Saber lo que publican sus competidores en TikTok y cómo responde su audiencia revela brechas que puede explotar. Este tutorial crea un canal de monitoreo de la competencia que rastrea la frecuencia de publicación, los temas de contenido, los estilos de video de mayor rendimiento y los puntos de referencia de participación para una lista de cuentas de la competencia. Cada verificación de perfil cuesta $0,005 y cada búsqueda de publicación cuesta $0,005 a través de la API Scavio TikTok con autenticación de token de portador.
Requisitos previos
- Python 3.9+ instalado
- solicita biblioteca instalada
- Una clave API de Scavio de scavio.dev
- Una lista de nombres de usuario de TikTok de la competencia
Guia paso a paso
Paso 1: Configurar la lista de competidores y buscar perfiles
Defina a sus competidores y obtenga las estadísticas de sus perfiles para establecer métricas de referencia.
Python
import os, requests, json, time
from datetime import datetime
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'}
COMPETITORS = ['competitor1', 'competitor2', 'competitor3']
def get_competitor_profile(username: str) -> dict:
resp = requests.post(f'{TT_URL}/profile', headers=TT_H,
json={'username': username})
data = resp.json().get('data', {})
stats = data.get('stats', {})
return {
'username': username,
'followers': stats.get('followerCount', 0),
'total_likes': stats.get('heartCount', 0),
'video_count': stats.get('videoCount', 0),
'sec_user_id': data.get('user', {}).get('secUid', ''),
}
for c in COMPETITORS:
profile = get_competitor_profile(c)
print(f'@{c}: {profile["followers"]:,} followers, {profile["video_count"]} videos')
time.sleep(0.3)Paso 2: Buscar y analizar patrones de publicación de competidores
Obtenga las publicaciones recientes de cada competidor y analice la frecuencia de publicación, las tasas de participación típicas y los temas de contenido.
Python
def analyze_competitor(username: str, sec_user_id: str) -> dict:
resp = requests.post(f'{TT_URL}/user/posts', headers=TT_H,
json={'sec_user_id': sec_user_id, 'count': 30})
posts = resp.json().get('data', {}).get('videos', [])
if not posts:
return {'username': username, 'error': 'No posts found'}
engagement_rates = []
view_counts = []
descriptions = []
for p in posts:
stats = p.get('stats', {})
views = stats.get('playCount', 0)
likes = stats.get('diggCount', 0)
comments = stats.get('commentCount', 0)
if views > 0:
engagement_rates.append((likes + comments) / views)
view_counts.append(views)
descriptions.append(p.get('desc', '').lower())
# Posting frequency
timestamps = sorted([p.get('createTime', 0) for p in posts if p.get('createTime')])
if len(timestamps) >= 2:
days_span = (timestamps[-1] - timestamps[0]) / 86400
posts_per_week = len(timestamps) / max(days_span / 7, 1)
else:
posts_per_week = 0
return {
'username': username,
'posts_analyzed': len(posts),
'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,
'posts_per_week': posts_per_week,
'top_video_views': max(view_counts) if view_counts else 0,
}Paso 3: Generar un informe de referencia competitivo
Recopile todos los datos de la competencia en un informe comparativo que muestre su posición en relación con la competencia e identifique las brechas de contenido.
Python
def competitor_report(competitors: list) -> dict:
results = []
for username in competitors:
profile = get_competitor_profile(username)
time.sleep(0.3)
if profile.get('sec_user_id'):
analysis = analyze_competitor(username, profile['sec_user_id'])
analysis['followers'] = profile['followers']
results.append(analysis)
time.sleep(0.3)
print('Competitor Benchmark Report')
print('=' * 70)
for r in sorted(results, key=lambda x: x.get('avg_views', 0), reverse=True):
print(f' @{r["username"]:15s} | {r["followers"]:>10,} followers | '
f'{r.get("avg_engagement", 0):5.1%} eng | '
f'{r.get("posts_per_week", 0):4.1f}/wk | '
f'{r.get("avg_views", 0):>10,.0f} avg views')
# Averages
avg_eng = sum(r.get('avg_engagement', 0) for r in results) / len(results) if results else 0
avg_freq = sum(r.get('posts_per_week', 0) for r in results) / len(results) if results else 0
print(f'\n Benchmark avg: {avg_eng:.1%} engagement, {avg_freq:.1f} posts/week')
print(f' Cost: ${len(competitors) * 0.010:.3f} ({len(competitors)} competitors x 2 calls)')
return {'results': results, 'avg_engagement': avg_eng, 'avg_frequency': avg_freq}
competitor_report(COMPETITORS)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 monitor_competitor(username):
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)
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', [])
views = [v.get('stats', {}).get('playCount', 0) for v in posts]
avg = sum(views) / len(views) if views else 0
print(f'@{username}: {stats.get("followerCount", 0):,} followers, {avg:,.0f} avg views')
for c in ['competitor1', 'competitor2']:
monitor_competitor(c)
time.sleep(0.3)Ejemplo en JavaScript
JavaScript
const SCAVIO_KEY = process.env.SCAVIO_API_KEY;
const TT_H = { Authorization: `Bearer ${SCAVIO_KEY}`, 'Content-Type': 'application/json' };
async function monitorCompetitor(username) {
const profile = await fetch('https://api.scavio.dev/api/v1/tiktok/profile', {
method: 'POST', headers: TT_H, body: JSON.stringify({ username })
}).then(r => r.json());
const stats = profile.data?.stats || {};
const uid = profile.data?.user?.secUid || '';
const posts = await fetch('https://api.scavio.dev/api/v1/tiktok/user/posts', {
method: 'POST', headers: TT_H, body: JSON.stringify({ sec_user_id: uid, count: 10 })
}).then(r => r.json());
const views = (posts.data?.videos || []).map(v => v.stats?.playCount || 0);
const avg = views.length ? views.reduce((a, b) => a + b, 0) / views.length : 0;
console.log(`@${username}: ${(stats.followerCount || 0).toLocaleString()} followers, ${avg.toLocaleString()} avg views`);
}
(async () => { for (const c of ['competitor1', 'competitor2']) { await monitorCompetitor(c); } })();Salida esperada
JSON
Competitor Benchmark Report
======================================================================
@competitor1 | 250,000 followers | 6.2% eng | 4.5/wk | 890,000 avg views
@competitor2 | 180,000 followers | 7.8% eng | 3.2/wk | 650,000 avg views
@competitor3 | 120,000 followers | 5.1% eng | 5.0/wk | 320,000 avg views
Benchmark avg: 6.4% engagement, 4.2 posts/week
Cost: $0.030 (3 competitors x 2 calls)