Follower count is a weak first filter. Creator fit depends on the audience, content, market, execution, and evidence you can inspect before contracting.
Score the work, not the popularity
Use a 0–2 rating for each dimension: 0 = mismatch or no evidence; 1 = plausible but unverified; 2 = supported by a relevant sample. Weight the dimensions according to the campaign’s job; do not present the total as a universal prediction.
| Dimension | What to inspect before outreach |
|---|---|
| Audience fit | Recent audience examples relevant to the target country and buyer task |
| Content fit | Whether the creator can explain or demonstrate the product naturally |
| Market fit | Language/register, location relevance, and any delivery or service constraints |
| Execution fit | Format, turnaround, revisions, and production expectations |
| Evidence quality | What analytics or past-work evidence is actually available, and its limits |
Separate a real evidence gap from a low score. A creator who does not share private audience data may still be a fit; record the unknown instead of inventing an estimate.
Example decision
A creator with a smaller but locally relevant audience may merit a test against a larger account whose geography is unclear. Ask both for the same decision-useful evidence, such as anonymized audience geography and recent format performance. Do not use screenshots without checking date range, metric definition, and whether paid distribution was included.
Before agreement, confirm the deliverable, disclosure, usage rights, approval steps, payment, and what happens if the post is delayed. Verify current country and platform requirements with official sources and qualified counsel where needed; this scorecard is not a permit check.
Optional AI-assisted work brief — Creator fit scorecard
Score shortlisted creators on audience-market fit, topic credibility, content quality, comment relevance, brand safety, delivery reliability, and rights clarity. Define evidence and weights before reviewing names, then run sensitivity checks so one subjective score cannot dominate. Treat follower count as context, not proof of reach or sales. Mark unknowns instead of filling them with guesses.
Creator shortlist scorecard
Audience fit
Does the creator reach the market and eligible audience the service can actually serve?
Credibility
Does their content demonstrate the topic, or only mention it?
Conversation
Are comments relevant questions and responses, not merely a large count?
Execution
Check past delivery, disclosure, and rights clarity. Mark missing evidence unknown.
Decision
Set weights before scoring; compare fit and risk separately from follower count.
Worked example — Do not let follower count win the shortlist
Creator A has a large following but most visible comments come from outside the service market; Creator B has a smaller relevant audience and demonstrates the task credibly. The scorecard should reveal that trade-off rather than bury it in one total. Keep market fit, content proof, safety, and commercial terms visible as separate dimensions, and verify audience data before contracting.
AI disclosure: AI tools assisted with drafting. The scoring scale is a planning aid, not a validated performance model.