How to Use This Tool
Channel Concentration data boundary: this page calculates leading-channel share from manually entered observations; it is not a live trending-keyword feed. When a field comes from Google Trends, its 0–100 value is normalized relative interest for the Channel Concentration comparison, not monthly search volume.
To reproduce a Channel Concentration result, preserve the country, YouTube Search property, time window, query spelling and capture date. Mixing worldwide Web Search with a United States YouTube Search snapshot changes the population behind leading-channel share and invalidates the Channel Concentration comparison.
Spot result pages where one publisher controls many visible positions. Counting unique competitors can hide that one channel occupies many of the most visible results.
Why Channel Concentration needs more than a raw total
The leading-channel share exposes concentration without pretending to measure every result or recommendation surface. For this page, the useful comparison is leading-channel share, not whichever input happens to be largest. The Channel Concentration result answers the decision in the heading and should not be reused as a score for a different workflow.
The exact Channel Concentration formula
Leading-channel share equals results from the most frequent channel divided by sampled results, multiplied by 100. The visible fields are Results from leading channel and Results sampled. For Channel Concentration, read each printed unit before entry and make the values describe one transaction, cohort or reporting window. If those scopes differ, the displayed leading-channel share may be arithmetically valid but operationally meaningless.
Interpreting leading-channel share
Record rank positions as well as counts and compare multiple sessions before deciding a query is dominated. The ten-percent comparison is deliberately narrow: it tests the influence of results from leading channel and is neither a forecast nor a confidence interval. Preserve the values used, their dates and the resulting decision so a later reviewer can reproduce why Channel Concentration supported the choice.
What this Channel Concentration model leaves out
The sample is personalized and position-blind; identical shares can represent very different ranking layouts. That is where Channel Concentration stops being trustworthy. If an excluded factor could reverse leading-channel share, extend the model explicitly or use the authoritative account system instead of hiding the factor inside an unexplained adjustment.
Evidence and independent verification
The reference reviewed for Channel Concentration is YouTube Help — How YouTube search works. YouTube Help — How YouTube search works supports the named definition or rule but does not supply private values for leading-channel share. Before acting on the result, reconcile the worked example with the relevant dashboard, invoice, export or measurement.
Private, reproducible calculation
Channel Concentration runs its arithmetic in the current browser tab and requests no login or API key. That keeps the Channel Concentration inputs away from the site's calculation server, while leaving the user responsible for detecting stale data or a changed platform rule. When an assumption changes, reopen YouTube Help — How YouTube search works and rerun the saved Channel Concentration scenario.
Sources & assumptions
Tool Spec v2 · verified 2026-08-22. Platform rules and fees can change; the editable inputs remain authoritative for your account.
Official references
- YouTube Help — How YouTube search works (checked 2026-08-22)
Model assumptions
- Inputs are manually copied from the same market, date range and reporting scope.
- The sample is personalized and position-blind; identical shares can represent very different ranking layouts.
- Google Trends values are relative 0–100 interest indices, not absolute search volumes.
- The page does not query YouTube, Google Trends, a creator account or a third-party keyword database.
