Score creators on content quality, not follower count
A creator with 500K subscribers and declining engagement is a worse bet than one with 50K subscribers who posts strong hooks every week. Subscriber count tells brands nothing about content quality. BrightBean scores what actually predicts campaign performance: hook patterns, title effectiveness, posting consistency, and niche-relative engagement.
The problem
Subscriber count doesn't predict campaign performance
Vanity metrics mislead brands
Your platform ranks creators by subscribers and total views. A 500K channel coasting on old viral hits outranks a 50K channel that's growing 20% month-over-month. Brands pick the bigger number and get disappointing results.
No signal for content quality
You can see that a creator has 200 videos. You can't tell if their hooks are strong, their titles follow proven patterns, or their posting schedule is reliable. Without these signals, your recommendations are guesswork.
With BrightBean
Score every creator on hook quality, title effectiveness, posting cadence, and engagement ratios. All relative to their niche, not raw numbers. Build recommendations brands can trust.
See it in action
Evaluating creators for a fitness brand campaign
A fitness brand wants 3 creators for a supplement launch. Your platform has 400 fitness creators in the database. Here's how BrightBean helps you surface the right ones.
Benchmark a creator's channel
Start with @fitness_sarah, a mid-size fitness creator. The /benchmark endpoint returns her performance scored against the fitness niche average, not just raw numbers.
Her views-per-subscriber ratio is 0.18, more than double the niche average of 0.08. She posts 3.5 times per week with a "high" consistency rating, meaning she rarely misses uploads. Her title scores average 76, well above the fitness niche average of 58.
The engagement trend reads "growing." This is a creator whose audience is expanding, not one riding old momentum.
{
"channel": "@fitness_sarah",
"channel_tier": "mid_size",
"subscribers": 87000,
"views_per_sub_ratio": 0.18,
"niche_avg_ratio": 0.08,
"posting_frequency": "3.5x/week",
"title_score_avg": 76,
"niche_title_score_avg": 58,
"consistency_rating": "high",
"engagement_trend": "growing"
}Analyze their content quality
Good benchmark numbers could hide inconsistent content. The /analyze/hook endpoint digs into the last 10 videos and shows you how the creator actually opens their content.
Sarah's hook score is 82, well above the fitness niche average of 61. She uses "result_first" hooks in 60% of her videos. That's the pattern where she leads with the outcome ("I lost 30 pounds in 60 days") before explaining how. It's one of the highest-performing hook types in fitness content.
The pattern consistency matters. One viral hook doesn't make a reliable creator. Ten strong hooks across her last ten videos does.
{
"hook_type": "result_first",
"hook_text": "I lost 30 pounds in 60 days with this one change...",
"hook_score": 82,
"avg_hook_score_in_niche": 61,
"retention_prediction": "above_average",
"hook_patterns_last_10_videos": [
"result_first", "contrarian_claim",
"question", "result_first",
"identity_callout", "result_first",
"question", "result_first",
"contrarian_claim", "result_first"
],
"dominant_style": "result_first (60%)"
}Compare two creators side by side
@fitness_sarah (87K subs)
Strong pick. High content quality with growing engagement.
@gym_bro_official (410K subs)
Big subscriber count, but low content quality and declining engagement. Risky for campaigns.
The 410K channel looks better on paper. But BrightBean shows a views-per-sub ratio of 0.03 (the niche average is 0.08), below-average title scores, and declining engagement. The 87K channel outperforms on every quality metric. Without these scores, your platform recommends the bigger channel. With them, you recommend the better one.
Build a quality score for your recommendation engine
Run /benchmark across your creator database and store the results. Now your platform has a quality dimension that subscribers alone can't provide.
Weight the scores however fits your product. Some platforms prioritize consistency for long-term brand deals. Others care most about hook quality for one-off sponsored videos. The raw data is yours to combine.
