Compare two follower tiers
Choose any two tiers. The figures and interpretation update immediately in your browser.
Full tier table
Tier-wide averages include creators with zero recorded GMV. Active-only averages exclude them. That denominator difference is why the two averages should not be used interchangeably.
| Tier | Creators | Active sellers | Active rate | Avg GMV · all | Avg GMV · active | GMV / 1K followers |
|---|---|---|---|---|---|---|
| Nano | 23,176 | 12,544 | 54.1% | $1,751 | $3,235 | $2,054 |
| Micro | 6,332 | 3,130 | 49.4% | $7,037 | $14,236 | $281 |
| Mid | 1,052 | 408 | 38.8% | $17,100 | $44,091 | $90 |
| Macro | 218 | 61 | 28.0% | $30,110 | $107,604 | $35 |
How to use these figures
- For conversion planning: compare active rate and GMV efficiency, then verify each candidate's current commerce activity.
- For reach planning: higher tiers provide larger audiences, but the lower active rate means screening remains essential.
- For mixed portfolios: use smaller creators for testing volume and larger creators selectively for reach or launch visibility.
What this tool cannot tell you
- It is not a creator fee calculator or rate card.
- Tier averages do not predict any individual campaign outcome.
- We do not estimate unavailable commission, engagement, city, or brand-collaboration fields.
Methodology and denominator note
The source dataset contains 30,782 Malaysia-based TikTok creators tagged in the beauty category as of 10 Jul 2026. The tier table covers 30,778 creators with a usable follower count; four records without a usable follower count are excluded from tier comparisons but remain in the category total.
"Active seller" means recorded TikTok Shop GMV greater than zero in the snapshot. GMV and items-sold figures are estimates derived from publicly listed TikTok Shop product and sales information. GMV per 1,000 followers is calculated from tier-level averages and should be read as an efficiency comparison, not a return forecast.
Read the full benchmark report for percentile distribution and MCN findings, or the Data Sources & Correction Policy for collection, refresh, correction, and exclusion practices.
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