7 Smart Strategies for Handling Google Ads Recommendations (Without Blindly Clicking 'Apply All')

Google Ads recommendations can feel like a blessing or a trap—depending on how you handle them. On one hand, Google's machine learning analyzes your account history, campaign settings, and platform trends to surface potentially useful suggestions. On the other hand, many of these recommendations nudge you toward broader targeting and higher spending, which coincidentally aligns perfectly with Google's revenue goals.

The "Apply All" button sits there, tempting you with the promise of instant optimization. But clicking it without critical evaluation is like accepting every piece of advice from a salesperson who gets paid on commission. Some suggestions genuinely improve performance. Others just increase your ad spend while diluting your targeting precision.

The difference between advertisers who thrive and those who struggle often comes down to how they handle these recommendations. Smart PPC managers don't ignore them entirely, but they don't blindly accept them either. They've developed systematic approaches for evaluating each suggestion against their actual campaign goals.

Whether you're managing your first campaign or your hundredth client account, these seven strategies will help you work with Google Ads recommendations like a seasoned pro—extracting the genuine value while protecting yourself from suggestions that serve Google's interests more than yours.

1. Treat Your Optimization Score as a Compass, Not a Command

The Challenge It Solves

That optimization score staring at you from the top of your Recommendations tab creates psychological pressure. It ranges from 0-100%, and anything below 80% can feel like failure. Google presents it as a measure of how well-optimized your campaigns are, which triggers our natural desire to maximize that number.

The problem? Chasing a 100% optimization score often means accepting recommendations that conflict with your actual business objectives. A campaign perfectly optimized for Google's definition of success might be poorly optimized for your specific conversion goals, profit margins, or brand positioning.

The Strategy Explained

Think of your optimization score as directional guidance rather than a performance metric. It shows you where Google sees potential changes, but it doesn't understand your business context the way you do. A campaign running at 65% optimization might be performing brilliantly if it's driving qualified leads at your target cost per acquisition.

The score becomes useful when you view it as a starting point for investigation rather than a destination. Instead of asking "How do I get to 100%?" ask "Which of these suggestions actually align with my campaign goals?" This mental shift transforms the score from a source of pressure into a tool for discovery.

Implementation Steps

1. Check your optimization score weekly, but immediately look past the percentage to the actual recommendations driving it.

2. Compare your current score against your actual performance metrics—if conversions are up and cost per acquisition is down, your "low" score might be perfect.

3. Accept that your optimization score will fluctuate as you dismiss recommendations, and that's completely fine if your business metrics are trending positively.

Pro Tips

Create a simple spreadsheet tracking your optimization score alongside your actual KPIs each week. You'll quickly see that the correlation between a high optimization score and strong business results is weaker than Google implies. This data becomes your evidence for confidently ignoring score pressure when your campaigns are performing well.

2. Categorize Recommendations by Risk Level Before Acting

The Challenge It Solves

Google Ads recommendations arrive as a mixed bag of high-impact changes and low-risk tweaks, but they're presented with equal visual weight. A suggestion to switch to broad match keywords (high risk) sits right next to a suggestion to add a sitelink extension (low risk). Without a framework for quickly assessing potential impact, you might spend equal time evaluating both—or worse, accept the risky one because it promises a bigger optimization score boost.

The Strategy Explained

Develop a mental triage system that sorts recommendations into three buckets before you evaluate their specific merits. Low-risk recommendations typically involve adding assets like extensions, headlines, or descriptions—they expand your options without removing what's working. Medium-risk suggestions include bid adjustments or budget increases that affect spending but don't fundamentally change targeting. High-risk recommendations alter who sees your ads: match type changes, audience expansions, or automated bidding switches that remove your manual controls.

This categorization lets you move quickly through low-risk items while dedicating serious analysis time to high-risk suggestions. It also helps you batch similar recommendations together for more efficient review.

Implementation Steps

1. Scan your recommendations list and mentally tag each one as green (low risk), yellow (medium risk), or red (high risk) based on whether it adds options, adjusts spending, or changes targeting.

2. Start with green recommendations—these are often quick wins that genuinely improve performance with minimal downside.

3. Move to yellow recommendations and evaluate them against your current budget constraints and performance trends before accepting.

4. Save red recommendations for last and treat them with healthy skepticism, requiring strong justification before implementation.

Pro Tips

Keep a personal reference list of recommendation types you've learned to automatically dismiss. For example, if broad match keyword suggestions have consistently hurt your campaigns in the past, you can confidently dismiss similar recommendations in seconds rather than re-evaluating the same concept repeatedly.

3. Always Check the Math Behind Bid Recommendations

The Challenge It Solves

Bid recommendations often come with enticing projections: "Increase your bid by 25% to get 40% more clicks." These suggestions can sound compelling, especially when Google's machine learning appears to have calculated the exact optimal bid. The challenge is that these projections focus on metrics Google can easily measure—clicks, impressions, visibility—rather than metrics you actually care about, like return on ad spend or profit per conversion.

