Ad Exclusions at Scale: Building & Maintaining a Centralized Blocklist for Google Ads

Stop firefighting placements — centralize exclusions so automation doesn't run your brand into risky inventory

Managing placement exclusions campaign-by-campaign used to be the norm — and the pain. By early 2026, with Google Ads adding account-level placement exclusions (rolling out across Performance Max, Demand Gen, YouTube, and Display), advertisers finally have a way to enforce a single source of truth for blocked inventory. This guide shows marketing teams and account owners how to build, segment, automate, and govern a centralized placement blocklist so you scale protection without slowing performance.

What you'll get from this guide

• Clear architecture for a centralized blocklist and recommended fields
• Segmentation strategies for different marketing and risk profiles
• Automation recipes to push updates across accounts and MCCs
• Governance workflows, SLAs, and reporting templates
• Advanced tactics for inventory management, measuring impact, and future-proofing

Why account-level exclusion matters in 2026

Google's January 15, 2026 update introduced a long-requested capability: a single exclusion list that applies account-wide. The change arrives against a backdrop of heavier automation in ad delivery and privacy-driven targeting shifts. When campaigns like Performance Max and Demand Gen increasingly make placement decisions on behalf of advertisers, the only practical way to keep brand safety and inventory quality consistent is through centralized guardrails.

"Once a placement is excluded at the account level, Google Ads automatically prevents spend on those websites, apps, or YouTube placements across all eligible campaigns." — Google Ads rollout, Jan 15, 2026

Anatomy of a centralized placement blocklist

Design the list as a lightweight database, not a flat text file. Each record should be an actionable asset with metadata that supports automation and governance.

Recommended fields

• Placement identifier — domain, app ID, YouTube channel ID, or placement URL
• Type — domain, app, YouTube, placement URL
• Reason — brand safety, malware, low performance, regulatory
• Severity — high/medium/low (for automated enforcement)
• Source — manual report, third-party signal, automated detector
• Owner — team or individual who added it
• Date added and Last reviewed
• Expiry / Review cadence — auto-expire or re-validate after X days
• Tags — geo, product-line, regulatory, competitor
• Exceptions — campaigns or products that are allowed
• Evidence — screenshots, report links, performance metrics

Segmentation: when to use account-level vs campaign-level exclusions

Not every exclusion belongs in a single global list. Use segmentation to balance safety, performance, and flexibility.

Common segmentation patterns

• Global safety list — high-severity inventory (malware, illegal, explicit) applied account-wide.
• Region-specific lists — country-level restrictions, language-sensitive content, or geo-regulatory issues.
• Brand vs Performance — brand-focused products get strict blocklists; direct-response campaigns get more granular, performance-driven exclusions.
• Product or vertical lists — certain industries (pharma, finance) may need extra restrictions.
• Test/Quarantine lists — transient list for placements under investigation before promotion to global blocklist.

Decision rules

1. If a placement is a legal or safety risk, put it on the global list.
2. If it’s a performance outlier but safe, tag it as performance and start with a campaign-level exclusion while you monitor.
3. Use exceptions sparingly — document justification and time limit.

Sources of truth: where exclusions should come from

Good blocklists synthesize multiple signals. Relying on a single input leads to bias or gaps.

• Internal reports — manual incident reports from brand, legal, or customer support teams.
• Ad performance data — placements with high spend and zero conversions or large negative post-view metrics.
• Third-party brand safety feeds — category classifiers, content taxonomy providers.
• Security feeds — malware, phishing, or fraud blocklists.
• Competitive intelligence — competitor domains or channels you explicitly want to avoid.
• Automated detectors — ML models that flag risky inventory using creative/context mismatches.

Practical build: step-by-step checklist

Follow this 8-step process to create your first centralized blocklist and connect it to Google Ads.

1. Inventory audit — export placement reports (last 90 days) across Display, YouTube, Demand Gen, and Performance Max. Identify spend concentration and negative signals.
2. Collect signals — pull internal reports, brand-safety vendor lists, and security feeds into a staging spreadsheet or database.
3. Normalize records — dedupe by canonical domain/app ID and normalize types.
4. Tag & prioritize — assign severity and tags (geo, product, reason).
5. Validate — sample placements, capture screenshots, and verify with the owning team.
6. Approval — route to governance owner for sign-off (for high-severity items require legal/brand OK).
7. Deploy — push the list to Google Ads API account-level exclusions (or to Manager account for multi-account use).
8. Monitor — run a 30/90-day review cycle and measure key metrics.

Automation recipes: keep the list accurate without manual toil

Automation reduces errors and speeds up response time. Use APIs and simple scripts to ingest signals, validate, and push updates to Google Ads.

Core automation flow

1. Ingest: scheduled jobs pull placement performance, third-party feeds, and incident reports into a staging table.
2. Score & triage: apply rules and an ML model to assign a confidence score and suggested severity.
3. Auto-flag low-risk items: auto-add items below a confidence threshold to a quarantine list for manual review.
4. Auto-block high-confidence items: for severity=high and confidence > X, automatically push to account-level exclusions with audit notes.
5. Notify & log: send notifications to owners and append entries in an immutable audit log.

Implementation options

• Google Ads API — best for programmatic, repeatable updates and MCC-level management. Use it to create and update account-level exclusion lists.
• Google Ads scripts — suitable for mid-complexity tasks when API access is limited; schedule scripts in MCCs for routine pushes.
• ETL + Cloud Functions — ingest feeds into BigQuery or a relational DB, run validation functions, and call the Ads API from cloud functions for deployment.
• No-code integrations — for smaller teams, use workflow tools (Make, Zapier) to automate approvals and uploads via the Ads interface or API wrappers.

