user has submitted in the form.
Google Cloud Natural Language node: This node analyses the sentiment of the response the user has provided and gives a score.
IF node: The IF node uses the score provided by the Google Cloud Natural Language node and checks if the score is negative (smaller than 0). If the score is negative we get the result as True, otherwise False.
Mattermost node: If the score is negative, the IF node returns true and the true branch of the IF node is executed. We connect the Mattermost node with the true branch of the IF node. Whenever the score of the sentiment analysis is negative, the node gets executed and a message is posted on a channel in Mattermost.
NoOp: This node here is optional, as the absence of this node won't make a difference to the functioning of the workflow.
This workflow can be used by Product Managers to analyze the feedback of the product. The workflow can also be used by HR to analyze employee feedback. You can even use this node for sentiment analysis of Tweets.
To perform a sentiment analysis of Tweets, replace the Typeform Trigger node with the Twitter node.
Note: You will need a Trigger node or Start node to start the workflow.
Instead of posting a message on Mattermost, you can save the results in a database or a Google Sheet, or Airtable. Replace the Mattermost node with (or add after the Mattermost node) the node of your choice to add the result to your database.
You can learn to build this workflow on the documentation page of the Google Cloud Natural Language node.
Nodes used in this workflow
Popular Google Cloud Natural Language and Mattermost workflows
Analyze feedback and send a message on Mattermost
This workflow analyzes the sentiments of the feedback provided by users and sends them to a Mattermost channel.
Typeform Trigger node: Whenever a user submits a response to the Typeform, the Typeform Trigger node will trigger the workflow. The node returns the response that the user has submitted in the form.
Google Cloud Natural Language node: This node analyses the sentiment of the response the user has provided and gives a score.
IF node: The IF node uses the score provided by the Google Cloud Natural Language node and checks if the score is negative (smaller than 0). If the score is negative we get the result as True, otherwise False.
Mattermost node: If the score is negative, the IF node returns true and the true branch of the IF node is executed. We connect the Mattermost node with the true branch of the IF node. Whenever the score of the sentiment analysis is negative, the node gets executed and a message is posted on a channel in Mattermost.
NoOp: This node here is optional, as the absence of this node won't make a difference to the functioning of the workflow.
This workflow can be used by Product Managers to analyze the feedback of the product. The workflow can also be used by HR to analyze employee feedback. You can even use this node for sentiment analysis of Tweets.
To perform a sentiment analysis of Tweets, replace the Typeform Trigger node with the Twitter node.
Note:* You will need a Trigger node or Start node to start the workflow.
Instead of posting a message on Mattermost, you can save the results in a database or a Google Sheet, or Airtable. Replace the Mattermost node with (or add after the Mattermost node) the node of your choice to add the result to your database.
You can learn to build this workflow on the documentation page of the Google Cloud Natural Language node.
Build your own Google Cloud Natural Language and Mattermost integration
Create custom Google Cloud Natural Language and Mattermost workflows by choosing triggers and actions. Nodes come with global operations and settings, as well as app-specific parameters that can be configured. You can also use the HTTP Request node to query data from any app or service with a REST API.
Google Cloud Natural Language and Mattermost integration details
Other integrations with Google Cloud Natural Language
Other integrations with Mattermost
Google Cloud Natural Language and Mattermost integration tutorials
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FAQs
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