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Flujo de trabajo

Semanal TikTok Contenido Resena

Resena your TikTok contenido rendimiento semanal. Rastrear views, engagement, y tendencias to optimizar your posting estrategia.

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Resumen

TikTok analytics inside el app son limited y reset frequently. Este flujo de trabajo ejecuta cada Sunday tarde, pulls your reciente publicaciones via el Scavio TikTok API, calculates semanal rendimiento metricas (views, likes, comentarios, shares, engagement tasa), identifies your top y bottom performers, y exporta un structured informe. Use it to spot cual contenido formats funciona, cuando your audiencia es mas active, y que to double down on next semana. One semanal ejecutar costs about 2-3 credits ($0.01-$0.015).

Desencadenador

Cron Sunday 8 PM UTC

Programación

Semanal Sunday 8 PM

Pasos del flujo de trabajo

1

Obtener Reciente Posts

Call Scavio TikTok API to retrieve todos publicaciones published in el past 7 dias for your cuenta.

2

Calcular Rendimiento Metricas

Compute total y promedio views, likes, comentarios, shares, y engagement tasa for el semana.

3

Clasificar Contenido Rendimiento

Sort publicaciones by engagement tasa y views to identificar top 3 y bottom 3 performers.

4

Comparar Against Prior Week

Cargar last week's informe y compute week-over-week deltas for todos metricas clave.

5

Exportar Semanal Informe

Escribir un structured JSON informe con metricas, posicionamientos, y recommendations.

Implementacion en Python

Python
import requests, os, json
from pathlib import Path
from datetime import date, timedelta

API_KEY = os.environ["SCAVIO_API_KEY"]
TH = {"Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json"}
USERNAME = "your_tiktok_username"
REPORTS_DIR = Path("tiktok_reports")
REPORTS_DIR.mkdir(exist_ok=True)

def fetch_user_posts(username: str) -> list:
    resp = requests.post(
        "https://api.scavio.dev/api/v1/tiktok/user/posts",
        headers=TH,
        json={"username": username},
        timeout=15,
    )
    resp.raise_for_status()
    return resp.json().get("posts", [])

def calculate_metrics(posts: list) -> dict:
    if not posts:
        return {"total_views": 0, "total_likes": 0, "avg_engagement": 0}
    total_views = sum(p.get("views", 0) for p in posts)
    total_likes = sum(p.get("likes", 0) for p in posts)
    total_comments = sum(p.get("comments", 0) for p in posts)
    total_shares = sum(p.get("shares", 0) for p in posts)
    avg_engagement = (total_likes + total_comments) / max(total_views, 1) * 100
    return {
        "post_count": len(posts),
        "total_views": total_views,
        "total_likes": total_likes,
        "total_comments": total_comments,
        "total_shares": total_shares,
        "avg_engagement_rate": round(avg_engagement, 2),
    }

def run_review():
    posts = fetch_user_posts(USERNAME)
    metrics = calculate_metrics(posts)
    ranked = sorted(posts, key=lambda p: p.get("likes", 0) + p.get("comments", 0), reverse=True)
    top_3 = [{"url": p.get("url", ""), "likes": p.get("likes", 0), "views": p.get("views", 0)} for p in ranked[:3]]
    bottom_3 = [{"url": p.get("url", ""), "likes": p.get("likes", 0), "views": p.get("views", 0)} for p in ranked[-3:]]

    prev_file = REPORTS_DIR / f"report_{date.today() - timedelta(days=7)}.json"
    wow_delta = {}
    if prev_file.exists():
        prev = json.loads(prev_file.read_text())
        for key in ["total_views", "total_likes", "total_comments"]:
            prev_val = prev.get("metrics", {}).get(key, 0)
            wow_delta[key] = metrics[key] - prev_val

    report = {"date": str(date.today()), "metrics": metrics, "top_3": top_3, "bottom_3": bottom_3, "wow_delta": wow_delta}
    out = REPORTS_DIR / f"report_{date.today()}.json"
    out.write_text(json.dumps(report, indent=2))
    print(f"Weekly review: {metrics['post_count']} posts, {metrics['total_views']} views, {metrics['avg_engagement_rate']}% engagement")
    return report

run_review()

