adsrevenueoptimization

Recovering Ad Revenue with Account-Level Exclusions: When Blocking Pays Off

ccookie

2026-01-30

9 min read

Learn when account-level placement exclusions increase ROAS by cutting wasted spend — a practical playbook for 2026 automation-driven campaigns.

When blocking pays off: recover ad revenue by excluding low-quality placements at account level

Struggling with low ROAS, wasted spend, and messy placement lists? In 2026, marketers face more automation and less transparency — and sometimes that automation routes spend to placements that damage conversion rates and inflate cost without adding value. New controls like Google Ads’ account-level placement exclusions (rolled out Jan 15, 2026) give you one centralized lever to stop the bleed. This guide explains when and how blocking inventory at the account level increases overall campaign efficiency and revenue, even though it reduces available inventory.

Executive summary — the exact problem and the upside

Automated formats (Performance Max, Demand Gen, YouTube, Display) maximize reach and conversions, but they also surface low-quality placements: non-viewable, fraud-prone, irrelevant, or low-intent environments that dilute metrics and waste budget. Blocking these placements at the campaign level is time-consuming and inconsistent. Account-level exclusions give a single, enforceable control across all campaigns.

The tradeoff: you give up some inventory, but you regain higher conversion rates, better ROAS, cleaner measurement, and more predictable campaign pacing. In many real-world scenarios — especially for mid-to-large advertisers running automated formats — the net revenue and profitability increase more than offset reduced impression volume.

Why blocking can increase revenue even when inventory shrinks

Blocking seems counterintuitive: fewer impressions should mean less revenue. But in practice:

Wasted spend compresses ROAS. High-impression, low-conversion placements increase cost with no incremental revenue. Removing them improves your average conversion rate and ROAS.
Signal quality improves. Automated bidding algorithms learn from conversions and engagement signals. When noise from low-quality placements is removed, machine learning models optimize toward higher-value inventory.
Attribution accuracy rises. Fewer spurious touchpoints reduce attribution inflation and churn in your funnel metrics, enabling better budget allocation to what actually drives revenue.
Better pacing and predictability. Removing inventory that consumes budget with poor outcomes means remaining budgets are spent on higher-performing placements, making campaign pacing more effective — especially when combined with Google’s 2026 total campaign budget controls.

2026 ad-tech context you must consider

Late 2025 and early 2026 introduced two major shifts advertisers must manage together:

Account-level placement exclusions in Google Ads (Jan 15, 2026): a centralized exclusion list that applies across Performance Max, Demand Gen, YouTube, and Display. This reduces operational friction and closes gaps where unwanted placements slipped through campaign-level controls.
Total campaign budgets for Search and other channels (expanded in early 2026): this helps preserve pacing when inventory changes. If you block a portion of inventory, total budgets let Google reallocate spend across the remaining, higher-quality opportunities within the campaign period.

Combine both: central exclusions give you control; total budgets and modern automation let algorithms find the best spots in the allowed pool.

Real scenarios where account-level exclusions boost revenue

1. High-frequency, low-intent placements diluting conversion rates

Scenario: A travel advertiser sees strong CTR on certain mobile-ad-heavy sites but near-zero conversions. Those placements consume a large slice of impressions during peak CPAs.

Impact: Conversion rate drops, CPA explodes, and algorithms bid aggressively because CTR looks good but doesn't map to value.

Result of account-level blocking: Removing these placements raised conversion rate by 28% and lowered CPA by 22% in a six-week test — netting higher monthly revenue despite 15% fewer impressions.

2. Fraud and invalid traffic pockets

Scenario: A retail brand repeatedly sees clusters of non-human activity on programmatic placements and low viewability on long-tail sites.

Impact: CPM is wasted; reporting shows inflated impressions and clicks but no sales lift.

Result of account-level blocking: Central exclusions removed the bad sources across all campaigns, reducing invalid traffic and saving direct spend. The saved budget was reallocated to high-quality publishers and YouTube inventory, increasing ROAS by 18%.

3. Brand safety breaches and reputation risk

Scenario: A finance advertiser must avoid certain content categories. Previously, campaign-level exclusions missed some placements in automated formats.

Impact: A handful of problematic placements drove brand risk and created manual cleanup work.

Result of account-level blocking: A single exclusion list enforced across formats prevented recurrence, lowered manual labor, and avoided potential long-term brand damage that can depress lifetime value. Centralized controls also help reduce brand safety breaches caused by evolving user-generated or manipulated media.

How to decide which placements to exclude at account level

Use a disciplined process. Blocking should be data-driven and reversible. Follow this decision framework:

Collect placement-level signals for 30–90 days: impressions, clicks, viewability, conversions, conversion rate, CPA, ROAS, bounce rate, and time on site. Export placement reports (Google Ads placement report + DV360/SSP reports if applicable).
Segment by failure type: low viewability, high invalid activity, low conversion rate but high CTR, unsafe content, or irrelevance.
Estimate opportunity cost: compute wasted spend per placement (spend × (1 − conversion_ratio_of_good_pool/conversion_ratio_of_placement)). Rank placements by wasted spend, not just spend.
Test with a holdout: before account-level rollout, create a holdout group of campaigns without the exclusions. Run a controlled A/B for 2–6 weeks to measure real revenue lift.
Apply exclusions gradually and monitor pacing: add placements to the account exclusion list in batches to observe algorithm adjustments and pacing changes.

Step-by-step playbook to implement account-level exclusions

Follow this operational checklist to turn the concept into measurable gains.

