Optimization Score: which recommendations to follow (and skip)

The Optimization Score is one of the most visible yet most misunderstood features in Google Ads. That percentage in the upper left corner of your account, somewhere between 0% and 100%, looks like a simple quality indicator. In reality, it is far more nuanced. A score of 100% does not automatically mean your campaigns are performing at their best, and a score of 70% does not mean something is wrong. This article explains what the Optimization Score actually measures, which recommendations you should embrace, and which ones deserve a healthy dose of skepticism. Because blindly following every Google suggestion means handing over control of your campaigns.

What is the Optimization Score and how does it work?

The Optimization Score is a value between 0% and 100% that Google calculates based on the number of open recommendations in your account. Each recommendation carries a specific weight. The more recommendations you apply or dismiss, the higher your score climbs. The score is calculated at the campaign, account, and manager level and is updated continuously.

Google's recommendations are designed to help advertisers get more out of their campaigns. In theory, that sounds reasonable. In practice, these recommendations are partly generated by algorithms that do not always account for your specific business goals, profit margins, seasonal patterns, or customer data. Google wants to encourage advertisers to spend more and use broader targeting, two objectives that do not always align with your ROAS target or cost-per-lead goal.

One important thing to know: dismissing a recommendation counts just as much toward your score as applying it. So you can achieve a higher Optimization Score by deliberately choosing which recommendations to reject and documenting your reasoning. That is precisely how a professional Google Ads agency approaches this score.

Recommendations you should almost always follow

Not every Google recommendation is suspect. There are categories of suggestions that consistently add value to virtually any account, regardless of industry or business model. Here are the most important ones.

• Add negative keywords: This is by far the most valuable category. Google identifies search terms that generate clicks but no conversions and advises adding them as negative keywords. This improves your Quality Score, reduces wasted budget, and increases ad relevance.
• Improve ad copy (RSA Ad Strength): Recommendations to improve your Responsive Search Ads, for example by adding more unique headlines or including keywords in the headline, are generally sound. Higher Ad Strength correlates with better CTR and lower CPC.
• Improve conversion tracking: If Google indicates that your conversion tracking is incomplete or inconsistent, always take it seriously. Good conversion data is the fuel for Smart Bidding. Without accurate conversion signals, no bidding strategy can perform optimally.
• Add assets and extensions: Sitelink extensions, callouts, structured snippets, image extensions: they expand your ad real estate at no extra cost and typically boost CTR.
• Address low search volume: If certain ad groups consistently receive few impressions, it signals that your keywords may be too specific or too narrow. Google's advice to consolidate or broaden those keywords is often correct.

For a client like ToetsJeKennis.nl, an online platform for exams and courses, recommendations around RSA Ad Strength and negative keywords are particularly effective. By consistently marking irrelevant terms like "free exam" or "practice questions PDF" as negative keywords, ad relevance improves and cost per conversion drops structurally. The same applies to Clima-Active.nl, an installer of air conditioning and heat pump systems looking for quote requests: excluding terms like "repair" or "breakdown" ensures only purchase-ready traffic reaches the campaign.

Recommendations to approach with caution

The other side of the coin is equally important. Google also generates recommendations that, if followed blindly, can harm your campaigns or unnecessarily grow your budget without proportional results. These are the categories where you always need a second opinion.

• Increase budget: Google almost always recommends increasing your daily budget, based on the percentage of time your campaign is "limited by budget." But a budget-limited campaign does not automatically deserve more budget. Your ROAS may not yet justify scaling, or there may be efficiency improvements to make before increasing investment.
• Enable broad match: The recommendation to convert existing exact match or phrase match keywords to broad match is one of the riskiest suggestions. Broad match gives Google significant freedom to show your ads on search terms far removed from your target audience. Without a robust system of negative keywords and daily search term mining, this can quickly open your account to irrelevant traffic.
• Lower Target CPA or Target ROAS: Google regularly advises loosening your tCPA or tROAS, arguing you can achieve more conversions with a more relaxed target. In reality, this means accepting a higher cost per lead or lower revenue per euro of ad spend. This is a business decision, not an algorithmic recommendation.
• Add Performance Max campaigns: Google increasingly recommends PMax campaigns as the solution for every account. While Performance Max can be powerful with sufficient conversion data and the right setup, it is not a one-size-fits-all solution. In accounts with limited historical data or thin margins, PMax can burn through budget quickly without transparency on where it goes.
• Enable automatically applied recommendations: This is perhaps the most dangerous recommendation of all. Allowing Google to automatically apply suggestions means losing direct control over changes in your account. Keywords can be added, bidding strategies can be adjusted, and budgets can be changed without your active approval.

