How to Use Google Ads Recommendations Tool Effectively

Google Ads Recommendations can identify tracking problems, missing ad assets, restricted campaigns, new targeting opportunities and potential changes to bidding or budgets.

However, a recommendation appearing in Google Ads does not automatically mean it is right for your business.

Some recommendations fix genuine technical problems. Others expand reach, increase automation, relax bidding targets or encourage additional spending. These changes may help the right campaign, but they can also increase costs, reduce control or generate more low-quality leads when applied without sufficient analysis.

The Recommendations page should therefore be treated as a diagnostic and idea-generation tool—not as an instruction list.

The best approach combines Google’s data and machine learning with:

• Accurate conversion tracking.

• Commercial objectives.

• Lead-quality and revenue data.

• Search-term analysis.

• Budget and capacity constraints.

• Human knowledge of the business.

• Controlled testing and performance review.

This guide explains how Google Ads Recommendations currently work, how optimisation score is calculated, which suggestions deserve attention and which should be treated with caution.

What Are Google Ads Recommendations?

Google Ads Recommendations are personalised suggestions generated from information such as:

• Campaign performance history.

• Current campaign settings.

• Conversion data.

• Search demand and market trends.

• Account structure.

• Ad and asset coverage.

• Budget limitations.

• Policy, feed and tracking problems.

• Features available for the campaign type.

Google describes the Recommendations page as a way to identify changes that could improve campaign performance and efficiency. However, Google also clarifies that its historical estimates do not predict whether an advert or campaign will perform well.

Recommendations can appear at campaign, account and Google Ads manager-account level. They are dynamic, so the available suggestions can change as campaigns collect data, settings change, or Google introduces new features.

A new campaign may initially show few or no recommendations because there is not enough history to generate relevant suggestions.

The Recommendations page is useful, but it is only one component of a complete Google Ads optimisation process.

How to Find the Recommendations Page

In Google Ads, open the Campaigns menu and select Recommendations.

Depending on the campaigns and features within the account, Google may organise suggestions into categories such as:

• Ads and assets.

• Automated campaigns.

• Bidding and budgets.

• Keywords and targeting.

• Repairs.

• Measurement.

• Other recommendations.

The exact mixture will vary between accounts. A Search campaign will not receive the same recommendations as a Shopping, Performance Max, Demand Gen, Video or App campaign.

Each card normally explains:

• What Google recommends changing.

• Why the account is eligible.

• The campaigns or assets affected.

• A potential performance impact or optimisation score uplift.

• The option to apply, edit or dismiss the suggestion.

Never select Apply all simply because several recommendations have been grouped together. Open the recommendation, inspect every proposed change and decide whether each item supports the campaign’s actual objective.

What Is Google Ads Optimisation Score?

Optimisation score is Google’s estimate of how well an account or campaign is configured to perform. It is displayed as a percentage between 0% and 100%.

Google calculates it using factors such as:

• Campaign statistics.

• Campaign settings.

• Campaign status.

• Available recommendations.

• The estimated impact of those recommendations.

• Recent recommendation history.

• Search volume and market trends.

Each recommendation can carry a percentage uplift. Applying it increases the displayed optimisation score by the stated amount.

However, dismissing a recommendation can also increase the score.

An account can therefore reach 100% by applying or dismissing all available recommendations. This is an important distinction: a 100% optimisation score does not prove that the account is profitable, correctly tracked or generating good-quality customers.

Google confirms that optimisation score can be displayed for active Search, Display, Video Action, App, Performance Max, Demand Gen and Shopping campaigns. It is separate from keyword-level Quality Score. Google’s explanation of optimisation score confirms that the two measurements are not the same.

Optimisation Score Is Not a Business KPI

Optimisation score measures alignment with Google’s currently available recommendations. It does not directly measure:

• Profit.

• Return on investment.

• Customer lifetime value.

• Gross margin.

• Lead quality.

• Sales conversion rate.

• Sales-team capacity.

• Cash flow.

• Incremental revenue.

• Whether the business can fulfil additional demand.

A lead-generation campaign could have a high optimisation score while attracting irrelevant enquiries. An ecommerce campaign could reach 100% while spending beyond its profitable marginal return.

Conversely, a tightly controlled campaign could have a lower score because the advertiser has deliberately rejected Broad Match, AI Max, Search Partners, Performance Max or a higher budget.

