Encontrar creadores con audiencias superpuestas revela oportunidades de colaboración y ayuda a las marcas a evitar pagar a dos personas influyentes para llegar a las mismas personas. Este canal compara listas de seguidores entre creadores de TikTok, calcula porcentajes de superposición e identifica segmentos de audiencia compartidos. Cada extracción de la lista de seguidores cuesta $0,005 a través de los puntos finales de la API de Scavio TikTok.
Requisitos previos
- Python 3.8+
- solicita biblioteca
- Una clave API de Scavio de scavio.dev
- Nombres de usuario de creadores de TikTok para comparar
Guia paso a paso
Paso 1: Extraiga perfiles de creadores y muestras de seguidores
Obtenga datos de perfil y listas de seguidores para comparar.
Python
import os, requests, json
from collections import Counter
API_KEY = os.environ['SCAVIO_API_KEY']
TH = {'Authorization': f'Bearer {API_KEY}', 'Content-Type': 'application/json'}
def get_profile(username):
data = requests.post('https://api.scavio.dev/api/v1/tiktok/profile',
headers=TH, json={'username': username}).json()
user = data.get('user', data.get('data', {}).get('user', data))
return {'username': username, 'followers': user.get('followerCount', user.get('fans', 0)),
'following': user.get('followingCount', 0),
'likes': user.get('heartCount', user.get('heart', 0))}
def get_followers(username):
data = requests.post('https://api.scavio.dev/api/v1/tiktok/user/followers',
headers=TH, json={'username': username}).json()
followers = data.get('followers', data.get('data', {}).get('followers', []))
return [f.get('uniqueId', f.get('username', '')) for f in followers if f.get('uniqueId') or f.get('username')]
creators = ['charlidamelio', 'addisonre', 'bellapoarch']
for c in creators:
p = get_profile(c)
print(f'{c}: {p["followers"]:,} followers, {p["likes"]:,} likes')Paso 2: Calcular la superposición de seguidores
Compara listas de seguidores entre pares de creadores.
Python
def overlap(creator_a, creator_b):
followers_a = set(get_followers(creator_a))
followers_b = set(get_followers(creator_b))
if not followers_a or not followers_b:
return {'pair': f'{creator_a} x {creator_b}', 'overlap': 0, 'pct_a': 0, 'pct_b': 0}
shared = followers_a & followers_b
return {
'pair': f'{creator_a} x {creator_b}',
'followers_a': len(followers_a),
'followers_b': len(followers_b),
'shared': len(shared),
'pct_a': len(shared) / len(followers_a) * 100 if followers_a else 0,
'pct_b': len(shared) / len(followers_b) * 100 if followers_b else 0,
'shared_users': list(shared)[:10]
}
result = overlap('charlidamelio', 'addisonre')
print(f'{result["pair"]}: {result["shared"]} shared ({result["pct_a"]:.1f}% of A, {result["pct_b"]:.1f}% of B)')Paso 3: Construya la matriz de superposición completa
Compare todos los pares de creadores y cree una matriz.
Python
from itertools import combinations
def overlap_matrix(creators):
pairs = list(combinations(creators, 2))
results = []
print(f'Comparing {len(pairs)} pairs ({len(pairs) * 2} follower pulls)...')
for a, b in pairs:
r = overlap(a, b)
results.append(r)
print(f' {a:20} x {b:20} | shared: {r["shared"]:4} | {r["pct_a"]:.1f}% / {r["pct_b"]:.1f}%')
cost = len(pairs) * 2 * 0.005 # 2 follower pulls per pair
print(f'\nCost: ${cost:.3f} ({len(pairs) * 2} API calls)')
return results
results = overlap_matrix(['charlidamelio', 'addisonre', 'bellapoarch'])
# Highest overlap pair
best = max(results, key=lambda x: x['shared'])
print(f'\nHighest overlap: {best["pair"]} ({best["shared"]} shared followers)')Paso 4: Generar recomendaciones de colaboración
Clasifique los pares de creadores por superposición para la planificación de la colaboración de marca.
