I’ve just discovered a game-changing update from Google Ads that’s making my life a whole lot easier. Now, Google Ads shows per-product campaign eligibility, which makes spotting gaps and overlaps a breeze.
With this new feature, I can see exactly which campaigns my products are eligible for, right within the Products section. This has transformed the way I approach campaign tracking.
How it works. I find the new dashboard in the Products section incredibly useful. It includes:
A table that shows product details, status, issues, and priority flags
A line graph summarizing campaign status trends
Filters that let me segment eligibility views
A pop-up panel listing “Eligible” and “Not eligible” campaigns per product
Why we care. This update helps me quickly identify products that are missing from essential campaigns or unintentionally overlapping, especially in Shopping and Performance Max. It saves me the hassle of bouncing between different campaign views to diagnose issues.
The big picture: These changes allow me to swiftly spot products not running in expected campaigns and identify overlap before it’s a budgeting issue, all while minimizing time spent on troubleshooting.
Between the lines. It’s clear that Google is focusing on giving advertisers like me more precise control over Shopping campaigns, a key factor in product-level optimization and profitability.
When. The feature is available now in Google Ads.
First seen. I first learned about this update thanks to Hana Kobzová from PPC News Feed.
I’ve noticed that when I leave Performance Max campaigns running without proper setup, they tend to focus on getting easy conversions, often leading to a rise in low-quality leads. While this can quickly rack up conversion numbers, the quality isn’t always great. Google tends to prioritize cheaper conversions, benefiting their revenue, but not necessarily my pipeline.
Many times, brands are surprised by these results after following Google’s sales advice too closely. Although low CPA metrics look tempting, they can often mask the fact that these new leads aren’t contributing to the real growth of my business.
That said, with the right adjustments, Performance Max can be optimized to generate high-quality leads. Building these ‘guardrails’ effectively is key to success, and I’m here to share what I’ve learned.
This guide will walk you through which strategies work for improving lead quality, tactics that don’t deliver desired results, and the notable differences between using Performance Max in Google versus Bing.
How to Improve Lead Quality in PMax Campaigns
Here are the actionable steps I’ve found to consistently impact lead quality:
Focus on conversion goals that align with higher quality targets. Try targeting metrics like closed-won leads or sales-qualified leads, which provide more valuable insights than just form fills. For this to work, ensure my CRM is accurately tracking offline conversions.
Utilize high-value audience signals. Target more specific behaviors, such as users who have ‘booked a meeting’ rather than just anyone who converts.
Concentrate on the correct audiences. Exclude irrelevant segments, and use Customer Match to help Google’s algorithms find users similar to my best customers.
Optimize campaign settings smartly. Examples include using brand exclusions, targeting high-performing geos, strategic scheduling, analyzing search themes, and employing site link extensions to channel traffic efficiently.
Refine forms for better lead filtering. Integrate reCAPTCHA to deter bots, implement field validation to block disposable domains, and include quality-check questions such as how they heard about my company or if they have budget allocations.
Some common optimizations don’t significantly enhance lead quality:
Switching bid strategies offers minimal impact.
Adding more assets or budget doesn’t inherently improve lead caliber.
I’ve learned to be cautious when seeking help from Google support, as results can vary.
Important Differences Between Google and Bing PMax Campaigns
Google and Bing both offer Performance Max campaigns, but they differ significantly. Google’s expansive network includes search, display, YouTube, discovery campaigns, and Gmail. If not carefully managed, this can lead to spam-driven conversions, particularly from display and YouTube.
Bing’s campaigns, on the other hand, focus on Bing search and their audience network, which covers display, Outlook, and MSN. I haven’t observed significant performance differences, but staying updated with platform changes is crucial.
Performance Max Isn’t Broken, but It Needs Control
Entering PMax for lead generation with caution is a wise approach. Although promising for ecommerce revenue, lead quality demands stringent campaign guidelines. For instance, preventing misaligned conversions for a luxury retailer requires effective PMax guardrails.
Considering Google’s shift towards automation and AI, it’s essential to continuously test and adapt. Recent updates like channel-level reporting and exclusion options offer new tools to shape my campaigns.
Achieving quality leads and a healthy ROI is possible by navigating the algorithm strategically. If past PMax efforts were paused due to poor returns, revisiting and applying lessons learned could significantly improve future outcomes.
I recently discovered that Performance Max now includes built-in A/B testing for creative assets. This feature offers advertisers a straightforward way to measure and enhance their advertising strategies.
Google is introducing a beta feature that allows me and other advertisers to conduct structured A/B tests on creative assets within a single Performance Max asset group. This setup enables me to split traffic between two sets of assets and evaluate performance through a controlled experiment.
