How Credits Work
- Each API call has a base credit cost
- Fetching more data costs more credits
- ML enrichment adds additional credits per item analyzed
Credit Costs by Endpoint
TikTok
YouTube
ML Analyze
Example Credit Calculations
10 TikTok posts without enrichment
10 TikTok posts without enrichment
- Base: 1 credit
- Posts: 10 × 1 = 10 credits
- Total: 11 credits
10 TikTok posts with sentiment enrichment
10 TikTok posts with sentiment enrichment
- Base: 1 credit
- Posts: 10 × 1 = 10 credits
- Enrichment: 10 × 2 = 20 credits
- Total: 31 credits
ML Analyze with 5 texts and all analyses
ML Analyze with 5 texts and all analyses
- Sentiment: 5 × 0.5 = 2.5 credits
- Topics: 5 × 1 = 5 credits
- Intent: 5 × 1 = 5 credits
- Keywords: 5 × 0.5 = 2.5 credits
- Total: 15 credits
Viewing Credit Usage
Every API response includes credit information in the metadata:Tips for Optimizing Credit Usage
Only request what you need
Use the
limit parameter wiselyBatch requests
Use bulk endpoints when fetching from multiple users
Selective enrichment
Only enable enrichments you actually need
Cache responses
Store data locally to avoid duplicate requests