Knowing what your competitors post on TikTok and how their audience responds reveals gaps you can exploit. This tutorial builds a competitor monitoring pipeline that tracks posting frequency, content themes, top-performing video styles, and engagement benchmarks for a list of competitor accounts. Each profile check costs $0.005 and each post fetch costs $0.005 via the Scavio TikTok API with Bearer token authentication.
Prerequisites
- Python 3.9+ installed
- requests library installed
- A Scavio API key from scavio.dev
- A list of competitor TikTok usernames
Walkthrough
Step 1: Set up the competitor list and fetch profiles
Define your competitors and pull their profile stats to establish baseline metrics.
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)Step 2: Fetch and analyze competitor posting patterns
Pull each competitor's recent posts and analyze posting frequency, typical engagement rates, and content themes.
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,
}Step 3: Generate a competitive benchmark report
Compile all competitor data into a benchmark report that shows where you stand relative to competitors and identifies content gaps.
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)Python Example
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)JavaScript Example
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); } })();Expected Output
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)