Compare Competitors Using Video Content Data

Veedcrawl’s profile endpoints let you run competitive analysis across multiple creators at the same time without needing a single video URL up front. Fetch profiles for each competitor, compare their posting behavior and engagement data, isolate their top-performing videos, then extract what makes those videos work. The entire workflow starts from usernames.

Fetch profiles for each competitor

Send a profile request for each creator you want to compare. You can run these in parallel — each returns bio info, stats, and up to 24 recent videos with per-post engagement data.

# Competitor 1
curl "https://api.veedcrawl.com/v1/tiktok/profile?username=competitor1&limit=24" \
  -H "x-api-key: YOUR_KEY"

# Competitor 2
curl "https://api.veedcrawl.com/v1/tiktok/profile?username=competitor2&limit=24" \
  -H "x-api-key: YOUR_KEY"

# Competitor 3
curl "https://api.veedcrawl.com/v1/tiktok/profile?username=competitor3&limit=24" \
  -H "x-api-key: YOUR_KEY"

# Competitor 1
curl "https://api.veedcrawl.com/v1/instagram/profile?username=competitor1&limit=24" \
  -H "x-api-key: YOUR_KEY"

# Competitor 2
curl "https://api.veedcrawl.com/v1/instagram/profile?username=competitor2&limit=24" \
  -H "x-api-key: YOUR_KEY"

# Competitor 3
curl "https://api.veedcrawl.com/v1/instagram/profile?username=competitor3&limit=24" \
  -H "x-api-key: YOUR_KEY"

Each response contains a videos array with the creator’s most recent posts. Here is the shape of a single TikTok profile response:

{
  "platform": "tiktok",
  "type": "profile",
  "username": "charlidamelio",
  "author": {
    "username": "charlidamelio",
    "displayName": "charli d'amelio",
    "verified": false
  },
  "stats": {
    "followers": null,
    "following": null,
    "likes": null,
    "videos": 847
  },
  "videos": [
    {
      "platform": "tiktok",
      "type": "video",
      "id": "7380000000000000000",
      "url": "https://www.tiktok.com/@charlidamelio/video/738...",
      "title": "this one goes out to everyone who said i couldn't dance",
      "description": "#fyp #dance",
      "stats": { "views": 14200000, "likes": 2100000, "comments": 18400, "shares": 312000 },
      "media": { "type": "video", "duration": 28.4, "thumbnailUrl": "https://..." },
      "tags": ["fyp", "dance"],
      "createdAt": "2026-04-21T14:33:00.000Z"
    }
  ]
}

Use the limit parameter (1–24) to control how many recent videos you retrieve per creator. Set limit=24 for the most complete picture, or limit=6 for a faster snapshot of just their most recent content.

Compare posting frequency, views, hashtags, and engagement

With profile data for all three creators, compute summary statistics across the videos arrays:

Posting frequency — count videos per creator over the createdAt date range
Average views — mean of video.stats.views across all posts
Top hashtags — aggregate and rank video.tags arrays by frequency
Engagement ratio — likes / views per video, then averaged per creator

A quick comparison table from three profile responses might look like:

Creator	Videos (30d)	Avg views	Top tag	Avg engagement
competitor1	18	2.4M	#fyp	14.8%
competitor2	9	890K	#tutorial	9.2%
competitor3	24	410K	#comedy	22.1%

Posting more does not always mean higher engagement. Use these numbers to identify which creator’s format is most efficient, not just most active.

Identify each creator's top-performing videos

Sort each creator’s videos array by stats.views or stats.likes descending. Select the top 2–3 posts per creator to analyze further.These are the videos worth extracting content patterns from — they represent what the algorithm is actually rewarding for that creator in that time window.

Extract content structure from top videos

Send each top-performing video URL to /v1/extract with a prompt designed to surface the patterns you want to compare across creators.

curl -X POST "https://api.veedcrawl.com/v1/extract" \
  -H "x-api-key: YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "url": "https://www.tiktok.com/@competitor1/video/738...",
    "prompt": "Identify the hook format, key claims, and call to action"
  }'

Poll the returned jobId:

curl "https://api.veedcrawl.com/v1/extract/job_xyz456" \
  -H "x-api-key: YOUR_KEY"

{
  "jobId": "job_xyz456",
  "status": "completed",
  "resultJson": {
    "hook_format": "Opens with a bold question addressed directly to camera",
    "key_claims": ["Most people are doing this wrong", "You only need three things"],
    "call_to_action": "Follow for part 2"
  }
}

Run this for your top 2–3 videos from each creator. The goal is to surface patterns — which hook formats appear in multiple top performers, which CTA types correlate with higher shares.

Synthesize findings into a competitive audit

Combine the quantitative profile data with the qualitative extraction results:

Volume and cadence — who posts how often, and does cadence correlate with reach?
Format patterns — which hook types and content structures show up in top performers?
Engagement efficiency — which creator gets the most engagement per post relative to their audience?
Content gaps — which topics or formats appear in one creator’s top content but not others?
CTA strategies — follow, link in bio, comment, share — which drives more interaction?

The full workflow — from three usernames to a structured competitive audit — runs on profile data alone. You only spend credits on extract jobs for the specific videos worth deeper analysis.

Profile endpoints run on the light rate limit tier: 120 requests per minute. At 24 posts per call, that gives you up to 2,880 posts of performance data per minute — enough to cover dozens of creators in a single run.

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Compare Competitors Using Video Content Data