Managing ads for multiple clients can be overwhelming. Manually checking competitors' Facebook campaigns, tracking your own ad performance, and spotting new competitor strategies is time-consuming and error-prone. What if you could set it and forget it, with fresh data landing in your inbox every morning?
That's where automated ad monitoring comes in. By combining the Apify Facebook Ads Scraper with scheduled runs, you can build a turnkey system that continuously monitors the ad landscape for your clients, flags changes, and gives you insights that would take hours to gather manually.
In this post, I'll walk you through setting up a real-world ad monitoring pipeline that tracks competitor ads over time, showing you exactly what's changing and why that matters for your strategy.
Why Scheduled Ad Monitoring Matters
Agencies and in-house teams manage dozens of variables across multiple client accounts:
- New competitor campaigns launching
- Ad copy changes and creative rotations
- Budget shifts and bid strategy adjustments
- Targeting changes and audience expansion
- Landing page updates tied to campaigns
Without automated monitoring, you're flying blind. You notice competitor changes by accident, react instead of being proactive, and miss growth opportunities.
Scheduled monitoring solves this by running data collection on your terms, not when you remember to check.
Setting Up Your First Scheduled Run
The Apify Facebook Ads Scraper can be triggered on any schedule you define. Here's how to think about it:
Daily monitoring for active accounts: Run every morning to catch overnight changes from your core competitors or clients.
Weekly monitoring for trend analysis: Run every Monday for a full week snapshot, catching slower-moving campaign adjustments.
Multiple runs per day for fast-moving industries: If you're in e-commerce or political advertising, twice daily captures the pace of change.
Let's set up a daily schedule. Navigate to the Apify Facebook Ads Scraper and select an existing input configuration or create a new one.
Your basic input looks like this:
{
"urls": [
"https://www.facebook.com/example.page/ads/?ref=page_internal"
],
"startUrls": [],
"proxyConfiguration": {
"useApifyProxy": true
},
"maxPostsPerPage": 20,
"scrollTimeout": 30000,
"useChrome": true
}
Once saved, go to the Schedules tab in Apify and create a new scheduled task. Set it to run daily at 7 AM in your timezone. This ensures fresh data is ready before your team's standup.
What Your Output Looks Like Across Multiple Runs
When the scraper runs daily, you accumulate data over time. Here's an abbreviated example of what two days of monitoring might reveal:
Day 1 Run Output:
{
"ads": [
{
"adId": "facebook_ad_12345",
"pageTitle": "TechStartup Inc.",
"headline": "AI-Powered Analytics Now Available",
"description": "Get real-time insights with our new platform",
"mediaUrl": "https://cdn.example.com/ad1.jpg",
"fundingEntity": "TechStartup Inc.",
"createdDate": "2026-04-03",
"status": "active",
"estimatedDailyBudget": "500-600 USD",
"targetingDemographics": {
"location": ["United States"],
"age": ["25-45"],
"interests": ["Technology", "Business"]
},
"scrapedAt": "2026-04-04T07:15:00Z"
},
{
"adId": "facebook_ad_12346",
"pageTitle": "TechStartup Inc.",
"headline": "Spring Launch Special - 30% Off",
"description": "Limited time offer on annual plans",
"mediaUrl": "https://cdn.example.com/promo.jpg",
"fundingEntity": "TechStartup Inc.",
"createdDate": "2026-04-04",
"status": "active",
"estimatedDailyBudget": "1200-1500 USD",
"targetingDemographics": {
"location": ["United States", "Canada"],
"age": ["20-50"],
"interests": ["SaaS", "Productivity"]
},
"scrapedAt": "2026-04-04T07:15:00Z"
}
],
"totalAdsFound": 2,
"scrapingRunId": "run-20260404-001"
}
Day 2 Run Output:
{
"ads": [
{
"adId": "facebook_ad_12345",
"pageTitle": "TechStartup Inc.",
"headline": "AI-Powered Analytics Now Available",
"description": "Get real-time insights with our new platform",
"mediaUrl": "https://cdn.example.com/ad1.jpg",
"fundingEntity": "TechStartup Inc.",
"createdDate": "2026-04-03",
"status": "active",
"estimatedDailyBudget": "500-600 USD",
"targetingDemographics": {
"location": ["United States"],
"age": ["25-45"],
"interests": ["Technology", "Business"]
},
"scrapedAt": "2026-04-05T07:12:00Z"
},
{
"adId": "facebook_ad_12346",
"pageTitle": "TechStartup Inc.",
"headline": "Spring Launch Special - 30% Off",
"description": "Limited time offer on annual plans",
"mediaUrl": "https://cdn.example.com/promo.jpg",
"fundingEntity": "TechStartup Inc.",
"createdDate": "2026-04-04",
"status": "active",
"estimatedDailyBudget": "1500-1800 USD",
"targetingDemographics": {
"location": ["United States", "Canada"],
"age": ["20-50"],
"interests": ["SaaS", "Productivity"]
},
"scrapedAt": "2026-04-05T07:12:00Z"
},
{
"adId": "facebook_ad_12347",
"pageTitle": "TechStartup Inc.",
"headline": "New Feature Alert: Team Collaboration",
"description": "Work together smarter with native team tools",
"mediaUrl": "https://cdn.example.com/feature.jpg",
"fundingEntity": "TechStartup Inc.",
"createdDate": "2026-04-05",
"status": "active",
"estimatedDailyBudget": "300-400 USD",
"targetingDemographics": {
"location": ["United States"],
"age": ["30-50"],
"interests": ["Enterprise", "Teams"]
},
"scrapedAt": "2026-04-05T07:12:00Z"
}
],
"totalAdsFound": 3,
"scrapingRunId": "run-20260405-001"
}
Notice what happened between Day 1 and Day 2:
- Ad 12345 : Still running, no changes (consistent strategy)
- Ad 12346 : Budget increased from 500-600 to 1500-1800 USD (clear signal of increased spend)
- Ad 12347 : Brand new ad (testing new audience or messaging)
This is the power of scheduled monitoring. You capture the delta automatically.