Use optimisation score to locate potential issues and opportunities. Do not use it as the main measure of account success.

For commercial evaluation, prioritise metrics such as:

• Cost per qualified lead.

• Cost per sales opportunity.

• Customer acquisition cost.

• Conversion value.

• Revenue.

• Gross profit.

• Return on ad spend.

• Lead-to-sale rate.

• New-customer revenue.

• Lifetime value.

If these outcomes happen after the initial website conversion, connect Google Ads with CRM data through offline conversion tracking.

The Main Types of Google Ads Recommendations

Google continually changes and expands the recommendation library. The following categories cover the suggestions most advertisers are likely to encounter.

The safest recommendations tend to repair faults. The most consequential recommendations tend to expand targeting, increase automation or change how Google spends the budget.

Recommendations That Usually Deserve Immediate Investigation

Some recommendations flag problems that can prevent campaigns from serving or cause conversion data to be lost.

Examples include:

• Broken landing-page URLs.

• Disapproved adverts or assets.

• Disapproved Shopping products.

• Merchant Center suspension warnings.

• Missing products in Shopping campaigns.

• Certification problems.

• Conversion actions that have stopped recording.

• A sudden reduction in conversion rate.

• Missing conversion parameters.

• Campaigns with no active adverts.

• Ad groups with no targeting.

• Conflicting negative keywords blocking intended traffic.

These should normally be investigated promptly, but even a repair recommendation needs verification.

For example, a reported conversion-rate reduction could reflect:

• A broken tag.

• A consent-management problem.

• A website release.

• A form malfunction.

• Lower-quality traffic.

• Seasonality.

• Conversion delay.

• A genuine decline in demand.

Do not assume the tracking tag is responsible until you have tested the complete conversion journey.

A proper Google Ads conversion-tracking audit should compare Google Ads data with the website, CRM, telephone system, ecommerce platform and analytics tools.

Measurement Recommendations

Measurement is one of the most important recommendation categories because Google’s automated systems can only optimise the data they receive.

Typical recommendations include:

• Set up conversion tracking.

• Repair conversion tracking.

• Enable auto-tagging.

• Set up enhanced conversions.

• Add conversion values.

• Include suitable conversion actions in account-level goals.

• Use data-driven attribution.

• Configure new-customer acquisition measurement.

• Add app or shop-visit conversions.

These recommendations can be valuable, but the proposed conversion configuration must reflect the business’s real objectives.

Do Not Optimise Every Conversion Equally

A lead-generation account might track:

• Form submission.

• Telephone call.

• Booked appointment.

• Qualified lead.

• Sales opportunity.

• Customer.

• Revenue.

These actions are not equally valuable.

If page views, contact-page visits, button clicks and real customers are all configured as primary conversions, Smart Bidding may optimise towards the easiest action rather than the most commercially valuable outcome.

A stronger lead-generation framework is:

For ecommerce, the primary conversion is normally a completed transaction with accurate order value and transaction ID.

For service businesses, CRM outcomes can help Google distinguish a cheap but unsuitable enquiry from a more expensive lead that becomes a profitable customer.

The objective is not simply to record more conversions. It is to give Google cleaner signals about which customers the business actually wants.

Ads and Asset Recommendations

Google may recommend adding or improving:

• Responsive search adverts.

• Headlines and descriptions.

• Sitelink assets.

• Sitelink descriptions.

• Callout assets.

• Structured snippets.

• Call assets.

• Image assets.

• Location assets.

• Price assets.

• Lead-form assets.

• Videos.

• Dynamic image or sitelink assets.

• Assets in different orientations.

These suggestions can improve advert coverage and give Google more combinations to test. Missing sitelinks, images or useful callouts can unnecessarily restrict an otherwise strong campaign.

However, asset quantity is not the same as asset quality.

Every suggested asset should be checked for:

• Factual accuracy.

• Brand tone.

• Legal and regulatory compliance.

• Relevance to the ad group.

• Alignment with the landing page.

• Meaningful differentiation.

• Correct pricing and promotions.

• Geographic accuracy.

• Clear calls to action.

Google can now use existing adverts, landing pages and other account content to suggest or improve responsive search advert assets. This is significantly more advanced than simply rearranging words from an existing advert.

AI-generated or automatically selected assets can still misunderstand the offer, use outdated website copy or combine messages in ways that are technically valid but commercially weak. Review the complete range of possible combinations, not only the preview Google initially displays.

