# We Replaced Our $999/Mo Trigify Subscription With $50/Mo of APIs. Here's the System. *Published: 03/06/2026* LinkedIn engagement tracking. Intent signals. Lead scoring. Trigify does all of it — and charges accordingly. We needed the same data across multiple campaigns but couldn't justify $999/month. So we b # We Replaced Our $999/Mo Trigify Subscription With $50/Mo of APIs. Here's the System. *LinkedIn engagement tracking. Intent signals. Lead scoring. Trigify does all of it — and charges accordingly. We needed the same data across multiple campaigns but couldn't justify $999/month. So we built our own. Here's the exact stack, scoring logic, cron jobs, and cost breakdown.* --- ## What Trigify Does (And Why It Works) Trigify tracks LinkedIn engagement in real-time. Someone comments on a competitor's post about sales automation? Trigify catches it. A VP at your target account likes three posts about "scaling outbound"? Trigify flags them. The value: people who engage with relevant LinkedIn content are signaling intent. They're not just scrolling — they're actively thinking about the problem you solve. We used it. It worked. We were paying $999/month for it. Then we needed to track multiple ICPs across different campaigns, and the math stopped making sense. --- ## Why We Built Our Own Three reasons: **1. Multi-campaign economics didn't work** We run cold email for clients across different industries. Each campaign needs different engagement signals, different keywords, different scoring logic. - Campaign A: Franchise candidates engaging with business ownership content - Campaign B: Marketing leaders engaging with SEO influencers (Neil Patel, Rand Fishkin) - Campaign C: SaaS buyers engaging with sales automation posts Trigify's pricing makes sense for one team tracking one ICP. At our scale, we were looking at $999-2,000/month minimum. **2. We needed custom scoring** Trigify gives you the engagement. You decide what it means. We wanted scoring baked in. Not "this person liked a post" but "this is a 75-point lead because they're a Director-level in our target industry, in our target location, showing ownership interest, with high engagement." That's custom logic. **3. We were already in the stack** Clay for enrichment. Apify for scraping. Webhooks everywhere. Building LinkedIn tracking into existing infrastructure was less work than another SaaS integration. --- ## The System: 4 Components `┌─────────────────────────────────────────────────┐

│ LINKEDIN INTENT SYSTEM │

├─────────────────────────────────────────────────┤

│ │

│ [Apify Actor] → [Scoring Engine] → [Clay] │

│ LinkedIn Post Node.js Script Webhook │

│ Search + State File + CRM │

│ │

│ ↑ │

│ Cron Job (Daily 7 AM ET) │

└─────────────────────────────────────────────────┘

` ### Component 1: Apify LinkedIn Post Search We use `harvestapi~linkedin-post-search`. Feed it queries, get structured post data. **Use Case A — Franchise Candidates:** `const SEARCH_QUERIES = [

"laid off considering business ownership",

"severance starting my own",

"funemployment what's next",

"tired of corporate want to own",

"VP laid off",

"Director position eliminated"

];

`**Use Case B — SEO/Marketing Leaders:** `const MONITORED_PROFILES = [

{ name: "Neil Patel", username: "neilkpatel" },

{ name: "Rand Fishkin", username: "randfishkin" },

{ name: "Alex Hormozi", username: "alexhormozi" }

];

// Scrape engagers on their recent posts

`Same infrastructure, different queries. **What Apify returns:** - Post content and URL - Author name, title, LinkedIn URL - Engagement metrics (likes, comments, shares) - Post date **Cost:** $1-3 per run depending on volume. ### Component 2: The Scoring Engine Raw posts mean nothing. A student posting about their "entrepreneurship journey" isn't a lead. A former VP of Sales posting about their severance package? Gold. We score every engager/author on multiple dimensions: `// ========== SCORING CONFIG ==========

// Title match (+30 points)

const TARGET_TITLES = [

'director', 'vp', 'vice president', 'svp',

'ceo', 'cfo', 'coo', 'cmo', 'cto', 'cro',

'general manager', 'regional manager',

'managing director', 'head of'

];

// Industry match (+20 points)

const TARGET_INDUSTRIES = [

'medical device', 'pharma', 'healthcare',

'financial services', 'banking', 'technology',

'consulting', 'saas', 'software'

];

// Location match (+15 points)

const TARGET_LOCATIONS = [

'florida', 'texas', 'pennsylvania', 'michigan',

'north carolina', 'colorado', 'arizona', 'ohio'

