Google Ads Optimisation Score Best Practices

Last updated: 6 August 2026

Executive Summary: Five Key Principles for Optimisation Score in 2026

Google Ads Optimisation Score is one of the most visible — and most misunderstood — metrics in the platform. Used well, it is a powerful triage tool that surfaces genuine setup gaps and prioritises improvement opportunities. Used poorly, it becomes a vanity target that drives harmful changes to bidding, budgets, and match types. The five principles below underpin everything in this article.

• Score is a recommendation inventory, not a performance report. Optimisation Score reflects the weighted value of available recommendations Google believes apply to your account. It does not measure profit, ROAS, or CPA. A score of 72% does not mean your account is underperforming; it means Google has identified recommendations it estimates would improve performance if applied.^[9]
• 100% is not the goal. Deliberately dismissing recommendations that conflict with your strategy reduces the score but improves the outcome. Experienced practitioners consistently target a healthy score — typically above 70% after strategic dismissals — rather than chasing 100% by accepting every suggestion.^[3]
• Apply, review, or dismiss — never auto-apply blindly. Every recommendation must be triaged against your conversion data quality, bidding strategy maturity, and business goals. Auto-apply is suitable for a narrow set of low-risk, reversible hygiene tasks only.^[3][12]
• Measurement quality comes first. Any recommendation involving bidding strategy, broad match, or budget scaling is unreliable if conversion tracking is broken or incomplete. Fix tracking before acting on growth recommendations.^[1][4]
• Judge changes by downstream KPIs, not score movement. Applying a recommendation may lift your score by several percentage points and simultaneously degrade ROAS. Always define a test window and KPI benchmark before applying significant recommendations, then review the outcome before keeping the change.^[10][14]

Benchmarks and Numbers at a Glance

Metric	Typical range or threshold	Applies when	Source
Optimisation Score range	0–100%	All Google Ads accounts; vendor-defined scale	[9]
Meaning of 100% score	Account “can perform at its full potential” — vendor claim	Achieved only when all recommendations are applied or dismissed; vendor claim, not an independent performance measure	[9]
Practitioner-recommended healthy score target (post-dismissal)	70–90%	After deliberately dismissing recommendations that conflict with strategy; independent practitioner guidance, not a Google threshold	[3][15]
Score impact per recommendation	Varies; each recommendation displays its individual score impact in the UI	Shown per recommendation on the Recommendations page; applies when recommendation is active and unactioned	[9][7]
Auto-apply review cadence (best practice)	At least once every 7 days	Accounts with any auto-apply settings enabled; practitioner guidance	[1][10][12]
Customer Match list refresh threshold	90 days	Google surfaces REFRESH_CUSTOMER_MATCH_LIST recommendation when a list has not been updated in 90 days	[3][15]
Minimum conversion data for Smart Bidding (Target CPA / Target ROAS)	30–50 conversions in the past 30 days (Google’s stated guideline — vendor claim)	Required before switching to Target CPA or Target ROAS bid strategies; vendor guidance	[5][11]
Broad match recommended minimum conversion volume	At least 30 conversions in 30 days before expanding to broad match — practitioner benchmark	Applies when evaluating USE_BROAD_MATCH_KEYWORD recommendation; insufficient data increases irrelevant traffic risk	[5][11]
Responsive Search Ad minimum asset count for full coverage	3 headlines pinned maximum; 15 headlines and 4 descriptions for full asset strength	Applies when Google surfaces RESPONSIVE_SEARCH_AD_ASSET recommendation; vendor claim	[3][8]
Budget recommendation trigger (MARGINAL_ROI_CAMPAIGN_BUDGET)	Shown when a campaign is budget-constrained on more than 20% of days in the reference window — vendor claim	Search and Shopping campaigns limited by budget; vendor claim based on API documentation	[3][8]
Score availability levels	Account level and campaign level	All account types; account score aggregates campaign scores weighted by spend and impact	[9][10]
Google Tag coverage recommendation trigger	Surfaces when tag fires on fewer than 100% of eligible conversion pages — vendor claim	IMPROVE_GOOGLE_TAG_COVERAGE recommendation; applies to accounts with partial tag deployment	[3][8]

