Browser

monitoring-tiktok-mentions-of-brand

Try it

Monitors TikTok for brand mentions and product discussions using apidojo's TikTok scraper on Apify. Triggers when the user asks to: track mentions of a brand on TikTok, monitor TikTok hashtags for brand content, find TikTok videos talking about a product or company, see what TikTok says about a brand this week, track TikTok reactions to a product launch, find TikTok creators who mentioned a competitor brand, monitor brand sentiment on TikTok, or discover viral TikTok content about a specific brand or product. Returns creator handle, views, likes, comments, sentiment signal, and video caption excerpt. Ideal for brand managers, community teams, crisis communications, and product marketing teams.

What it does

Tracks TikTok content mentioning a brand via branded hashtags and keyword searches. TikTok is the fastest-moving platform for brand sentiment — viral criticism or praise can emerge in hours.

The skill document

Monitoring TikTok Mentions of a Brand

Tracks TikTok content mentioning a brand via branded hashtags and keyword searches. TikTok is the fastest-moving platform for brand sentiment — viral criticism or praise can emerge in hours.

Prerequisites

  • APIFY_TOKEN environment variable set
  • Optional: Apify MCP server installed

Inputs

ParameterTypeRequiredDefaultNotes
startUrlsarrayOptional[]TikTok URLs — user profiles, hashtags, music pages, search, locations
keywordsarrayOptional[]Search keywords/terms to find posts
sortTypestringOptionalRELEVANCESort order for keyword results: RELEVANCE, MOST_LIKED, DATE_POSTED
locationstringOptional—ISO 3166-1 alpha-2 country code for regional filtering (e.g. US, GB)
maxItemsnumberOptionalUnlimitedMaximum posts to return across the run
includeSearchKeywordsbooleanOptionalfalseAdd the matched search keyword field to each post
customMapFunctionstringOptional—JavaScript function to transform each output object

Workflow

Progress:
- [ ] Step 1: Run tiktok-scraper for branded hashtags
- [ ] Step 2: Filter by view count and date
- [ ] Step 3: Classify sentiment and content type
- [ ] Step 4: Identify trending posts and crisis signals
- [ ] Step 5: Deliver monitoring report

Step 1: Run the Actor

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

# 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-scraper"
Input:
{
  "keywords": ["#[BRAND]", "#[BRAND]review", "#[BRAND]honest"],
  "maxItems": 200
}

REST API fallback:

curl -X POST   "https://api.apify.com/v2/acts/apidojo~tiktok-scraper/runs?token=$APIFY_TOKEN"   -H "Content-Type: application/json"   -d '{
    "keywords": ["#[brand]", "#[brand]review", "#[brand]honest"],
    "maxItems": 200
  }'

Step 2: Classify and Score

Content type:

UNBOXING = "unboxing", "first impression", "first look"
REVIEW = "review", "honest", "real talk", "thoughts on"
COMPLAINT = "disappointed", "refund", "scam", "doesn't work", "returning"
TUTORIAL = "how to", "tips", "tutorial"
ENTERTAINMENT = trend audio, no product focus

Sentiment (lexical — same model as Twitter sentiment skill):

  • Use positive/negative/neutral indicators
  • Weight by diggCount (likes) as community agreement signal

Virality signal:

virality = playCount / (follower_count_of_creator + 1)

If virality > 2.0: post is reaching well beyond the creator's audience — flag as TRENDING

Step 3: Crisis Detection

Flag CRISIS_ALERT when:

  • Any single post with playCount > 500K AND sentiment = NEGATIVE
  • More than 5 complaint posts in 48 hours
  • Comment-to-view ratio > 3% on a negative post (high engagement = controversy)

Step 4: Edge Cases

  • Hashtag overloaded with unrelated content: Add brand sub-product or model name to narrow
  • Brand has low TikTok presence (< 10 posts): This is notable data — report it; brand may need proactive TikTok strategy
  • Duet/Stitch posts about brand: These count as mentions but are often reactions to original content — classify as REACTION and note the source video

Output Format

# TikTok Brand Monitor: [BRAND_NAME]
Period: [DATE_RANGE] | Posts collected: [N] | Total estimated reach: [N] views | Date: [DATE]

## Overall Sentiment
Positive: [X%] | Negative: [X%] | Neutral: [X%]
⚠️ CRISIS ALERTS: [N] (posts above threshold — see below)

## Content Type Distribution
Unboxing: [N] | Reviews: [N] | Complaints: [N] | Tutorials: [N]

## Trending Posts (> 100K Views)
| Creator | @Handle | Views | Likes | Sentiment | Type | Caption Preview |
|---------|---------|-------|-------|-----------|------|----------------|

## CRISIS ALERTS (Negative + High Reach)
| Creator | Views | Complaint Theme | Days Live | Post URL |
|---------|-------|----------------|-----------|---------|

## Top Advocates
| Creator | @Handle | Followers | Views | Post Type | Score |
|---------|---------|-----------|-------|----------|-------|

Troubleshooting

Very few posts found: Brand may be using a different hashtag convention. Try product name without brand (#[product] not #[brand]product). All results are unboxing/haul content: Normal for consumer brands — this is positive. Set monitoring to alert only on negative content. Crisis alert triggered by troll campaign: Check if complaint posts are from a cluster of new accounts (created within 30 days, < 100 followers) — may be coordinated; note this context in report.

