Account-Level Placement Exclusions: A Practical Setup Guide for Google Ads Managers

Stop wasting time patching brand-safety holes: a practical playbook for Google Ads account-level placement exclusions

If you manage multiple Google Ads campaigns—Performance Max, Demand Gen, YouTube, Display—you've felt the pain of fragmented exclusion controls. Blocking bad placements campaign-by-campaign eats hours, costs you control, and leaves room for surprise spend. In January 2026 Google rolled out account-level placement exclusions, centralizing blocking so you can protect ad inventory across the whole account. This playbook gives you a step-by-step implementation guide, naming conventions, audit checklists, and common pitfalls so you can deploy account-level exclusions safely and at scale.

Why account-level placement exclusions matter in 2026

By late 2025 and into 2026 the ad ecosystem continued shifting: Google accelerated automation (Performance Max and Demand Gen dominate new spend), YouTube Shorts viewership surged, and privacy-driven measurement changes pushed more spend toward algorithmic placements. That increased the need for robust guardrails. Account-level placement exclusions (announced January 15, 2026) let you apply central blocks across eligible campaign types, removing the previous error-prone campaign-by-campaign workflow.

The key advantages:

• Scale: One list blocks placements across all eligible campaigns.
• Consistency: Aligns brand-safety rules across teams and markets.
• Efficiency: Reduces time to deploy new blocks from hours to minutes.
• Control over automation: Stronger guardrails for automated formats like Performance Max.

Quick playbook (executive summary)

1. Audit current placement exposure and tag risky inventory.
2. Create a taxonomy and naming convention for exclusion lists.
3. Build and version an account-level exclusion list in Google Ads shared library.
4. Stage rollout (pilot on low-risk campaigns, then scale).
5. Monitor performance and iterate weekly for 30 days, then monthly.
6. Govern: maintain change log, approvals, and quarterly audits.

Step-by-step implementation guide

Step 1 — Audit: map where risk lives

Start with a rapid inventory audit to know what to exclude. Use a 30–90 day lookback and export placement data from Display, YouTube, and Performance Max placements. Segment by:

• Placement domain, app ID, or YouTube channel
• Impressions, spend, clicks, conversions, viewability, and fraud signals
• CTR and conversion rate by placement
• Brand-safety flags (indirect: low viewability, high bounce rate, high invalid traffic)

Produce a short list of high-risk placements (e.g., domains with high spend but zero conversions and low viewability) and a medium-risk list for review. This audit creates the baseline you'll use to measure the impact of exclusions.

Step 2 — Define a taxonomy and naming convention

Consistency matters. Use a versioned naming convention so teams know what changed and when. Recommended pattern:

ALPE - [Category] - [Scope] - v[version] - YYYYMMDD

• ALPE = Account-Level Placement Exclusion
• [Category] = BrandSafety | LowQuality | Competitor | App | YouTubeChannel
• [Scope] = Global | US | EU | Retail | Prospecting
• v[version] = v1, v2…
• YYYYMMDD = deployment date

Example: ALPE - BrandSafety - Global - v1 - 20260115

Step 3 — Build the master lists

Create separate lists for distinct categories to avoid overblocking. Keep lists small, targeted, and reasoned:

• BrandSafety: explicit content, extremist content, illegal activities
• LowQuality: domains/apps with very low viewability or fraudulent patterns
• Competitor: competitor domains and official channels
• ChannelExclusions: specific YouTube channels or playlists

Use domain-level blocks where possible, and only block app IDs or YouTube channels when necessary. Document the reason for every blocked placement in a separate column: "Reason: low viewability; Evidence: GA bounce 92%". That makes later audits defensible.

Step 4 — Create and apply account-level exclusions

In Google Ads (Shared Library or the new account-level controls), create the lists using your names. Best practices:

• Assign an owner and approver for each list.
• Use the UI for the first rollout to validate behavior; migrate to API for scale.
• When applying, scope to the entire account first in a pilot environment where possible.

Note: Some campaign types or legacy settings might not honor account-level exclusions; test for each campaign format. If you use a manager account across multiple client accounts, decide whether to maintain exclusions per account or centrally push via API.

