Starting March 1, 2026, Google’s update is a game changer for those of us using ad scheduling. This change will actively pace our budgets, potentially reaching the full 30.4x monthly limit, even if our campaigns are running only on specific days.
Understanding the Change. Many of us may recall how Google used to pace our budgets based on active days. But with this update, they will aim to hit the full monthly cap within our scheduled times.
How It Works:
The 2x daily overspend rule remains in place.
The 30.4x average daily budget monthly cap is unchanged.
Our campaigns will continue to run only within scheduled hours.
Google’s new approach attempts to hit the full monthly budget within our existing schedule.
Why This Matters. Previously, if we ran campaigns on limited schedules, like weekends, our monthly spend was naturally lower. But now, we might see a significant increase in spending thanks to this pacing change—without any alteration to daily budgets or billing limits.
For instance, if we have a $100 daily budget set for weekends-only, our spend could jump from around $800 to $1,600 monthly because Google will try to maximize our spending on each active day.
Google’s Perspective. Ginny Marvin from Google clarified that this shift aims to better match the pacing with our expectations for monthly spending limits. While we won’t exceed billing caps, we should anticipate an adjustment in how budgets are approached.
According to Ginny, only those who received direct notifications of this update will be affected, and the change will roll out gradually.
What It Means for Us. Essentially, this isn’t about raising limits but about how Google utilizes current ones. If we rely on ad scheduling to contain our spending, this might cause unexpected increases unless we adjust our daily budgets accordingly.
Steps to Take Now:
Review all campaigns using ad scheduling.
Recalculate daily budgets to align with your true monthly goals.
Consider lowering daily budgets to maintain previous spending levels.
The Bottom Line. Google’s not altering our spending capacity, just the pace at which we might reach it. Ensure to modify flighted or part-time campaigns before March 2026.
Initial Insight. This update was first brought to my attention by Jordan Fry, who shared Google’s message on LinkedIn.
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.
Let me share a few valuable lessons I’ve learned about PPC advertising from seasoned experts. Even the most experienced among us encounter pitfalls—like hastily launching campaigns or leaving automation unchecked. Recently, I joined Greg Kohler from ServiceMaster Brands and Susan Yen from SearchLab Digital at SMX Next, where we candidly discussed the mistakes that catch us off guard.
Read on to discover the blunders that even the most seasoned marketers must navigate.
Never launch campaigns on a Friday
This is a well-known pitfall, yet it continues to happen. Susan Yen mentioned that due to client demands, campaigns often go live on Fridays, leading to weekend chaos if things go awry. A minor error like an inflated budget setting can cause significant issues.
Greg Kohler emphasizes the importance of reviewing setups with fresh eyes. Wait until Monday to launch; doing so may avert unnecessary problems. Even experts can become overconfident, only to be reminded of these lessons by a Friday crisis.
Takeaway: Avoid launching before the weekend or holidays and stand firm if clients push. It protects both your peace of mind and campaign performance.
Location targeting disasters
Greg shared an experience where an error in location targeting meant campaigns ran in the wrong timezone. By Saturday, ads intended for a U.S. audience accumulated thousands of views in Europe instead.
Takeaway: Configure location settings directly within the Google Ads interface to minimize risks and ensure precise targeting.
The search term report trap
Susan stressed that search term reports are essential for every campaign. Ignoring them can lead to wasted clicks and difficult client conversations later on. She advises checking these reports monthly to avoid irrelevant traffic.
Takeaway: Routine reviews help refine what to target or exclude, enhance performance, and maintain efficient account strategy.
Google Ads Editor vs. interface: A constant battle
The gap between the Google Ads Editor and the interface often leaves teams in a bind. Susan’s team preps in Excel before using Editor for bulk edits but prefers the interface to ensure accuracy in settings.
Takeaway: Use the interface for tasks requiring precision, like responsive ads or location targeting.
The automatically created assets problem
Automatically created assets often default to ‘on,’ requiring tedious navigation to disable. New types of assets can inadvertently apply to all campaigns.
Takeaway: Regularly review these settings. Set reminders to maintain control as new features roll out.
Importing campaigns from Google to Microsoft Ads
Yen warned of the pitfalls of importing Google campaigns directly into Microsoft Ads due to discrepancies in budget assumptions and automation settings.
Takeaway: Treat Microsoft Ads independently with a tailored strategy post-import for optimal results.
The App placement nightmare
A slip in excluding app audiences can direct spend to irrelevant categories. Yen advises vigilance, as settings to exclude these are often hidden.
Takeaway: Establish comprehensive exclusion lists to guard against inappropriate targeting.
Content exclusions and placement control
Applying content exclusions from the start helps avoid placement in irrelevant or inappropriate contexts, though manual follow-up remains necessary.
Takeaway: Consistent reviews ensure Google honors your settings, preventing unwelcome surprises.
Call tracking quality issues
Susan highlighted the importance of client communication in effectively tracking call quality, advocating for monthly check-ins focused on conversion metrics.
Kohler suggested distinguishing first-time from repeat callers in analytics to optimize automated bidding systems.
