Elegir al creador de TikTok equivocado para una asociación de marca desperdicia presupuesto y daña la credibilidad. Las métricas de vanidad, como el recuento de seguidores, ocultan una participación falsa, publicaciones inconsistentes y contenido fuera de marca. Este tutorial crea un proceso de investigación de creadores utilizando la API Scavio TikTok para verificar las tasas de participación reales, la coherencia del contenido, las señales de la audiencia y la frecuencia de publicación. Cada llamada a la API cuesta $ 0,005 y le brinda datos por los que las plataformas de influencers cobran cientos por mes para acceder.
Requisitos previos
- Python 3.9+ instalado
- solicita biblioteca instalada
- Una clave API de Scavio de scavio.dev
- Una lista de nombres de usuario de creadores de TikTok para evaluar
Guia paso a paso
Paso 1: Extraer el perfil y las estadísticas del creador
Utilice el punto final del perfil de TikTok para obtener el recuento de seguidores, el recuento de seguidores, el total de me gusta y la biografía de un creador. La proporción de seguidores/seguidos es una rápida señal de autenticidad.
Python
import os, requests, time
SCAVIO_KEY = os.environ['SCAVIO_API_KEY']
TT_URL = 'https://api.scavio.dev/api/v1/tiktok'
TT_H = {'Authorization': f'Bearer {SCAVIO_KEY}', 'Content-Type': 'application/json'}
def get_creator_profile(username: str) -> dict:
"""Get creator profile data."""
resp = requests.post(f'{TT_URL}/profile', headers=TT_H,
json={'username': username})
data = resp.json().get('data', {})
user = data.get('user', {})
stats = data.get('stats', {})
return {
'username': username,
'nickname': user.get('nickname', ''),
'bio': user.get('signature', ''),
'verified': user.get('verified', False),
'sec_user_id': user.get('secUid', ''),
'followers': stats.get('followerCount', 0),
'following': stats.get('followingCount', 0),
'total_likes': stats.get('heartCount', 0),
'total_videos': stats.get('videoCount', 0),
'follower_ratio': stats.get('followerCount', 0) / max(stats.get('followingCount', 1), 1),
}
profile = get_creator_profile('charlidamelio')
print(f"Creator: @{profile['username']} ({profile['nickname']})")
print(f"Followers: {profile['followers']:,}")
print(f"Total likes: {profile['total_likes']:,}")
print(f"Videos: {profile['total_videos']}")
print(f"Follower ratio: {profile['follower_ratio']:.0f}:1")
print(f"Verified: {profile['verified']}")Paso 2: Analizar contenido reciente y tasas de participación
Extraiga las publicaciones recientes del creador y calcule las tasas de participación reales. La participación promedio por debajo del 2% en TikTok es una señal de alerta para los seguidores falsos.
Python
def analyze_content(username: str, sec_user_id: str) -> dict:
"""Analyze a creator's recent content for engagement quality."""
resp = requests.post(f'{TT_URL}/user/posts', headers=TT_H,
json={'sec_user_id': sec_user_id, 'count': 20})
posts = resp.json().get('data', {}).get('videos', [])
if not posts:
return {'error': 'No posts found'}
engagement_rates = []
view_counts = []
for post in posts:
stats = post.get('stats', {})
views = stats.get('playCount', 0)
likes = stats.get('diggCount', 0)
comments = stats.get('commentCount', 0)
shares = stats.get('shareCount', 0)
if views > 0:
eng_rate = (likes + comments + shares) / views
engagement_rates.append(eng_rate)
view_counts.append(views)
avg_engagement = sum(engagement_rates) / len(engagement_rates) if engagement_rates else 0
avg_views = sum(view_counts) / len(view_counts) if view_counts else 0
view_consistency = min(view_counts) / max(view_counts) if view_counts and max(view_counts) > 0 else 0
return {
'posts_analyzed': len(posts),
'avg_engagement_rate': avg_engagement,
'avg_views': avg_views,
'min_views': min(view_counts) if view_counts else 0,
'max_views': max(view_counts) if view_counts else 0,
'view_consistency': view_consistency, # Higher = more consistent
'engagement_quality': 'good' if avg_engagement > 0.05 else 'average' if avg_engagement > 0.02 else 'low',
}
# Need sec_user_id from profile step
if profile.get('sec_user_id'):
content = analyze_content(profile['username'], profile['sec_user_id'])
print(f"Content Analysis: @{profile['username']}")
print(f" Posts analyzed: {content['posts_analyzed']}")
print(f" Avg engagement: {content['avg_engagement_rate']:.1%}")
print(f" Avg views: {content['avg_views']:,.0f}")
print(f" View consistency: {content['view_consistency']:.0%}")
print(f" Quality: {content['engagement_quality']}")Paso 3: Verifique la seguridad de la marca y la relevancia del contenido
Busque en las descripciones de los videos del creador contenido seguro para la marca. Compruebe si su contenido se alinea con el nicho de su marca analizando los temas de los videos.