Our responsive search adverts guide explains how to build assets around customer intent, the business offer and the landing page rather than merely aiming for an “Excellent” Ad Strength rating.

Should You Follow Ad Strength Recommendations?

Ad Strength evaluates whether an advert contains the variety, quantity and relevance of assets Google recommends. It can help identify incomplete responsive adverts.

It should not be treated as a direct profitability score.

An advertiser may improve Ad Strength by adding more headlines while accidentally weakening the clarity of the offer. Excessive variation can also create combinations that do not communicate a coherent message.

Use Ad Strength to identify possible limitations, then evaluate actual performance using:

• Conversion rate.

• Conversion value.

• Qualified-lead rate.

• Cost per acquisition.

• Asset reporting.

• Search-term relevance.

• Landing-page performance.

A lower-rated but carefully controlled advert can sometimes be more commercially effective than an advert designed primarily to satisfy the platform’s completeness indicator.

Bidding and Budget Recommendations

Bidding and budget suggestions can have a substantial effect on spending and traffic.

Current examples include recommendations to:

• Use Maximise Clicks.

• Use Maximise Conversions.

• Use Maximise Conversion Value.

• Introduce a Target CPA.

• Introduce a Target ROAS.

• Use Target Impression Share.

• Adjust CPA or ROAS targets.

• Move unused budgets.

• Increase budgets.

• Prepare for predicted increases in traffic.

• Use portfolio bidding and shared budgets.

These recommendations are generated from campaign data and simulations, but they do not automatically understand the complete financial position of the business.

Evaluate the Conversion Data First

Before changing to conversion-based bidding, verify:

• Primary conversions are commercially meaningful.

• Duplicate conversions are not being counted.

• Consent settings are not causing major data gaps.

• Conversion values are accurate.

• Telephone calls are measured consistently.

• CRM outcomes are being imported correctly.

• Conversion volume is reasonably stable.

• The conversion window reflects the sales cycle.

Automated bidding can be highly effective, but it will optimise whatever conversion goals it is given—even if those goals represent poor-quality leads.

Read our complete Google Ads bidding strategies guide before changing strategy solely because a recommendation appears.

Treat Budget Forecasts as Marginal Decisions

A recommendation to increase budget may forecast more conversions, but the additional conversions may arrive at a higher marginal CPA.

For example:

The recommendation may correctly forecast 25 additional recorded conversions. It does not prove that those additional conversions will produce enough qualified leads, customers or profit.

Before raising the budget, ask:

• Is the campaign already profitable?

• Is impression share being lost because of budget?

• Are the additional searches commercially relevant?

• Can the sales team manage more leads?

• Is fulfilment capacity available?

• Is the forecast based on real sales or superficial conversions?

• Would another campaign produce a better marginal return?

• Could landing-page or conversion-rate improvements generate more value first?

A campaign being “Limited by budget” is not automatically a problem. It simply means Google believes more eligible traffic is available than the current budget can purchase.

Keywords and Targeting Recommendations

This category often presents the greatest tension between reach and control.

Google may recommend:

• Adding new keywords.

• Adding Broad Match keywords.

• Removing redundant keywords.

• Removing non-serving keywords.

• Removing conflicting negative keywords.

• Adding audience segments.

• Refreshing Customer Match lists.

• Enabling Search Partners.

• Using Display Expansion.

• Using optimised targeting.

• Uploading customer lists.

• Targeting more Shopping products.

• Turning on AI Max.

Some suggestions can uncover valuable demand. Others can materially change who sees the adverts.

Adding New Keywords

Review every suggested keyword individually.

Check:

• Search intent.

• Relevance to the service or product.

• Geographic meaning.

• Likely commercial value.

• Existing keyword coverage.

• Appropriate landing page.

• Potential ambiguity.

• Expected cost.

• Negative keyword conflicts.

A keyword being related to the website does not necessarily mean it should be targeted. Informational, employment, research, DIY and low-value searches can appear semantically relevant while having little commercial value.

Adding Broad Match Keywords

Broad Match can help mature Smart Bidding campaigns find searches beyond the advertiser’s explicit keyword list. It can also broaden traffic beyond what a small or poorly measured account can manage.

Broad Match is most defensible when:

• Conversion tracking is accurate.

• Conversion goals represent real business value.

