Getting Started with Scoop for Slack

Installation

For Administrators

  1. Access Scoop Admin Panel

    • Log into your Scoop Analytics account
    • Navigate to Integrations → Slack
  2. Click "Add to Slack"

    ![Screenshot: Add to Slack button in Scoop admin panel]

  3. Authorize Permissions

    • Review the requested permissions
    • Select your Slack workspace
    • Click "Allow" ![Screenshot: Slack OAuth permission screen]
  4. Configure Workspace Mapping

    • Scoop will automatically map your Slack workspace to your Scoop organization
    • Verify the correct datasets are available

For Users

Once your admin has installed Scoop, you're ready to go! No individual setup required.

First Steps

1. Find Scoop in Your Workspace

Scoop appears as a bot in your workspace. You can:

  • Message @Scoop in any channel
  • Send a direct message to Scoop
  • Visit the Scoop App Home

![Screenshot: Scoop bot in Slack workspace member list]

2. Open App Home

Click on Scoop in your workspace members list, then click "Home" tab.

![Screenshot: Scoop App Home showing welcome message and dataset options]

The App Home provides:

  • Quick access to datasets
  • Upload functionality
  • Getting started guides
  • Current session status

3. Select Your First Dataset

Before analyzing data, you need to select a dataset:

In a channel:

@Scoop dataset

In a direct message:

dataset

![Screenshot: Dataset selection dropdown in Slack]

4. Ask Your First Question

Once you've selected a dataset, try these sample queries:

@Scoop show me all the data
@Scoop what are the top 10 records?
@Scoop create a chart of revenue by month
@Scoop what patterns do you see in this data?

Understanding Responses

Private vs. Public Messages

  • In channels: Responses are private (ephemeral) by default
  • Share button: Makes your insight visible to everyone
  • Direct messages: All responses are visible in the DM thread

![Screenshot: Private Scoop response with "Share with Channel" button]

Response Types

Scoop provides different types of responses:

  1. Tables: Formatted data results
  2. Visualizations: Charts and graphs
  3. ML Insights: Pattern discoveries and predictions
  4. Text Summaries: AI-generated explanations

Next Steps