Python
def check_brand_fit(username: str, sec_user_id: str, brand_keywords: list) -> dict:
"""Check if a creator's content fits your brand."""
resp = requests.post(f'{TT_URL}/user/posts', headers=TT_H,
json={'sec_user_id': sec_user_id, 'count': 20})
posts = resp.json().get('data', {}).get('videos', [])
descriptions = [post.get('desc', '').lower() for post in posts]
all_text = ' '.join(descriptions)
# Check brand keyword relevance
keyword_matches = {kw: sum(1 for d in descriptions if kw.lower() in d)
for kw in brand_keywords}
relevance = sum(keyword_matches.values()) / (len(descriptions) * len(brand_keywords)) if descriptions and brand_keywords else 0
# Brand safety checks
unsafe_terms = ['controversial', 'scandal', 'banned', 'nsfw', 'drama']
safety_flags = [t for t in unsafe_terms if t in all_text]
# Check if creator does sponsored content
sponsored_count = sum(1 for d in descriptions if any(w in d for w in ['#ad', '#sponsored', '#partner', 'collab']))
return {
'keyword_relevance': keyword_matches,
'relevance_score': relevance,
'safety_flags': safety_flags,
'brand_safe': len(safety_flags) == 0,
'sponsored_posts': sponsored_count,
'sponsored_rate': sponsored_count / len(descriptions) if descriptions else 0,
}
if profile.get('sec_user_id'):
brand_fit = check_brand_fit(profile['username'], profile['sec_user_id'],
['dance', 'fashion', 'lifestyle', 'beauty'])
print(f"Brand Fit Analysis:")
print(f" Relevance: {brand_fit['relevance_score']:.0%}")
print(f" Brand safe: {brand_fit['brand_safe']}")
print(f" Sponsored posts: {brand_fit['sponsored_posts']} ({brand_fit['sponsored_rate']:.0%})")
print(f" Keywords: {brand_fit['keyword_relevance']}")Paso 4: Generar el informe de investigación de creadores
Combine todas las señales en una puntuación de investigación y una recomendación. El informe proporciona información clara sobre lo que se puede o no hacer para cada creador.
Python
def vet_creator(username: str, brand_keywords: list) -> dict:
"""Full creator vetting report."""