Related skills

AdMapix

Fetch raw ad creative, app, ranking, and revenue data from AdMapix as structured JSON.

by fly0pants4.3k installs296 stars

diagram-generator

Generate and edit Draw.io, Mermaid, and Excalidraw diagrams from natural language using a structured JSON spec.

by nssa.io1.0k installs47 stars

Join meeting

Join a video meeting as an AI bot with voice, avatar, and screenshare across four operating modes.

by johnpatternai21 installs8 stars

Productivity

Find why your productivity system keeps failing, then apply the smallest fix — capacity math, bottleneck routing, durable local notes.

by Iván855 installs69 stars

Memory

Stores durable facts in a categorized, plain-markdown vault on disk, alongside your agent's built-in memory.

by Iván558 installs18 stars

More from apidojo-io

Browse all skills

tracking-twitter-thought-leaders

Identifies and tracks thought leaders and key voices in any industry on Twitter/X using apidojo's scrapers. Triggers when the user asks to: find the top voices in an industry on Twitter, identify thought leaders in a niche, discover who has the most influence in a topic area on X, find experts tweeting about a subject, build a list of influencers to engage with on Twitter, track who is gaining followers fastest in a category, or identify key opinion leaders in a field for PR or partnership outreach. Returns name, handle, follower count, engagement rate, bio keywords, and recent top tweets. Ideal for PR teams, community managers, and B2B content marketers.

by apidojo-io1 installs

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.

by apidojo-io1 installs

building-journalist-outreach-list-from-twitter

Builds targeted journalist and media contact lists from Twitter/X using apidojo's Twitter scrapers on Apify. Triggers when the user asks to: find journalists covering a specific beat or topic on Twitter, build a media outreach list from Twitter, identify reporters writing about an industry, find editors or writers at specific publications on X, create a PR contact list from Twitter, discover freelance journalists in a niche, or compile a list of media contacts for a press release or story pitch. Returns name, handle, publication affiliation from bio, follower count, and recent article topics. Ideal for PR agencies, startup communications teams, and founders doing press outreach.

by apidojo-io1 installs

discovering-viral-tiktok-content-trends

Discovers viral content trends and trending formats on TikTok using apidojo's TikTok scraper on Apify. Triggers when the user asks to: find trending content formats on TikTok, discover what is going viral on TikTok in a niche, identify viral TikTok hooks or video styles to adapt, research TikTok trends for a product category, find what content formats are performing best on TikTok right now, discover trending sounds or concepts in a niche on TikTok, or analyze what drives viral TikTok engagement in a specific category. Returns trending hashtags, view counts, engagement metrics, content format patterns, and hook analysis. Ideal for TikTok content creators, brand social teams, and video content strategists.

by apidojo-io1 installs

extracting-tiktok-comments-for-research

Extracts and analyzes TikTok comments from any video or creator using apidojo's TikTok Comments scraper on Apify. Triggers when the user asks to: scrape TikTok comments from a video, analyze what viewers say about a TikTok post, extract comment data for sentiment analysis, find top comments on a viral TikTok video, collect TikTok user feedback from comments, build a dataset of TikTok community reactions, study audience sentiment on TikTok content, or research what a target audience cares about from TikTok comments. Returns commenter username, comment text, likes on comment, reply count, and timestamp. Ideal for market researchers, brand managers, content creators, and academic researchers.

by apidojo-io1 installs

finding-software-engineers-on-twitter

Finds software engineers and developers to recruit using apidojo's Twitter scrapers on Apify. Triggers when the user asks to: find software engineers on Twitter for recruiting, discover developers to hire from their Twitter profile, find backend frontend or full-stack engineers on X for talent sourcing, identify programmers by tech stack on Twitter, find software engineers who are open to work on Twitter, build a developer recruiting pipeline from social, or find engineers tweeting about job search or career changes. Returns handle, name, tech stack (from bio/tweets), follower count, and open-to-work signals. Ideal for technical recruiters, startup hiring managers, and engineering talent acquisition teams.

by apidojo-io1 installs