Implementacion en JavaScript

JavaScript
const TH = {'Authorization': 'Bearer '+process.env.SCAVIO_API_KEY, 'Content-Type': 'application/json'};
const fs = await import('fs');

const USERNAME = 'your_tiktok_username';
const REPORTS_DIR = 'tiktok_reports';
try { fs.mkdirSync(REPORTS_DIR); } catch {}

async function fetchUserPosts(username) {
  const r = await fetch('https://api.scavio.dev/api/v1/tiktok/user/posts', {method:'POST', headers:TH, body:JSON.stringify({username})});
  return (await r.json()).posts || [];
}

const posts = await fetchUserPosts(USERNAME);
const totalViews = posts.reduce((s,p)=>s+(p.views||0),0);
const totalLikes = posts.reduce((s,p)=>s+(p.likes||0),0);
const totalComments = posts.reduce((s,p)=>s+(p.comments||0),0);
const totalShares = posts.reduce((s,p)=>s+(p.shares||0),0);
const avgEngagement = totalViews > 0 ? Math.round((totalLikes+totalComments)/totalViews*10000)/100 : 0;
const metrics = {postCount:posts.length, totalViews, totalLikes, totalComments, totalShares, avgEngagementRate:avgEngagement};

const ranked = [...posts].sort((a,b)=>(b.likes||0)+(b.comments||0)-(a.likes||0)-(a.comments||0));
const top3 = ranked.slice(0,3).map(p=>({url:p.url||'', likes:p.likes||0, views:p.views||0}));
const bottom3 = ranked.slice(-3).map(p=>({url:p.url||'', likes:p.likes||0, views:p.views||0}));

const today = new Date().toISOString().split('T')[0];
const prevDate = new Date(Date.now()-7*86400000).toISOString().split('T')[0];
let wowDelta = {};
try {
  const prev = JSON.parse(fs.readFileSync(REPORTS_DIR+'/report_'+prevDate+'.json', 'utf8'));
  wowDelta = {totalViews: totalViews-(prev.metrics.totalViews||0), totalLikes: totalLikes-(prev.metrics.totalLikes||0)};
} catch {}

const report = {date:today, metrics, top3, bottom3, wowDelta};
fs.writeFileSync(REPORTS_DIR+'/report_'+today+'.json', JSON.stringify(report, null, 2));
console.log('Weekly review: '+metrics.postCount+' posts, '+metrics.totalViews+' views, '+metrics.avgEngagementRate+'% engagement');

Plataformas utilizadas

TikTok

Descubrimiento de videos, creadores y productos en tendencia

Preguntas frecuentes

TikTok analytics inside el app son limited y reset frequently. Este flujo de trabajo ejecuta cada Sunday tarde, pulls your reciente publicaciones via el Scavio TikTok API, calculates semanal rendimiento metricas (views, likes, comentarios, shares, engagement tasa), identifies your top y bottom performers, y exporta un structured informe. Use it to spot cual contenido formats funciona, cuando your audiencia es mas active, y que to double down on next semana. One semanal ejecutar costs about 2-3 credits ($0.01-$0.015).

Este flujo de trabajo usa un cron sunday 8 pm utc. Semanal Sunday 8 PM.

Este flujo de trabajo usa las siguientes plataformas de Scavio: tiktok. Cada plataforma se llama a traves del mismo endpoint de API unificado.

Si. El plan gratuito de Scavio incluye 50 creditos al registrarte sin tarjeta de credito. Es suficiente para probar y validar este flujo de trabajo antes de escalarlo.

Semanal TikTok Contenido Resena

Resena your TikTok contenido rendimiento semanal. Rastrear views, engagement, y tendencias to optimizar your posting estrategia.

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Alternativas

  • Alternativa a Tavily
  • Alternativa a SerpAPI
  • Alternativa a Firecrawl
  • Alternativa a Exa

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