What Optimisation Score Measures

Optimisation Score is a Google-generated estimate of how well an account is positioned to achieve its performance potential, expressed as a percentage between 0 and 100.^[9] It is calculated at both the account (customer) level and the individual campaign level, with the account-level score aggregating campaign scores weighted by estimated spend impact.^[7][9]

The score is not a direct measurement of profit, ROAS, CPA, impression share, or any independent business KPI. It is, in practical terms, a weighted inventory of available recommendations. Each recommendation Google surfaces carries an estimated score impact value; applying or dismissing a recommendation adjusts the score accordingly.^[9] Google does not publicly disclose the weighting formula in detail, which means the score should be treated as a recommendation-weighted estimate rather than a transparent, auditable metric.^[7]

The score changes in three ways: it increases when you apply a recommendation, it increases when you dismiss a recommendation (because dismissing removes it from the pending pool), and it can decrease when Google identifies new optimisation opportunities in your account that were not previously present.^[9]

Because the score responds equally to applying and dismissing recommendations, a well-managed account with many deliberate dismissals can legitimately sit at 85–90% and be far better run than a naively managed account sitting at 100% that has accepted every suggestion uncritically.^[3]

In terms of what drives the score, Google organises recommendations into broad families: bidding and budgets, keywords and targeting, ads and assets, automated campaigns, and measurement and tracking.^[3][11] Measurement-related recommendations — including the IMPROVE_GOOGLE_TAG_COVERAGE and conversion tracking fix types — have become increasingly prominent in recent documentation, reflecting Google’s emphasis on measurement quality as a prerequisite for effective automation.^[3][8]

Is 100% the Goal?

No — and this distinction is critical. Google defines a score of 100% as meaning the account “can perform at its full potential,” but this is a vendor claim based on the premise that all currently surfaced recommendations are correct for the account.^[9] In practice, many recommendations benefit Google’s ecosystem — broader reach, higher spend, more automation — as much as they benefit the advertiser.

The best practitioners in 2026 treat Optimisation Score the way a senior engineer treats compiler warnings: every warning deserves a read, most deserve a fix, but some reflect deliberate architectural choices that should be suppressed with a documented reason. Blindly eliminating all warnings produces clean output that may still fail at runtime.^[3][5]

A consistently maintained score in the range of 70–90% — achieved through a mix of genuine improvements and documented strategic dismissals — is a more credible signal of account health than 100% achieved by accepting every recommendation.^[3][15] This is especially true for accounts with tightly controlled brand terms, narrow match-type strategies, fixed budget ceilings, or CPA targets that leave little room for exploratory spend.

The key discipline is intentionality. A score of 65% where every dismissed recommendation has a documented reason is strong account management. A score of 65% where the manager has never reviewed the Recommendations tab is neglect. The number alone tells you nothing about the quality of the decision-making behind it.

Recommendation Types Explained

Google organises its recommendations into several broad families, each covering a different dimension of account setup and performance. Understanding what each family targets — and what risks each carries — is the foundation of effective triage.^[3][11]

Bidding and Budget Recommendations

These include suggestions to switch bid strategy (for example, from Manual CPC to Target CPA or Target ROAS), to increase daily budgets on constrained campaigns (MARGINAL_ROI_CAMPAIGN_BUDGET), and to adjust target CPA or ROAS values. These recommendations carry the highest score weights and the highest risk. They should never be auto-applied.^[3][5]

Keywords and Targeting Recommendations

This family includes USE_BROAD_MATCH_KEYWORD (the successor to the deprecated KEYWORD_MATCH_TYPE recommendation^[15]), keyword expansion suggestions, and audience targeting additions. These change the shape of traffic entering the account and require conversion data validation before application.^[1][11]