The promo date problem
Litner pointed out issues with scheduled assets appearing outside their promotional windows, urging manual checks to ensure proper timing.
Kohler echoed similar concerns with automated rules potentially misfiring.
Takeaway: Verify scheduled actions on their launch dates manually to prevent mishaps.
AI Max settings and control
The issues of AI-driven campaign settings defaulting to active require diligence in monitoring and fine-tuning each setting.
Takeaway: Despite AI advancements, practice consistent oversight to manage budget spend effectively.
Account-level settings that haunt you
Susan flagged the risk of overlooking critical account-level settings that can derail campaigns silently, suggesting a standardized checklist approach.
Takeaway: Establish and follow a thorough account setup checklist to catch any hidden conflicts with campaign goals.
Final wisdom
Here are several recurring themes from our discussion:
Always double-check automation; it’s not immune to errors.
New perspectives reveal potential errors.
Effective client communication prevents misunderstanding.
Manual reviews maintain balance as automation increases.
Keep updating exclusion lists to mitigate repeated issues.
The takeaway is that everyone makes mistakes. The difference lies not in avoiding them but in swiftly addressing them, learning from experiences, and creating systems to prevent recurrence. As Kohler notes, stay vigilant, question automation, and avoid the temptation of a Friday launch.
I’ve been there myself. A client approaches me, eager to upscale their Google Ads spend from €10,000 to €100,000 monthly. Like any dedicated PPC manager, I dive into the usual strategies:
Refine bidding strategies.
Test new ad copy.
Expand keyword lists.
Optimize landing pages.
Boost Quality Scores.
Launch Performance Max campaigns.
Several months in, the ad spend only grows by 15%. The client is content, but I know we can do better.
Here’s a harsh truth I’ve learned: much of what we consider PPC optimization is really just sophisticated procrastination.
The theory of constraints, introduced by Eliyahu Goldratt, offers insights for PPC much like it does for manufacturing. It shows that every system has a single constraint that limits its potential.
It doesn’t matter if the marketing team is super-efficient if the production capacity is what’s limited. Likewise, a 20% improvement in ad copy CTR isn’t useful if the real constraint lies in budget or conversion tactics.
This theory calls for radical focus: pinpoint the weakest link, make it your priority, and tune out the rest.
Applying this to PPC means stopping the widespread optimization efforts. Detect the primary barrier, resolve it, and press on.
Over time, managing PPC accounts has shown me that scaling challenges usually fit within one of seven categories:
Budget: Profitability could be higher, but client approval caps spending.
For instance, a campaign might run successfully at €10,000 monthly, with scope to go to €50,000, yet the client hesitates due to risk aversion or cash flow concerns.
Developing a compelling business case that showcases past ROI and projected returns is vital here.
I ignore ad copy tests or keyword expansions because, if I can’t increase budget, they won’t help.
Impression Share: Already capturing over 90% share, limiting traffic growth.
Entering new markets or ad platforms can often be the solution for these scenarios.
The Creative aspect needs tightening when high impressions yield low CTRs, and so on for conversion rate, fulfillment, profitability, and tracking or attribution challenges.
With my diagnostic steps, I start by running an audit to benchmark the key metrics—impression share, CTRs, CPCs, and conversion rates— to pinpoint what’s genuinely holding the account back.
The moment I finish an audit and single out the top challenge, the focus becomes precise. For instance, if it turns out conversion rate optimization can unlock growth, that’s where all my efforts channel into until I see a breakthrough.
Every time the constraint is overcome, a new bottleneck emerges, signifying growth and the movement to new phases. It is both a marker of success and a roadmap to what needs attention next.
I’ve noticed a significant shift in how Google Ads operates. No longer is it about simply targeting keywords. Now, it’s all about understanding and leveraging user intent. Here’s what this evolution means for eligibility, structure, and PPC strategy.
Most PPC teams, myself included, have operated on autopilot: compiling keyword lists, assigning match types, and structuring ad groups around search terms. This was the norm.
However, Google’s auction process has transformed. Search interactions are evolving into more conversational experiences. People engage with AI as if they’re having a dialogue, asking follow-up questions and refining their inquiries. AI now reasons through a question before linking it to suitable ads.
Today, the auction isn’t kicked off by a keyword but by the user’s implied intent. If I’m still relying on exact and phrase match structures, I’m planning for a system that’s no longer there. It’s time to embrace intent as the foundation—not the specific words typed, but the underlying goals they signify.
With this intent-first approach, I find a more resilient strategy. It allows me to effectively design campaigns, creativity, and metrics, especially as Google rolls out new AI-focused formats.
While keywords still play a role, they no longer serve as the framework.
Recently, I’ve learned about changes happening under the hood during a search.
Google’s AI now utilizes a method called “query fan out,” which breaks down complex queries into subtopics and conducts simultaneous searches to provide a comprehensive response.
The auction begins even before users finish typing. Importantly, AI can deduce commercial intent from purely informational searches.
