Methodology: How We Estimate Creator Earnings

Where the data comes from

Two things are worth being upfront about. First, we do not use paid, scraped, or commercially-licensed datasets — every input below is publicly available. Second, and more importantly: we do not research all 1,590 niche/country combinations individually. We set a baseline rate per niche and a multiplier per audience country, then compute the grid from those two inputs. The section below explains exactly what that means.

1. Advertising benchmark studies. Aggregated CPM and eCPM data published in the open by ad-tech platforms and market-research firms. These give us the baseline advertiser demand curve for each niche in the largest audience markets, before any platform revenue-share is applied.
2. Creator income disclosures. Public revenue snapshots that creators themselves share in blog posts, podcast interviews, YouTube “how much I earned” videos, and X/Twitter threads breaking down their own monthly payouts. These are the strongest real-world calibration points, but they carry selection bias (creators who publicly share tend to be doing well), so we cross-reference across many creators before moving a niche baseline.
3. Industry newsletters and creator-economy analyst reports. Free public issues from independent analysts covering monetization trends by niche and platform, seasonal RPM shifts, and policy changes such as YouTube revenue-share updates or TikTok Creator Rewards Program eligibility changes.
4. Platform documentation. YouTube and TikTok's own creator resource pages, Partner Program terms, Help Center payout FAQs, and public policy announcements. This is the authoritative source for revenue-share splits (YouTube 55/45, TikTok Rewards eligibility thresholds), monetization requirements, and platform-level restrictions.

How the grid is actually built

Platforms do not publish per-niche, per-country payout tables, and no public source covers all 1,590 combinations. Rather than invent per-cell research we do not have, we use a transparent two-factor model:

1. A baseline RPM per niche, anchored to a United States audience and derived from the sources above. Niches with similar advertiser economics share a baseline — across our 30 niches there are roughly 14 distinct baseline values, so for example the cooking, beauty, parenting, history, news and politics baselines are identical.
2. A multiplier per audience country, reflecting advertiser demand and consumer purchasing power in that market. Countries at similar income and ad-market maturity share a multiplier — across our 50+ countries there are roughly 21 distinct multipliers, so the United States and Switzerland resolve to the same factor, as do the UK, New Zealand and Sweden.

Every cell is then simply niche baseline × country multiplier. The low–high band is a fixed ratio around that midpoint (the high end is roughly 1.9× the low end), and YouTube Premium is modeled as a further ~15% of the midpoint. This means the figures are internally consistent by construction, and it also means an apparent pattern in the data — for instance that the US-to-Bangladesh gap is about 8.3× in every niche — is a property of the model, not an independent finding about those markets.

We think this is the honest trade-off for a free tool: a transparent model that gets you into the right order of magnitude, rather than the appearance of granular research behind every one of several thousand pages. It also means you should treat the ranking of niches and countries as more meaningful than the precise gap between any two specific cells.

How the YouTube RPM calculator works

We start from an estimated RPM range (revenue per 1,000 views) for your niche and audience country. RPM is already net of YouTube's revenue share — creators keep 55% of ad revenue and YouTube takes 45%. We then apply:

• Video length: videos under 8 minutes earn slightly less (no mid-roll ads); 15+ minute videos add an estimated +30% mid-roll bonus, shown as a separate line so it is never double-counted.
• YouTube Premium revenue is added as a small separate stream.
• Results are shown as a low–high range built from the niche/country RPM band, not a single point estimate.

How the TikTok earnings calculator works

TikTok income is the sum of the streams you select, each modeled separately:

• Creator Rewards Program: a view-based payout, only counted if you meet the eligibility thresholds (10,000+ followers and 100,000+ views in 30 days).
• TikTok Shop: monthly views × an estimated view-to-order conversion rate × average order value × a 5–15% commission, adjusted by niche and audience purchasing power.
• Live gifts: based on live session frequency and a realistic concurrent-viewer estimate capped by your follower base.
• Brand deals: a per-post rate that scales with follower count and niche value, multiplied by your chosen number of deals per month.

Niche matters: commerce-heavy niches like beauty, fashion, and health carry higher TikTok Shop and brand-deal value than entertainment or gaming.

Assumptions & limitations

• These are estimates. Real earnings vary with engagement, watch time, ad quality, seasonality, sell-through, and platform algorithm changes.
• Programmatic pages use representative assumptions (e.g. posting frequency) that you can override in the interactive calculators.
• We deliberately show ranges instead of a single number to reflect real-world variance.
• No personal data is collected — every calculation runs entirely in your browser.

Update cadence

We review and refresh the underlying benchmarks periodically as new creator income data becomes available. This dataset was last updated in July 2026.

Between full refreshes we track major payout changes announced by YouTube and TikTok (revenue-share updates, Creator Rewards formula changes, new eligibility thresholds), advertiser CPM trend reports from ad-tech vendors, and public creator-income disclosures shared on social media, podcasts, and industry newsletters. When a shift is large enough to move a niche baseline or a country multiplier meaningfully, we update that input — which shifts every cell derived from it — rather than waiting for a full cycle.

Why we show ranges, not single numbers

A creator's real earnings for any given month depend on dozens of variables that our calculator cannot see: watch-time retention, ad-blocker penetration in your specific audience, how many mid-rolls the algorithm inserts on any given upload, seasonality (Q4 typically pays 30–50% more than Q1), and the health of the broader ad market. Quoting a single figure would imply a false precision that the data simply does not support.

The low end of each range assumes conservative monetization (lower CPMs within the niche/country band, fewer mid-rolls, modest engagement). The high end assumes a fully-monetized channel firing on all cylinders. Most creators land somewhere in between. If you want a single planning number, use the midpoint of our range and treat anything above as upside.