At E-4motion.com, the webshop for new electric folding bikes, we saw a striking example of why the broad match recommendation can be dangerous. Google advised converting the exact match keywords around "buy electric folding bike" to broad match. Without intervention, this would have led to impressions on search terms like "cheap bike," "rent electric scooter," or even "folding trailer rental," three categories completely outside the product range that only generate wasted budget.

How AdBrains AI evaluates and filters recommendations

At AdBrains, we have developed an automated system that analyzes every incoming Google Ads recommendation before a single change is made to an account. That system operates through multiple AI agents working together in a multi-agent verification process, and it is precisely this approach that fundamentally differentiates our working method from manual account management.

When Google generates a new recommendation, it is immediately fed into our analysis system. The first AI agent classifies the recommendation by type and urgency. The second agent compares the recommendation against current account performance, the active bidding strategy, and the client's margin targets. The third agent tests the recommendation against the historical behavior of similar recommendations in comparable accounts. The fourth agent formulates the final verdict: apply, apply with modifications, or dismiss with a documented reason.

This multi-agent verification system prevents impulsive or counterproductive recommendations from being acted upon. In practice, our AI assesses approximately 73% of all Google recommendations as "do not apply" in the current account context. That sounds high, but it precisely reflects how selective a well-managed account should be with the recommendations Google generates.

Additionally, our automated search term mining system runs daily across all accounts. This system automatically detects which search terms generate clicks but no conversions and adds them as negative keywords, before Google itself generates a recommendation. This keeps our accounts one step ahead of the platform's own suggestions.

For RSA recommendations, we run a dedicated RSA improvement system. This system analyzes the Ad Strength of all ads in managed accounts daily. Ads with POOR status are automatically flagged and rewritten by our AI, with alternative headlines and descriptions that better match the searcher's intent and the landing page. This not only raises Ad Strength but also improves Quality Score and CTR.

Finally, in all AdBrains-managed accounts, the automatically applied recommendations setting is disabled by default. We actively monitor that Google does not push through unapproved changes. Every account change is logged, assessed, and only executed after validation by our AI system. This keeps the advertiser in full control, even when campaigns largely run on autopilot.

The combination of proactive search term mining, RSA optimization, and filtered recommendation processing ensures that AdBrains accounts consistently outperform accounts managed manually or those blindly targeting a high Optimization Score. A high ROAS or low CPL is always the goal, not a high percentage in a dashboard.

A practical framework: how to evaluate recommendations yourself

Not everyone has an AI system available to filter recommendations. But with a structured approach, you can make significantly better decisions on your own. The table below provides a practical overview of the most common recommendation types and the corresponding assessment criteria.

This framework helps you quickly and structurally assess every incoming recommendation. The core message is always the same: evaluate the suggestion against your own goals, not against the percentage Google wants to increase.

Frequently asked questions about the Optimization Score

Should I aim for an Optimization Score of 100%?

No. A score of 100% only means you have applied or dismissed all of Google's open recommendations. It says nothing about the actual performance of your campaigns. It is far more meaningful to optimize for ROAS, CPL, conversion volume, and Quality Score than for a number in a dashboard. In well-managed accounts, a score of 65-80% is often the most realistic outcome, because recommendations that do not fit the strategy are deliberately dismissed.

What happens if I dismiss a recommendation?

When you dismiss a recommendation, it disappears from your open recommendations list and your Optimization Score rises as if you had applied it. Google may re-surface the recommendation later if the situation changes. It is good practice to provide a reason when dismissing, both for your own documentation and for Google's algorithm.

Are automatically applied recommendations always bad?

Not necessarily, but they require extreme caution. Some automatically applied recommendations, such as adding responsive search ads based on landing page content, are relatively safe. But others, such as automatically increasing budgets or enabling broad match, can have a major impact on your campaign strategy and budget. The general recommendation is to disable automatically applied recommendations unless you have a robust system to monitor consequences daily.

How does the Optimization Score affect Smart Bidding performance?

The Optimization Score has no direct influence on Smart Bidding. Smart Bidding operates based on your conversion data, goals, and signals such as device, location, time of day, and audience. What does affect Smart Bidding is the quality of your conversion tracking and the completeness of your conversion signals. Recommendations aimed at improving conversion tracking are therefore indirectly valuable for your bidding strategy as well. Use server-side tracking and Enhanced Conversions to maximize data quality wherever possible.