Practical notes for automation

• Respect API quotas and rate limits; batch updates when possible.
• Keep a human-in-the-loop for high-severity blocks to avoid costly false positives.
• Record every API push with user, timestamp, and reason in an audit log.
• Version your list — never overwrite without a snapshot and rollback plan.

Governance: rules, roles, and SLAs

Automation without governance becomes a source of risk. Define clear ownership and processes so exclusions are reliable, auditable, and reversible.

Governance essentials

• List owner — the single point of accountability for the blocklist.
• Approver roles — brand, legal, and data owners must be defined for different severity tiers.
• Change SLA — time-to-block for high-risk items (e.g., 4 hours), medium (24–48 hours), low (7 days).
• Review cadence — auto-review flags after 30 days for quarantine items and 90 days for the main list.
• Appeals process — a documented path for campaign teams to request an exception, with time-limited approvals and monitoring requirements.
• Reporting — weekly governance report with blocked spend, removed placements, appeals, and measurement of impact on CPA/CTR.

Maintenance: prevent list rot and measurement blind spots

Maintenance is the ongoing work that prevents a blocklist from becoming obsolete or overly restrictive.

Daily / Weekly

• Run automated integrity checks — duplicates, invalid IDs, expired entries.
• Alert on any blocked placement that still generated spend (sign of misconfiguration).

Monthly

• Review placements marked for review and triage to keep false positives low.
• Analyze performance metrics for campaigns that intersect with exclusions.

Quarterly

• Conduct a full audit of the blocklist with brand and legal stakeholders.
• Evaluate governance KPIs and update SLAs or approval thresholds.

Inventory management & measurement: what to track

Blocklists affect both safety and reach. Track metrics that show operational health and business impact.

• Blocked spend — historical spend that was avoided due to exclusions (estimate from sampling before block).
• Spend leakage — any spend on placements that should be blocked (indicator of config errors).
• CPA / ROAS delta — compare cohorts before/after blocking to quantify impact.
• False positive rate — percentage of placements later removed due to legitimate performance.
• Time-to-block — SLA adherence for different severities.

Segmentation recipes — real-world examples

1) Safety-first consumer brand

1. Global high-severity list for malware and explicit content.
2. Geo-specific lists for markets with local restrictions.
3. Weekly automated ingest from brand-safety vendor; human review for items flagged as medium severity.

2) Performance-driven DTC brand

1. Start with performance-only exclusions at campaign level for low-converting placements.
2. Promote repeated offenders (X occurrences in 30 days) to account-level performance list.
3. Monthly rollback checks to ensure reach isn't unnecessarily limited.

3) Regulated industry (finance, healthcare)

1. Conservative global exclusion list for any unverified health/finance publishers.
2. Strict approval process for exceptions with legal sign-off and 30-day review.

Advanced strategies and 2026 trends to watch

As we move further into 2026, several developments influence blocklist strategy:

• Automation-first ad formats — Performance Max and Demand Gen will continue to expand inventory reach; centralized exclusions remain the primary control vector.
• ID-lite targeting — with fewer deterministic signals, placement behavior matters more, so dynamic scoring models that evaluate content adjacency will gain value.
• Supply chain transparency — more advertisers will demand supply-path signals and publisher verification; blocklists should integrate supply information when available.
• ML-assisted suggestions — internal models can recommend placements to quarantine based on sudden performance drops or content shifts. See work on predictive detection like ML-assisted suggestions for analogous patterns in security.
• Cross-platform consistency — your blocklist strategy should include other ecosystems (social, programmatic) to avoid inconsistent brand exposure.

Common pitfalls and how to avoid them

• Over-blocking — avoid killing reach by blocking whole domains when only specific subpaths are problematic. Use targeted exclusions where possible.
• Stale lists — set review cadences and auto-expiry to keep the list current.
• Lack of versioning — always snapshot before bulk changes and keep a rollback method.
• No measurement — implement basic KPIs from day one; otherwise you won't know if exclusions improved or hurt performance.
• Governance bottlenecks — strike a balance between control and speed. Use automated gating for high-confidence items to maintain momentum.

Quick 30-day rollout plan

1. Week 1: Export placement reports and compile signals into a staging sheet.
2. Week 2: Normalize, tag, and prioritize. Create global safety list items and quarantine items.
3. Week 3: Deploy core high-severity items to account-level exclusions. Implement automation for ingest and notifications.
4. Week 4: Establish governance roles, SLAs, and start the 30-day rollout plan. Produce first impact report.

Actionable takeaways

• Start with a small, high-severity global list to get immediate risk reduction without sacrificing reach.
• Segment by geo, product, and risk level — don’t treat every exclusion the same.
• Automate ingestion and deployment but keep human sign-off for high-impact blocks.
• Governance is non-negotiable: assign owners, SLAs, and a review cadence.
• Measure impact on spend, CPA, and false positive rate to continuously optimize.

Final checklist before you go live

• Staging list exported and deduped
• Severity tags and owners assigned
• Approval flow in place for high-severity items
• Deployment automation configured (API or scripts)
• Audit logging enabled and snapshot taken
• Monitoring dashboard and SLAs documented

Conclusion — start small, automate smart, govern strictly

Account-level placement exclusions give advertisers a powerful lever in 2026 to protect brands while letting Google's automation run efficiently. The trick is not simply to build a long list of blocked domains — it's to design a governed, segmented, and automated system that balances safety with reach. Use the templates and checklists above to stand up a defensible process in 30 days, then iterate with measurement and ML to shrink your mean time to block without growing operational overhead.

Ready to build your centralized blocklist? Start with the 30-day rollout plan above: export your placement reports today, create the global safety list, and schedule the first automation job. If you want a turnkey checklist or governance template tailored to your account structure, contact your team or download a starter template from your internal resources — then execute the first deployment within one sprint.

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