Google Ads has recently adjusted how Performance Max (PMax) and Shopping campaigns enter the auction and compete for the SERP, changing the game for ecommerce advertisers. Previously, PMax campaigns had automatic priority, often winning out regardless of competition. Now, with ad rank determining which campaign enters the auction, advertisers face new challenges—ranging from increased costs to reduced control over bidding. This post will unpack the changes, explore their impact on ecommerce brands, and offer actionable strategies for optimizing your campaigns to stay competitive in this evolving landscape.
What This Means for Advertisers
The shift to ad rank determining whether PMax or Shopping campaigns enter the auction brings significant changes to how ecommerce advertisers manage costs and control over their bidding strategies.
Increased Costs
Under the previous system, a lower-bid Shopping campaign might have still entered the auction, as PMax campaigns were given priority. Now, ad rank favors higher bids, meaning advertisers will see their higher CPC bids competing more frequently, driving up costs. For instance, an advertiser who used to run a Shopping campaign with a $0.75 CPC might have consistently won auctions. But now, that same campaign could lose to a PMax campaign bidding $1.50, even though the overall ROAS might have been better with the lower bid.
This change pushes advertisers into a position where higher bids—and, by extension, higher costs—become necessary to maintain visibility. As a result, balancing budget and performance becomes even more critical.
Reduced Control Over Bidding
Smart Bidding, already a challenge for advertisers seeking more granular control, now plays an even larger role. With ad rank determining auction winners based on CPC, advertisers lose further control over which campaign gets exposure. Smart Bidding algorithms might increase CPCs based on predicted performance, often without aligning with the advertiser’s specific goals.
While advertisers can still set target CPA/ROAS and budget limits, the final bid decision—heavily influenced by Google's algorithm—remains largely out of their control. This shift introduces more unpredictability in campaign performance, making it difficult to fine-tune strategies without overspending.
Ad Rank and Smart Bidding Mechanics
Ad Rank Explained
Ad rank is the formula Google uses to determine which ads appear in auctions and in what order. The formula looks like this:
Ad rank = CPC bid x Expected CTR (Quality Score)
- CPC Bid: This is the maximum amount you're willing to pay for a click. It’s one of the most direct variables you control.
- Expected CTR (Quality Score): Google estimates how likely your ad is to be clicked based on its relevance, past performance, and the search query. This means Google’s algorithm looks for signals that predict the user’s engagement with the ad.
In the context of Performance Max (PMax) and Shopping campaigns, ad creatives are often similar, which means the expected CTR doesn't vary significantly between them. This leads to the CPC bid becoming the critical factor in determining ad rank. The higher your bid, the better your chances of securing a spot in the auction. For advertisers, this means that keeping CPCs low while maintaining high visibility is becoming increasingly difficult under this ad rank formula.
The direct consequence of this is that higher CPC bids will likely win when PMax and Shopping campaigns are competing for the same placements. Without strategic optimization, this dynamic can quickly inflate costs, reducing overall ad efficiency and putting pressure on campaign budgets.
Smart Bidding’s Role
Smart Bidding, a key feature within Google Ads, automates bid adjustments based on signals like target CPA (Cost Per Acquisition), ROAS (Return on Ad Spend), and your campaign's budget constraints. However, Smart Bidding introduces complexities around how marginal CPA/ROAS influences bids.
- Marginal CPA/ROAS: This concept refers to how Smart Bidding increases bids when a campaign performs better than expected. For instance, if a campaign is outperforming its target ROAS (e.g., 1200% ROAS vs. a 1000% target), Smart Bidding may increase CPCs further to capture more conversions based on predicted value.
While this can drive additional conversions, it can also lead to higher-than-expected CPCs, straining your budget. Smart Bidding's decisions often prioritize short-term gains—higher conversions in the moment—over long-term efficiency. This is where advertisers lose some control; while they can set budgets and targets, the algorithm’s optimization based on marginal CPA/ROAS can result in unpredictable CPC increases.
