Deep Influencer Analyzer Actor
Pricing
from $0.01 / 1,000 results
Deep Influencer Analyzer Actor
Deep analysis of influencers for partnership evaluation, including audience quality assessment, engagement authenticity detection, content style analysis, brand safety scoring, growth trend analysis, etc. Audience Quality Engagement Content Style Brand Safety Growth Trends Partnership Eval
Pricing
from $0.01 / 1,000 results
Rating
0.0
(0)
Developer
The Howlers
Maintained by CommunityActor stats
2
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18
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0
Monthly active users
2 days ago
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Influencer Analyzer
Scores influencers for partnership fit from real profile metrics and recent posts: audience quality signals, engagement authenticity, content stats, brand safety (caption keyword scan) and an overall partnership potential. Optional AI content assessment with your own OpenAI or Anthropic key.
Important: where the data comes from
This actor does not scrape Instagram, TikTok, YouTube, LinkedIn or X itself. It analyzes data you give it:
- Per influencer in the input:
followers,following,postsCountandposts(recent posts withcaption,likes,comments, and optionallyurl,timestamp,type), or - A discovery dataset (
discoveryDatasetId) whose items already carry real metrics, for example from the influencer-discovery actor run with demo mode off.
If an influencer has no usable data, the actor writes an error row (status: "error", errorCode: "NO_PROFILE_DATA") explaining what to supply, and does not charge for it. It never fills in placeholder numbers. Items that came from a demo-mode discovery run are skipped the same way (errorCode: "SAMPLE_SOURCE_DATA").
Any score the supplied data cannot support is returned as null and listed in unavailableFields.
Quick start
Real analysis with supplied data
{"influencers": [{"platform": "instagram","username": "some_creator","followers": 12000,"following": 800,"postsCount": 300,"posts": [{ "caption": "New drop #style link in bio", "likes": 400, "comments": 20 },{ "caption": "Morning run", "likes": 350, "comments": 15 },{ "caption": "Giveaway time #giveaway", "likes": 900, "comments": 120 }]}],"analysisModules": ["audienceQuality", "engagementAuthenticity", "contentStyle", "brandSafety"]}
Preview the output format (demo mode)
Set "demoMode": true. Every row is labeled isSampleData: true with random numbers that do not describe the real account. Demo rows are not charged.
What each module needs
| Module | Needs | Output |
|---|---|---|
audienceQuality | followers and following | Heuristic score from follower/following ratio and post count |
engagementAuthenticity | 3 or more posts with likes/comments | Like-to-comment ratio, consistency, spike detection |
contentStyle | posts | Content types, hashtag and caption stats (no style score) |
brandSafety | post captions | Keyword scan with your flagKeywords added to the defaults |
growthTrend, competitorOverlap, sponsorshipHistory | not implemented yet | Listed in unavailableFields |
analysisDepth: "comprehensive" with aiProvider and a matching API key adds an AI-written content assessment based on the supplied posts.
Input parameters
| Parameter | Type | Default | Description |
|---|---|---|---|
influencers | array | - | Influencers to analyze, with optional real metrics and posts |
discoveryDatasetId | string | - | Dataset ID from the influencer-discovery actor |
analysisDepth | string | "standard" | quick, standard or comprehensive |
postsToAnalyze | integer | 12 | Maximum supplied posts analyzed per influencer |
analysisModules | array | 4 core modules | Which modules to run |
brandContext | object | - | Passed to the AI assessment |
aiProvider | string | "none" | openai, anthropic or none (BYOK) |
openaiApiKey / anthropicApiKey | string | - | Your key for the AI assessment |
flagKeywords | array | - | Extra brand safety keywords |
demoMode | boolean | false | Return labeled sample data instead of analyzing |
webhookUrl | string | - | Receives results and errors when the run finishes |
Pricing
Pay per event:
| Event | When it is charged | Price |
|---|---|---|
| Influencer Analyzed | An influencer with at least 2 modules scored from real data | $0.05 |
Not charged: demo mode rows, error rows, and partial rows where fewer than 2 modules could be scored (these are marked charged: false). Apify's standard actor start and per-result platform events still apply.
Output fields
status (ok, error or sample), isSampleData, dataSource, charged, profile metrics, overallScore (average of the scores that could be computed), per-module scores and details, partnershipPotential (high, medium, low, not_recommended or insufficient_data), strengths, concerns, recommendations, suggestedCollabTypes, unavailableFields.
Built by John Rippy | Actor Arsenal