Outbrain - Popular Rules
This article showcases 15+ critical automation rules for Outbrain based on analysis of 1,867 real-world rules deployed by high-performing media buyers. These patterns reveal what actually works at scale: aggressive section-level control, sophisticated bid optimization, and fraud detection automation. On Outbrain, section-level management (415 pause rules, 80 bid adjustments) is what separates profitable campaigns from average ones—it's the engine that high-volume buyers use to scale. This guide focuses on the patterns that move the needle, with thresholds you can adjust to match your payout structures.
In This Article
- Section-Level Control & Bid Optimization
- Sophisticated Publisher Blocking
- Fraud Detection & Bot Prevention
- Campaign Budget & ROI Management
- Creative Performance & Scaling
Section-Level Control & Bid Optimization
This is the core of Outbrain automation. Sections are placements within publishers—think of them as publisher subsites or contexts. Section-level control is unique to Outbrain and is how 711 buyers scale profitably. The data shows 415 pause rules at the section level and 80 bid adjustment rules, proving this is where the action happens.
1. Pause Sections: High Spend, Crushing Payout (3x Spend Rule)
Description: Kill sections spending 3x your payout with zero conversions. This is aggressive but critical—it's the pattern used in 9 rules from real buyers managing cost bleed.
Data Interval: Last 14 Days
| Metric | Condition | Value |
|---|---|---|
| Amount Spent | > | 300% of Current Payout |
| Tracker Conversions | = | 0 |
Action: Pause Section
Scheduling: Run once daily
Real buyer note: If your payout is $30 and a section has spent $90+ with zero conversions, it's a drain. This rule fires automatically to prevent waste.
2. Pause Sections: High LP CTR but Zero Conversions (Landing Page Mismatch)
Description: Sections with abnormally high LP CTR (75%+) but zero conversions indicate audience misalignment—your headline attracts clicks but offer fails. Kill it and move budget.
Data Interval: Last 7 Days
| Metric | Condition | Value |
|---|---|---|
| Amount Spent | > | $5 |
| LP CTR | > | 75% |
| Tracker Conversions | = | 0 |
Action: Pause Section
Scheduling: Run once daily
3. Pause Sections: Abnormally High CTR (1%+ on Native)
Description: Native CTR above 1% is rare and usually indicates bot activity, poisoned data, or fraud. Outbrain native typically runs 0.2-0.5% CTR. Use this as a fraud red flag.
Data Interval: Last 7 Days
| Metric | Condition | Value |
|---|---|---|
| Amount Spent | > | $2 |
| CTR | > | 1% |
| Tracker Conversions | < | 1 |
Action: Pause Section
Scheduling: Run once daily
4. Optimize Section Bid: Sophisticated Bid Ranges (Advanced Multi-Condition)
Description: This is the pattern high-volume buyers use: set bids based on a combination of CPC (cost per click), EPC (earnings per click), conversion volume, and cost. This rule applies a tiered bid strategy.
Data Interval: Last 14 Days
| Metric | Condition | Value |
|---|---|---|
| Avg CPC | >= | 0.15 AND <= 0.25 |
| EPC | >= | 2 AND <= 4 |
| Tracker Conversions | > | 1 |
| Amount Spent | > | $200 |
Action: Set Section Bid to 30% above current bid
Scheduling: Run every 2 days
Media buyer insight: This rule targets sections with balanced metrics—decent click costs, good earnings potential, proven conversions, and adequate spend. The 30% increase signals confidence. Adjust thresholds to your vertical's norms.
5. Reduce Section Bid: High Cost Per Acquisition
Description: When section CPA exceeds 100% of your campaign's target CPA, reduce bid to bring costs in line. This prevents overweight sections from eating margins.
Data Interval: Last 14 Days
| Metric | Condition | Value |
|---|---|---|
| Tracker CPA | > | 100% of Campaign.CPA |
| Amount Spent | > | $100 |
Action: Reduce Section Bid by 15-20%
Scheduling: Run every 2 days
6. Reactivate Sections: Positive ROI After Pause
Description: If a paused section recovers to positive ROI over 7 days, resume it. This captures sections that had temporary dips but stabilize.
Data Interval: Last 7 Days
| Metric | Condition | Value |
|---|---|---|
| Tracker ROI | > | 5% |
| Tracker Clicks | > | 15 |
Action: Start Section
Scheduling: Run every 2 days
Sophisticated Publisher Blocking
While publisher-level blocking accounts for 711 rules in the dataset, it's less critical than section-level control for high-volume buyers. However, blocking patterns at the widget level remain important for brand safety and quality gates.
7. Pause Publishers: High Spend, Zero Conversions
Description: If a publisher has spent meaningful money with zero conversions, stop it. This fires across all sections of that publisher.