• The campaign receives sufficient conversion data.

• Smart Bidding is already stable.

• Search terms are reviewed regularly.

• Negative keywords are comprehensive.

• The budget can support exploration.

• CRM feedback identifies lead quality.

For a new lead-generation campaign with limited data, starting with high-intent Exact and Phrase Match keywords can provide greater control. Broad Match can then be tested when the account has better data and a clear baseline.

Our keyword match-type guide explains how Exact, Phrase and Broad Match now use meaning and intent rather than operating as purely literal matching rules.

Removing Redundant or Non-Serving Keywords

Account simplification can be beneficial, but inspect the proposed removals before applying them.

Keywords may appear redundant while still serving a deliberate purpose, such as:

• Separating brand and non-brand traffic.

• Preserving different landing pages.

• Maintaining geographic segmentation.

• Comparing match types.

• Protecting reporting structures.

• Controlling high-value commercial terms.

• Supporting a temporary or seasonal campaign.

Similarly, a keyword receiving no traffic may still be useful if it represents an important but infrequent high-value service.

Do not keep thousands of obsolete keywords without reason, but do not let account tidiness override commercial structure.

Removing Conflicting Negative Keywords

This recommendation can identify genuine mistakes where a negative keyword blocks an intended positive keyword.

Always inspect the conflict in context. The negative may have been added intentionally to route searches into another campaign or prevent a low-quality variation from triggering an advert.

Use the Search Terms Report alongside a structured negative keyword process before changing exclusions.

Recommendations to Enable AI Max

Eligible Search campaigns may receive a recommendation to turn on AI Max.

AI Max extends the existing Search campaign with additional Google AI capabilities designed to identify more relevant searches and adapt adverts to the user’s query. This can include broader search matching and asset optimisation features.

Turning it on is not a routine repair. It is a targeting and automation decision.

Before enabling AI Max, examine:

• Current Exact and Phrase Match performance.

• Search-term quality.

• Landing-page suitability.

• Brand controls.

• URL controls and exclusions.

• Conversion accuracy.

• Lead-quality feedback.

• Geographic targeting.

• Budget available for exploration.

• Whether a controlled experiment is available.

AI Max may be valuable when an established campaign has strong tracking and is ready to expand. It is less compelling when the existing campaign already struggles with irrelevant traffic, weak lead quality or insufficient conversion data.

The correct question is not whether AI Max is good or bad. The question is whether its additional reach can be evaluated against a reliable commercial baseline.

Recommendations to Create Performance Max

Google may recommend creating a Performance Max campaign because it can advertise across multiple Google channels using automated bidding, targeting and asset combinations.

Performance Max can be highly effective for ecommerce accounts with:

• Accurate purchase values.

• A strong Merchant Center feed.

• Good product imagery.

• Sufficient transaction volume.

• Appropriate margin and inventory controls.

• Reliable new-customer data.

For lead generation, it requires more caution. If Google receives only basic form submissions, the campaign may optimise towards people who complete forms cheaply rather than people who become suitable customers.

Before applying a Performance Max recommendation, decide:

• Which conversion goals it will use.

• Whether lead quality is imported from the CRM.

• How brand traffic will be handled.

• Whether the campaign overlaps existing Search or Shopping activity.

• Which URLs Google can use.

• Which assets and products are eligible.

• How success will be measured.

• What evidence would justify scaling or stopping the test.

Read our Performance Max guide before replacing a controlled campaign structure with a more automated one.

Search Partners, Display Expansion and Optimised Targeting

Recommendations that enable additional networks or audience expansion can increase reach without increasing the nominal daily budget.

That does not make them risk-free.

Additional inventory can change:

• Traffic sources.

• User intent.

• Placement quality.

• Conversion rate.

• Lead quality.

• Cost distribution.

• Reporting visibility.

A recommendation may highlight that a campaign could receive more conversions at a similar reported CPA. The result still depends on whether the conversion being measured represents a useful customer.

Test expansion separately where possible. Compare source-level performance and examine CRM outcomes rather than judging the change solely by platform-reported conversion volume.

How Auto-Apply Recommendations Work

Google allows selected recommendation types to be applied automatically at account level.

Advertisers can choose individual recommendation categories or broader bundles such as maintaining adverts or growing the business. Google then checks the account regularly and applies eligible changes.