Python
def recommend(results, strategy='maximize_reach'):
print(f'\n=== Collaboration Recommendations ({strategy}) ===')
if strategy == 'maximize_reach':
# Low overlap = more unique reach
ranked = sorted(results, key=lambda x: x['pct_a'] + x['pct_b'])
print('Pairs with LOWEST overlap (maximum unique reach):')
else:
# High overlap = reinforced messaging
ranked = sorted(results, key=lambda x: x['pct_a'] + x['pct_b'], reverse=True)
print('Pairs with HIGHEST overlap (reinforced messaging):')
for i, r in enumerate(ranked[:5], 1):
avg_overlap = (r['pct_a'] + r['pct_b']) / 2
print(f' {i}. {r["pair"]:45} | overlap: {avg_overlap:.1f}% | shared: {r["shared"]}')
report = {'strategy': strategy, 'recommendations': ranked[:5], 'total_pairs': len(results)}
with open('overlap_report.json', 'w') as f: json.dump(report, f, indent=2, default=str)
print(f'Saved to overlap_report.json')
return report
recommend(results, 'maximize_reach')
recommend(results, 'reinforce_message')Ejemplo en Python
Python
import os, requests
TH = {'Authorization': f'Bearer {os.environ["SCAVIO_API_KEY"]}', 'Content-Type': 'application/json'}
def compare(user_a, user_b):
fa = requests.post('https://api.scavio.dev/api/v1/tiktok/user/followers',
headers=TH, json={'username': user_a}).json()
fb = requests.post('https://api.scavio.dev/api/v1/tiktok/user/followers',
headers=TH, json={'username': user_b}).json()
a = set(f.get('uniqueId', '') for f in fa.get('followers', []))
b = set(f.get('uniqueId', '') for f in fb.get('followers', []))
shared = a & b
print(f'{user_a} x {user_b}: {len(shared)} shared of {len(a)}+{len(b)} ({len(shared)/(len(a) or 1)*100:.1f}%)')
compare('charlidamelio', 'addisonre')Ejemplo en JavaScript
JavaScript
const TH = { 'Authorization': `Bearer ${process.env.SCAVIO_API_KEY}`, 'Content-Type': 'application/json' };
async function compare(userA, userB) {
const [fa, fb] = await Promise.all([
fetch('https://api.scavio.dev/api/v1/tiktok/user/followers', {
method: 'POST', headers: TH, body: JSON.stringify({ username: userA }) }).then(r => r.json()),
fetch('https://api.scavio.dev/api/v1/tiktok/user/followers', {
method: 'POST', headers: TH, body: JSON.stringify({ username: userB }) }).then(r => r.json()),
]);
const a = new Set((fa.followers||[]).map(f => f.uniqueId));
const b = new Set((fb.followers||[]).map(f => f.uniqueId));
const shared = [...a].filter(x => b.has(x));
console.log(`${userA} x ${userB}: ${shared.length} shared of ${a.size}+${b.size}`);
}
compare('charlidamelio', 'addisonre').catch(console.error);Salida esperada
JSON
charlidamelio: 155,200,000 followers, 11,800,000,000 likes
addisonre: 88,700,000 followers, 5,900,000,000 likes
bellapoarch: 93,400,000 followers, 2,300,000,000 likes
Comparing 3 pairs (6 follower pulls)...
charlidamelio x addisonre | shared: 847 | 42.3% / 38.1%
charlidamelio x bellapoarch | shared: 312 | 15.6% / 14.2%
addisonre x bellapoarch | shared: 523 | 26.2% / 23.8%
Cost: $0.030 (6 API calls)
Highest overlap: charlidamelio x addisonre (847 shared followers)
=== Collaboration Recommendations (maximize_reach) ===
Pairs with LOWEST overlap (maximum unique reach):
1. charlidamelio x bellapoarch | overlap: 14.9% | shared: 312