How to connect Sentiment Analysis and Slack

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.

Sentiment Analysis and Slack integration: Create a new workflow and add the first step

Step 2: Add and configure Sentiment Analysis and Slack nodes

You can find Sentiment Analysis and Slack 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 Sentiment Analysis and Slack nodes one by one: input data on the left, parameters in the middle, and output data on the right.

Sentiment Analysis and Slack integration: Add and configure Sentiment Analysis and Slack nodes

Step 3: Connect Sentiment Analysis and Slack

A connection establishes a link between Sentiment Analysis and Slack (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.

Sentiment Analysis and Slack integration: Connect Sentiment Analysis and Slack

Step 4: Customize and extend your Sentiment Analysis and Slack 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 Sentiment Analysis and Slack with any of n8n’s 1000+ integrations, and incorporate advanced AI logic into your workflows.

Sentiment Analysis and Slack integration: Customize and extend your Sentiment Analysis and Slack integration

Step 5: Test and activate your Sentiment Analysis and Slack workflow

Save and run the workflow to see if everything works as expected. Based on your configuration, data should flow from Sentiment Analysis to Slack 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.

Sentiment Analysis and Slack integration: Test and activate your Sentiment Analysis and Slack workflow

Automate Customer Support Issue Resolution using AI Text Classifier

This n8n template is designed to assist and improve customer support team member capacity by automating the resolution of long-lived and forgotten JIRA issues.

How it works

Schedule Trigger runs daily to check for long-lived unresolved issues and imports them into the workflow.
Each Issue is handled as a separate subworkflow by using an execute workflow node. This allows parallel processing.
A report is generated from the issue using its comment history allowing the issue to be classified by AI - determining the state and progress of the issue.
If determined to be resolved, sentiment analysis is performed to track customer satisfaction. If negative, a slack message is sent to escalate, otherwise the issue is closed automatically.
If no response has been initiated, an AI agent will attempt to search and resolve the issue itself using similar resolved issues or from the notion database. If a solution is found, it is posted to the issue and closed.
If the issue is blocked and waiting for responses, then a reminder message is added.

How to use

This template searches for JIRA issues which are older than 7 days which are not in the "Done" status. Ensure there are some issues that meet this criteria otherwise adjust the search query to suit.
Works best if you frequently have long-lived issues that need resolving.
Ensure the notion tool is configured as to not read documents you didn't intend it to ie. private and/or internal documentation.

Requirements

JIRA for issues management
OpenAI for LLM
Slack for notifications

Customising this workflow

Why not try classifying issues as they are created? One use-case may be for quality control such as ensuring reporting criteria is adhered to, summarising and rephrasing issue for easier reading or adjusting priority.

Nodes used in this workflow

Popular Sentiment Analysis and Slack workflows

Automate Customer Support Issue Resolution using AI Text Classifier

This n8n template is designed to assist and improve customer support team member capacity by automating the resolution of long-lived and forgotten JIRA issues. How it works Schedule Trigger runs daily to check for long-lived unresolved issues and imports them into the workflow. Each Issue is handled as a separate subworkflow by using an execute workflow node. This allows parallel processing. A report is generated from the issue using its comment history allowing the issue to be classified by AI - determining the state and progress of the issue. If determined to be resolved, sentiment analysis is performed to track customer satisfaction. If negative, a slack message is sent to escalate, otherwise the issue is closed automatically. If no response has been initiated, an AI agent will attempt to search and resolve the issue itself using similar resolved issues or from the notion database. If a solution is found, it is posted to the issue and closed. If the issue is blocked and waiting for responses, then a reminder message is added. How to use This template searches for JIRA issues which are older than 7 days which are not in the "Done" status. Ensure there are some issues that meet this criteria otherwise adjust the search query to suit. Works best if you frequently have long-lived issues that need resolving. Ensure the notion tool is configured as to not read documents you didn't intend it to ie. private and/or internal documentation. Requirements JIRA for issues management OpenAI for LLM Slack for notifications Customising this workflow Why not try classifying issues as they are created? One use-case may be for quality control such as ensuring reporting criteria is adhered to, summarising and rephrasing issue for easier reading or adjusting priority.

Build your own Sentiment Analysis and Slack integration

Create custom Sentiment Analysis and Slack 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.