Notion Database Automation with Make

Overview: I helped a client automate the tagging of a massive Notion database—over 4,000 pages, each with 12 multi-select properties. Previously, the client was manually reviewing and tagging each page, a process that was extremely time-consuming. I proposed using Make to automate the workflow, turning a multi-day manual task into a scalable, semi-automated system.

The dataset was larger and more complex than expected. Each page contained unstructured text that needed to be parsed for property tagging.

The client’s Notion entries used inconsistent formatting (e.g., Shift+Enter instead of Enter), which caused initial demo crashes.

Make limitations required careful planning: only 3,200 output bundles per module, dependency on Notion API limits, and the need for fallback “escape routes” for non-compliant entries.

Built a Make scenario that processed database entries while handling variations in structure.

Created fallback paths to flag improperly structured entries, preventing errors in future runs.

Conducted extensive testing, iterating until the automation reliably processed large batches of data.

Designed the workflow to be maintainable, exportable, and easily adjustable for future updates.

Truly understand your dataset before building automation. Assumptions can lead to costly errors.

Always test, test, test, even when it seems like it’s working.

Tools like Make are only as powerful as the APIs they connect to—expect limits and plan around them.

Even a failed demo can reveal unexpected opportunities: the client saw value in my skills and booked 1:1 consulting sessions, showing that failure doesn’t mean lack of impact.

The client gained a scalable automation system for managing their Notion database.

Reduced manual tagging from days/weeks to minutes per batch.

Opened opportunities for consulting and coaching, leveraging expertise in Notion and automation.

Make (Integromat)

Notion API