analyzing-competitor-tiktok-content-strategy …

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Analyzing Competitor TikTok Content Strategy

Scrapes a competitor's TikTok profile to pull their recent videos, engagement data, posting patterns, and hashtag usage. Reverse-engineers what's working for them so you can learn from it or differentiate against it.

Prerequisites

APIFY_TOKEN environment variable set
Optional: Apify MCP server installed

Inputs

Parameter	Type	Required	Default	Notes
`startUrls`	array	Optional	`[]`	TikTok URLs — user profiles, hashtags, music pages, search, locations
`keywords`	array	Optional	`[]`	Search keywords/terms to find posts
`sortType`	string	Optional	`RELEVANCE`	Sort order for keyword results: `RELEVANCE`, `MOST_LIKED`, `DATE_POSTED`
`location`	string	Optional	—	ISO 3166-1 alpha-2 country code for regional filtering (e.g. `US`, `GB`)
`maxItems`	number	Optional	Unlimited	Maximum posts to return across the run
`includeSearchKeywords`	boolean	Optional	`false`	Add the matched search keyword field to each post
`customMapFunction`	string	Optional	—	JavaScript function to transform each output object

Workflow

Progress:
- [ ] Step 1: Get competitor TikTok handle(s)
- [ ] Step 2: Pull profile stats with tiktok-profile-scraper
- [ ] Step 3: Pull recent videos with tiktok-scraper
- [ ] Step 4: Identify top-performing content patterns
- [ ] Step 5: Deliver content strategy analysis

Step 1: Clarify Parameters

Ask the user for:

Competitor TikTok handle(s) — up to 5 accounts (without @)
Number of recent videos to analyze (default: 50 — last 2-3 months of content)
Analysis focus — top content, posting cadence, hashtag strategy, or all three

Step 2: Pull Profile Stats

Recommended — run_actor.js (handles waiting, output, and file saving automatically):

bash

# Quick answer (prints table to chat)
node scripts/run_actor.js \
  --actor "apidojo~tiktok-scraper" \
  --input '{"param": "value"}'

# Save as CSV
node scripts/run_actor.js \
  --actor "apidojo~tiktok-scraper" \
  --input '{"param": "value"}' \
  --output YYYY-MM-DD_results.csv --format csv

# Save as JSON
node scripts/run_actor.js \
  --actor "apidojo~tiktok-scraper" \
  --input '{"param": "value"}' \
  --output YYYY-MM-DD_results.json --format json

APIFY_TOKEN must be set in environment or .env file.

If Apify MCP is available:

Tool: apify:run-actor
Actor: "apidojo~tiktok-profile-scraper"
Input:
{
  "usernames": ["[handle1]", "[handle2]"]
}

REST API fallback:

bash

curl -X POST \
  "https://api.apify.com/v2/acts/apidojo~tiktok-profile-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"usernames": ["[handle1]", "[handle2]"]}'

Extract: fans, heart (total likes), video count, following, bio text.

Step 3: Pull Recent Videos

If Apify MCP is available:

Tool: apify:run-actor
Actor: "apidojo~tiktok-scraper"
Input:
{
  "profiles": ["https://www.tiktok.com/@[handle1]", "https://www.tiktok.com/@[handle2]"]
}

REST API fallback:

bash

curl -X POST \
  "https://api.apify.com/v2/acts/apidojo~tiktok-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "profiles": ["https://www.tiktok.com/@[handle1]"]
  }'

Step 4: Analyze Content Patterns

From the video dataset, extract:

Top 10 videos by play count:

Title/caption, views, likes, comments, shares, date, hashtags

Posting frequency:

dates = [video.createTimeISO for each video]
days_covered = max(dates) - min(dates)
posting_rate = total_videos / days_covered (posts per day)

Hashtag analysis: Extract all hashtags across videos. Count frequency. Top 10 = their core hashtag strategy.

Content format patterns: From captions, classify videos into buckets:

Educational/Tutorial (contains: "how to", "tips", "learn", numbers like "5 ways")
Entertainment/Humor (reactions, trends, dances)
Promotional (product mentions, CTAs, "link in bio")
Behind-the-scenes (BTS, day-in-life, founder story)
UGC/Response (reply to comment format)

Hook patterns in top videos: Look at the first line of captions in the top 10 videos. What do they have in common?

Step 5: Format Analysis

Output Format

# TikTok Content Strategy Analysis: @[COMPETITOR]
Videos analyzed: [N] | Period: [start]–[end] | Date: [DATE]

## Account Overview
Followers: [N] | Total likes: [N] | Videos posted: [N] | Avg likes per video: [N]
Overall engagement rate: [X.X%]

## Posting Pattern
- Frequency: [X] videos per week
- Best-performing days: [day], [day] (based on publish date of top videos)
- Average video length: [X] seconds (if available)

## Top 5 Videos (by Views)
| # | Caption Excerpt | Views | Likes | Comments | Hashtags | Date |
|---|----------------|-------|-------|----------|----------|------|
| 1 | "[caption]"   | [N]   | [N]   | [N]      | [tags]   | [date] |

## Content Mix
| Format | % of Videos | Avg Views |
|--------|-------------|-----------|
| Educational | [X%] | [N] |
| Entertainment | [X%] | [N] |
| Promotional | [X%] | [N] |
| BTS/Story | [X%] | [N] |

## Top Hashtags Used
1. #[tag] — used in [N] of [total] videos
2. #[tag] — [N] videos
3. #[tag] — [N] videos

## Hook Patterns in Top Content
- Top performing hooks start with: [pattern — e.g., questions, numbers, bold claims]
- Example: "[first line of top video]"

## What's Working for Them
1. [Insight 1 — specific, actionable]
2. [Insight 2]
3. [Insight 3]

## Gap / Differentiation Opportunity
[What they're NOT doing that could be a strategic opening]

Troubleshooting

Profile scraper returns no videos: The account may have few posts or have gone inactive. Check the handle. Top videos all very old: Account may have slowed down. Note this in the analysis. Hashtags missing from results: Some captions don't use hashtags. Analyze caption text for topic signals instead.

analyzing-competitor-tiktok-content-strategy