How FaceTube estimates an influencer rate: model and sensitivity

By Mohamed Ismaili · Updated September 1, 2026

Direct answer: The FaceTube model breaks an estimate into scenario base, engagement, deliverables, rights and exclusivity so every assumption remains visible and editable.

Method and assumptions

Each table is generated from an explicit formula. Assumptions are scenario parameters, not observations attributed to the Moroccan market.

Estimate = base scenario × engagement factor × rights factor × deliverables/exclusivity factors

Why this simulation is useful

The informational value comes from the method: make assumptions visible, show how each variable changes the outcome and let readers reproduce the calculation. The goal is not to publish an unverifiable average but to provide a reproducible decision framework.

How to read the results

Never select a row merely because it looks similar to your situation. Replace assumptions with your own data, compare several scenarios and keep room for uncertainty. A simulation is most useful for understanding sensitivity.

What the model cannot know

The model does not know actual audience quality, contract clauses, seasonality, ad mix, retention or advertiser demand. Those factors need separate evaluation.

Practical interpretation

Sensitivity analysis does not seek a single “correct price”; it reveals which assumptions matter most. If the amount changes sharply when the rights factor moves from 1.00 to 1.35, usage rights should become an explicit part of the brief and contract.

Four-step decision process

1) identify the variable you actually know; 2) replace the matching assumption; 3) calculate low, central and high cases; 4) record what remains unknown before deciding. This discipline prevents an educational number from becoming a fake market truth.

Sources and limitations

For platform metric definitions, FaceTube prioritizes official documentation. Tables on this page do not claim proprietary data collection; they are calculated from the published assumptions. See the FaceTube methodology.

Turn the simulation into your own analysis

Export your own data where the platform allows it, select a stable period and record the date. Replace each assumption with an observed or contractual value. If a variable remains unknown, do not hide it: build at least two plausible cases. Analytical quality comes more from this audit trail than from displaying false precision.

Reproducible audit trail

To verify the calculation, record inputs, formula, unit, date and result. Another person should be able to reproduce the same row and obtain the same value. If a platform update changes the result, preserve the old assumption and explain the change rather than erasing the history.