Brands searching for fitness creators now see quality scores alongside subscriber counts. They can filter for "consistency_rating: high" or "engagement_trend: growing" and find creators who will actually deliver.
import requests
# Score every creator in your database
for creator in platform_creators:
resp = requests.post(
"https://api.brightbean.xyz/v1/benchmark",
headers={"Authorization": f"Bearer {API_KEY}"},
json={"channel": creator.youtube_handle}
)
data = resp.json()
# Store in your creator profile
creator.quality_score = data["title_score_avg"]
creator.consistency = data["consistency_rating"]
creator.engagement_trend = data["engagement_trend"]
creator.views_per_sub = data["views_per_sub_ratio"]
creator.save()
# Now brands can filter:
# "Show me fitness creators with
# consistency_rating: high AND
# engagement_trend: growing"Getting started
Integration path for your platform
Most platforms run an initial batch to score their existing creator database, then score new creators as they're added.
Initial setup
Batch score your creator database
Run /benchmark for each creator in your database. Store the results alongside your existing creator profiles. For 10,000 creators, this takes about 90 minutes with parallel requests.
# Benchmark call per creator
curl -X POST https://api.brightbean.xyz/v1/benchmark \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{"channel": "@fitness_sarah"}'Each call returns views_per_sub_ratio, title_score_avg, consistency_rating, engagement_trend, and niche comparisons.
Ongoing
Use scores in search, filter, and recommendations
Add BrightBean scores to your creator search filters. Let brands filter by quality_score, consistency, and engagement_trend. Surface high-quality creators in your recommendation engine instead of just sorting by subscriber count.
# Re-score monthly to catch trends
# Detect rising creators early
# Flag declining engagement before campaigns
SELECT * FROM creators
WHERE niche = 'fitness'
AND consistency_rating = 'high'
AND engagement_trend = 'growing'
ORDER BY title_score_avg DESCRe-score creators monthly. A creator who was "growing" in January might be "declining" by March. Fresh data means better recommendations.
Why it matters
The data your platform is missing
Content quality scoring
Hook patterns, title effectiveness, and thumbnail analysis per creator. Not just view counts.
Niche-relative benchmarks
A fitness creator is compared to fitness averages. A tech reviewer to tech averages. Not one global bar.
Consistency tracking
Posting cadence, engagement trends, and quality over time. Spot rising creators and declining ones.
Common questions from influencer platforms
How is this different from pulling YouTube API data directly? +
The YouTube Data API gives you raw metrics: subscriber count, view count, video metadata. BrightBean adds a scoring layer on top. You get title effectiveness scores, hook pattern classification, posting consistency ratings, and engagement trends. All benchmarked against niche averages. The YouTube API tells you a creator has 87K subscribers. BrightBean tells you that creator's content quality is in the top 15% of their niche.
Can I score creators across different niches fairly? +
Yes. Every score is relative to the creator's niche. A title score of 76 in fitness means that creator's titles outperform 76% of fitness titles. A score of 76 in tech means the same thing within tech. You can safely compare a fitness creator's relative performance to a beauty creator's relative performance, because both are measured against their own category.
How many creators can I analyze per month? +
Each /benchmark call is one API call. The Standard plan covers 100,000 calls/month, enough to benchmark 100,000 creators or re-score your existing database multiple times. The Growth plan goes to 500,000 calls/month. For platforms with millions of creators, contact us for custom volume pricing.
Can I build a creator scoring feature into my platform? +
That's the primary use case. Call BrightBean's API, store the scores in your database, and surface them in your creator profiles, search filters, and recommendation engine. Most platforms weight the scores to match their specific needs. One platform might care most about consistency for long-term partnerships. Another might prioritize hook quality for sponsored video campaigns.
What about creators with small but engaged audiences? +
BrightBean scores quality, not size. A 10K subscriber channel with a views-per-sub ratio of 0.25, high title scores, and a "growing" engagement trend will rank above a 500K channel with low content quality. This is exactly the kind of creator that brands miss when they sort by subscriber count. Your platform can surface them.
How often should I re-score creators? +
Monthly works for most platforms. Creator quality shifts over time. Someone posting 4 times a week in January might drop to once a week by April. Monthly re-scoring catches these changes before they affect campaign recommendations. For high-value brand partnerships, score the specific creators right before the pitch to get the freshest data.
Score creators on what actually matters.
Free tier: 500 API calls, no credit card required.