The Strategy Explained

Before accepting any bid recommendation, run the numbers through your own business math. If Google suggests raising your bid from $2.00 to $2.50, calculate what that means for your cost per conversion based on your current conversion rate. Then compare that projected cost per conversion against your target CPA or ROAS goals.

The key insight here is that more clicks at a higher cost per click doesn't automatically translate to better business outcomes. Sometimes a lower bid that generates fewer but more qualified clicks delivers better overall results. Google's recommendations optimize for their revenue (more clicks at higher prices), while your job is optimizing for your profitability.

Implementation Steps

1. When you see a bid recommendation, note your current bid, the suggested bid, and the projected impact Google claims.

2. Calculate your current cost per conversion by dividing your total ad spend by conversions in the relevant time period.

3. Project your new cost per conversion assuming the higher bid with Google's estimated click increase, using your actual conversion rate (not Google's optimistic projections).

4. Accept the recommendation only if the projected cost per conversion stays within your target range and you have budget room for the increased spend.

Pro Tips

Pay special attention to bid recommendations that appear right after you've made manual bid adjustments. Google's algorithm sometimes interprets your strategic bid decrease as a mistake and immediately suggests raising it back up. Trust your own recent decisions and dismiss these recommendations unless something has fundamentally changed in your campaign performance.

4. Use the 'Dismiss' Button Strategically

The Challenge It Solves

Many advertisers treat the dismiss button as a way to temporarily hide recommendations they don't want to deal with right now. This creates a growing backlog of dismissed items that clutters your account and makes it harder to spot genuinely new suggestions. Worse, dismissed recommendations often reappear in slightly modified forms, forcing you to re-evaluate the same basic concept multiple times.

The Strategy Explained

Dismissing a recommendation should be an active optimization decision, not passive procrastination. When you dismiss something, you're making a deliberate choice that this suggestion doesn't align with your campaign strategy. Treat dismissal with the same intentionality you'd apply to accepting a recommendation—it's equally important to document what you're choosing not to do and why.

The dismiss button becomes powerful when you use it to train yourself on your campaign priorities. Each dismissal reinforces your strategic boundaries: these are the types of changes that don't fit your approach, regardless of how Google frames them. Over time, this builds pattern recognition that makes future recommendation reviews faster and more confident.

Implementation Steps

1. Before dismissing a recommendation, take ten seconds to articulate why it doesn't fit your strategy—this mental step prevents lazy dismissals.

2. Dismiss recommendations that conflict with your documented campaign goals, even if they promise impressive-sounding metrics.

3. Periodically review your dismissed recommendations (found in the Dismissed section) to see if any deserve reconsideration based on changed circumstances.

Pro Tips

Create dismiss categories in your mind: "Conflicts with match type strategy," "Outside budget constraints," "Wrong audience targeting," "Automated feature we're avoiding." This makes dismissal decisions faster and more consistent across your account. When similar recommendations reappear later, you can quickly reference your category and dismiss them again without re-analyzing.

5. Cross-Reference Keyword Suggestions with Your Search Terms Report

The Challenge It Solves

Google frequently recommends adding new keywords to your campaigns, often suggesting related terms or broader variations of your existing keywords. These suggestions arrive without context about whether real people are actually searching for those terms and clicking your ads. You're being asked to make a decision based on Google's algorithmic prediction rather than actual user behavior in your account.

The Strategy Explained

Your Search Terms Report contains the real queries that triggered your ads and drove clicks. This is actual intent data from people who saw your ads and took action. Before accepting any keyword recommendation, check whether that exact keyword or close variations already appear in your search terms data. If it does, you can see the actual conversion rate, cost per click, and conversion volume it's generating.

This approach flips the evaluation process. Instead of guessing whether a recommended keyword might work, you're looking at evidence of whether it already is working (or failing) in your account. Keywords that show strong performance in your search terms deserve to be added as exact or phrase match terms. Keywords that don't appear at all in your search terms might not be worth adding, regardless of Google's recommendation.

Implementation Steps

1. When you see a keyword recommendation, open your Search Terms Report in a new tab before making any decision.

2. Search for the recommended keyword or close variations within your search terms data from the past 30-90 days.

3. If the term appears with strong metrics (good conversion rate, acceptable CPA), add it as a more restrictive match type to gain better control.

4. If the term appears with poor metrics or doesn't appear at all, dismiss the recommendation and focus on keywords with proven performance.

Pro Tips

Tools like Keywordme make this cross-referencing process significantly faster by letting you work directly within your Search Terms Report to identify high-performing queries and convert them to keywords without switching between tabs or building spreadsheets. When you can validate recommendations against real data in seconds instead of minutes, you're more likely to do it consistently.

6. Set Up a Weekly Review Rhythm Instead of Reacting in Real-Time

The Challenge It Solves

Google Ads recommendations appear continuously, and the platform sends notifications encouraging you to review them immediately. This creates pressure to constantly check your recommendations tab and make quick decisions. The problem with real-time reaction is that you're evaluating suggestions without sufficient data, often making changes before you can assess whether your previous optimizations are working.

