Which faceless, automatable content niche to start next — measured with free data, re-scored on every workflow run. loading…
Click a row to see how its score was calculated. Click a header to sort.
Select a niche in the table.
Hollow points: money estimate still pending (weight 1.0). Opportunity on a log scale.
Wikipedia human pageviews, 12-month rolling average, first window = 100.
5-year weekly series. YoY = mean of last 52 weeks ÷ previous 52, from the keyword queried on its own. Level compares it with a shared anchor keyword.
Top 5 rising queries per niche over the last 12 months ("Breakout" = growth over 5,000%).
Videos published in the last 90 days vs the same 90 days a year earlier. Counts are Google's estimates; views from the top 50 results.
Subscribers and posting rate from the 100 newest posts.
Every request that failed. Its value is left blank in the scores, never set to zero.
RPM/CPM ranges from at least two cited sources per niche. These are estimates, not measured data.
Demand divided by competition is the core of keyword opportunity scores such as the Keyword Effectiveness Index. The target is the high-demand, low-supply quadrant from Parrot Analytics' demand vs supply matrix. The √P_d term damps tiny niches: with no demand there is no opportunity, however low the competition.
YouTube totalResults is an estimate, and YouTube stands in for still-image platforms that have no free count API.
Wikipedia pageviews track search interest but weight broad topics heavily.
Google Trends is read through pytrends, which is archived and often rate-limited.
Reddit gives a single snapshot, so posting rate but not its growth.