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Overview

Slack is a great channel to share reports and alerts. With Python and AI, creating a Slackbot catered to your specific needs has never been easier.

Here are some examples of alerts and reports you may want to create:

• Automated alerts based on a certain metric threshold. For example if your weekly active users drop by a certain percentage.
• Weekly marketing pipeline reports
• Lists of self-service onboarded users in the past 24 hours

Your options are limitless and fully customizable to your needs.

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Step-by-step guide to creating a Slackbot

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Step 1: Creating a Slack app and token

To create these alerts and scheduled Slack reports, we’re going to create a custom Slack app. Start by navigating to the Slack app API page and click Create New App.

Follow these steps:

1. Opt in to Create from scratch
2. Provide a name and the workspace you want the app to be added to
3. Click Create App

Once your app is create, on the left hand side, select OAuth & Permissions, then follow these steps:

1. Under Scope and Bot Token Scopes click Add an OAuth Scope. If the bot is going to send messages to Slack, make sure you select the chat:write.public scope. This scope allows the app to write to publich channels they’re not a part of. If you need to add the app to private channels or chats, you will need to select additional scopes.
2. Under OAuth Tokens on that same page, click Install to your_workspace
3. Once the app is invited to your workspace, take note of the token. Your token should start with xoxb-. If it doesn’t, you may not have generated a bot token

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Step 2: Configuring your Slack message

Now that you have your Slack bot token, we can configure the message you want to send to Slack.

Start by querying your data and storing the data you want to share as a Python DataFrame string or image. Then follow these steps:

1. Insert a new cell in your Smartbook or workflow and select Slack Send
2. Add your bot token to the Token input
3. Compose your message and insert Python variables using {{your_dataframe}}

Here’s an example message using two DataFrames and an image:

Latest marketing campaign performance summary:
{{ai_marketing_campaign_summary}}

Here are the top users in terms of increased widget creation:
{{top_increases}}

Here are the top users in terms of decreased widget creation:
{{top_decreases}}

Users created by month:
{{fig}}

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Step 3: Scheduling your updates

Once you’ve created your Slack cell with the message you want to send and verified that it works, you can now schedule your app to run at whatever cadence you would like.

Scheduling your bot to run is the same as scheduling a report. Check out our page on scheduling to learn more.