];

// Intent signals (+25 points max)

const HIGH_PRIORITY_SIGNALS = [

'own boss', 'business ownership', 'franchise',

'buy a business', 'entrepreneurship', 'severance',

'next chapter', 'building something'

];

// High engagement bonus (+20 points for 100+ engagement)

// Forward-looking language (+10 points)

`**Minimum threshold:** 20 points. Director (30) + target industry (20) + ownership interest (25) = 75 points. Qualified. Random person who mentioned "entrepreneur" once? Maybe 10 points. Filtered out. ### Component 3: Exclusion Filters Equally important — what we DON'T want: `const EXCLUSION_KEYWORDS = [

'student', 'intern', 'entry level', 'junior',

'recent graduate', 'mlm', 'network marketing',

'crypto', 'bitcoin', 'nft', 'cannabis',

'we are hiring', 'recruiting for', 'my team is hiring'

];

`Cuts raw results by 60-70%. That's the point. ### Component 4: State Management + Deduplication Daily runs. Same queries. Without deduplication, duplicates everywhere. `const STATE_FILE = 'data/linkedin-seen.json';

// Structure:

{

"seen": ["linkedin.com/post/abc123", "linkedin.com/post/def456"],

"lastRun": "2026-02-15T12:00:00Z"

}

`Every processed URL goes into the seen array. Next run skips anything we've seen. Zero infrastructure. Just a JSON file. ### Component 5: Clay Webhook Qualified, scored, deduplicated leads get pushed to Clay: `const payload = {

fullName: lead.author?.name,

linkedinProfileUrl: lead.author?.linkedinUrl,

currentTitle: lead.author?.info,

postText: lead.content?.substring(0, 2000),

postUrl: lead.linkedinUrl,

qualityScore: lead._score,

scoreReasons: lead._scoreReasons.join(', '),

foundDate: new Date().toISOString().split('T')[0]

};

await fetch(CLAY_WEBHOOK_URL, {

method: 'POST',

headers: { 'Content-Type': 'application/json' },

body: JSON.stringify(payload)

});

`From there, Clay handles: - Email enrichment (Apollo, LeadMagic, etc.) - Company enrichment - Verification - Push to CRM or email tool We're just feeding it high-quality intent signals. --- ## The Cron Setup This runs automatically. No manual intervention. `

Crontab entry (7 AM ET daily)

0 12 cd /path/to/scripts && node linkedin-intent-scraper.js 2>&1

`*We use a scheduling system that:* - *Runs the scraper at 7 AM ET* - *Processes results through scoring* - *Pushes to Clay* - *Reports stats to Slack/Telegram* ***Actual cron job payload:*** `Run LinkedIn intent scraper.

  1. Execute: node scripts/linkedin-intent-scraper.js

  2. Scoring engine filters to 50+ point leads

  3. Push qualified leads to Clay webhook

  4. Report: raw posts, qualified leads, new leads pushed

`*Runs daily. Takes 5-10 minutes. Costs $2-5 per run.* *---* ## *Multiple Campaigns, Same Infrastructure* *The power is running different configs through the same system:* *| Campaign | Search Strategy | Scoring Focus | Output |* *|----------|-----------------|---------------|--------|* *| Franchise Candidates | Keyword search (layoff + ownership) | Title seniority, financial readiness | Clay → EmailBison |* *| Marketing Leaders | Influencer engagers (Neil Patel, Hormozi) | CMO/VP Marketing titles only | Clay → Outbound CRM |* *| SaaS Buyers | Topic search (sales automation) | SaaS industry, company size | Clay → HubSpot |* *Same Apify actor. Same scoring engine. Different config files.* ***Client config example:*** `{

"name": "Marketing Leaders",

"monitored_profiles": [

{ "name": "Neil Patel", "username": "neilkpatel" },

{ "name": "Alex Hormozi", "username": "alexhormozi" }

],

"qualification": {

"min_score": 50,

"title_keywords": ["CMO", "VP Marketing", "Head of Marketing"],

"title_exclude": ["Intern", "Coordinator", "Freelance"]

},

"output": {

"type": "clay_webhook",

"webhook_url": "https://api.clay.com/v3/sources/webhook/xxx"