Make the most of Smart Bidding in both PMax and Shopping campaigns by using the right strategy for your goals. For example, if your goal is maximizing revenue, Target ROAS is a suitable option. Alternatively, Target CPA is ideal when controlling acquisition costs is your priority. For visibility, Maximize Clicks works well but may drive CPCs higher, while Maximize Conversions with a strict budget helps optimize your spending without allowing CPCs to spiral out of control.
To manage these rising CPCs and maintain control over performance, advertisers need to look beyond bidding tactics alone. Optimizing your data feed quality—the foundation of your product ads—plays a pivotal role in improving ad rank and driving cost efficiency. Let's explore how data feed quality directly impacts ad rank and your campaign’s success.
Why Data Feed Quality is Critical to Ad Rank in Shopping and PMax Ads
Data feed quality is not just a peripheral detail in ad campaigns—it directly influences ad rank and performance. Google evaluates the relevance and completeness of your product data when determining how well your ads align with user intent. Incomplete or inaccurate data can lower your relevance score, leading to a lower ad rank and reduced visibility.
Here are some key areas where data feed quality impacts ad rank:
- Product Titles: Well-optimized product titles with relevant keywords improve your ad's relevance and CTR (Quality Score), which in turn boosts your ad rank. Titles that fail to capture key search terms will hurt your competitiveness in auctions.
- Product Descriptions: Google’s algorithm scans descriptions to assess how well they match user queries. Clear, concise descriptions filled with relevant details not only increase the chances of a click but also enhance the ad’s relevance score.
- Pricing Accuracy: Incorrect or inconsistent pricing across different channels can lead to disapproval of products in your feed, impacting your campaign’s visibility. Accurate pricing is crucial for Google to trust your ad and rank it appropriately.
- GTINs (Global Trade Item Numbers): Missing or incorrect GTINs can reduce ad relevance, making it harder for Google to match your products to relevant searches. Ensuring that GTINs are consistent and correct helps improve your ad’s placement in auctions.
- High-Quality Images: Image URLs that are broken or low-quality reduce the likelihood of clicks, which impacts your CTR. High-quality images attract users and improve the ad’s performance in auctions.
Poor data feed quality can lead to severe consequences, such as product disapprovals and lower relevance scores, which negatively affect ad rank. For example, inaccurate values or missing attributes can result in Google disapproving your products or decreasing visibility. This leads to wasted ad spend as your ads fail to reach the intended audience or enter auctions, ultimately impacting the overall success of your campaigns.
Here’s a simplified formula to illustrate how data feed quality indirectly supports your ad rank:
Ad rank (boost) = CPC bid x (Expected CTR + Data Quality Enhancements)
This equation shows that data feed optimizations can enhance your expected CTR, raising your overall ad rank without needing to rely solely on increasing CPC bids. For example, a well-optimized title might raise your CTR by a few percentage points, helping you compete more effectively with lower bids.
GoDataFeed is designed to tackle these common data feed issues, automating the process of optimizing product feeds across multiple channels. With GoDataFeed, your product data is always accurate, comprehensive, and aligned with Google’s best practices, helping you maximize your ad rank for both Shopping and PMax ads.
Potential Impact on Campaign Performance (Q4 and Beyond)
1. Campaign Performance
As we move into Q4—the most critical time of year for ecommerce advertisers—the effects of Google’s ad rank shift will likely become more pronounced. Shopping campaigns that previously thrived on lower bids might now struggle to compete with Performance Max (PMax) campaigns. As PMax takes precedence, especially in auctions with higher CPC bids, you’ll likely see increased competition driving up your overall CPCs, which can lead to shrinking margins during this peak season.
With higher CPCs, your campaign budgets will be stretched thinner, forcing advertisers to adapt quickly to maintain performance. You may also find that previously reliable Shopping campaigns need additional optimization or higher bids to keep up.
