Documentation Index
Fetch the complete documentation index at: https://theoptimizer.io/docs/llms.txt
Use this file to discover all available pages before exploring further.
This page covers 15+ critical automation rules for Outbrain based on analysis of 1,867 real-world rules deployed by high-performing media buyers. On Outbrain, section-level management is what separates profitable campaigns from average ones — 415 pause rules and 80 bid adjustments operate at the section level, making it the engine that high-volume buyers use to scale. Publisher-level blocking and campaign safety nets round out the stack, but the section is where your profit margin lives. Adjust thresholds to match your payout structures.
Section-level control & bid optimization
Sections are placements within publishers — think of them as publisher subsites or contexts. Section-level control is unique to Outbrain and is how buyers scale profitably at high volume.
Rule 1: pause sections — high spend, crushing payout (3× spend rule)
Kill sections spending 3× your payout with zero conversions. This is aggressive but critical.
Data Interval: Last 14 days | Scheduling: Once daily
| Metric | Condition | Value |
|---|
| Amount Spent | > | 300% of Current Payout |
| Tracker Conversions | = | 0 |
If your payout is 30andasectionhasspent90+ with zero conversions, it’s a drain. This rule fires automatically to prevent waste.
Rule 2: pause sections — high LP CTR but zero conversions (landing page mismatch)
Sections with abnormally high LP CTR (75%+) but zero conversions indicate audience misalignment — your headline attracts clicks but the offer fails. Kill it and move budget.
Data Interval: Last 7 days | Scheduling: Once daily
| Metric | Condition | Value |
|---|
| Amount Spent | > | $5 |
| LP CTR | > | 75% |
| Tracker Conversions | = | 0 |
Rule 3: pause sections — abnormally high CTR (1%+ on native)
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 | Scheduling: Once daily
| Metric | Condition | Value |
|---|
| Amount Spent | > | $2 |
| CTR | > | 1% |
| Tracker Conversions | < | 1 |
Rule 4: optimize section bid — sophisticated bid ranges (advanced multi-condition)
Set bids based on a combination of CPC, EPC, conversion volume, and cost. This rule applies a tiered bid strategy that high-volume buyers use consistently.
Data Interval: Last 14 days | Scheduling: Every 2 days
| Metric | Condition | Value |
|---|
| Avg CPC | >= | 0.15 AND <= 0.25 |
| EPC | >= | 2 AND <= 4 |
| Tracker Conversions | > | 1 |
| Amount Spent | > | $200 |
This rule targets sections with balanced metrics — decent click costs, good earnings potential, proven conversions, and adequate spend. Adjust thresholds to your vertical’s norms.
Rule 5: reduce section bid — high cost per acquisition
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 | Scheduling: Every 2 days
| Metric | Condition | Value |
|---|
| Tracker CPA | > | 100% of Campaign.CPA |
| Amount Spent | > | $100 |
Rule 6: reactivate sections — positive ROI after pause
If a paused section recovers to positive ROI over 7 days, resume it. This captures sections that had temporary dips but have stabilized.
Data Interval: Last 7 days | Scheduling: Every 2 days
| Metric | Condition | Value |
|---|
| Tracker ROI | > | 5% |
| Tracker Clicks | > | 15 |
Sophisticated publisher blocking
While publisher-level blocking accounts for a large share of rules in the dataset, it’s less critical than section-level control for high-volume buyers. However, blocking patterns at the publisher level remain important for brand safety and quality gates.
Rule 7: pause publishers — high spend, zero conversions
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 | Scheduling: Once daily
| Metric | Condition | Value |
|---|
| Amount Spent | >= | $20 |
| Tracker Conversions | = | 0 |
Rule 8: pause publishers — extreme spend velocity with negative ROI
Some publishers spend fast but burn money. If they’re burning 80% of your daily budget with poor ROI, pause to prevent runaway losses.
Data Interval: Today | Scheduling: Every 4 hours
| Metric | Condition | Value |
|---|
| Amount Spent | >= | 80% of Daily Budget |
| Tracker ROI | <= | −50% |
Rule 9: block publishers by name — brand safety tier
Use name matching to block known low-quality publishers. This is foundational quality control.
Data Interval: Last 7 days | Scheduling: Once daily
| Metric | Condition | Value |
|---|
| Name | contains | [your blacklist terms] |
| Impressions | >= | 10 |
Fraud detection & bot prevention
Sophisticated buyers use 3+ condition rules (448 out of 1,867 rules in the dataset). Fraud detection is a key use case — don’t skip it.
Rule 10: detect publisher click vs. traffic source click mismatch (bot detection)
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 | Scheduling: Once daily
| Metric | Condition | Value |
|---|
| Publisher Clicks | <= | 10% of TS Clicks |
| Amount Spent | >= | $10 |
Publisher clicks reflect actual user engagement. TS (traffic source) clicks are Outbrain’s record. A large gap between the two signals fraudulent inventory.
Rule 11: bot detection — high impressions, near-zero engagement
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 | Scheduling: Every 2 days
| Metric | Condition | Value |
|---|
| Impressions | >= | 20,000 |
| CTR | < | 0.1% |
| Tracker Conversions | < | 1 |
Rule 12: fraud detection — high cost per click with no payout
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 | Scheduling: Every 2 days
| Metric | Condition | Value |
|---|
| Tracker CPA | > | 95% of Current Payout |
| Amount Spent | >= | $50 |
| Tracker Conversions | < | 1 |
Campaign budget & ROI management
These are the safety nets that prevent catastrophic losses.
Rule 13: scale profitable campaigns — high spend velocity + positive ROI
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 | Scheduling: Every 4 hours
| Metric | Condition | Value |
|---|
| Amount Spent | >= | 80% of Daily Budget |
| Tracker ROI | > | 0% |
Rule 14: pause campaigns — severe sustained losses
If a campaign is bleeding money over 2 weeks ($300+ spend at −70% ROI or worse), emergency stop it before compounding losses.
Data Interval: Last 14 days | Scheduling: Every 6 hours
| Metric | Condition | Value |
|---|
| Amount Spent | >= | $300 |
| Tracker ROI | <= | −70% |
Rule 15: kill campaigns — spent budget without ROI
A campaign that’s spent 70% of daily budget yet shows CPA 130% above campaign average is not scaling — it’s hemorrhaging.
Data Interval: Last 7 days | Scheduling: Every 6 hours
| Metric | Condition | Value |
|---|
| Amount Spent | >= | 70% of Daily Budget |
| Tracker CPA | > | 130% of Campaign.CPA |
This fires on campaigns that can’t optimize through section or publisher control — they’re systemically broken. Pause and investigate the offer or audience targeting before reactivating.
Ad-level rules are less frequent because section-level control dominates, but creative scaling is still crucial.
Rule 16: pause creatives — high spend, zero conversions
Individual creatives that accumulate cost without conversions should be paused to redirect budget to winners.
Data Interval: All time | Scheduling: Every 3 days
| Metric | Condition | Value |
|---|
| Amount Spent | >= | $100 |
| Tracker Conversions | = | 0 |
Where to start
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 stays consistent: move fast on winners, kill losers aggressively, and watch for fraud signals constantly.