Ads and Assets Recommendations

Includes RESPONSIVE_SEARCH_AD_ASSET additions, sitelink and callout extensions, image assets, and headline or description diversification. These are generally lower risk and often worth applying, provided the suggested content is accurate and on-brand.^[1][3]

Automated Campaign Recommendations

Suggestions to create Performance Max campaigns, upgrade existing campaigns to PMax, or enable additional campaign types. These represent significant structural changes that alter how Google allocates budget across inventory and should be treated as strategic decisions requiring full review, not recommendations to accept at face value.^[1][11]

Measurement and Tracking Recommendations

Includes IMPROVE_GOOGLE_TAG_COVERAGE, conversion tracking setup fixes, and enhanced conversion configuration. These are almost always worth acting on because weak measurement degrades the quality of every other recommendation in the account.^[3][8]

Recommendations to Apply

The following recommendation types are generally safe to apply — either immediately or after a brief content review — because they improve account completeness, fix genuine defects, or address measurement gaps without fundamentally altering traffic acquisition or spend behaviour.^[1][3]

Conversion Tracking and Measurement Fixes

Any recommendation in the IMPROVE_GOOGLE_TAG_COVERAGE or conversion tracking repair category should be prioritised above all others. Measurement quality is the prerequisite for every other optimisation; Smart Bidding, broad match, and budget recommendations all rely on accurate conversion data to function correctly.^[3][8] If the tag is misfiring, apply the fix before acting on any growth recommendation.

Responsive Search Ad Assets

Adding headlines, descriptions, and asset extensions to RSAs generally improves Ad Strength, gives Google’s system more legitimate combinations to test, and is reversible if the additions perform poorly. Review suggested copy for accuracy and brand compliance before applying, but do not treat this as a high-risk change.^[1][3]

Sitelinks, Callouts, and Structured Snippets

These assets improve ad real estate and relevance without changing bidding or targeting. Apply them after a content review. Ensure destination URLs are live and the copy reflects current offers — particularly important around seasonal promotions in Q4 2026 when landing pages change frequently.^[1]

Keyword Cleanup Recommendations

When Google recommends removing keywords that have zero impressions over 90 days, are redundant due to match-type overlap, or are conflicting with negatives, these are generally safe to action — but only after you verify in your own data that those keywords are genuinely non-contributing. Do not accept keyword removal recommendations in bulk without a per-keyword check.^[3]

Customer Match List Refresh

When the REFRESH_CUSTOMER_MATCH_LIST recommendation appears — triggered after 90 days without a list update^[15] — refreshing the list with current CRM data is straightforward best practice, provided you have the data governance processes in place to do so compliantly under Australian Privacy Act obligations.

Recommendations to Dismiss

Certain recommendations appear frequently, carry high score weights, and look compelling in the UI — but routinely conflict with sound account management. Dismissing these with documented reasons is not bad practice; it is good practice.^[3][5]

Bid Strategy Changes Without Sufficient Data

Recommendations to switch from Manual CPC or Enhanced CPC to Target CPA or Target ROAS should be dismissed unless the account is recording at least 30 conversions per 30 days with consistent conversion value tracking.^[5][11] Switching to Target ROAS on a campaign with 12 conversions a month places Smart Bidding in a permanent learning state and typically increases CPA before any improvement emerges.

Broad Match Expansion Without Smart Bidding and Conversion Volume

The USE_BROAD_MATCH_KEYWORD recommendation should be dismissed unless three conditions are simultaneously met: Smart Bidding is active, the campaign records at least 30 conversions per 30 days, and a weekly search-term review process is in place to identify and negate irrelevant queries.^[5][11] If any one of those conditions is absent, broad match is likely to increase spend on irrelevant queries faster than Smart Bidding can learn to suppress them.