profile = get_creator_profile(username)
time.sleep(0.3)
if not profile.get('sec_user_id'):
return {'username': username, 'verdict': 'ERROR', 'reason': 'Profile not found'}
content = analyze_content(username, profile['sec_user_id'])
time.sleep(0.3)
brand_fit = check_brand_fit(username, profile['sec_user_id'], brand_keywords)
# Scoring (0-100)
scores = {
'engagement': min(content.get('avg_engagement_rate', 0) * 1000, 30), # Max 30
'consistency': content.get('view_consistency', 0) * 20, # Max 20
'relevance': brand_fit.get('relevance_score', 0) * 25, # Max 25
'safety': 15 if brand_fit.get('brand_safe') else 0, # Max 15
'authenticity': min(profile.get('follower_ratio', 0) / 10, 10), # Max 10
}
total = sum(scores.values())
verdict = 'APPROVE' if total >= 60 else 'REVIEW' if total >= 40 else 'REJECT'
report = {
'username': username,
'followers': profile['followers'],
'avg_engagement': content.get('avg_engagement_rate', 0),
'avg_views': content.get('avg_views', 0),
'brand_safe': brand_fit.get('brand_safe'),
'relevance': brand_fit.get('relevance_score', 0),
'scores': scores,
'total_score': total,
'verdict': verdict,
'credits_used': 3,
'cost': 0.015,
}
print(f"\nCreator Report: @{username}")
print(f"Verdict: {verdict} (Score: {total:.0f}/100)")
print(f" Followers: {profile['followers']:,}")
print(f" Engagement: {content.get('avg_engagement_rate', 0):.1%}")
print(f" Brand safe: {brand_fit.get('brand_safe')}")
print(f" Relevance: {brand_fit.get('relevance_score', 0):.0%}")
for k, v in scores.items():
print(f" {k:15s}: {v:.1f}")
return report
report = vet_creator('charlidamelio', ['dance', 'fashion', 'lifestyle'])Ejemplo en Python
Python
import os, requests, time
SCAVIO_KEY = os.environ['SCAVIO_API_KEY']
TT_H = {'Authorization': f'Bearer {SCAVIO_KEY}', 'Content-Type': 'application/json'}
def vet_creator(username):
# Get profile
resp = requests.post('https://api.scavio.dev/api/v1/tiktok/profile', headers=TT_H,
json={'username': username})
data = resp.json().get('data', {})
stats = data.get('stats', {})
uid = data.get('user', {}).get('secUid', '')
time.sleep(0.3)
# Get posts
resp2 = requests.post('https://api.scavio.dev/api/v1/tiktok/user/posts', headers=TT_H,
json={'sec_user_id': uid, 'count': 10})
posts = resp2.json().get('data', {}).get('videos', [])
eng_rates = []
for p in posts:
s = p.get('stats', {})
views = s.get('playCount', 1)
eng_rates.append((s.get('diggCount', 0) + s.get('commentCount', 0)) / views)
avg_eng = sum(eng_rates) / len(eng_rates) if eng_rates else 0
print(f'@{username}: {stats.get("followerCount",0):,} followers, {avg_eng:.1%} engagement')
vet_creator('charlidamelio')Ejemplo en JavaScript
JavaScript
const SCAVIO_KEY = process.env.SCAVIO_API_KEY;
const TT_H = { Authorization: `Bearer ${SCAVIO_KEY}`, 'Content-Type': 'application/json' };
async function vetCreator(username) {
const profile = await fetch('https://api.scavio.dev/api/v1/tiktok/profile', {
method: 'POST', headers: TT_H, body: JSON.stringify({ username })
}).then(r => r.json());
const stats = profile.data?.stats || {};
const uid = profile.data?.user?.secUid || '';
const posts = await fetch('https://api.scavio.dev/api/v1/tiktok/user/posts', {
method: 'POST', headers: TT_H, body: JSON.stringify({ sec_user_id: uid, count: 10 })
}).then(r => r.json());
const videos = posts.data?.videos || [];
const engRates = videos.map(v => {
const s = v.stats || {};
return (s.diggCount + s.commentCount) / (s.playCount || 1);
});
const avgEng = engRates.length ? engRates.reduce((a,b) => a+b, 0) / engRates.length : 0;
console.log(`@${username}: ${(stats.followerCount || 0).toLocaleString()} followers, ${(avgEng * 100).toFixed(1)}% engagement`);
}
vetCreator('charlidamelio');Salida esperada
JSON
Creator: @charlidamelio (Charli D'Amelio)
Followers: 155,200,000
Total likes: 11,800,000,000
Videos: 2,340
Follower ratio: 4250:1
Verified: True
Content Analysis: @charlidamelio
Posts analyzed: 20
Avg engagement: 5.2%
Avg views: 8,450,000
View consistency: 45%
Quality: good
Creator Report: @charlidamelio
Verdict: APPROVE (Score: 72/100)
engagement : 30.0
consistency : 9.0
relevance : 18.8
safety : 15.0
authenticity : 10.0