YouTube Keyword Search Tool.
Automated weekly YouTube keyword tracking with derived growth metrics — built without writing a line of backend code.
There's no good way to track what creators are making around a keyword over time.
YouTube search shows you what's popular right now, not what's been uploaded recently or how specific content is trending over weeks. For brands, music managers, analysts, and creators trying to understand a niche, there was no tool that combined keyword tracking, content filtering, and longitudinal performance data in one place.
A self-updating keyword database with growth metrics baked in.
YKST runs every Sunday via Make.com — querying YouTube for new uploads matching specified keywords, filtering out Shorts, non-English content, and irrelevant results, then adding the survivors to an Airtable database. At 7, 14, 30, and 60 days, it re-fetches view and subscriber counts for each video and calculates derived metrics: week-over-week growth, likes-per-view, and breakout indicators.
Automated ingestion
Weekly Make.com automation handles search, filtering, and database updates with no manual intervention required.
Longitudinal tracking
View, like, and subscriber snapshots at 7, 14, 30, and 60 days turn a single data point into a growth curve.
Derived metrics
Week-over-week growth, likes-per-view, and breakout flags calculated automatically — the insights, not just the raw numbers.
How it came together
- 01
Defined the use case
Identified the core need: track what creators are uploading around specific keywords and how those videos perform over time.
- 02
Built the ingestion pipeline
Designed a Make.com scenario that queries the YouTube Data API, applies content filters, and writes matching videos to Airtable.
- 03
Added longitudinal snapshots
Built a second automation to re-fetch performance data at 7, 14, 30, and 60 days and log each snapshot as a separate record.
- 04
Calculated derived metrics
Set up Airtable formulas to calculate week-over-week growth, likes-per-view ratio, and breakout flags from the raw snapshot data.
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