Influencer Brand Fit Evaluator

What does Influencer Brand Fit Evaluator do?

Influencer Brand Fit Evaluator scores any Instagram or TikTok creator against your own campaign requirements and returns a criterion-by-criterion verdict with written reasoning, summary counts, and an overall fit percentage. You write the criteria in plain English — location history, age range, follower floor, content tone, brand-safety rules — and get back a structured, machine-readable answer for each one.

It evaluates one creator per run. To score a roster, run it once per handle (or in parallel via the API).

Why evaluate influencer brand fit?

• Vet creators before you reach out: Screen a shortlist against your brand guidelines in minutes instead of reading through profiles by hand.
• Make the criteria explicit: Location history, age range, audience size, engagement quality, and tone become named checks with a pass/partial/fail verdict, not a gut call.
• Reduce campaign waste: Catch misaligned creators before a contract, not after the first post.
• Automate the workflow: Pipe fit scores straight into your CRM, n8n workflow, or marketing dashboard through the Apify API.

What data does Influencer Brand Fit Evaluator return?

Field	Type	Description
brandFitId	String	Unique ID for this brand fit analysis
evaluationId	String	ID of the underlying influencer evaluation — reusable in later runs
influencerId	String	Internal identifier for the evaluated creator
handle	String	Creator's social media handle
platform	String	instagram or tiktok
brandName	String	Brand the analysis was run for
fitScore	Number	Overall fit percentage, 0–100
summary	Object	Criteria counts: totalCriteria, metFully, metPartially, notMet, unknown
evaluation	Array	One entry per criterion, each with criterion, fitLevel, and reasoning
processingTimeSecs	Number	How long the analysis took
updatedAt	String	ISO 8601 timestamp of the result

How to evaluate an influencer against your brand criteria

1. Create a free Apify account if you don't have one.
2. Open Influencer Brand Fit Evaluator and click Try for free.
3. Enter your Brand Name and your Brand Fit Criteria — one requirement per line.
4. Enter an Influencer Handle (for example natgeo) and pick the Platform.
5. Click Start, then download the result from the Dataset tab as JSON, CSV, Excel, or HTML.

Already evaluated this creator? Paste the evaluationId from that earlier run instead of the handle — the evaluator reuses the existing profile analysis and skips straight to scoring your criteria.

How much does it cost?

Pay-per-event pricing. You are charged for completed work, not for runtime, and a failed run charges nothing for the analysis.

Two things can be charged in a run:

• Brand fit analysis — charged once, when the analysis completes successfully.
• Influencer evaluation — charged only when you supply a handle with no evaluationId, so a full profile evaluation has to run first. Supply an evaluationId and this is skipped entirely.

Reusing an evaluationId across several sets of criteria is the cheapest way to test different campaign briefs against the same creator. Current per-event prices, including the discounts on paid Apify plans, are on the Pricing tab.

Input

See the Input tab for the full schema. Key fields:

Parameter	Type	Default	Description
brandName	String	required	Your brand or company name (1–100 characters)
criteria	String	required	Your requirements, one per line (10–10,000 characters)
influencerHandle	String	optional	Handle such as natgeo or @natgeo. Required unless evaluationId is given
platform	String	instagram	instagram or tiktok
evaluationId	String	optional	Evaluation ID from an earlier run. Skips re-evaluating the creator

Example input

{
  "brandName": "Nightly Traffic",
  "criteria": "Must have lived in Dallas for >3 years.\nIs younger than 35.\nHas more than 10K followers.",
  "influencerHandle": "natgeo",
  "platform": "instagram"
}

Output

Results are saved to the Dataset tab and download as JSON, CSV, Excel, or HTML.

Each item includes:

• Identity: brandFitId, evaluationId, influencerId, handle, platform, brandName
• Scoring: fitScore, summary counts by fit level
• Detail: evaluation array with the verdict and reasoning for every criterion
• Metadata: processingTimeSecs, updatedAt

Sample output

{
  "brandFitId": "brand_fit_1785937214781563018",
  "evaluationId": "eval_1784682550964999395",
  "influencerId": "natgeo",
  "handle": "natgeo",
  "platform": "instagram",
  "brandName": "Nightly Traffic",
  "fitScore": 33.33,
  "summary": {
    "totalCriteria": 3,
    "metFully": 1,
    "metPartially": 0,
    "notMet": 2,
    "unknown": 0
  },
  "evaluation": [
    {
      "criterion": "Must have lived in Dallas for >3 years.",
      "fitLevel": "not_met",
      "reasoning": "National Geographic is a global media organization headquartered in Washington, D.C. since 1888, rather than an individual person. It has no history of being located in Dallas."
    },
    {
      "criterion": "Is younger than 35.",
      "fitLevel": "not_met",
      "reasoning": "National Geographic is a long-standing corporate brand and scientific institution founded in 1888, over 130 years old."
    },
    {
      "criterion": "Has more than 10K followers.",
      "fitLevel": "met_fully",
      "reasoning": "The National Geographic account significantly exceeds the requirement, currently reaching over 268 million followers worldwide."
    }
  ],
  "processingTimeSecs": 23.48,
  "updatedAt": "2026-08-05T13:40:38.426Z"
}

Tips

• Put one requirement per line. A single criterion bundling three conditions gets one verdict and one score slot, which blurs the result.
• Make criteria checkable from public information. "Has more than 10K followers" scores cleanly; "would enjoy our product" comes back as unknown.
• Save the evaluationId from each run. Reusing it to test another set of criteria against the same creator is both faster and cheaper.
• unknown means the evidence wasn't there, not that the creator failed. It scores as zero, so several unknown verdicts drag the percentage down — read the reasoning before rejecting anyone.

FAQ

How is the fit score calculated?

Each criterion is worth a share of the total: met_fully counts as 1, met_partially as 0.5, and not_met and unknown as 0. The score is the sum of those points divided by totalCriteria, times 100. Three criteria scored one met_fully and two not_met gives 33.33%.

Can I evaluate TikTok creators as well as Instagram?

Yes. Set platform to instagram or tiktok.

Can I score several influencers at once?

Each run evaluates one creator. Start one run per handle — through the API tab or a scheduled task — and the results collect in separate datasets.

What does evaluationId actually save me?

The creator's profile evaluation is the expensive half of the work. Once it exists, any number of different brand criteria can be scored against it without redoing it, so pass the ID back in for follow-up runs.

Is this legal?

The evaluator only uses publicly available profile and content information. Check the platform's Terms of Service and make sure you have a legitimate purpose for the analysis.

Support

• Bugs / feature requests → Issues tab
• Programmatic access → API tab

Disclaimer: Our Actors are ethical and do not extract any private user data, such as email addresses, gender, or location. They only extract what the user has chosen to share publicly. We therefore believe that our Actors, when used for ethical purposes by Apify users, are safe. However, you should be aware that your results could contain personal data. Personal data is protected by the GDPR in the European Union and by other regulations around the world. You should not scrape personal data unless you have a legitimate reason to do so. If you're unsure whether your reason is legitimate, consult your lawyers.