Step 5 — Stage rollout (pilot, expand, enforce)

Never flip a global block overnight. Follow a three-phase rollout:

1. Pilot: Apply the list to a small set of prospecting Display and YouTube campaigns for 7–14 days.
2. Expand: Add high-volume campaigns and Performance Max after validating no negative impact.
3. Enforce: Apply globally once metrics confirm safety and performance gains.

During the pilot, track impressions, spend, conversion rate, CPA, and remarketing list size (if applicable). Use a control split if possible—duplicate one campaign without the account-level exclusion to measure incremental impact.

Step 6 — Monitor, measure, and iterate

Key metrics to monitor after applying exclusions:

• Spend shifted: where did impressions move?
• CPA and conversion rate changes
• Invalid traffic and viewability improvements
• Search impression share or reach impact for brand campaigns

Expect short-term fluctuations as automation re-optimizes. Measure over 14–30 days and compare against your pre-change baseline.

Common pitfalls and how to avoid them

• Overblocking: Blocking too broadly (e.g., entire domains with diverse inventory) can reduce reach and increase CPA. Solution: prefer specific placements or channels, and test incremental lists.
• Insufficient evidence: Blocking without documented metrics undermines stakeholder buy-in. Solution: attach data evidence to every block and maintain a change log.
• One-size-fits-all lists: Not every market or product needs the same blocks. Solution: create scoped lists by region, product line, or funnel stage.
• Ignoring automation lag: Algorithmic campaigns reroute spend; expect transient variance. Solution: measure over 2–4 weeks and use control campaigns.
• Conflicts with campaign-level exclusions: Campaign-level negatives may duplicate or override behavior. Solution: document hierarchy: Account-level lists apply broadly; campaign-level lists remain for exceptions.
• No governance: Changes without approvals cause churn. Solution: require owner, approver, and change log entries before deployment.

Naming convention and versioning templates

Enforce these fields in a shared spreadsheet or your change management system:

• List Name (use the ALPE pattern)
• Owner
• Approver
• Deployment Date
• Placement Count
• Reason / Evidence
• Rollback Plan

Sample entry:

ALPE - LowQuality - Global - v2 - 20260128 | Owner: media_ops@brand.com | Approver: head_of_marketing@brand.com | 145 placements | Reason: low viewability + high bounce | Rollback: revert to v1

Audit checklist: keep inventory safe (weekly & quarterly)

Use this checklist to maintain hygiene. Convert it into a one-click audit in your dashboard if you have BI resources.

Weekly quick-check

• Verify account-level lists are active and unchanged (compare to change log).
• Review top 20 placements by spend and impressions—ensure none are unintentionally blocked or unblocked.
• Check CPA and conversion rate for campaigns affected by recent changes.
• Look for sudden spikes in invalid traffic or viewability drops.

Monthly deep audit

• Run a 90-day placement report and compare to blocked lists—identify false positives or new risky placements.
• Confirm list scope (Global vs Regional) still matches account strategy.
• Audit change log and verify approvals for every change.
• Validate that account-level exclusions are being honored across all eligible campaign types (Performance Max, Demand Gen, Video, Display).

Quarterly governance review

• Stakeholder review of all lists and policies.
• Performance impact analysis: CPA, ROAS, reach, and conversion lift post-exclusions.
• Update taxonomy and version policy if needed.
• Training refresh for media buyers and external agencies.

Advanced strategies for large accounts and MCCs

For manager accounts and multi-brand setups, central control and API automation are essential.

• Centralized vs decentralized: Decide whether to maintain a single global ALPE per client or localize by brand. Centralized is simpler; decentralized provides business-specific nuance.
• Automate with Google Ads API: Use API scripts to propagate lists, record deployments, and sync versions across accounts. Maintain a source-of-truth CSV in cloud storage and use a one-click deploy script to update lists and log changes.
• Integrate with SIEM/BrandSafety feeds: Connect third-party brand-safety providers or internal signals to automatically add placements to a quarantine list that requires manual approval to move to ALPE.