Auto-apply can currently affect areas such as:

• Advert improvements.

• Dynamic Search Ads.

• Advert rotation.

• Bidding strategies and targets.

• Broad Match.

• New keywords.

• Audience segments.

• Search Partners.

• Redundant or non-serving keywords.

• Conflicting negative keywords.

• Conversion tracking upgrades.

Google states that auto-apply recommendations do not directly increase the account’s budget. However, they can still change bids, targets, keywords, networks and traffic allocation within the available budget.

That can materially alter campaign performance.

Which Recommendations Are Safe to Auto-Apply?

There is no universal list that is safe for every account.

For most advertisers, material changes to the following areas should require manual approval:

• Bid strategy.

• CPA or ROAS targets.

• Broad Match.

• New keywords.

• AI Max.

• Search Partners.

• Display Expansion.

• Optimised targeting.

• Dynamic Search Ads.

• Conversion goals.

• Advert text.

• Keyword removal.

Even maintenance recommendations can create unintended consequences. A supposedly redundant keyword may support a deliberate structure, while an automatically removed negative keyword may expose the campaign to irrelevant searches.

If auto-apply is used, restrict it to clearly understood categories and audit its history regularly.

Google provides Manage and History areas within the auto-apply settings. Automatically applied changes can also be reviewed in Change History.

How to Audit Auto-Apply Settings

Use the following process:

1. Open the Recommendations page.

2. Select the auto-apply settings.

3. Review every enabled recommendation category.

4. Disable categories that were not deliberately approved.

5. Open the History tab.

6. Check which recommendations have recently been applied.

7. Review Change History for the exact account changes.

8. Compare the changes with campaign and CRM performance.

9. Record approved settings in the account-management documentation.

This check should also be completed when taking over an existing account. Auto-apply may have been enabled by a previous user, agency or account administrator.

A Practical Framework for Reviewing Each Recommendation

Before applying any material recommendation, answer the following questions.

What Problem Is It Trying to Solve?

Identify the actual issue:

• Is the campaign unable to serve?

• Is conversion tracking broken?

• Is advert coverage incomplete?

• Is the campaign restricted by budget?

• Is Google attempting to expand reach?

• Is a new feature being promoted?

If the recommendation does not solve a clearly defined problem or opportunity, its value is uncertain.

Does It Support the Business Objective?

Determine whether the campaign is trying to generate:

• Revenue.

• Profit.

• Qualified leads.

• Booked appointments.

• Shop visits.

• Brand visibility.

• Market share.

• New customers.

• A specific return on ad spend.

A recommendation optimised for more clicks is not necessarily suitable for a campaign measured by profitable sales.

Is the Underlying Data Reliable?

Check conversion tracking, attribution, values and CRM integration before allowing Google to make decisions from them.

Poor data supplied to a sophisticated bidding system still produces poor optimisation.

What Will the Recommendation Change?

Establish whether the proposal affects:

• Spend.

• Bids.

• Search coverage.

• Networks.

• Advert messaging.

• Landing pages.

• Conversion goals.

• Campaign structure.

• Reporting.

• Automation.

The more areas it changes, the more carefully it should be tested.

What Could Go Wrong?

Consider the main downside:

• Higher spend.

• Higher CPA.

• Lower ROAS.

• Irrelevant searches.

• Poor-quality leads.

• Brand-policy problems.

• Geographic errors.

• Campaign overlap.

• Loss of reporting clarity.

• Insufficient sales or fulfilment capacity.

How Will Success Be Measured?

Define the expected result before making the change.

For lead generation, this might include:

• Qualified-lead volume.

• Cost per qualified lead.

• Sales opportunities.

• Customers.

• Revenue.

For ecommerce, it might include:

• Conversion value.

• ROAS.

• Gross-margin proxy.

• New-customer revenue.

• Product-level profitability.

Apply, Dismiss or Test?

Each recommendation should lead to one of three decisions.

Dismissal is a valid optimisation decision. Google explicitly recognises that advertisers know their products and goals and allows irrelevant recommendations to be dismissed.

Dismissed recommendations can reappear later if the campaign remains eligible.

Where sufficient volume exists, use a Google Ads experiment for major changes such as:

• A new bid strategy.

• Broad Match expansion.

• AI Max.

• A substantially different CPA or ROAS target.

• New landing pages.

• Major targeting changes.