Building Your Change Detection System
With multiple runs, you can create a simple system to flag what changed:
- Store each run's output in your data warehouse or cloud storage
- Compare Day N to Day N-1 on fields like budget, targeting, and creative
- Flag significant changes : New ads, budget increases over 20%, targeting expansion
- Route alerts to your team : Slack notifications, daily email summary, or a dashboard
Here's a simple Python snippet to detect budget changes:
import json
from datetime import datetime
def detect_budget_changes(today_run, yesterday_run):
today_ads = {ad['adId']: ad for ad in today_run['ads']}
yesterday_ads = {ad['adId']: ad for ad in yesterday_run['ads']}
changes = []
for ad_id, today_ad in today_ads.items():
if ad_id in yesterday_ads:
yesterday_budget = extract_budget_min(yesterday_ads[ad_id]['estimatedDailyBudget'])
today_budget = extract_budget_min(today_ad['estimatedDailyBudget'])
pct_change = ((today_budget - yesterday_budget) / yesterday_budget) * 100
if abs(pct_change) >= 20:
changes.append({
'adId': ad_id,
'headline': today_ad['headline'],
'previousBudget': yesterday_ads[ad_id]['estimatedDailyBudget'],
'newBudget': today_ad['estimatedDailyBudget'],
'percentageChange': round(pct_change, 1),
'timestamp': datetime.now().isoformat()
})
else:
changes.append({
'adId': ad_id,
'headline': today_ad['headline'],
'changeType': 'NEW_AD',
'budget': today_ad['estimatedDailyBudget'],
'timestamp': datetime.now().isoformat()
})
return changes
def extract_budget_min(budget_str):
# Parses "500-600 USD" to 500
return int(budget_str.split('-')[0])
Setting Up Apify Webhooks for Real-Time Alerts
Don't just let data pile up. Connect your scheduled runs to webhooks so you get notified immediately when something changes.
In Apify, navigate to your scheduled task and add a webhook that fires on successful completion. Set it to POST to your backend endpoint:
https://your-api.com/webhooks/facebook-ads-monitor
Your webhook receiver can then:
- Compare today's run against yesterday's
- Highlight significant changes
- Send Slack notifications to your team
- Log the delta to a dashboard
This turns your scheduled scraper into an active monitoring system.
Best Practices for Long-Term Monitoring
1. Archive by date : Store each run in a timestamped folder so you can always trace historical changes. This is critical for client reports and competitive analysis.
2. Set retention policies : After 90 days, moves data to cold storage to save on costs. You probably don't need a year of ad data in hot storage.
3. Deduplicate carefully : The same ad (same adId) appearing across multiple runs is normal. Don't treat it as a duplicate error.
4. Monitor the monitor : Ensure your scheduled runs are actually completing. Set up alerts if a run fails for 2+ days in a row.
5. Version your configurations : If you change what you're monitoring, save the old config and start a new scheduled run. This prevents mixing data from different targeting rules.
Real-World Use Case: Multi-Client Agency
Imagine you manage ads for 10 clients. Instead of checking each client's ads manually every week (hours of work), you set up 10 scheduled runs, each targeting one client's Facebook page. Every Monday morning at 7 AM, fresh data arrives.
Your system compares Monday to the prior Monday and generates a report: "Competitor A increased spend by 25% on product launch ads. Competitor B launched 3 new campaigns in the healthcare vertical."
Your team now has a 15-minute briefing instead of a 3-hour research session. That's the ROI of scheduled monitoring.
Getting Started
Head to the Apify Facebook Ads Scraper and create your first scheduled run today. Start with daily monitoring of your top 3 competitors, get a week of data, then expand from there.
The infrastructure for competitive advantage is just a few clicks away. Make it automatic, and you'll have insights your competitors still gather manually.
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