2. Shifts in Key Metrics
CPC Increases: One of the earliest signs of this change will be a noticeable increase in CPCs, especially as PMax campaigns push Shopping campaigns out of auctions. If you start seeing consistent CPC growth, it may be due to this increased competition between your campaigns.
ROAS and CPA Fluctuations
With the shift in ad rank mechanics, it’s essential to closely monitor key performance metrics like ROAS and CPA. These metrics may start fluctuating due to the unpredictable nature of Smart Bidding combined with this new prioritization model. For example, you could experience a short-term boost in conversions at a higher cost, which may not align with your long-term profitability goals.
Recommendation
To stay ahead of these shifts, set up regular monitoring of your CPCs, ROAS, and CPA. Tools like GoDataFeed can help automate the tracking and optimization of your product data feeds, ensuring your product listings remain competitive. By keeping a close eye on how your Shopping and PMax campaigns are performing under this new ad rank system, you can quickly adapt your bidding and budget strategies to avoid unnecessary cost spikes.
How to Mitigate the Impact on Your Campaigns
If you have multiple ad campaigns running that are trying to target the same products, they will essentially "bid against each other" in the advertising auction, leading to higher costs per click (CPCs) because you are essentially competing with yourself.
Here’s how you can mitigate any negative effects:
Avoid Campaign Overlap
A significant challenge in the new ad rank system is campaign overlap between Performance Max (PMax) and Shopping campaigns. When both campaign types are targeting the same products, they compete in the auction, often driving up your CPCs unnecessarily. One of the most effective strategies to counter this is to reduce product coverage overlap between the two campaigns.
You can segment products based on brand, product type, or profitability to avoid overlap. For example, assign high-margin products to PMax, where automation can maximize returns, while lower-margin or niche products may perform better in Shopping campaigns where manual bid control can keep costs in check. This segmentation prioritizes high-revenue potential while keeping CPCs under control.
To do this, consider segmenting your products based on campaign types. For example, you might allocate high-margin or top-performing products to PMax, where automation and cross-channel exposure can drive performance, while keeping Shopping campaigns focused on lower-margin products or specific categories where manual control over bidding is more critical. By assigning each campaign type to a distinct set of products, you reduce direct competition between PMax and Shopping campaigns, allowing each to work independently without escalating your costs.
Another approach is to exclude certain product groups from PMax campaigns and reserve them solely for Shopping campaigns, or vice versa, ensuring that you minimize internal bidding conflicts. Using campaign exclusions strategically allows you to preserve CPC efficiency while maintaining control over your bidding and targeting across various product lines.
How to reduce product coverage overla
1. Segment your product catalog
Divide your product inventory into distinct groups based on factors like price range, product category, or target audience, then create separate campaigns focused on each segment.
[Learn how to automate product catalog segmentation with GoDataFeed.]
2. Use negative targeting
Exclude specific products from certain campaigns to prevent them from competing with other campaigns targeting different product sets.
3. Adjust bidding strategies
Set different bid adjustments depending on the campaign and product to prioritize which products should be shown more aggressively in the ad auction.
4. Monitor campaign performance
Regularly analyze your campaign data to identify areas of overlap and make adjustments as needed.
Benefits of reducing overla
Lower CPCs
By minimizing competition between your own campaigns, you can generally expect to pay less per click.
Improved campaign efficiency
Each campaign can focus on its specific target audience and product set, leading to more effective ad delivery.
Better ROI
By optimizing your ad spend, you can potentially increase your return on investment.
Use Data Monitoring Tools with Key Features
Effective data monitoring is essential to mitigate the impact of these changes and to avoid blind spots in your campaign performance. To stay on top of ad rank conflicts and optimize bidding, look for tools that offer the following key features:
- Real-Time Ad Rank Tracking: This feature allows you to see which campaign type—PMax or Shopping—is winning in the ad auction. By tracking ad rank in real time, you can make informed adjustments to your bids or campaign structures to ensure you’re not overpaying for clicks or losing visibility due to internal competition.