Data Interval: Last 7 Days
| Metric | Condition | Value |
|---|---|---|
| Amount Spent | >= | $20 |
| Tracker Conversions | = | 0 |
Action: Pause Publisher
Scheduling: Run once daily
8. Pause Publishers: Extreme Spend Velocity with Negative ROI
Description: Some publishers spend fast but burn money. If they're burning 80% of daily budget with poor ROI, pause to prevent runaway losses.
Data Interval: Today
| Metric | Condition | Value |
|---|---|---|
| Amount Spent | >= | 80% of Daily Budget |
| Tracker ROI | <= | -50% |
Action: Pause Publisher
Scheduling: Run every 4 hours
9. Block Publishers by Name: Brand Safety Tier
Description: Use name matching to block known low-quality publishers. This is foundational QC.
Data Interval: Last 7 Days
| Metric | Condition | Value |
|---|---|---|
| Name | contains | [Your blacklist terms] |
| Impressions | >= | 10 |
Action: Pause Publisher
Scheduling: Run once daily
Fraud Detection & Bot Prevention
This is critical and often overlooked. The data shows sophisticated buyers use 3+ condition rules (448 out of 1,867 rules). Fraud detection is a key use case.
10. Detect Publisher Click vs Traffic Source Click Mismatch (Bot Detection)
Description: When publisher clicks are 10% or less of traffic source clicks, it's a massive red flag for bot activity. Real users follow the click path; bots don't.
Data Interval: Last 7 Days
| Metric | Condition | Value |
|---|---|---|
| Publisher Clicks | <= | 10% of TS Clicks |
| Amount Spent | >= | $10 |
Action: Pause Section
Scheduling: Run once daily
Why this matters: Publisher clicks reflect actual user engagement. TS (traffic source) clicks are Outbrain's record. A huge gap = fraudulent inventory.
11. Bot Detection: High Impressions, Near-Zero Engagement
Description: Sections with 20k+ impressions but CTR below 0.1% with zero conversions are likely bot-filled or low-quality content blocks.
Data Interval: Last 7 Days
| Metric | Condition | Value |
|---|---|---|
| Impressions | >= | 20000 |
| CTR | < | 0.1% |
| Tracker Conversions | < | 1 |
Action: Pause Section
Scheduling: Run every 2 days
12. Fraud Detection: High Cost Per Click with No Payout
Description: If you're paying high CPCs (relative to your payout) but earning nothing, demand-side fraud or bad inventory is likely.
Data Interval: Last 14 Days
| Metric | Condition | Value |
|---|---|---|
| Tracker CPA | > | 95% of Current Payout |
| Amount Spent | >= | $50 |
| Tracker Conversions | < | 1 |
Action: Pause Section
Scheduling: Run every 2 days
Campaign Budget & ROI Management
These are the safety nets that prevent catastrophic losses.
13. Scale Profitable Campaigns: High Spend Velocity + Positive ROI
Description: When a campaign is hitting 80% of daily budget AND showing positive ROI, increase budget to capture more volume before hitting the cap.
Data Interval: Last 7 Days
| Metric | Condition | Value |
|---|---|---|
| Amount Spent | >= | 80% of Daily Budget |
| Tracker ROI | > | 0% |
Action: Increase Campaign Budget by 25-30%
Scheduling: Run every 4 hours
14. Pause Campaigns: Severe Sustained Losses
Description: If a campaign is bleeding money over 2 weeks (70%+ spend with losses), emergency stop it before compounding losses.
Data Interval: Last 14 Days
| Metric | Condition | Value |
|---|---|---|
| Amount Spent | >= | $300 |
| Tracker ROI | <= | -70% |
Action: Pause Campaign
Scheduling: Run every 6 hours
15. Kill Campaigns: Spent Budget Without ROI
Description: A campaign that's spent 70% of daily budget yet shows CPA 130% above campaign average? It's not scaling, it's hemorrhaging.
Data Interval: Last 7 Days
| Metric | Condition | Value |
|---|---|---|
| Amount Spent | >= | 70% of Daily Budget |
| Tracker CPA | > | 130% of Campaign.CPA |
Action: Pause Campaign
Scheduling: Run every 6 hours
Media buyer reality: This fires on campaigns that can't optimize through section/publiser control—they're systemically broken.
Creative Performance & Scaling
Ad-level rules are less frequent because section-level control dominates, but creative scaling is crucial.
16. Pause Creatives: High Spend, Zero Conversions
Description: Individual creatives that accumulate cost without conversions should be paused to redirect budget to winners.
Data Interval: All Time
| Metric | Condition | Value |
|---|---|---|
| Amount Spent | >= | $100 |
| Tracker Conversions | = | 0 |
Action: Pause Ads
Scheduling: Run every 3 days
The framework above represents real patterns from 1,867 deployed rules. Focus first on section-level control and fraud detection—that's where your profit margin lives. Adjust thresholds based on your payout and risk tolerance, but the logic remains the same: move fast on winners, kill losers aggressively, and watch for fraud signals constantly.