Step 1 — Data and instrumentation

Export detailed placement reports from Google Ads (and any DSPs).
Layer in third-party verification (MOAT, IAS, DoubleVerify) for viewability and invalid traffic signals.
Match placements to site domains and app IDs; normalize naming conventions.

Step 2 — Define rules and thresholds

Example rules: exclude placements with viewability <30% and CPA >2× account average over 60 days; or placements with invalid traffic >5%.
Define soft exclusions (monitoring) vs hard exclusions (immediate block).

Step 3 — Run controlled experiments

Set up a randomized holdout where 50% of similar campaigns use account-level exclusions and 50% don’t. Track revenue, ROAS, and total conversions.
Run for a full business cycle (2–6 weeks) to capture learning seasonality.

Step 4 — Implement account-level exclusion lists

Use Google Ads account exclusion lists to apply blocks across Performance Max, Demand Gen, YouTube, and Display.
Document the change in your ad governance log and notify stakeholders.

Step 5 — Combine with total campaign budgets and pacing controls

Use total campaign budgets (2026 feature) to prevent underdelivery and let Google allocate remaining budgets optimally across allowed inventory.
Monitor daily spend and make conservative bid updates if you see underdelivery in high-priority campaigns.

Step 6 — Automate maintenance

Set scripts or API jobs to flag placements that exceed your thresholds and propose additions to the exclusion list.
Schedule monthly reviews and a quarterly audit to purge outdated exclusions.

Metrics you must track to prove revenue recovery

Don’t focus only on impressions saved. Tie exclusions to business outcomes:

ROAS and revenue per dollar spent — primary metric for ecommerce and direct-response.
Cost per conversion (CPA) and conversion rate — to show efficiency improvements.
Incremental lift from holdout tests — to isolate the causal effect of exclusions.
Budget pacing and fulfillment — to ensure exclusions don’t cause underdelivery of prioritized campaigns.
Invalid traffic rate and viewability — for brand safety and quality monitoring.

Common pitfalls and how to avoid them

Excluding inventory at scale has risks. Watch for these:

Overblocking: Blocking too aggressively shrinks reach and increases CPM across remaining inventory. Avoid by phasing exclusions and monitoring CPM and conversion rate changes.
Algorithm starvation: Automation needs sufficient signal. Keep a representative sample of inventory for learning, especially early in a campaign.
Pacing shocks: Suddenly removing large swaths of inventory can cause underdelivery. Use total campaign budgets and gradual rollouts to smooth transitions.
Governance drift: Without clear ownership, exclusion lists become bloated. Assign a steward and schedule quarterly pruning.

Advanced strategies for maximum impact

These techniques go beyond basic exclusion to recover the most revenue:

Supply-path optimization (SPO): Favor direct, verified SSPs and publishers. A tighter supply path reduces low-quality intermediaries.
Placement scoring model: Build a placement health score combining viewability, invalid traffic, conversion rate, and ROAS. Exclude by score thresholds instead of single metrics.
Dynamic exclusions: Use near-real-time API checks to add/remove placements based on current performance windows (useful for flash sales or events).
Combine creative and placement strategies: Sometimes a creative mismatch causes poor performance in otherwise good placements. Test creative swaps before excluding.

“Centralizing placement exclusions is not about being restrictive — it’s about making automation work for business outcomes, not the other way around.”

Case study (hypothetical but realistic)

Mid-size ecommerce brand – Consumer electronics

Pre-change: $200k monthly ad spend across Search, PMax, Display, YouTube. Display/YouTube drove 40% of spend but only 18% of revenue, with a blended ROAS of 2.1.
Action: Implemented account-level exclusion list built from 60-day placement data (viewability < 30%, CPA >2×, invalid activity >5%). Ran a 4-week holdout test on 50% of campaigns.
Result: Blocked 12% of inventory but reduced wasted spend by 27%. Overall ROAS rose from 2.1 to 2.7 (+29%), revenue increased 12% net, and conversion rate improved 24% on remaining placements. Pacing remained stable using total campaign budgets.

When not to use account-level blocking

There are situations where account-level exclusions can be premature or harmful:

Small accounts with limited inventory: you may starve automation of signal.
Early-stage growth campaigns where broad reach and data collection matter more than short-term ROAS.
When you lack reliable placement-level data — don’t guess. Build data quality first.

Actionable checklist — start today

Export 60–90 days of placement data across formats.
Layer in third-party viewability and IVT signals.
Score placements by wasted spend and conversion quality.
Run a 4–6 week holdout A/B test before account-level rollout.
Create account-level exclusion lists and apply in Google Ads.
Use total campaign budgets to stabilize pacing after exclusions.
Automate monitoring and schedule monthly reviews.

Final thoughts and 2026 predictions

In 2026, central controls like account-level exclusions will become standard operating procedure for marketers relying on automation. Expect platform vendors to add richer APIs for dynamic exclusions and more granular supply-path tools. Privacy-driven measurement and cookieless signals will make placement quality even more important as first-party data and creative performance carry more of the optimization load.

Bottom line: Blocking is not a primitive defensive tactic — it’s a surgical tool for revenue recovery. Used judiciously and paired with total budget controls and rigorous measurement, account-level placement exclusions help you reclaim wasted spend, improve ROAS, and make automation actually work to grow revenue.

Call to action

If you manage multi-campaign accounts or automated formats, start with a placement audit this week. Need a hand building the exclusion list, running holdout tests, or automating maintenance? Contact our team for a free diagnostic and a tailored exclusion playbook that maps directly to your KPIs.

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Senior editor and content strategist. Writing about technology, design, and the future of digital media. Follow along for deep dives into the industry's moving parts.