Build a creator shortlist

Follower count is the worst available predictor of whether a creator will sell your product. This guide builds a shortlist on evidence instead.

Rank on efficiency, not reach

gpm — gross revenue per thousand views — is neutral to audience size. A creator with 40k followers and a gpm of 85 is a better partner than one with 900k followers and a gpm of 6, and costs a fraction as much.

curl -X POST https://api.unif.dev/v1/creators/search \
  -H "Authorization: Bearer $UNIF_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "market": "US",
    "period": { "preset": "last_30d" },
    "currency": "USD",
    "filters": {
      "category_ids": ["cat_beauty_personal_care"],
      "followers": { "gte": 20000, "lte": 300000 },
      "revenue": { "gte": 25000 },
      "gpm": { "gte": 40 },
      "avg_commission_rate": { "lte": 0.25 }
    },
    "sort": [{ "field": "gpm", "direction": "desc" }],
    "limit": 50
  }'

Filter	Reasoning
`followers: 20k–300k`	Below 20k, one good video distorts every metric. Above 300k, rates climb faster than conversion does.
`revenue: { gte: 25000 }`	Proof they have actually sold, not just posted.
`gpm: { gte: 40 }`	The efficiency bar. Calibrate it to your category’s price point.
`avg_commission_rate: { lte: 0.25 }`	They work at rates you can afford.

categories on a creator is ordered by their revenue share, not by self-declared niche. A creator who posts about fitness but sells supplements is returned under supplements — which is what you wanted to know.

Start from a product, not a category

The highest-signal sourcing query does not start from a category at all. It starts from a product like yours and asks who already sells it.

curl "https://api.unif.dev/v1/products/prd_01k3m9x7v2q8r4t6y0b1n5d7fa/creators?period=last_90d&limit=50" \
  -H "Authorization: Bearer $UNIF_API_KEY"

These creators have demonstrated they can move this exact kind of product to an audience that buys it. Run it across your three closest competitor products and intersect:

from collections import Counter

appearances = Counter()
for product_id in competitor_product_ids:
    for creator in list_product_creators(product_id, period="last_90d"):
        appearances[creator["id"]] += 1

# Creators who converted for more than one competitor product
proven = [cid for cid, n in appearances.items() if n >= 2]

A creator who appears for two or three competing products is not a one-off — they sell the category.

Filter out the profile you do not want

Two checks remove most bad shortlist entries.

Too many shops

shops_count above roughly 40 in a 30-day window usually means a creator taking every offer that arrives. Volume, not endorsement.

candidates = [c for c in candidates if c["metrics"]["shops_count"] <= 40]

Engagement without sales

High engagement_rate with low gpm is an entertainment audience, not a buying one. Both matter; neither alone is enough.

candidates = [
    c for c in candidates
    if c["metrics"]["gpm"] >= 40 or c["metrics"]["engagement_rate"] < 0.06
]

Check the trend before you sign

A creator’s 30-day numbers can be a tail. Look at the shape:

curl "https://api.unif.dev/v1/creators/crt_01k3…fa/timeseries?metrics=revenue,gpm&granularity=week&period=last_90d" \
  -H "Authorization: Bearer $UNIF_API_KEY"

weeks = [p["values"]["gpm"] for p in series["data"]]
recent, earlier = weeks[-4:], weeks[:4]

trend = sum(recent) / len(recent) - sum(earlier) / len(earlier)

A gpm trending down over twelve weeks means their audience is fatiguing on commerce content. The 30-day snapshot will not tell you that.

Save and monitor

curl -X POST https://api.unif.dev/v1/lists \
  -H "Authorization: Bearer $UNIF_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "Creator shortlist — US skincare Q4",
    "entity_type": "creator",
    "item_ids": ["crt_01k3…fa", "crt_01k3…fb"]
  }'

Then a tracker on the list, so you know when a partner’s performance changes while you are working with them:

{
  "name": "Partner performance drift",
  "source": { "type": "list", "list_id": "lst_01k3…fb" },
  "schedule": "weekly",
  "conditions": [
    { "metric": "gpm", "change": "pct", "over": "30d", "lte": -0.25 },
    { "metric": "follower_growth", "lte": 0 }
  ]
}

Re-read the shortlist quarterly with the same query. Creator performance moves faster than almost anything else in commerce data, and a list from two quarters ago is a list of who used to convert.

Getting started

Core concepts

Workflows

Guides

Platform

Release notes

Build a creator shortlist

Rank on efficiency, not reach

Start from a product, not a category

Filter out the profile you do not want

Check the trend before you sign

Save and monitor

​Rank on efficiency, not reach

​Start from a product, not a category

​Filter out the profile you do not want

​Check the trend before you sign

​Save and monitor

Rank on efficiency, not reach

Start from a product, not a category

Filter out the profile you do not want

Check the trend before you sign

Save and monitor