Methodology
Every estimate should be reproducible, bounded, and honest about missing information.
Platform-specific analysis
We do not apply a universal views-to-money formula. Each analyzer uses inputs relevant to that platform and keeps platform revenue separate from sponsorships and other creator-business income.
YouTube scenarios distinguish long-form and Shorts views. TikTok scenarios account for the share of views that may qualify for a rewards programme. Instagram scenarios model sponsorship activity separately because follower count is not an advertising payout. Twitch scenarios use subscriptions and viewer hours. These inputs are deliberately isolated so that a convenient number from one platform is never silently reused for another.
Ranges and confidence
Results are expressed as low and high scenarios with an arithmetic midpoint. Model evidence ratings are uncalibrated heuristics, not a probability of payment or measured accuracy. Public-profile identity scores are separate from earnings estimates.
A range is a sensitivity test, not a prediction interval. Its lower and upper bounds show what the selected assumptions produce. They do not prove that an account is eligible for monetization, that every view was monetized, or that a platform paid a particular rate.
What the calculator includes
Each result identifies the revenue category it models. Platform advertising remains separate from sponsorships, memberships, affiliate sales, merchandise, licensing, donations, taxes, agency fees, production expenses, and other business income or costs. A combined total is shown only when its component scenarios have usable inputs.
Source hierarchy
User-authorized account analytics would provide the strongest evidence, followed by recent metrics copied by the user from a trusted dashboard, then permitted public platform data. Lifetime views and follower totals are useful context but weak evidence for a current month. Missing inputs remain missing; they are not filled with invented values.
How to reproduce a scenario
Record the platform, measurement period, input values, content-format mix, audience geography, and the result assumptions shown beside the estimate. Re-entering the same inputs into the same model should produce the same range. When comparing two creators, use equivalent periods and source quality.
Verified analytics
Analytics may only be called verified after a creator authorizes an official OAuth connection. SocialRevCounter never requests platform passwords.
Limitations
Public metrics cannot reveal private contracts, invalid-traffic adjustments, revenue shares, demonetized views, country-level playback, seasonal advertiser demand, or whether a creator has accepted a monetization programme. SocialRevCounter therefore describes outputs as scenarios or estimates and never as actual earnings.
For a practical walkthrough, read How creator earnings estimates work and Why views do not equal revenue.
Model rates and reproducible formulas
Model revision: 9 September 2026. These are illustrative planning coefficients retained from the prototype. They have not been calibrated against a representative creator dataset. No platform publishes or endorses these ranges, and linking to platform documentation does not validate them.
Amounts are monthly USD. Each formula is evaluated at the low and high coefficients. The displayed midpoint is their arithmetic average, not the most likely result. Actual receipts can be zero or outside the modeled range.
| Model | Calculation |
|---|---|
| YouTube advertising | Split monthly views into long-form and Shorts using the entered Shorts share. Long-form views ÷ 1,000 × $1.20–$5.50; Shorts views ÷ 1,000 × $0.015–$0.09. Add each endpoint, then apply the audience multiplier. |
| TikTok rewards scenario | Monthly views × qualified share ÷ 1,000 × $0.18–$0.95 × audience multiplier. No qualified views means zero modeled rewards. |
| Instagram sponsorship scenario | Followers ÷ 1,000 × sponsored posts × engagement multiplier × $8–$28. Engagement multiplier = 0.7 + min(1.6, entered engagement percentage ÷ 4). It stops increasing at 6.4% engagement. Zero sponsored posts means zero modeled sponsorships. |
| Facebook video scenario | Monthly views ÷ 1,000 × $0.45–$3.20 × audience multiplier. This simplification does not reproduce an account’s monetization statement. |
| Twitch subscriptions and ads | Paid subscribers × $2–$3.50 assumed monthly creator receipts, plus viewer hours ÷ 1,000 × $0.60–$3.50 assumed advertising receipts. Neither coefficient is a disclosed contract term. |
| X custom scenario | Impressions ÷ 1,000 × your entered low and high rates. No default rate or audience adjustment. This is not a payout model for the current programme. |
Audience location: known value versus unknown
For YouTube, TikTok, and Facebook, the illustrative multiplier is 0.82 + (US audience percentage ÷ 100 × 0.55). An entered 0% uses 0.82; 50% uses 1.095; 100% uses 1.37. This is a sensitivity assumption, not a measured market-price relationship.
When the audience field is blank, the low result uses 0.82 and the high result uses 1.37. We do not invent a share or label it a global average. The internal evidence rating is reduced. Instagram, Twitch, and the custom X scenario do not use this adjustment.
Other starting values and missing evidence
Visible metric fields start at zero for you to replace with known values or deliberate assumptions. Zero is never evidence that the account has no audience or revenue. Form inputs specify Shorts share, qualified share, and engagement directly; callers omitting them receive prototype defaults of 0% Shorts, 35% qualified views, and 0% engagement respectively. Those defaults are assumptions, not recovered metrics.
What the evidence rating means
Ratings are uncalibrated model heuristics. They are not measured accuracy, statistical confidence, or a probability of payment. Baseline internal scores differ by model and do not establish individual account eligibility. Missing audience location caps applicable model scores at 35. Public-profile identity confidence is a separate question from confidence in earnings.
Sources, examples, and model changes
YouTube’s revenue definitions explain the difference between advertiser costs and creator analytics. Our advertising-only coefficients should not be described as YouTube Analytics total RPM. X’s programme announcement prompted removal of the old impressions-based preset on this model revision.
Worked-example cards run through the same calculation engine as submitted scenarios. They are fictional teaching inputs, not a creator research dataset. Formula changes should update the explanation and visible revision date. Existing saved scenarios are recalculated when reopened; obsolete X presets are removed rather than carried forward as current estimates.
Try the format comparison, sponsorship walkthrough, or creator budget.