Budget Increases on Campaigns With Unstable CPA

Budget increase recommendations (MARGINAL_ROI_CAMPAIGN_BUDGET) should be dismissed when the account’s CPA is trending upward, conversion tracking is incomplete, or the business has a fixed monthly budget ceiling. Even when a campaign is legitimately budget-constrained, the correct response is a considered budget review aligned with board-approved spend limits — not auto-applying a platform-suggested increase.^[3][5]

Dynamic Search Ad Creation in Brand-Controlled Accounts

DSA recommendations should be dismissed for accounts where brand messaging, legal compliance, or pricing accuracy requires tight copy control. DSAs generate headlines directly from page content, which can surface outdated offers, incorrect pricing, or off-brand phrasing that a manually authored RSA would not.^[3]

Automated Campaign Upgrade Suggestions

Recommendations to upgrade existing campaigns to Performance Max or to create new PMax campaigns should be treated as strategic decisions requiring a full briefing, not single-click actions. PMax operates across all Google inventory and shifts budget allocation control to Google’s systems; this may be appropriate but should never be actioned from the Recommendations tab without a separate strategic review.^[1][11]

The Risks of Auto-Apply

Auto-apply is the feature that allows Google to implement recommendations on your behalf without manual approval. It is managed at the account level, meaning the settings apply across all campaigns rather than being configurable per campaign.^[10][14] Google provides a history log of auto-applied changes, and email notifications can be enabled to alert you when changes occur.^[1]

The core risk is not that auto-apply makes changes — it is that it makes changes at a pace and scale that outstrips the account manager’s ability to detect and reverse them before they cause measurable harm. An account with auto-apply enabled across bidding, broad match, and budget categories can absorb a cluster of interconnected changes overnight that collectively destabilise a campaign’s learning period and inflate CPA for weeks.^[3][12]

What to Enable for Auto-Apply (Low-Risk Only)

The following recommendation types are broadly considered low-risk for auto-apply because they are either easily reversible, additive rather than structural, or address genuine defects with no strategic downside:^[1][10][12]

• Ad and asset additions (sitelinks, callouts, structured snippets) — provided you review the suggestion feed regularly for off-brand content.
• Redundant keyword removal — where the keyword has zero impressions for 90+ days.
• Conversion tag fixes where Google can automatically implement the correction via the Google Tag.

What to Never Enable for Auto-Apply

• Bid strategy changes of any kind.^[3][12]
• Budget increases or reallocation.^[3][5]
• Broad match keyword expansion.^[5][11]
• Target CPA or Target ROAS value adjustments.^[3][12]
• New campaign creation, including Performance Max.^[1][11]
• Audience targeting expansion.^[12][18]

Maintaining Oversight

Best practice is to review the auto-apply change history at a minimum weekly cadence — specifically by navigating to Recommendations > Auto-apply history and cross-referencing with the account’s Change History report.^[1][10][12] Any change that correlates with a CPA increase, CTR drop, or impression quality degradation in the week following the auto-apply event should be reversed immediately and the relevant recommendation type removed from auto-apply settings.

Using Score in Audits and Across Accounts

At the account level, Optimisation Score is most useful as an audit triage tool: it tells you where Google believes the largest improvement opportunities exist and lets you prioritise which campaigns to examine first.^[10][14] At the campaign level, individual scores help pinpoint which specific campaigns are contributing most to the aggregate gap.^[10]

For managers overseeing multiple accounts — whether in an agency context or an in-house team running multiple brands — the Recommendations tab in Google Ads Manager (MCC) surfaces scores and recommendations across accounts, making it possible to identify systematic patterns: for example, if 14 out of 20 accounts are receiving the same IMPROVE_GOOGLE_TAG_COVERAGE recommendation, that signals a deployment process issue rather than 14 individual account problems.^[10][14]

Building an Audit Workflow Around Score

A practical audit workflow for 2026 uses Optimisation Score as the entry point, not the conclusion:^[10][12]

• Start by noting the account score and which recommendation categories contribute most to the gap between current score and 100%.
• Cross-reference each recommendation against the account’s conversion data, bid strategy maturity, and budget constraints before making any change.
• Compare score movement over the past 30 days with KPI movement over the same period — if score went up but ROAS went down, interrogate which changes were made.
• Review the auto-apply history and change history simultaneously; score-changing events and performance-changing events should be traced to the same change log.
• Document every dismissed recommendation with a reason; this creates an audit trail that supports account continuity when the account changes hands.