The Strategy Explained

Batching your recommendation reviews into a consistent weekly schedule gives you multiple advantages. First, you accumulate enough performance data between reviews to make informed decisions based on trends rather than daily fluctuations. Second, you can evaluate multiple recommendations together, spotting patterns or conflicts that aren't obvious when reviewing items individually. Third, you avoid over-optimization—the common mistake of making too many changes too quickly, which makes it impossible to determine what's actually affecting performance.

A weekly rhythm also creates mental space for strategic thinking. When you're not constantly reacting to new recommendations, you can approach each review session with fresh perspective and clearer judgment about whether suggestions align with your broader campaign goals.

Implementation Steps

1. Choose a consistent day and time each week for recommendation reviews—treat it as a recurring appointment you don't skip.

2. During your review session, look at performance data from the previous week alongside your recommendations to provide decision-making context.

3. Make all your recommendation decisions in this single session rather than piecemeal throughout the week.

4. Ignore recommendation notifications between your weekly reviews unless you're running time-sensitive campaigns that require daily attention.

Pro Tips

Pair your weekly recommendation review with your regular campaign performance analysis. When you're already looking at conversion trends, cost changes, and search term performance, you're in the perfect mindset to evaluate whether recommendations would improve or disrupt your current trajectory. This integration makes recommendation review feel like a natural part of campaign management rather than an extra task.

7. Document Your Decisions to Build Institutional Knowledge

The Challenge It Solves

After weeks or months of reviewing recommendations, you start to forget which suggestions you've already evaluated and why you made certain decisions. This becomes especially problematic when similar recommendations reappear in modified forms, when you're training team members who need to understand your approach, or when you're managing multiple client accounts with different strategies. Without documentation, you're constantly re-learning the same lessons.

The Strategy Explained

Creating a simple system to track your recommendation decisions transforms individual choices into strategic knowledge. This doesn't require complex tools—a basic spreadsheet or shared document works perfectly. The goal is capturing the recommendation type, your decision, and the brief reasoning behind it. Over time, this documentation reveals patterns in what works for your specific campaigns and business model.

This institutional knowledge becomes invaluable when circumstances change. If your budget increases, you can review previously dismissed recommendations that were outside your spending constraints. If you bring on a new team member, they can understand your strategic approach by reading past decisions rather than making the same mistakes you've already learned from.

Implementation Steps

1. Create a simple tracking sheet with columns for date, recommendation type, decision (accepted/dismissed), and brief reasoning.

2. After each weekly recommendation review, spend five minutes logging your key decisions—focus on significant choices rather than documenting every minor dismissal.

3. Review your documentation monthly to identify patterns: Are you consistently dismissing certain recommendation types? Are accepted recommendations actually improving performance?

4. Use these insights to refine your evaluation criteria and speed up future recommendation reviews.

Pro Tips

For agency teams managing multiple client accounts, create a shared template that everyone uses for documentation. This standardization helps you spot cross-account patterns and develop best practices that work across different industries and campaign types. When a strategy proves successful for one client, you can quickly identify similar opportunities in other accounts by referencing your documentation.

Putting It Into Practice: Your Google Ads Recommendations Playbook

These seven strategies work together to create a systematic approach for handling Google Ads recommendations. You don't need to implement everything at once—start with the risk categorization framework and weekly review rhythm, since these create immediate structure around your decision-making process.

Once you're comfortable with those foundations, add the practice of checking math behind bid recommendations and cross-referencing keyword suggestions with your search terms data. These validation steps prevent the most common costly mistakes while building your confidence in rejecting recommendations that don't serve your goals.

The documentation habit and strategic dismissal approach can come last, but they're what transform you from someone who handles recommendations competently into someone who builds genuine expertise over time. Your documented decisions become a playbook that makes every future review faster and more effective.

Remember that your optimization score will fluctuate as you implement these strategies, and that's perfectly fine. The goal isn't a perfect score—it's campaign performance that actually drives your business forward. When your cost per acquisition is hitting targets and your conversion volume is growing, a 70% optimization score is infinitely better than a 95% score attached to campaigns hemorrhaging budget on broad match keywords you never wanted.

The real shift happens when you stop seeing recommendations as commands from Google and start viewing them as suggestions to evaluate against your strategic priorities. Some will genuinely improve your campaigns. Many won't. Your job is knowing the difference.

If you're managing campaigns where search term analysis plays a central role in your optimization process, you'll find that having the right tools makes these strategies significantly easier to execute. Start your free 7-day trial of Keywordme to optimize Google Ads campaigns 10X faster—without leaving your account. Remove junk search terms, build high-intent keyword groups, and apply match types instantly, right inside Google Ads. No spreadsheets, no switching tabs, just quick, seamless optimization. Manage one campaign or hundreds and save hours while making smarter decisions.