Change one principal variable, define the success metric in advance and allow for conversion delay before making a final decision.

How to Apply or Dismiss Recommendations

To apply a recommendation:

1. Open the Recommendations page.

2. Select View recommendation.

3. Inspect all proposed changes.

4. Edit the selection where the interface permits.

5. Select Apply only when the changes are acceptable.

To dismiss a recommendation:

1. Open the recommendation.

2. Review the full details.

3. Select the dismissal option.

4. Choose an accurate reason where requested.

Google records applied recommendations in Change History. According to its current apply-and-dismiss guidance, an incorrectly applied recommendation can normally be undone through Change History within 30 days. Partially applied recommendations cannot necessarily be reversed through the same undo function, so review bundled changes especially carefully.

How to Measure the Result of an Applied Recommendation

Do not judge a material change the following morning.

Allow time for:

• Bid-strategy learning.

• Conversion delay.

• Sales-cycle delay.

• CRM qualification.

• Seasonality.

• Day-of-week variation.

• Budget pacing.

• Statistical noise.

Record:

• What changed.

• When it changed.

• Why it changed.

• Which campaigns were affected.

• The expected outcome.

• The primary and guardrail metrics.

• When the result will be reviewed.

Avoid making several unrelated changes simultaneously. If the bid strategy, keywords, adverts, budget and landing page all change together, it becomes difficult to determine which change caused the result.

A Recommended Weekly Workflow

A practical Recommendations review can form part of a wider weekly optimisation routine.

First, Check Repairs and Measurement

Investigate:

• Disapprovals.

• Suspensions.

• Broken URLs.

• Missing feed items.

• Tracking warnings.

• Conversion-rate anomalies.

• Certification problems.

Second, Review Auto-Apply History

Confirm that no unexpected changes have been made to:

• Bidding.

• Targets.

• Keywords.

• Advert assets.

• Networks.

• Conversion goals.

Third, Review Ads and Assets

Look for genuine gaps in:

• Sitelinks.

• Callouts.

• Structured snippets.

• Images.

• Videos.

• Calls.

• Locations.

• Responsive advert coverage.

Fourth, Evaluate Targeting Suggestions

Check proposed keywords, audiences and expansion features against:

• Search intent.

• Negative keywords.

• CRM outcomes.

• Current campaign structure.

• Available budget.

Fifth, Evaluate Bidding and Budget Changes

Compare Google’s estimate with:

• Cost per qualified lead.

• Customer acquisition cost.

• Revenue.

• Profit.

• Capacity.

• Marginal return.

Finally, Apply, Test or Dismiss

Document the decision and expected outcome. Do not leave irrelevant recommendations untouched merely because dismissing them feels like ignoring Google’s advice.

Common Mistakes to Avoid

The most frequent Recommendations mistakes include:

• Applying everything to reach a 100% score.

• Treating optimisation score as a profitability metric.

• Increasing budget before checking lead quality.

• Enabling Broad Match without reliable conversion data.

• Changing bid strategy during a short-term fluctuation.

• Allowing weak micro-conversions to guide Smart Bidding.

• Automatically accepting AI-generated advert assets.

• Enabling Performance Max without planning overlap and measurement.

• Removing keywords without understanding campaign structure.

• Enabling Search Partners or audience expansion without monitoring traffic quality.

• Failing to audit auto-apply settings.

• Making several large changes simultaneously.

• Evaluating results before conversion and sales delays have passed.

Final Thoughts

Google Ads Recommendations has developed from a relatively simple list of advert and keyword suggestions into a broader AI-assisted optimisation layer covering measurement, bidding, budgets, assets, targeting and campaign automation.

It can save time, identify genuine faults and reveal opportunities that might otherwise be missed.

It can also encourage changes that increase reach, automation or expenditure without accounting for the advertiser’s complete commercial position.

Use Google’s recommendations as evidence—not instructions.

The strongest decisions combine:

• Google’s account and auction data.

• Accurate online and offline conversion tracking.

• Search-term and audience analysis.

• CRM lead-quality data.

• Revenue and profit.

• The advertiser’s knowledge of its customers.

• Controlled experiments.

• Independent professional judgement.

The goal is not to achieve the highest possible optimisation score. It is to build a Google Ads account that produces more qualified customers, revenue and profit at a sustainable cost.

For a wider account review, use our Google Ads audit guide or explore the complete Google Ads guide.