Playbooks

• “Were there any large changes in sales numbers yesterday?”
• “Send me a daily report on product usage from the past 24 hours”
• “Run our forecasting model every time the S&P drops 1% in an hour — notify me and send back a report on our exposure”

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Overview

• Data Sources — Connect to your organization’s databases and data warehouses
• Analysis Logic — Define questions, queries, and analytical processes in natural language
• Scheduling — Set up automated runs on daily, weekly, monthly, or custom cron schedules
• Delivery — Send results to Slack channels, email recipients, or other destinations

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Getting Started

1

Create your first Playbook

Navigate to the Playbooks section in your TextQL dashboard and click Create New Playbook.

• Write your analysis — Use plain English to describe what you want to analyze. Be specific about metrics, time periods, and filters
• Attach datasets — Attach relevant datasets if you know which ones to use
• Preview and test — Run a preview to see sample results and refine until the output matches your expectations

2

Configure scheduling

• Scheduled — Set up recurring runs. Choose daily, weekly, or monthly, and set an execution time aligned with when your source data updates
• Manual — On-demand execution only
• Custom — Advanced users can use cron expressions for complex schedules

Time and Day

Run on a fixed schedule, such as every weekday at 9:00 AM or every Monday at 3:00 PM

Custom

Run on a custom or irregular schedule using cron expressions

3

Set up delivery

• Slack — Select target channels and tag specific users. Recipients can ask Ana follow-up questions directly in the thread
• Email — Add recipient email addresses. Emails include formatted reports with charts and tables

4

Deploy and monitor

Review all settings, then click Deploy to activate scheduled execution. From the Playbooks dashboard you can:

• Monitor execution history and success/failure rates
• Update analysis logic, recipient lists, or schedules at any time

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Slack Integration

• Channel Delivery — Send results to any Slack channel where the TextQL bot is present
• User Tagging — Notify specific team members about important insights
• Rich Formatting — Results include charts, tables, and formatted text
• Threaded Conversations — Keep discussions organized with threaded responses
• Context Playbooks — Associate playbooks with specific Slack channels for contextual analysis

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Best Practices

• Be specific about what you want to analyze
• Include context like time periods, filters, and business logic
• Reference specific metrics and KPIs by name
• Test with various scenarios before deploying

• Choose appropriate channels for different types of analysis
• Target the right stakeholders for each insight
• Keep recipient lists updated as teams change

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Troubleshooting

• Failed Executions — Check data source connectivity and query syntax
• Delivery Problems — Verify Slack bot permissions and email addresses
• Performance Issues — Simplify complex queries or adjust data ranges