}

}

`*Add a new campaign = add a new JSON file. The system handles the rest.* *---* ## *The Cost Breakdown* *Real numbers from last month (running 3 campaigns):* *| Item | Cost |* *|------|------|* *| Apify (LinkedIn scraping) | $38 |* *| Clay (enrichment credits) | ~$12 (included in existing plan) |* *| Infrastructure | $0 (runs on existing server) |* *| **Total** | **~$50** |* ***Trigify equivalent:** $999/month (and that's one campaign)**Savings:** 95%* *---* ## *What This Looks Like Running* *Sanitized output from a real run:* `==================================================

LinkedIn Intent Scraper - Marketing Leaders

Campaign: influencer-engagers

==================================================

🚀 Starting Apify scraper...

Profiles: Neil Patel, Alex Hormozi

Posts found: 8 (last 48 hours)

📊 Scraping engagers...

Neil Patel post (2.4K likes): 847 engagers scraped

Alex Hormozi post (1.8K likes): 612 engagers scraped

Total raw engagers: 1,459

📊 Scoring results:

Title match (CMO/VP): 89

Excluded (students/recruiters): 312

Below threshold (<50): 847

Qualified leads: 89

🆕 New leads (not seen before): 34

🎯 Top leads to push:

[82] Sarah Chen - CMO at TechStartup

Commented: "This is exactly our strategy..."

[75] Mike Rodriguez - VP Marketing, FinServ Co

Liked post about content distribution

[71] Jennifer Park - Head of Marketing, SaaS Inc

Commented: "Would love to learn more..."

✅ Pushed 34/34 to Clay

==================================================

✅ Complete! 34 qualified marketing leaders

==================================================

`*1,459 engagers scraped.* *312 excluded immediately (wrong titles).* *847 scored too low.* *89 qualified.* *34 were new.* *Those 34 leads are now in Clay, getting enriched, ready for outreach.* *Tomorrow, same process. New posts. New engagers. Compounding intent data.* *---* ## *The Limitations (When to Just Pay for Trigify)* ***What we gave up:*** - ***Real-time monitoring.** We run daily. Trigify watches continuously. If you need to jump on engagement within hours, Trigify wins.* - ***Engagement on specific posts.** We search for keywords or scrape influencer engagers. Trigify can monitor engagement on YOUR specific post. Different capability.* - ***Maintenance.** Apify actors change. LinkedIn's structure changes. We've fixed the scraper twice in six months. Trigify handles that.* - ***UI/reporting.** We're looking at JSON and Clay dashboards. Trigify has purpose-built analytics.* ***When Trigify makes sense:*** - *Single ICP, single team* - *Need real-time alerts* - *Want to monitor your own posts* - *Don't have existing Clay infrastructure* - *Engineering time > subscription cost* ***When DIY makes sense:*** - *Multiple ICPs or client campaigns* - *Custom scoring logic needed* - *Already have Clay/enrichment workflows* - *Volume economics favor API costs* - *Comfortable maintaining scripts* *---* ## *How to Build This* ***Step 1: Apify setup*** *Sign up at apify.com. Actor: *`*harvestapi~linkedin-post-search*`*. Test with a few queries manually.* ***Step 2: Define scoring logic*** *What makes someone a lead for YOU?* - *Target titles* - *Target industries* - *Intent keywords* - *Disqualifiers* ***Step 3: Clay webhook*** *Create "Pull in data from webhook" source in Clay. You get a URL. That's your destination.* ***Step 4: Write the glue*** *Node.js script:* - *Call Apify with queries* - *Score each result* - *Filter to qualified leads* - *Dedupe against state file* - *POST to Clay webhook* *~250 lines of code. Not complicated.* ***Step 5: Schedule it*** *Cron job. GitHub Actions. Whatever you use. Daily is usually enough.* *---* ## *The Takeaway* *Trigify is a good product. We used it.* *But at $999/month for one campaign, the math didn't work when we needed to track franchise candidates, marketing leaders, and SaaS buyers simultaneously.* *Same infrastructure, three campaigns: $50/month total.* *The code isn't complicated. The logic isn't proprietary. The infrastructure is commodity.* *Sometimes "we can build this" is the right answer.* *---* We run cold email infrastructure for B2B companies. If you want leads (not LinkedIn scrapers), that's what we actually sell: [buzzlead.io](https://buzzlead.io)* --- Source: https://buzzlead.io/blogs/trigify-replacement-system