Why it matters to me. In the past, creative testing within Performance Max was often guesswork. With Google’s new native A/B asset experiments, I can now perform controlled tests directly within PMax without needing to launch separate campaigns.
How it works for me. I select one Performance Max campaign and asset group, then define a control asset set using my existing creatives and a treatment set with new alternatives. Shared assets can be utilized across both versions. After setting a desired traffic split, like 50/50, the experiment runs for several weeks, allowing me to apply the winning assets based on actual performance data.
Why this is beneficial for me. Conducting tests within the same asset group isolates the impact of the creatives I’ve designed, minimizing interference from changes in campaign structure. This controlled split allows me to obtain clearer reporting, helping my team make data-driven decisions based on solid performance metrics rather than assumptions.
What I’ve learned so far. Early testing indicates that shorter experiments—especially those under three weeks—can yield unstable results, particularly in accounts with lower volume. I’ve found that extending the test duration and avoiding simultaneous campaign changes significantly enhances reliability.
My takeaway. Performance Max is evolving into a more testable platform. I now have the ability to validate creative decisions using built-in experiments, reducing reliance on trial and error approaches.
Source of insight. A Google Ads expert noticed the update and shared insights on LinkedIn.
When I first heard about Performance Max, I was skeptical. It seemed like an unfinished product, but over the past 18 months, Google has made significant improvements in transparency and control. If you haven’t revisited Performance Max since its early days, now is the perfect time to take another look.
As I learned from Mike Ryan at SMX Next, the advancements are worthy of attention.
Taking a Fresh Look at Performance Max
Performance Max evolved from Smart Shopping campaigns, introduced with much excitement in 2019. Yet, industry experts quickly pointed out issues with transparency and control, which Google is only now beginning to address.
Smart Shopping took away vital controls critical for managing campaigns effectively. Essential features like promotional controls and search term reporting vanished, leaving many of us feeling limited.
Fortunately, Performance Max reintroduces much-needed functionality, enhancing what was once lacking.
Understanding Performance Max Search Terms
In my experience, search terms are crucial for understanding the effectiveness of our campaigns. With Performance Max, Google has added a unique match type that brings detailed and scriptable data, allowing us to optimize with precision.
Search Term Insights vs. Campaign Search Term View
Initially, Google introduced search term insights, grouping queries into categories. Unfortunately, these lacked depth as they didn’t provide essential cost data.
The game-changer, though, is the new campaign-level search term view, offering access to more metrics and clearer visibility on performance.
While these insights are only available at the search network level, they offer significant improvement over past limitations.
Search Theme Reporting
Through Performance Max, I’ve realized search themes act as a positive targeting method. By checking conversion data and the source of traffic, I can ascertain the value of search themes, identifying whether they contribute effectively or remain underutilized.
Search Term Controls and Optimization
Negative Keywords
At first, negative keywords in Performance Max were limited, which was frustrating. But now, they are fully supported and much more robust, giving me the control I need to fine-tune performance.
Brand Exclusions
While Performance Max tends to favor brand queries because of their high intent, I’ve noticed that using negative keywords provides a stronger solution for ensuring optimal performance without leakage.
Optimization Strategy
My strategy involves identifying non-performing search terms with higher-than-average clicks but zero conversions, making them strong candidates for exclusion. This approach prevents overcorrection while maintaining a focus on impactful terms.
Modern Optimization Approaches
Instead of spending countless hours manually reviewing search terms, I leverage automation. Using the API for high-volume accounts and scripts for mid-range volumes significantly optimizes my workflow.
Channels and Placements Reporting
Channel Performance Report
One of the tools I now rely on is the channel performance report, offering insights across different networks like Discover and Display. Though interpreting some diagrams can be tricky, it provides valuable data on how different channels perform.
Channel and Placement Controls
Placement Exclusions
Through API and Report Editor data, I focus on excluding specific placements that seem irrelevant or pose risks, particularly in sensitive content areas like politics and children’s videos on YouTube.
Tools for Placement Review
For reviews, especially in other languages, I’ve found that using Google Sheets’ translation function is effective. It helps me quickly determine the relevance of YouTube placements without relying on external systems.
Search Partner Network
The inability to opt out of the Search Partner Network can be frustrating. However, I mitigate this by prioritizing exclusions where performance is subpar compared to the Google Search Network.
Device Reporting and Targeting
Device Analysis
Analyzing device performance provides deeper insights into how specific products perform across different devices. This often reveals advantages or challenges when compared to competitors.