Score as a Client Reporting Tool

Optimisation Score should be used cautiously in client reporting. Presenting it as a performance metric risks creating pressure to chase 100% at the expense of genuine outcomes. If score is included in reports, it should always be contextualised alongside CPA, ROAS, and conversion volume — and clients should be briefed that strategic dismissals intentionally keep the score below 100%.^[3][9]

Broad Match and Budget Recommendations

Broad match and budget recommendations are the two recommendation types that most frequently cause harm when applied without adequate preparation. They also carry some of the highest score weight values in the system, which makes them disproportionately tempting to action when an account manager is under pressure to improve a score.^[3][5]

Broad Match: The Conditions for Safe Adoption

Broad match is not inherently dangerous — but it is conditionally safe. The 2026 consensus across practitioner and platform guidance is that broad match works well when it is paired with Smart Bidding, sufficient conversion volume, and active search-term monitoring.^[5][11] The conditions are:

• Smart Bidding (Target CPA or Target ROAS) is already active and out of its learning period.
• The campaign records at least 30 conversions per 30 days with consistent conversion value.^[5][11]
• A search-term review is conducted at a minimum weekly cadence to identify and negate irrelevant expansions.
• A negative keyword list is in place and current.

If those four conditions are not simultaneously met, the USE_BROAD_MATCH_KEYWORD recommendation should be dismissed. The deprecated KEYWORD_MATCH_TYPE recommendation has been replaced by USE_BROAD_MATCH_KEYWORD in the current API documentation^[15], so any accounts still showing the older recommendation type are seeing a legacy item that should be treated identically.

Budget Recommendations: Incremental Scaling Over Platform Suggestions

The MARGINAL_ROI_CAMPAIGN_BUDGET recommendation surfaces when Google estimates a campaign is budget-constrained — typically when it is limited by budget on more than approximately 20% of days in the reference window.^[3][8] The recommendation itself is not wrong to surface; budget constraints are a genuine performance limiter. The problem is the scale and timing of the suggested increase, which is calculated to maximise spend allocation rather than to respect the account’s CPA stability or business budget ceiling.

Best practice is to use the recommendation as a signal — “this campaign is constrained and may benefit from more budget” — and then make an independent, incremental budget decision based on current CPA trajectory, ROAS, and business capacity. A conservative rule of thumb is to increase the daily budget by no more than 15–20% at a time and allow a 7-day stabilisation period before evaluating the impact.^[4][5]

Common Mistakes to Avoid

The following mistakes recur across accounts of all sizes and budget levels. Each one either degrades account performance directly or undermines the measurement quality needed to make sound decisions.^[3][5][12]

Treating Score as a KPI in Reporting

Including Optimisation Score as a primary performance metric in executive or client reports creates the wrong incentive structure. Stakeholders who see score as a performance measure will pressure account managers to maximise it, which leads to accepting recommendations that increase spend and reach at the cost of CPA efficiency. Score belongs in the operational dashboard of an account manager, not in a client-facing performance summary alongside ROAS and CPA.^[9][10]

Applying Recommendations in Bulk Without Individual Review

The “Apply all” button on the Recommendations page is one of the most dangerous features in the platform. Applying all pending recommendations in a single click can simultaneously change bid strategies, expand match types, increase budgets, and create new ad variations — a cluster of interconnected changes that are impossible to attribute individually if performance subsequently degrades.^[3][12]

Ignoring Score for Months, Then Acting Quickly

An account where the Recommendations tab has been unreviewed for 60 days may accumulate 15–20 pending recommendations. The temptation to action them all in one session to quickly recover score creates the same bulk-apply risk described above. Best practice is a weekly or fortnightly triage cadence that catches recommendations individually when their context is fresh.^[10][12]

