In the competitive world of online advertising, many business owners and marketers feel a mix of excitement and confusion when navigating Google Ads recommendations. While these suggestions can seem helpful, they require careful handling to ensure they truly serve your business goals. Let's dive into why these recommendations exist, how auto-apply settings can impact your campaigns, and how to make informed decisions to keep your ads performing well.
What Google Ads Recommendations Actually Do
Google Ads recommendations are automated suggestions that claim to improve the effectiveness of your campaigns. They include adding keywords, adjusting bidding strategies, or implementing new ad extensions. These are not personalized to your business goals; instead, they are generated by algorithms analyzing campaign data at scale.
For instance, Google might suggest switching from a “manual CPC” bidding strategy to an “enhanced CPC” or “maximized conversions” model. While these may work for some accounts, they don't always align with specific goals like staying within a strict budget or targeting niche audiences.
Why They Exist
The purpose behind recommendations is straightforward: encourage advertisers to engage more with Google Ads features. This engagement often leads to spending more money on campaigns, but not always with better results. While Google benefits financially, businesses must balance these suggestions with their objectives.
In fact, the controversial optimization score, a percentage number Google gives your account, exists mainly to nudge advertisers into considering these suggestions. It’s essential to remember that scoring 100% does not mean your campaigns are perfectly optimized; it simply means you interacted with or dismissed every recommendation.
Auto-Apply Recommendations: Risk or Reward?
Auto-apply recommendations allow Google to enact certain changes without notifying you. This might sound convenient, but it’s not risk-free. Auto-applied changes can include increasing your daily budget, tweaking bids, or even introducing broad match keywords that may not fit your strategy.
Problems With Auto-Apply:
- Control Loss: Auto-apply takes away the ability to approve changes yourself.
- Mismatched Goals: Algorithms don’t fully understand your unique business conditions.
- Overspending Risks: Some automatically applied changes, such as increasing bids, may inflate costs disproportionately.
That said, minor auto-applied suggestions, like bid adjustments under certain conditions, might benefit highly generalized campaigns. Still, cautious oversight is critical.
How to Manage Recommendations Effectively
The decision to follow or ignore a recommendation should always be based on data, strategy, and ongoing testing. Here’s a quick guide:
Step 1: Understand the Optimization Score
While hitting 100% isn't necessary, aim to review and dismiss irrelevant recommendations regularly. This ensures the score doesn’t penalize your engagement status, especially if you're working toward Google Partner certification.
Step 2: Categorize Suggestions
Not all recommendations carry the same weight. Prioritize items related to conversion tracking, ad disapprovals, or broken links. These directly affect campaign functionality. On the other hand, frequent pushes to add broad match keywords or increase the budget should invite hesitation and scrutiny.
Step 3: Test Before Rolling Out
Experimenting separately is key. If Google suggests transitioning to a new bid strategy, set up an experiment to compare performance over 30-60 days instead of applying changes to all campaigns.
Step 4: Auto-Apply Settings
Go to the “All Campaigns” view, find the “Auto-Apply” settings, and deselect unnecessary categories. Google only supports automatic applications for 22 types of recommendations, so don't hesitate to disable categories that affect strategic elements like broad match keywords or audience expansions.
Step 5: Regular Monitoring
Make it a point to check campaigns weekly or bi-weekly. Adjustments the algorithm applies might steer performance toward inefficient regions or audiences over time.
Common Mistakes to Avoid
-
Ignoring Suggestions Entirely
While skepticism is justified, outright dismissal of every recommendation may lead you to miss out on beneficial tweaks, such as enhanced ad extensions or fixing broken tracking codes. -
Blind Acceptance
On the flip side, auto-accepting suggestions without understanding the implications can cause damage. Budget suggestions, for instance, may increase clicks but hurt profitability in tight-margin businesses. -
Lack of Testing
Testing new strategies or setups through controlled experiments ensures any failures don't jeopardize your whole account. -
Chasing the Optimization Score
Trying to meet 100% optimization for its own sake adds unnecessary changes and distracts from achieving measurable goals.
Final Insights From My Experience
As someone who’s worked across industries and manages digital campaigns regularly, I’ve noticed one recurring truth: You know your business far better than Google’s algorithm does. No AI, no matter how advanced, can understand your profit margins, loyal customers, or long-term business goals as well as you. Recommendations can spark ideas, but using them blindly is like handing over your keys to a driver who doesn’t know your destination.
Instead, approach these tools as assistants, not decision-makers. Keep auto-apply settings off, flag high-priority issues like tracking errors, and turn recommendations into experiments rather than sweeping changes.
Additional Resources
If you're looking for more practical advice on how to handle recommendations and drive meaningful results, take a look at The Best Way to Manage and Dismiss Google Ads Recommendations. For getting started with setup adjustments, Google's guide on applying recommendations gives clear instructions.
Google Ads can be an incredible growth lever for startups and small businesses. Just remember: automation exists to support your strategy, not replace it. By staying informed and in control, you’ll ensure your campaigns are targeted, your spend is intentional, and ultimately, your results are aligned with your vision for success.