Device Targeting Considerations
Splitting campaigns by device can hurt data volume, impacting machine learning effectiveness. It’s crucial to weigh the benefits of splitting against the potential for data fragmentation.
Conclusion
Reflecting on Performance Max’s evolution, it’s evident that Google has made impressive strides in offering advertisers like myself more control and transparency. While it’s not without flaws, it’s a far more effective tool for ecommerce success now than ever before.
The key lies in understanding available data, using modern tools to streamline processes, and applying performance insights strategically to achieve the best results.
I recently discovered how crucial first-party data has become in the evolving landscape of AI-powered advertising. It’s fascinating to see how it shapes the optimization and measurement of automated ad campaigns.
During a chat with Search Engine Land, I learned from Julie Warneke, CEO of Found Search Marketing, about the profound impact first-party data has on profitable advertising, regardless of potential changes to Google’s third-party cookie policies.
Embracing first-party data means tapping into customer information that I own, typically stored in a CRM, like lead details, purchase history, revenue, and customer value collected from various touchpoints.
This type of data is distinct from platform-owned or browser-based data, over which I have limited control.
Digital advertising has evolved over the years. The shift from focusing on impressions and clicks to outcomes emphasizes profitable conversions, according to Warneke. Advertisers who provide AI systems with quality customer data gain a significant edge.
Although rising cost-per-clicks (CPCs) are inevitable in paid media, first-party data enhances conversion quality, revenue, and return on ad spend, making higher costs justifiable with better results.
By leveraging first-party data tied to revenue and customer value, AI bidding systems can target users resembling high-value customers, even beyond usual demographic or geographic signals, leading to better conversions.
Among campaign types, Performance Max (PMax) thrives with first-party data activation. It performs best when I shift from manual optimizations to feeding it accurate data, allowing the system to learn, as Warneke highlighted.
Even small and mid-sized businesses can leverage first-party data, as seen in Warneke’s examples of success with small customer lists. The challenge lies in setting up proper infrastructure for tracking, consent management, and data flow.
Common mistakes include weak data capture, where brands rely on browser-side tracking that falters on platforms like iOS, and broken feedback loops from sporadic CRM data uploads. Continuous data streams are crucial.
Warneke advises taking a step back to audit how data is captured, stored, and relayed to platforms. Incremental improvements can pave the way for significant long-term gains, even starting with a small portion of a budget as a test.
Ultimately, AI optimization reflects the quality of signals received. By refining first-party data, I can influence outcomes favorably, avoiding inefficiency risks.
As a new advertiser, I’ve often found myself overwhelmed by Google’s Performance Max recommendations.
While well-intentioned, following them blindly can reduce my control and insight, leaving me to wonder if I’m truly making the best strategic decisions.
Initially, my journey with Performance Max felt promising. Google Ads reps offered support, but I soon realized their alignment was more with Google’s interests than my own business objectives.
It’s important to remember that they don’t have insight into my specific needs or business goals. They encourage the adoption of new features that might not align with my early-stage needs.
Understanding Google Reps’ Role
Google Ads reps are not strategic consultants for my business. Their main role is to promote Google’s products and services.
Your margins or cash flow are not their concerns. Their focus isn’t on whether my ads are profitable, but on pushing newer ad types and increasing my ad spend.
Therefore, understanding their incentives helps in taking their advice with the right perspective.
Performance Max provides efficiency and scale for Google. However, for a new advertiser, this can lead to unclear insights and misaligned strategies.
Performance Max: Who Does it Really Benefit?
Performance Max often benefits Google more than it benefits me as the advertiser.
Google controls how my budget is allocated across various channels, offering limited visibility into how these funds drive results. For me, this can be challenging, especially when new and needing clear insights.
This model monetizes Google’s ecosystem efficiently, but leaves me with diluted budgets and unpredictable costs.
Understanding these dynamics helps ensure my campaign choices are aligned with my actual business needs.
Rethinking Google’s ‘Best Practices’
What Google labels as ‘best practices’ might not fit my specific business strategy.
Recommendations often stem from aggregated data rather than being tailored for my unique circumstance, creating a gap between my needs and their blanket solutions.
For budding advertisers like myself, what’s globally optimal might not serve my business nuances and constraints.
The Value of Earning Automation
I’ve learned that automation success is something to be earned with data, not started with blindly.
Shopping Ads have provided me with high-intent, controllable data—essential for testing and learning.
This approach allows a clearer understanding of what truly works, paving the way for informed decisions.
When done right, these strategies lay a solid foundation for future automation without risking budget waste.
