Google Ads: Prioritize Control, Transparency, and Search Campaigns

This conversation reveals the hidden complexities and often counterintuitive dynamics of managing Google Ads, particularly for those focused on performance and long-term success. It highlights how seemingly straightforward tasks like handling performance drops or optimizing scores can unravel into a game of understanding system mechanics and human behavior. The core thesis is that true advantage in Google Ads doesn't come from following Google's automated suggestions blindly, but from a deep, analytical understanding of how the platform's systems interact with business goals, often requiring a willingness to embrace immediate discomfort for delayed, significant payoffs. This analysis is crucial for PPC managers, agency owners, and business leaders who want to move beyond surface-level metrics and build sustainable, high-performing ad strategies. It offers a strategic framework for identifying and exploiting the blind spots of less sophisticated competitors.

The Illusion of Optimization: Why Google's Score Means Nothing

The immediate impulse when faced with a sudden drop in Google Ads performance is to panic. Dan’s question, “What is your approach? What's your favorite report to analyze? What's your system for dealing with it?” is the perennial cry of the PPC manager. Chris Schaeffer’s response, however, immediately pivots from the expected technical deep-dive to a more fundamental diagnostic: is the problem actual performance decline, or a breakdown in tracking? This distinction is critical because it frames the subsequent analysis. A tracking issue, while urgent, is a solvable technical glitch, far preferable to a genuine performance erosion.

When tracking is confirmed, Schaeffer identifies two primary levers: bidding and targeting. The analysis of targeting often involves scrutinizing search terms, comparing historical data to identify keywords that have gone rogue or ceased to perform. This isn't just about finding a single bad keyword, but understanding how shifts in search query patterns can dramatically alter campaign spend and efficiency. He points out that bidding strategies like Max Clicks, Maximize Conversions, and even manual bidding can allow keywords to "get out of hand," consuming disproportionate budget without delivering proportional results.

The bidding side is equally nuanced. A sudden drop could stem from bids being too high or too low, often traceable through the change history. A drastic reduction in a Target CPA or Target ROAS, for instance, can plummet ad positions, decimating click-through rates and, consequently, conversions. Schaeffer also highlights a common, compounding problem: a tracking error that inflates conversion numbers. This can send automated bidding systems into a frenzy, bidding aggressively on irrelevant terms and creating a distorted picture of success that rapidly burns through budget.

"The first thing that I look at is, I'll do a comparison, a before and after. And oftentimes this ends up being the problem: the client changed their website and all tags that I had were removed. So now anyone that fills out a form, I get no more forms."

This initial diagnostic sets the stage for understanding the systemic nature of ad performance. It’s not just about setting bids; it’s about the entire ecosystem of tracking, targeting, and bidding interacting.

The conversation then pivots to a more insidious, yet common, aspect of Google Ads management: the optimization score and recommendations. Othy’s question about dismissing recommendations to boost the score touches on a fundamental flaw in Google’s system. Schaeffer’s candid response reveals that the optimization score is, in his view, a "game," a "gimmick," and a "waste of time" because it can be artificially inflated without any actual improvement in account performance. Dismissing recommendations, while requiring effort, is often a necessary evil for agencies needing to maintain Google partnership status or simply to keep irrelevant, potentially damaging suggestions off their clients' dashboards.

"So when you go into your recommendations tab, there are three little tiny dots up at the top right of each and every recommendation. You can click this and then it'll pop up a menu. One of the options in the menu is to dismiss the recommendation and it'll ask you why you're doing it. You don't have to answer and you just hit dismiss and what it does is it moves your optimization score up."

This practice, while seemingly a workaround, underscores a critical insight: Google’s automated systems are not always aligned with a client’s specific business objectives. The "damage done to accounts" by blindly accepting recommendations--like adding broad match keywords with automated bidding--is presented as a significant, often unquantifiable, cost. The act of dismissing recommendations becomes a form of active defense, a way to assert control and prevent algorithmic missteps from derailing performance. This highlights the tension between Google's push for automation and the need for human oversight and strategic intervention. The advantage here lies with those who understand this dynamic and proactively manage it, rather than passively accepting the platform’s nudges.

The Narrow Path to Dominance: Why Search Reigns Supreme

The third question delves into the labyrinth of Google Ads campaign types, with the user exploring Demand Gen and Performance Max for retargeting. Schaeffer’s response is a stark declaration: Search is the only serious campaign type. This isn't a casual preference; it's a deeply held conviction forged from years of managing high-spend accounts. The core argument against other campaign types--Display, Video, Demand Gen, Performance Max (outside of specific e-commerce use cases)--is their lack of transparency and control. They are presented as "set it and forget it" options, opaque black boxes where advertisers have minimal ability to "tweak around with" settings.

