> ## Documentation Index
> Fetch the complete documentation index at: https://docs.veedcrawl.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Compare Competitors Using Video Content Data
> Analyze multiple creators in parallel — posting frequency, engagement rates, top content, and hook formats — starting from usernames alone.
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.
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.
```bash TikTok theme={null}
# 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"
```
```bash Instagram theme={null}
# 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:
```json theme={null}
{
"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.
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.
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.
Send each top-performing video URL to `/v1/extract` with a prompt designed to surface the patterns you want to compare across creators.
```bash theme={null}
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`:
```bash theme={null}
curl "https://api.veedcrawl.com/v1/extract/job_xyz456" \
-H "x-api-key: YOUR_KEY"
```
```json theme={null}
{
"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.
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.