A defensible, sourced formula for pricing any creator deal on any platform. Open methodology. Anyone with the same inputs gets the same answer.
A brand asks "what's your rate." A creator picks a number that feels right. The brand counters. They meet in the middle. Nobody knows if the deal was fair.
OCRS replaces the guessing game with math anyone can audit. Five multipliers. Every input publicly measurable. Every coefficient sourced from industry benchmarks. Every output shipped with a confidence range.
The OCRS fair rate equals Base Media Value (BMV) multiplied by Content Multiplier (CM) multiplied by Rights Multiplier (RM) multiplied by Quality Adjustment (QA) multiplied by Market Adjustment (MA).
Each component answers one plain question. None of them require proprietary data — every input is measurable from public profile metrics and deal terms.
What is this audience worth?
Bayesian-shrunk median views × platform CPM. Small samples are pulled toward the category prior so a single viral post can't fake market value.
How much work went into the post?
Length × production × concept × deliverable count. Captures cinematic mini-films, scripted skits, and bundled cut-downs — not just the raw clip.
What can you do with the content?
Organic only is the floor. Whitelisting, 6-/12-month paid rights, category exclusivity, and perpetual usage stack on top — every line item priced.
Is this audience real and engaged?
Engagement vs. niche benchmark, clipped 0.7×–1.5×. Authenticity and consistency factors plug in from time-series data in v1.1.
When and where is it running?
Geo tier × niche demand × seasonality. A Q4 finance deal in the US prices very differently from a Q1 gaming deal in SEA.
Every coefficient OCRS uses, exposed in full. Sourced from Influencer Marketing Hub, IAB, eMarketer, and the OCRS validation study. Updated annually.
Drives BMV — Base Media Value
| Platform | CPM | Category prior (views) |
|---|---|---|
| TikTok | $9 | 50,000 |
| Instagram Reels | $15 | 15,000 |
| YouTube Shorts | $12 | 25,000 |
| YouTube Long-form | $35 | 8,000 |
ER benchmark drives QA factor; MA multiplier drives Market Adjustment
| Niche | ER benchmark | MA multiplier |
|---|---|---|
| Beauty | 4.0% | 1.20 |
| Fashion | 3.5% | 1.10 |
| Fitness | 5.0% | 0.95 |
| Food | 5.5% | 0.90 |
| Finance | 3.0% | 1.40 |
| Tech | 3.0% | 1.30 |
| Gaming | 4.5% | 0.85 |
| Lifestyle | 4.0% | 1.00 |
| Parenting | 5.0% | 1.05 |
| Travel | 4.0% | 0.95 |
| Business | 2.8% | 1.30 |
Tier 1 = full rate; tiers 2–4 discount by purchasing power
| Tier | Multiplier |
|---|---|
| Tier 1 (US, UK, AU, DE, FR, JP) | 1.00 |
| Tier 2 (CA, IT, ES, KR, BR) | 0.85 |
| Tier 3 (MX, IN, SEA) | 0.60 |
| Tier 4 (emerging markets) | 0.40 |
Brand spend skews toward Q4 holiday push; Q1 is the floor
| Quarter | Multiplier |
|---|---|
| Q1 (Jan–Mar) | 0.85 |
| Q2 (Apr–Jun) | 0.95 |
| Q3 (Jul–Sep) | 1.00 |
| Q4 (Oct–Dec) | 1.25 |
Longer formats command higher rates per delivered post
| Length | Multiplier |
|---|---|
| Under 15s | 0.80 |
| 15–30s | 1.00 |
| 30–60s | 1.20 |
| 1–3 min | 1.50 |
| 3–10 min | 2.00 |
| Over 10 min | 3.00 |
Add 0.5 for 3mo category exclusivity, 1.0 for 6mo, 1.0 for perpetual
| Tier | Multiplier |
|---|---|
| Organic only | 1.00 |
| Whitelisting / dark posts (90d) | 1.50 |
| Paid media rights (6 months) | 2.00 |
| Paid media rights (12 months) | 2.50 |
Recent posts, not lifetime average
Likes + comments ÷ views × 100
How many recent posts back the median above. More posts = OCRS trusts your data more (less pulled toward the platform prior).
+0.15 each, capped at +0.5
Cut-downs, edits, variants
USD. Leave blank to skip.
OCRS v1.0 — Authenticity and consistency factors default to 1.0 until v1.1 wires the time-series pipeline.
OCRS is an open methodology for pricing creator deals. Fair Rate = BMV × CM × RM × QA × MA — five multipliers covering audience value, content effort, usage rights, audience quality, and market context. Every coefficient is sourced from public benchmarks (Influencer Marketing Hub, IAB, eMarketer). Every input is publicly measurable. Anyone with the same inputs gets the same answer.
No. OCRS is an open standard for pricing — it ships independently of any platform. CreatorScore publishes and maintains v1.0, but the methodology, formula, and coefficients belong to the industry. Any tool, agency, or marketplace can implement OCRS without integrating CreatorScore. The trust score and OCRS are deliberately decoupled.
Most rate calculators output a single number with no sourcing. OCRS outputs a fair rate plus a confidence band (±15% baseline, widening to ±25% or ±40% on small samples). It explicitly prices rights, exclusivity, and production effort line-by-line. And it documents every coefficient, so brands can defend the number to finance and creators can negotiate from a sourced position.
Fair Rate = BMV × CM × RM × QA × MA. BMV (Base Media Value) is Bayesian-shrunk median views × platform CPM. CM (Content Multiplier) is length × production × concept × deliverable count. RM (Rights Multiplier) prices usage tiers and exclusivity. QA (Quality Adjustment) compares engagement to niche benchmark. MA (Market Adjustment) is geo × niche × season. Each piece is independently auditable.
Creator data is noisy. A single viral post can fake market value if you average a small sample. OCRS applies Bayesian shrinkage to median views (pulling small samples toward the category prior) and reports a confidence band that widens as sample size shrinks. Below 30 posts the band is ±25%; below 10 posts it's ±40%.
Authenticity and consistency factors require time-series data (posting cadence, follower growth shape, engagement stability) that not every public profile exposes consistently. v1.0 defaults both to 1.0. v1.1 will compute them from the ScrapeCreators historical data pipeline. The fair rate in v1.0 is therefore a slightly conservative estimate — premium creators with high consistency will see lifts in v1.1.
Yes. The methodology is open. Implement it in your CRM, marketplace, agency pricing sheet, or rate card software. The full PDF documents every coefficient and edge case. If you submit deals to the validation study, you're directly improving the v1.1 coefficients for everyone.
Anonymous deal submissions (platform, niche, geo, season, deliverable, rights, and what was actually paid) train the v1.1 coefficients. Submissions are write-only — no submitter can read others' data. We publish aggregated learnings in the next version of the methodology PDF.