Reading data from Notion
Reading data from the warehouse
Read modeled data from the warehouse, which joins data from Stripe, application database and product analytics.
I recommend modeling the data in a separate workflow, ideally using dbt. The
Updating Notion
Update existing entries with revenue and engagement data
DataFrame SQL makes it easy to join data from Notion with data from your warehouse
Add new customers
Add customers who self-served, that you haven't talked to yet
Flag teams with high engagement
You may want to continue here by creating some segments based on your data, to surface which teams have recently started hitting the limits of the free tier, or just ramped up their usage.
The flow is pretty similar – query the warehouse to identify the right teams, join it with the Notion data, then update the Status column.
Schedule it
When you make all this work, it's time to Schedule the notebook on a regular basis. Since you'll be relying on it for weeks to come, make sure to set up email alerts in case it fails.
You can also embed a little note in your CRM to know the last time the notebook successfully ran.