Trending Ad Hook Spotter

Trending Ad Hook Spotter

Scan social platforms for what's trending in your space right now — viral posts, hot debates, breaking news, memes — and translate each trend into a concrete ad hook you can run while the topic is still hot.

Core principle: The highest-performing ads ride cultural and industry moments. This skill finds those moments before your competitors do and tells you exactly how to capitalize.

When to Use

• "What's trending in our space that we could run ads about?"
• "Find viral hooks for our paid campaigns"
• "What topics are hot in [industry] right now?"
• "I want to ride a trend with a paid campaign"
• "What should we be running ads about this week?"

Prerequisites

• Environment variable: APIFY_API_TOKEN — required for Reddit scraping (optional if using only web_search + HN API)
• Web search access — your AI agent must support web_search or equivalent for Twitter/X and LinkedIn lookups
• No API key needed for Hacker News (Algolia HN API is free and public)

Phase 0: Intake

1. Your product — Name + one-line description
2. Industry/category — What space are you in? (e.g., "AI sales tools", "developer infrastructure")
3. ICP keywords — 5-10 keywords that define your buyer's world
4. Competitor names — So we can spot when they become part of a trend
5. Platforms to scan (default: all):
   • Twitter/X
   • Reddit (specific subreddits if known)
   • LinkedIn
   • Hacker News
6. Content velocity — How fast can you create ads? (Same-day / 2-3 days / Weekly)

Phase 1: Social Scanning

1A: Twitter/X Trend Scan (web_search)

Use web_search with site:x.com or site:twitter.com to find trending posts — no scraper or credentials needed:

# Industry trending topics
web_search: "<industry keyword> (viral OR trending OR hot take OR thread) site:x.com"

# Competitor mentions (momentum signals)
web_search: "<competitor1> OR <competitor2> (raised OR launched OR shut down OR acquired OR outage) site:x.com"

# Pain/frustration spikes
web_search: "<category> (broken OR frustrating OR tired of OR switched from) site:x.com"

Run 3-5 queries to cover:

• Industry trending topics and hot takes
• Competitor momentum signals (launches, outages, funding)
• Pain/frustration spikes in the category
• Viral threads with high engagement

Score each tweet/thread by engagement velocity (likes + retweets relative to account size and age).

1B: Reddit Trend Scan (Apify)

Use the trudax/reddit-scraper-lite actor to scan relevant subreddits for hot posts:

Browse specific subreddits (for trending/hot posts):

POST https://api.apify.com/v2/acts/trudax~reddit-scraper-lite/runs?token=$APIFY_API_TOKEN
Content-Type: application/json

{
  "startUrls": [
    {"url": "https://www.reddit.com/r/SUBREDDIT1/hot/"},
    {"url": "https://www.reddit.com/r/SUBREDDIT2/hot/"}
  ],
  "maxItems": 30
}

Search by keyword (for specific topics):

POST https://api.apify.com/v2/acts/trudax~reddit-scraper-lite/runs?token=$APIFY_API_TOKEN
Content-Type: application/json

{
  "searches": ["<industry keyword> OR <competitor>"],
  "maxItems": 30
}

Poll until the run finishes:

GET https://api.apify.com/v2/acts/trudax~reddit-scraper-lite/runs/{RUN_ID}?token=$APIFY_API_TOKEN

When status is SUCCEEDED, fetch results:

GET https://api.apify.com/v2/datasets/{DATASET_ID}/items?token=$APIFY_API_TOKEN

Output fields: Each item has dataType ("post" or "comment"), title (posts only), body, communityName, upVotes, numberOfComments (posts), url, createdAt.

Look for:

• Posts with unusually high upvote/comment ratios
• "What do you use for [X]?" threads (buying intent)
• Complaint threads about incumbents
• "I just switched from X to Y" posts

1C: LinkedIn Trend Scan (web_search)

Use web_search with site:linkedin.com/posts to find high-engagement KOL posts — no scraper or credentials needed:

web_search: "<industry keyword> site:linkedin.com/posts"
web_search: "<competitor_name> site:linkedin.com/posts"
web_search: "<KOL_name> <industry keyword> site:linkedin.com/posts"
web_search: "<trending topic> site:linkedin.com/pulse"

Run queries for:

• 5-10 key opinion leaders (KOLs) in the space — search their names + topic keywords
• Industry-level keyword searches to find viral posts
• Competitor mentions from thought leaders

Identify high-engagement posts on topics relevant to your product category.

1D: Hacker News Scan (Algolia HN API)

Use the free Algolia HN Search API — no API key needed:

Search for relevant stories:

GET https://hn.algolia.com/api/v1/search?query=KEYWORD&tags=story&hitsPerPage=20

Search for recent stories (past 7 days):

GET https://hn.algolia.com/api/v1/search?query=KEYWORD&tags=story&numericFilters=created_at_i>UNIX_TIMESTAMP_7_DAYS_AGO&hitsPerPage=20

Get front page stories (current trending):

GET https://hn.algolia.com/api/v1/search?tags=front_page&hitsPerPage=30

The response includes points, num_comments, title, url, and created_at for each story. Sort by points to find the highest-engagement discussions.

Run queries for:

• Each ICP keyword
• Each competitor name
• The product category
• Check front page for anything tangentially related

Phase 2: Trend Identification & Scoring