Recipe: Scheduled reports and readouts
1min read
TL;DR: On a schedule, this playbook queries your data source, summarizes the results into a readout, and delivers it to Slack or email. Trigger is a schedule (e.g. weekday mornings); outputs are a formatted summary and optional chart link.
Who this is for
Data, analytics, and ops teams that send recurring metrics readouts by hand.
What you'll need
- Connectors: BigQuery (or your warehouse/HTTP data API), Slack and/or email.
- Secrets: Warehouse/API credentials, Slack token or email API key.
- Trigger: Schedule (cron) for the cadence you want.
How to build it with Ask Ballet
- Open the Console on Home.
- Paste the prompt below; set your query, cadence, and recipients.
- Review the plan and confirm.
- Connect the data source and Slack/email, then set the schedule.
Build a playbook that runs every weekday at 8am. Query BigQuery for yesterday's key
metrics (signups, active users, revenue) and the week-over-week change. Summarize the
results in a short readout with the top movers and any anomalies. Post the summary to
#daily-metrics in Slack and email it to the leadership list. Include a link to the
dashboard.
What the playbook does
- Schedule trigger — runs on the configured cron.
- HTTP/Code step (query) — runs the query against the warehouse.
- Code step (summarize) — computes deltas and writes the readout.
- HTTP step (deliver) — posts to Slack and/or sends the email.
Variations and tips
- Start with a manual run to validate the query and formatting before scheduling.
- Keep heavy aggregation in the warehouse query; use the Code step for formatting.
- Feed clean tables from Data sync and ETL so reports stay reliable.