A Lesson in Practicality: Reviewing a Case Study
Consider a chocolatier’s experience—a new Google Ads account, $3,000 spent, but only one purchase. Incorrect conversion tracking led to misleading data.
After reworking the setup to a Shopping campaign, results began improving quickly, informing future campaigns with real performance data.
Why Shopping Ads Offer Insight
Focused on real behaviors and intent, Shopping Ads give granular control and transparency, which is crucial when each marketing dollar counts.
This control allows me to experiment deliberately, understanding and scaling the strategies that work.
Adopting a Hybrid Approach
A mix of Standard Shopping and selective Performance Max can be powerful once a data foundation is set.
This balance ensures sustainable growth by protecting proven strategies while allowing room for innovation driven by Performance Max.
Strategizing for Long-term Success
Starting small with clear data-driven campaigns creates a launchpad for successful automation.
By validating products and refining acquisition costs through Shopping Ads, I set the stage for Performance Max to elevate proven strategies.
It’s all about disciplined, strategic advertising that safeguards my investment and fuels long-term growth.
I’ve discovered a game-changing PPC framework that not only predicts user intent but also extends beyond traditional search methods to connect your content with the right audience.
Search marketing continues to thrive, with Google reaching over $100 billion in ad revenue in just one quarter, primarily driven by search ads. However, relying solely on search won’t yield the results many businesses anticipate anymore.
During the SMX Next event, I learned from Google Ads Coach Jyll Saskin Gales that genuine performance now hinges on integrating traditional search with an expansive PPC strategy.
The challenge with traditional Search Marketing
In my experience as a search marketer, I excel at reaching individuals actively searching for what I offer. Yet, there’s an entire audience segment that aligns with my target market but hasn’t started their search journey.
The actual opportunity lies at the crossroads of user intent and audience fit.
Consider the term [vacation packages]. This could be queried by different groups like a family with kids, honeymooners, or retirees. While the keyword remains the same, each group requires unique messaging and offers.
Understanding targeting capabilities in Google Ads
There are two primary targeting types I focus on:
Content targeting places ads in specific locations.
Audience targeting displays ads to particular user types.
For instance, targeting [flights to Paris] is content targeting, while targeting users “in-market for trips to Paris” uses audience targeting. Google’s in-market audiences are crafted by analyzing various signals like user searches, browsing behavior, and location data.
The three types of content targeting
Keyword targeting: Engage users when they search on Google, extending to dynamic ad groups and Performance Max.
Topic targeting: Present ads next to content about specific subjects in display and video campaigns.
Placement targeting: Present ads on particular websites, apps, YouTube channels, or videos where my ideal customers already engage.
The four types of audience targeting
Google’s data: Prebuilt segments include detailed demographics, affinity segments, in-market segments, and life events, usable by any advertiser across most campaigns.
Your data: Target website visitors, app users, and those engaging with my Google content using Customer Match, though remarketing is restricted for sensitive topics.
Custom segments: Convert content targeting into audience targeting by crafting segments based on search behavior, interests, and user site or app preferences. Names vary across campaigns, such as “custom segments” and “custom search terms” in video.
Automated targeting: This entails optimized targeting, audience expansion, and lookalike segments deriving new users from existing data.
Building a targeting strategy
To construct a cutting-edge targeting strategy, I need to address these two essential questions:
How can I leverage Google Ads to promote my offer?
How can I connect with a specific audience using Google Ads?
For instance, targeting Google Ads professionals for lead generation software could involve building tailored segments targeting users of the Google Ads app, visitors of industry-relevant sites like searchengineland.com, or searchers utilizing specific Google Ads terms like “Performance Max.”
Layering in content targeting, such as YouTube placements on industry educational channels and topic targeting around search marketing, enhances my outreach.
Strategies for sensitive interest categories
In cases where I operate within restricted categories like legal or healthcare, and cannot employ custom segments or remarketing, non-linear targeting becomes crucial. I focus entirely on the audience and ignore direct offers. Selecting any Google data audience with an overlapping potential and letting creative content filter it out helps tremendously.
Employ industry-specific terminology, acronyms, and visuals that resonate with and are recognizable to my target audience. Others will likely disregard it.
Remember: High CPCs aren’t the enemy
From my perspective, low-quality traffic poses the real challenge. It’s more beneficial to incur a $10 click with a 10% conversion rate than a $1 click with an infinitesimal 0.02% conversion rate.
When analyzing targeting strategies, I focus on conversion rates and cost per acquisition instead of merely cost per click.
Search alone can’t deliver the results you’re used to
By expanding beyond traditional search keywords and incorporating content and audience targeting, I can ensure the right people see my ads and achieve robust results.
