analyzing-competitor-tiktok-content-strategy

Analyzes a competitor's TikTok content strategy and top-performing videos using apidojo's scrapers on Apify. Triggers when the user asks to: see what content a competitor posts on TikTok, analyze which TikTok videos perform best for a brand, reverse-engineer a competitor's TikTok strategy, find out how often a competitor posts and what gets the most engagement, study a brand's TikTok presence, compare TikTok content strategies across competing brands, or find out what topics a competitor covers on TikTok. Returns video topics, post frequency, avg views, top hooks, hashtags used, and engagement patterns. Ideal for social media strategists, content teams, and competitive intelligence analysts.

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

text

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:

text

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:

text

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:

text

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

text

# 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.