- Performance and Budget Alerts: Set up alerts for CPC spikes or when ad spend reaches specific thresholds. These alerts will notify you when campaign costs start escalating or performance begins to fluctuate unexpectedly, allowing for quick intervention to adjust bidding or pause conflicting campaigns.
- Bid Optimization Visibility: Understanding how Smart Bidding adjusts your CPC based on predicted performance is crucial. This feature provides transparency into how your bids are being optimized by Google’s algorithm. You’ll be able to see the variables influencing your bid adjustments and tweak your campaigns accordingly, whether it’s targeting, product-level bids, or performance-based bidding strategies.
- Product-Level Performance Tracking: This feature enables you to track the performance of individual products across both PMax and Shopping campaigns. By identifying which products are seeing the most competition, you can adjust your bids, move products to different campaigns, or restructure ad sets to ensure each product is performing optimally.
By leveraging these tools, you gain actionable insights into the dynamics between PMax and Shopping campaigns. This information empowers you to adjust bids, pause underperforming campaigns, and refine your overall campaign structure to avoid overspending and inefficiency.
Refine Target CPA/ROAS
If you’re using Smart Bidding in conjunction with these campaigns, refining your target CPA (Cost Per Acquisition) or ROAS (Return on Ad Spend) is an essential step to control excessive bidding. As Smart Bidding adjusts bids based on campaign performance, fine-tuning these targets allows you to set guardrails around your spending while still maximizing conversions.
For example, if you notice that Smart Bidding is inflating CPCs because your campaign is performing better than expected, it may be time to adjust your ROAS or CPA targets. By lowering or tightening your target ROAS (e.g., from 1200% to 1000%), you can prevent Smart Bidding from pushing bids too high. Similarly, adjusting your CPA to reflect more realistic acquisition costs can help curb aggressive bidding.
Key Insight: Regularly review and adjust your target CPA/ROAS settings, especially during peak periods like Q4. As competition increases, these targets may need to shift to ensure that your campaigns remain aligned with your overall goals and budget constraints. Small adjustments to these targets can make a significant difference in maintaining CPC efficiency and keeping campaign costs manageable.
Next Steps: Navigating Google’s Prioritization Change
Google’s shift from a priority-based system to an ad rank-driven auction process has introduced new challenges for ecommerce advertisers.
Key takeaways to keep in mind:
- The shift from prioritization to ad rank impacts campaign visibility and costs, especially during peak seasons like Q4.
- Understanding the mechanics of ad rank and Smart Bidding is critical to managing your CPCs and ensuring campaigns stay aligned with your goals.
Final Recommendations
Monitor Closely: Make it a priority to use data tracking and monitoring tools to stay on top of ad rank conflicts and CPC increases. Real-time insights allow you to act quickly when your campaigns start competing against one another, helping you avoid unnecessary cost spikes. Additionally, monitor your product data feeds for errors or inconsistencies (like missing GTINs or incorrect pricing) that could lower your ad rank and increase costs.
Refine Campaign Structures: A key strategy for avoiding inflated CPCs is to eliminate product overlap between PMax and Shopping campaigns. Consider assigning specific product groups to either PMax or Shopping to reduce internal competition and maintain a more efficient ad structure. Also, ensure product feeds are optimized for each campaign type, as differences in data feed quality between campaigns can lead to unnecessary competition or missed opportunities.
Adjust Budgets and Targets: Regularly revisit your target CPA/ROAS and campaign budgets to ensure they are aligned with your performance goals, particularly during high-competition periods. Fine-tuning these targets helps Smart Bidding make decisions that maximize conversions without inflating costs. In parallel, optimize product titles and descriptions in your data feed to boost relevance and ad rank, reducing the need for higher bids to compete effectively.