FAQ on Google Ads Recommendations and Auto-Apply
1. What are Google Ads Recommendations?
Google Ads Recommendations are automated suggestions aimed at improving your campaigns, such as adding keywords, adjusting bids, or using ad extensions. These aren't tailored to your unique business goals, they are generated by platform algorithms analyzing campaign data at scale. Understand Google Ads Recommendations
2. Why do Google Ads Recommendations exist?
Recommendations exist to prompt advertisers to use more Google Ads features, which often increases ad spend. While helpful in some cases, they can prioritize platform-level optimizations over individual business strategies. Learn why recommendations exist
3. What is the Google Ads Optimization Score?
The Optimization Score measures whether you interact with Google Ads Recommendations, rather than campaign success. Achieving a 100% score means you've reviewed or dismissed all suggestions, not necessarily that your account is perfectly optimized. Learn about Google Optimization Score
4. Should I auto-apply Google Ads Recommendations?
Generally, you should avoid auto-applying recommendations, as they can increase daily budget or add keywords that might not align with your goals. Manual review ensures you retain control over campaign adjustments. Understand Google Ads Auto-Apply
5. How can I manage auto-apply settings?
You can manage auto-apply settings in the "Recommendations" tab under "All Campaigns." Opt-out of auto-apply to maintain control over changes like bid adjustments and keyword additions. Manage auto-apply settings
6. What are the risks of auto-applying recommendations?
Auto-applied changes can result in loss of control, mismatched goals, and overspending. Algorithms lack the ability to fully understand your business nuances. Learn about risks of auto-apply
7. What steps should I take to review recommendations manually?
Begin by categorizing recommendations based on importance, focusing on conversion tracking and ad functionality over budget increases or broad keywords. Test changes through experiments before full adoption. Explore manual review strategies
8. How do I test recommendations before applying them?
Create controlled experiments using suggestions, such as testing new bid strategies, over 30, 60 days. This ensures changes are beneficial without restructuring entire campaigns. Learn about Google Ads experiments
9. Why shouldn’t I chase a 100% optimization score?
Reaching 100% optimization score by accepting all recommendations may lead to unnecessary changes that dilute strategy focus. Prioritize measurable business outcomes over the score itself. Discover the truth about optimization scores
10. How often should I review Google Ads Recommendations?
Regular monitoring (weekly or bi-weekly) is essential to ensure algorithm-applied changes don't negatively affect account performance over time. Learn about monitoring strategies
About the Author
Violetta Bonenkamp, also known as MeanCEO, is an experienced startup founder with an impressive educational background including an MBA and four other higher education degrees. She has over 20 years of work experience across multiple countries, including 5 years as a solopreneur and serial entrepreneur. Throughout her startup experience she has applied for multiple startup grants at the EU level, in the Netherlands and Malta, and her startups received quite a few of those. She’s been living, studying and working in many countries around the globe and her extensive multicultural experience has influenced her immensely.
Violetta Bonenkamp's expertise in CAD sector, IP protection and blockchain
Violetta Bonenkamp is recognized as a multidisciplinary expert with significant achievements in the CAD sector, intellectual property (IP) protection, and blockchain technology.
CAD Sector:
- Violetta is the CEO and co-founder of CADChain, a deep tech startup focused on developing IP management software specifically for CAD (Computer-Aided Design) data. CADChain addresses the lack of industry standards for CAD data protection and sharing, using innovative technology to secure and manage design data.
- She has led the company since its inception in 2018, overseeing R&D, PR, and business development, and driving the creation of products for platforms such as Autodesk Inventor, Blender, and SolidWorks.
- Her leadership has been instrumental in scaling CADChain from a small team to a significant player in the deeptech space, with a diverse, international team.
IP Protection:
- Violetta has built deep expertise in intellectual property, combining academic training with practical startup experience. She has taken specialized courses in IP from institutions like WIPO and the EU IPO.
- She is known for sharing actionable strategies for startup IP protection, leveraging both legal and technological approaches, and has published guides and content on this topic for the entrepreneurial community.
- Her work at CADChain directly addresses the need for robust IP protection in the engineering and design industries, integrating cybersecurity and compliance measures to safeguard digital assets.
Blockchain:
- Violetta’s entry into the blockchain sector began with the founding of CADChain, which uses blockchain as a core technology for securing and managing CAD data.
- She holds several certifications in blockchain and has participated in major hackathons and policy forums, such as the OECD Global Blockchain Policy Forum.
- Her expertise extends to applying blockchain for IP management, ensuring data integrity, traceability, and secure sharing in the CAD industry.
Violetta is a true multiple specialist who has built expertise in Linguistics, Education, Business Management, Blockchain, Entrepreneurship, Intellectual Property, Game Design, AI, SEO, Digital Marketing, cyber security and zero code automations. Her extensive educational journey includes a Master of Arts in Linguistics and Education, an Advanced Master in Linguistics from Belgium (2006-2007), an MBA from Blekinge Institute of Technology in Sweden (2006-2008), and an Erasmus Mundus joint program European Master of Higher Education from universities in Norway, Finland, and Portugal (2009).
She is the founder of Fe/male Switch, a startup game that encourages women to enter STEM fields, and also leads CADChain, and multiple other projects like the Directory of 1,000 Startup Cities with a proprietary MeanCEO Index that ranks cities for female entrepreneurs. Violetta created the "gamepreneurship" methodology, which forms the scientific basis of her startup game. She also builds a lot of SEO tools for startups. Her achievements include being named one of the top 100 women in Europe by EU Startups in 2022 and being nominated for Impact Person of the year at the Dutch Blockchain Week. She is an author with Sifted and a speaker at different Universities. Recently she published a book on Startup Idea Validation the right way: from zero to first customers and beyond, launched a Directory of 1,500+ websites for startups to list themselves in order to gain traction and build backlinks and is building MELA AI to help local restaurants in Malta get more visibility online.
For the past several years Violetta has been living between the Netherlands and Malta, while also regularly traveling to different destinations around the globe, usually due to her entrepreneurial activities. This has led her to start writing about different locations and amenities from the POV of an entrepreneur. Here’s her recent article about the best hotels in Italy to work from.