Measuring impact: a mini case study

Example (anonymized): an e-commerce retailer implemented account-level exclusions in January 2026. They followed the staged rollout method and used a control cohort to measure effect.

• Baseline (30 days pre-change): Display + YouTube: 1.2M impressions, $120k spend, 2.1% conversion rate, CPA $45.
• Pilot (14 days): Applied targeted ALPE lists to prospecting campaigns.
• Outcome (30 days post-change): Impressions down 6%, spend down 9%, conversion rate up 14% (from 2.1% to 2.4%), CPA down 21% (from $45 to $35.50).

Key takeaways: the brand lost some low-quality reach but increased efficiency; automation reallocated budget to higher-performing placements. The team used the naming/versioning system to revert two placements that had unintentionally reduced remarketing pool size.

Practical remediation for common issues

• If conversions fall after applying ALPE: run a placement-level diagnostic and compare against the control campaign. Consider restoring specific placements and re-testing.
• If reach tightens: loosen low-priority lists (e.g., LowQuality) while keeping BrandSafety enforced.
• If account-level exclusions are ignored in a campaign: confirm campaign type eligibility and check for conflicting campaign-level settings or policies.
• If you suspect false positives from automated brand-safety signals: quarantine placements in a "Review" list rather than full block—review for 7 days before moving to ALPE.

Operational checklist before your first deployment

• Complete baseline placement audit and export data.
• Create taxonomy and adopt the ALPE naming convention.
• Assemble approval chain and assign owners.
• Build targeted lists and populate reason/evidence columns.
• Perform a pilot on non-critical campaigns with a control cohort.
• Set monitoring dashboards for CPA, conversions, spend shift, and invalid traffic.
• Schedule weekly and monthly audits and a quarterly governance review.

Final recommendations and future-proofing

Account-level placement exclusions are a major operational win in 2026, but they are not a set-and-forget solution. Treat ALPE as a living control: version it, justify every change with data, and govern it centrally. Consider the following forward-looking practices:

• Leverage programmatic brand-safety signals and link them to a quarantine workflow.
• Use API-driven deployment and audit logging to ensure compliance across large accounts.
• Combine ALPE with contextual targeting strategies to reduce reliance on negative matching alone.
• Train automated campaign models by allowing them to explore high-quality placements—use ALPE to block only true risks, not every unknown.

Closing — action plan (first 7 days)

1. Day 1: Export 60-day placement report and build initial risk list.
2. Day 2: Create ALPE taxonomy and naming conventions; set up change log.
3. Day 3–4: Build BrandSafety and LowQuality lists; document evidence.
4. Day 5: Pilot deployment to two prospecting campaigns with control split.
5. Day 6–7: Monitor daily for anomalies; prepare week-2 expansion plan.

Account-level placement exclusions are the operational guardrails you need in a 2026 ad stack dominated by automation and privacy-driven shifts. With a clear taxonomy, staged rollout, naming/version discipline, and routine audits you can reduce wasted spend, protect brand safety, and keep automation working for you instead of against you.

Ready to implement? Use the audit checklist and naming templates in this playbook to deploy your first account-level exclusions this week. If you want a deployment-ready template (CSV, change-log sheet, and monitoring dashboard blueprint), download our free kit or contact our team for a custom rollout plan.

Call to action

Get the deployment kit: a pre-formatted CSV for ALPE lists, a change-log template, and a monitoring dashboard blueprint to keep your ad inventory safe. Deploy smarter and faster—start your ALPE rollout today.

Related Reading

• Department Store Liquidations: How Saks Global Trouble Could Mean Steals on Branded Kits
• Repurposing Longform Video into Biteable Podcast Clips: A Workflow for Entertainment Channels
• Ethical Boundaries and Consent: What Massage Professionals Should Learn from High-Profile Allegations in the Music Industry
• Marketing Budgets vs. Privacy: Auditing Data Sharing When Using Google’s Total Campaign Budgets
• Art & Travel: Small Museums and Unexpected Finds in Rural Hot-Springs Towns