Dismissing Without Documenting Reasons

A dismissed recommendation with no documented reason provides no audit trail. When the account changes hands — as accounts frequently do — the incoming manager sees a dismissed recommendation and has no way to know whether it was dismissed strategically or accidentally. Always use the dismissal reason field, even for self-evident cases.^[3][14]

Acting on Growth Recommendations Before Fixing Measurement

Applying a Target ROAS bid strategy or broad match expansion on an account with a broken conversion tag or incomplete Google Tag coverage produces Smart Bidding optimised toward incomplete data. The resulting performance degradation is often attributed to the bid strategy change rather than the measurement gap, leading to a cycle of strategy reversals that never address the root cause.^[3][8]

Confusing Score Movement With Performance Improvement

A score that moves from 61% to 85% after a triage session is a positive signal — but it needs to be validated against actual KPIs over the following 14–30 days. Score movement confirms that recommendations were actioned; it does not confirm that performance improved. Always define a measurement window and KPI baseline before applying significant recommendations.^[9][10]

What Changed Recently (Last 30 Days)

As of August 2026, Google has not published a single consolidated changelog for Optimisation Score and recommendations in the preceding 30 days. The sources available confirm that the core framework — 0–100% scale, recommendation-weighted calculation, account and campaign level visibility — is unchanged.^[1][3] However, several developments in the recommendation catalogue and platform behaviour are notable for practitioners conducting account audits in this period.

Recommendation Catalogue Updates

The KEYWORD_MATCH_TYPE recommendation type has been formally deprecated in Google’s API documentation and replaced by USE_BROAD_MATCH_KEYWORD.^[15] Any accounts still displaying the legacy recommendation type should treat it identically to the new type. Practitioners auditing accounts that have not been reviewed since early 2026 may find both variants in their recommendation history.

The following recommendation types are currently documented as active and are being prominently surfaced in accounts across Search, Shopping, and Performance Max campaigns:^[3][8][11]

• MARGINAL_ROI_CAMPAIGN_BUDGET — budget increase for constrained campaigns.
• USE_BROAD_MATCH_KEYWORD — replacement for deprecated match-type recommendation.
• RESPONSIVE_SEARCH_AD_ASSET — ad asset additions and diversification.
• SET_TARGET_ROAS — bid strategy upgrade recommendation.
• REFRESH_CUSTOMER_MATCH_LIST — triggered at 90-day list staleness.
• IMPROVE_GOOGLE_TAG_COVERAGE — measurement gap identification.

Emphasis on Measurement-First Recommendations

Google’s current documentation and recommendation guidance places increased emphasis on measurement quality as a prerequisite for other optimisations.^[3][8] The IMPROVE_GOOGLE_TAG_COVERAGE recommendation type is now explicitly listed as part of the scored recommendation system, meaning tag coverage gaps directly reduce Optimisation Score. This is a meaningful change from earlier iterations of the system, where measurement recommendations were advisory rather than score-weighted.

Value-Based Bidding and ROAS Guidance

Google’s current best-practice signals are strongly oriented toward value-based bidding — specifically setting or optimising Target ROAS — for e-commerce and lead generation accounts with sufficient conversion volume.^[3][11] The SET_TARGET_ROAS recommendation is being surfaced more aggressively in accounts currently on Target CPA or Maximise Conversions. As noted throughout this article, this recommendation should only be actioned when conversion value tracking is consistent and the campaign is recording sufficient volume.^[5][11]

Auto-Apply Oversight Remains Critical

There is no indication from available sources that Google has changed the mechanics of auto-apply in the past 30 days. However, practitioners reviewing accounts set up prior to mid-2026 should audit their auto-apply settings, as the default configuration may have been altered during earlier platform updates. Navigate to Recommendations > Auto-apply settings and verify that only low-risk recommendation types are enabled.^[1][10]

Important caveat: the sources underpinning this article do not include a dated Google changelog for the 30 days prior to August 2026. The developments described above reflect the current documented state of the platform rather than confirmed changes within a specific 30-day window.^[1][3] Account managers should use Change History and the auto-apply history log to verify what has actually changed in their specific accounts over any given period.

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