Ejecutar una campaña de hashtag en TikTok sin seguimiento es volar a ciegas. Necesita saber: cuántos videos usaron su hashtag, el total de vistas generadas, qué creadores generaron la mayor participación y cuál es la tendencia de la campaña a lo largo del tiempo. Este tutorial crea un rastreador de campañas de hashtag utilizando los puntos finales de la API de Scavio TikTok. Realice un seguimiento del rendimiento de la campaña, identifique el contenido de mejor rendimiento y genere informes a $0,005 por llamada a la API.
Requisitos previos
- Python 3.9+ instalado
- solicita biblioteca instalada
- Una clave API de Scavio de scavio.dev
- Una campaña de hashtag de TikTok para realizar un seguimiento
Guia paso a paso
Paso 1: Extraer datos de descripción general del hashtag
Utilice el punto final del hashtag para obtener el recuento total de vídeos y ver las estadísticas del hashtag de su campaña.
Python
import os, requests, time, json
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'}
def get_hashtag_overview(hashtag: str) -> dict:
"""Get hashtag stats overview."""
resp = requests.post(f'{TT_URL}/hashtag', headers=TT_H,
json={'hashtag': hashtag})
data = resp.json().get('data', {})
challenge = data.get('challengeInfo', data)
stats = challenge.get('stats', data.get('stats', {}))
return {
'hashtag': hashtag,
'video_count': stats.get('videoCount', 0),
'view_count': stats.get('viewCount', 0),
'timestamp': datetime.now().isoformat(),
}
overview = get_hashtag_overview('tiktokmademebuyit')
print(f"Hashtag: #{overview['hashtag']}")
print(f"Videos: {overview['video_count']:,}")
print(f"Views: {overview['view_count']:,}")Paso 2: Obtener y analizar vídeos de campaña
Coloque videos debajo del hashtag de su campaña. Analice las tasas de participación, identifique a los principales creadores y realice un seguimiento de los temas de contenido.
Python
def get_campaign_videos(hashtag: str, count: int = 20) -> list:
"""Get videos from a hashtag campaign."""
resp = requests.post(f'{TT_URL}/hashtag/videos', headers=TT_H,
json={'hashtag': hashtag, 'count': count, 'cursor': 0})
videos = resp.json().get('data', {}).get('videos', [])
results = []
for v in videos:
stats = v.get('stats', {})
author = v.get('author', {})
views = stats.get('playCount', 0)
likes = stats.get('diggCount', 0)
comments = stats.get('commentCount', 0)
shares = stats.get('shareCount', 0)
eng_rate = (likes + comments + shares) / views if views > 0 else 0
results.append({
'video_id': v.get('id', ''),
'description': v.get('desc', '')[:100],
'author': author.get('uniqueId', ''),
'author_followers': author.get('stats', {}).get('followerCount', 0) if isinstance(author.get('stats'), dict) else 0,
'views': views,
'likes': likes,
'comments': comments,
'shares': shares,
'engagement_rate': eng_rate,
})
results.sort(key=lambda x: x['views'], reverse=True)
return results
videos = get_campaign_videos('tiktokmademebuyit')
print(f'Campaign videos: {len(videos)}')
print('\nTop performers:')
for v in videos[:5]:
print(f' {v["views"]:>12,} views | {v["engagement_rate"]:5.1%} eng | @{v["author"]:15s} | {v["description"][:30]}')Paso 3: Identificar los principales creadores y patrones de contenido
Descubra qué creadores generan la mayor participación en la campaña y qué patrones de contenido funcionan mejor.
Python
def analyze_campaign_creators(videos: list) -> dict:
"""Identify top creators and content patterns."""
creator_stats = {}
for v in videos:
author = v['author']
if author not in creator_stats:
creator_stats[author] = {'videos': 0, 'total_views': 0,
'total_likes': 0, 'total_engagement': 0}
cs = creator_stats[author]
cs['videos'] += 1
cs['total_views'] += v['views']
cs['total_likes'] += v['likes']
cs['total_engagement'] += v['engagement_rate']
# Calculate averages and rank
ranked = []
for author, stats in creator_stats.items():
stats['author'] = author
stats['avg_engagement'] = stats['total_engagement'] / stats['videos'] if stats['videos'] else 0
stats['avg_views'] = stats['total_views'] / stats['videos'] if stats['videos'] else 0
ranked.append(stats)
ranked.sort(key=lambda x: x['total_views'], reverse=True)
# Engagement analysis
all_eng = [v['engagement_rate'] for v in videos]
avg_eng = sum(all_eng) / len(all_eng) if all_eng else 0
all_views = [v['views'] for v in videos]
return {
'unique_creators': len(creator_stats),
'top_creators': ranked[:10],
'avg_engagement': avg_eng,
'total_views': sum(all_views),
'avg_views': sum(all_views) / len(all_views) if all_views else 0,
}
analysis = analyze_campaign_creators(videos)
print(f"Unique creators: {analysis['unique_creators']}")
print(f"Total views: {analysis['total_views']:,}")
print(f"Avg engagement: {analysis['avg_engagement']:.1%}")
print(f"\nTop creators:")
for c in analysis['top_creators'][:5]:
print(f" @{c['author']:15s} | {c['videos']} videos | {c['total_views']:>10,} views | {c['avg_engagement']:.1%} eng")Paso 4: Crear el informe de seguimiento de la campaña
Generar un informe completo de campaña. Realice un seguimiento del hashtag a lo largo del tiempo ejecutándolo periódicamente y comparando instantáneas.