"Whenever I look at businesses that are spending millions of dollars on Google Ads, you know, multiple millions, it is not millions in Demand Gen, it is not millions in Performance Max, it is not millions in App Installs, Video, Hotel campaign types. None of these are serious contenders for my time that I'm going to put into Google Ads discussions because they don't, they don't move the needle."

This lack of control, Schaeffer argues, leads to homogeneity. Most Performance Max or Video campaigns look the same, use the same "boring settings," and achieve "crappy success." There’s no room for customization, no opportunity to differentiate from competitors who are likely using the exact same uninspired approach. The competitive advantage, therefore, lies in the complexity and nuance of Search campaigns, where skilled management can yield unique results.

However, Schaeffer does concede limited utility for other campaign types. Display campaigns, particularly for remarketing, can be effective. He also notes success with highly specific, targeted placements on niche websites and with meticulously tested, highly targeted audiences. For e-commerce, Standard Shopping campaigns are a strong contender, often preferred over Performance Max. Performance Max itself is acknowledged as having a role, but almost exclusively for its shopping component in e-commerce, where it can sometimes outperform Standard Shopping. The overarching theme is that these other channels are, at best, secondary tools, requiring significant upfront testing and audience research to yield even modest results, and they pale in comparison to the strategic depth and control offered by Search. The implication is clear: those who master Search while others chase the allure of automated, opaque systems will build a durable competitive moat.

The Unnecessary Hurdles of "New Customer Only" Bidding

The final question addresses the "bid for new customers only" setting in Google Ads. Ephrin’s query about its practical performance is met with a definitive stance from Schaeffer: he doesn't use it, and he has "zero experience with it." This isn't due to a lack of opportunity, but a series of fundamental objections that render the feature impractical for his approach.

The primary hurdle is its requirement for value-based bidding strategies like Maximize Conversion Value and Target ROAS. Schaeffer expresses a strong aversion to these strategies, ranking them low in his personal hierarchy of preferred bidding methods. This alone is a significant barrier.

Beyond bidding strategy, the requirement to pass customer data to Google is a major point of contention. Schaeffer dismisses this as a "joke," highlighting the widespread struggles even large advertisers face with basic conversion tracking accuracy. The idea that businesses can reliably pass customer data to Google for this feature to function effectively is presented as highly improbable, bordering on impossible. The technical complexity and the need for near-perfect data accuracy create "impassable hoops" for most businesses.

"So at what extent do you think people can correctly send customer data to Google and it be reliable? Reliable enough for the system to work? I think we're at essentially zero here. I think it's absolutely ridiculous."

Furthermore, the setting demands significant data volume to function correctly, adding another layer of inaccessibility for smaller or niche businesses. Schaeffer concludes that the effort required to jump through these technical and data-volume hoops, all to trust Google with more unseeable data for a specific optimization, is not worth the potential reward. He believes the desired outcome--acquiring new customers--can be achieved through other, more controllable means. The "bid for new customers only" setting is thus framed as an overly complex, unreliable, and ultimately unnecessary feature that demands too much trust and technical overhead for uncertain gains. The advantage, again, lies with those who can achieve similar goals through more transparent and manageable strategies, avoiding the pitfalls of opaque, data-intensive Google features.

Key Action Items

• Immediate Action (0-1 Week):
  • Verify Conversion Tracking: For any sudden performance drop, immediately compare before-and-after conversion tracking data across all channels (forms, calls, e-commerce). Prioritize fixing broken tracking over performance analysis.
  • Review Change History: Scrutinize the Google Ads change history for the period preceding any performance drop. Look for manual bid adjustments, target CPA/ROAS changes, or significant budget shifts.
  • Audit Search Term Reports: Regularly review search term reports for anomalies--keywords consuming excessive spend, or new terms appearing that are irrelevant or low-quality.
  • Dismiss Irrelevant Recommendations: Proactively dismiss Google Ads recommendations that do not align with your specific business goals or strategy, especially those that seem to inflate the optimization score without clear performance benefits.
• Short-Term Investment (1-3 Months):
  • Segment Campaign Types: Focus primary management efforts on Search campaigns. Evaluate other campaign types (Display remarketing, Standard Shopping) for specific, well-defined use cases where control and targeted audiences can be leveraged.
  • Develop a "Search Term Guardrail" System: Implement a process to monitor and actively manage search terms, especially for automated bidding strategies, to prevent budget bleed on non-performing queries.
• Long-Term Investment (6-18 Months):
  • Build Expertise in Search Campaign Granularity: Invest time in understanding and leveraging the granular controls within Search campaigns to create unique strategies that competitors cannot easily replicate.
  • Establish a "No-Go" List for Automated Features: Create a documented list of Google Ads features (e.g., "bid for new customers only," certain recommendation types) that will not be used due to complexity, lack of transparency, or unreliability, and stick to it. This requires discipline but builds a robust, defensible strategy.