Watch: Building a Modern Targeting Strategy Like a Pro + Live Q&A
Have you ever wondered where your Performance Max ads truly run? With the latest Google Ads API v23 update, we finally have the answer!
An exciting change has arrived with the v23 Ads API launch. Now, Performance Max campaign results can be broken down by channel, including Search, YouTube, Display, Discover, Gmail, Maps, and Search Partners. Previously, all your performance data was lumped together, obscuring critical insights.
Here’s the inside scoop. In earlier API versions, I always received a MIXED value for the ad_network_type segment in my Performance Max campaigns. But with v23, these results have transformed into distinct channel enums. It’s a major step forward for those of us who crave precision in reporting and optimization.
Why this matters to us. This update isn’t just about new features — it reshapes how we comprehend Performance Max. With channel-specific reporting now on the table, marketers gain much-needed clarity on where these ads are displayed.
How we can leverage this. Now, we can access channel-level data at the campaign, asset group, and even individual asset levels. This means we can observe how each creative piece performs across Google’s array of platforms. Coupled with v22 segments like ad_using_video and ad_using_product_data, the possibilities for optimizing video performance on YouTube or Shopping ads on Search are endless.
Attention, developers. Upgrading to v23 unveils a level of reporting detail that was previously unreachable. If your system relied on the old MIXED values, it’s time to gear up for the new channel enums.
Keep an eye out for:
Channel data is accessible only for dates beginning June 1, 2025.
Remember, asset group–level channel reporting remains exclusively within the API and is not visible in the Google Ads UI.
The takeaway. The newest Google Ads API rollout quietly transforms what was once a black-box campaign category into an analyzable channel-specific type. Finally, advertisers like you and me can dive into the metrics we’ve long sought.
As I delve into Google Ads API v23, I’m excited to share this update marks the beginning of a faster-paced release cycle in 2026. With this update, I’m now able to access improved Performance Max reporting, sophisticated AI-driven audience tools, and more detailed campaign controls.
What’s new:
Performance Max Transparency: I’ve discovered that PMax campaigns now offer ad network type breakdowns, making it easier for me to analyze performance.
More Detailed Invoices: Through InvoiceService, I can retrieve campaign-specific costs, regulatory fees, and adjustments, allowing for more precise financial tracking.
More Precise Scheduling: It’s a game-changer for me to now schedule campaigns using precise start and end date-times instead of limiting to date-only fields.
Local Data Access: I’m now able to access store location details via PerStoreView, which matches the data in the Stores report accurately.
New Audience Dimension: With life-event-based audience building through LIFE_EVENT_USER_INTEREST, my Insights tools are more powerful than ever.
Smarter Demand Gen Planning: The conversion rate forecasts I rely on now vary by surfaces such as Gmail and Shorts, enhancing my strategy planning.
Generative AI Audiences: I can efficiently translate free-text audience descriptions into structured attributes, simplifying audience target creation.
Expanded Shopping Metrics: The inclusion of new competitive and conversion metrics by conversion date helps me improve my shopping ads performance.
Why I care: A quicker update cycle means I can leverage new features faster. With Google’s shift towards automation and AI-driven insights, staying on top of these updates helps me optimize campaigns effectively.
Between the lines: These updates require my team to upgrade client libraries and code, so scheduling development time is crucial to benefit fully from v23.
Bottom line: The Google Ads API v23 is setting the stage for 2026. I’m ready to embrace these improvements that introduce faster releases coupled with enhanced AI insights, refined reporting, and better campaign control for large-scale advertisers.
I’ve noticed something pretty exciting in Google’s recent update to Performance Max. They have introduced one-click ad previews, making it incredibly easy to review creatives directly from the asset group table. This update feels like a breath of fresh air to anyone who’s ever been bogged down by the previous clunky process.
What’s new? Now, with just a click on any image or video within the Asset Groups table, I can instantly see how my ads will look across different Performance Max placements, without needing to navigate away from the page.
Why we care. Before this, checking ad previews meant jumping through various hoops into different views or settings. Now, everything is streamlined, keeping my workflow smooth and efficient, which makes creative quality assurance and iteration a lot less of a hassle.
Between the lines. There has been consistent feedback about the transparency limitations of Performance Max. So, even these small UI changes that bring creatives to the forefront are a big deal for me and many others in the field.
The bottom line. While one-click previews aren’t a game-changer in terms of strategy, they are a real time-saver. This especially helps when I’m handling large asset libraries or frequent creative updates.
First seen. This handy update was first spotted by Paid Search marketer Bia Camargo, adding another reason to appreciate these nuanced yet impactful changes.