Python
TRACKING_FILE = 'campaign_tracker.json'
def load_tracking_history() -> list:
if os.path.exists(TRACKING_FILE):
with open(TRACKING_FILE) as f:
return json.load(f)
return []
def save_tracking_snapshot(snapshot: dict):
history = load_tracking_history()
history.append(snapshot)
with open(TRACKING_FILE, 'w') as f:
json.dump(history, f, indent=2)
def campaign_report(hashtag: str) -> dict:
"""Generate a full campaign tracking report."""
overview = get_hashtag_overview(hashtag)
time.sleep(0.3)
videos = get_campaign_videos(hashtag, count=20)
analysis = analyze_campaign_creators(videos)
snapshot = {
'timestamp': datetime.now().isoformat(),
'hashtag': hashtag,
'video_count': overview['video_count'],
'total_views': analysis['total_views'],
'unique_creators': analysis['unique_creators'],
'avg_engagement': analysis['avg_engagement'],
'top_creator': analysis['top_creators'][0]['author'] if analysis['top_creators'] else '',
'credits_used': 2,
'cost': 0.010,
}
save_tracking_snapshot(snapshot)
# Check growth vs previous snapshot
history = load_tracking_history()
if len(history) >= 2:
prev = history[-2]
view_growth = snapshot['total_views'] - prev.get('total_views', 0)
creator_growth = snapshot['unique_creators'] - prev.get('unique_creators', 0)
print(f'Growth since last check:')
print(f' Views: +{view_growth:,}')
print(f' Creators: +{creator_growth}')
print(f'\nCampaign Report: #{hashtag}')
print(f' Total videos: {overview["video_count"]:,}')
print(f' Sample views: {analysis["total_views"]:,} (from {len(videos)} videos)')
print(f' Unique creators: {analysis["unique_creators"]}')
print(f' Avg engagement: {analysis["avg_engagement"]:.1%}')
print(f' Top creator: @{snapshot["top_creator"]}')
print(f' Tracking cost: ${snapshot["cost"]}')
print(f' History: {len(history)} snapshots')
return snapshot
campaign_report('tiktokmademebuyit')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 track_hashtag(hashtag):
# Hashtag overview
resp = requests.post('https://api.scavio.dev/api/v1/tiktok/hashtag', headers=TT_H,
json={'hashtag': hashtag})
stats = resp.json().get('data', {}).get('stats', {})
time.sleep(0.3)
# Recent videos
resp2 = requests.post('https://api.scavio.dev/api/v1/tiktok/hashtag/videos', headers=TT_H,
json={'hashtag': hashtag, 'count': 10, 'cursor': 0})
videos = resp2.json().get('data', {}).get('videos', [])
total_plays = sum(v.get('stats', {}).get('playCount', 0) for v in videos)
creators = len(set(v.get('author', {}).get('uniqueId', '') for v in videos))
print(f'#{hashtag}: {stats.get("videoCount", 0):,} total videos')
print(f' Recent sample: {total_plays:,} plays from {creators} creators')
track_hashtag('tiktokmademebuyit')Ejemplo en JavaScript
JavaScript
const SCAVIO_KEY = process.env.SCAVIO_API_KEY;
const TT_H = { Authorization: `Bearer ${SCAVIO_KEY}`, 'Content-Type': 'application/json' };
async function trackHashtag(hashtag) {
const overview = await fetch('https://api.scavio.dev/api/v1/tiktok/hashtag', {
method: 'POST', headers: TT_H, body: JSON.stringify({ hashtag })
}).then(r => r.json());
const stats = overview.data?.stats || {};
const videos = await fetch('https://api.scavio.dev/api/v1/tiktok/hashtag/videos', {
method: 'POST', headers: TT_H, body: JSON.stringify({ hashtag, count: 10, cursor: 0 })
}).then(r => r.json());
const vids = videos.data?.videos || [];
const plays = vids.reduce((s, v) => s + (v.stats?.playCount || 0), 0);
const creators = new Set(vids.map(v => v.author?.uniqueId)).size;
console.log(`#${hashtag}: ${(stats.videoCount || 0).toLocaleString()} total videos`);
console.log(` Recent: ${plays.toLocaleString()} plays from ${creators} creators`);
}
trackHashtag('tiktokmademebuyit');Salida esperada
JSON
Hashtag: #tiktokmademebuyit
Videos: 45,200,000
Views: 892,000,000,000
Campaign videos: 20
Top performers:
8,234,567 views | 7.2% eng | @shopqueen | This product is everything I
5,891,234 views | 5.8% eng | @dealsunder50 | Amazon finds you NEED from T
Unique creators: 18
Total views: 28,450,000
Avg engagement: 5.4%
Campaign Report: #tiktokmademebuyit
Total videos: 45,200,000
Sample views: 28,450,000 (from 20 videos)
Unique creators: 18
Avg engagement: 5.4%
Top creator: @shopqueen
Tracking cost: $0.010
History: 1 snapshots