For example, if someone asks, “Why is my pool green?” Google understands they’re troubleshooting, not shopping, but identifies potential product needs and displays ads for pool-cleaning supplies. The AI’s reasoning layer recognizes the solution products offer.
This change in auction logic focuses on matching offerings to the user’s inferred intent, rather than merely matching keywords to queries. Recognizing this shift is crucial, or I risk misinterpreting the user journey.
I’ve come to appreciate the intricacies of an intent-first approach. It doesn’t eliminate the need for keyword research but changes how I prioritize keywords. Now, I align campaigns to the user’s intent.
This strategy encourages me to consider:
What problem is the user addressing?
What stage of decision-making are they in?
What role does the product play in solving their issue?
Realizing that the same intent can emerge from various queries and that identical queries can express different intents based on context has been illuminating. Phrases like “Best CRM” might indicate a need for feature comparison or a readiness to purchase; Google’s AI can now make those distinctions, and so should my campaigns.
This shift is more mental than tactical. While I still build keyword lists, they’re now organized by intent rather than match type. My ad copy speaks directly to user goals instead of echoing search terms.
Moving from keywords to intent isn’t merely a tactical alteration—it’s a strategic lens through which I plan for future campaigns, especially as Google enhances its AI-driven ad formats.
Reorganizing campaigns around intent rather than keywords has its immediate effects, impacting eligibility and landing page efficacy while fundamentally influencing system learning.
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
I’m thrilled to share that Google Ads has launched a transformative new Experiment Center, providing us advertisers with a centralized platform to test strategies and analyze their impact before scaling them up.
What’s new. With Google’s latest update, we now have access to a comprehensive help page introducing the Experiment Center. This innovative dashboard merges traditional Experiments and Lift Studies, allowing us to handle tests regarding bidding, targeting, and creatives. Simultaneously, we can measure brand, search, or conversion lift, all in one place.
Why it matters. Previously, experimenting within Google Ads was a bit scattered. Different tests lived in separate areas, making it cumbersome to streamline our strategies. A unified hub simplifies this process drastically, reducing complexity and enabling us to confidently validate our strategies before increasing our budgets.
How it works: The new layout is a breath of fresh air, enhancing setup and reporting efficiency. Now, key insights from our tests are displayed together, rather than being spread out across various tools. This consolidation allows us to quickly compare outcomes, grasp the impacts, and take action faster.
Between the lines. Google is clearly investing heavily in experimentation, and the Experiment Center is the latest in a line of updates. With enhancements like expanded A/B testing in Shopping and Performance Max campaigns, alongside the new Campaign Mix Experiments beta, this platform equips us with the tools needed to adapt to an automated landscape, ensuring our strategies remain impactful and clear.
Bottom line: If you haven’t already, it’s time to dive into the Experiment Center. Formalize your testing around bidding, targeting, and creative strategies, leveraging lift studies and experiments to validate your approaches before rolling them out on a larger scale.
I’ve discovered that Google is introducing a fascinating new tool called Campaign Mix Experiments (beta). This innovative framework allows me and other advertisers to experiment across various campaign types, budgets, and settings all within a single, unified setup.
How it works:
As an advertiser, I can create up to five experiment arms, each with its own unique combination of campaigns. This means I can include the same campaign in multiple arms and distribute traffic among them.
Google’s mix experiments support a wide range of campaigns, including Search, Performance Max, Shopping, Demand Gen, Video, and App campaigns, though it does exclude Hotels.
I’m able to customize traffic splits starting at a minimum of 1%, and the results are adjusted to the smallest split for a fair comparison — ensuring accuracy in our findings.
What I can test:
The beta provides an exciting opportunity to explore and test budget allocation across different campaign types. I can also assess account structures, varying between consolidation and fragmentation.
It allows me to examine differing bidding strategies, targeting options, and feature adoptions, alongside studying cross-channel performance interactions, beyond just individual campaign impacts.
Why I care. With this new tool, I can go beyond individual campaign testing, gaining insights into how various campaign types interact and identifying which combinations yield the most substantial business outcomes.
Reporting details: I can monitor results through the Experiment summary and campaign-level reporting, selecting from confidence intervals like 95%, 80%, or 70%, and focus on key metrics such as ROAS, CPA, conversions, or conversion value.
Best practices:
I make sure to keep the experiment arms similar, only altering one variable at a time. I align the total budgets across these arms unless budget allocation itself is the variable being tested.
It’s advised to avoid shared budgets and significant changes while the experiment is underway, and to run these tests for at least six to eight weeks to ensure the results are statistically reliable.
Between the lines: Google is shifting the focus from a single-campaign victory to understanding how the right mix of efforts can lead to success, especially as automation reshapes the landscape.
Bottom line: By utilizing campaign mix experiments, I gain a realistic view of how different campaign types and financial plans work collaboratively. This empowers me to make informed decisions on where my spending truly adds value.
Amy Hebdon shares lessons from early mistakes in her career, emphasizing the importance of managing relationships alongside campaigns.
I recently had the opportunity to interview Amy Hebdon, an international expert in paid search and the founder of Paid Search Magic, on episode 337 of PPC Live The Podcast. We talked about real-life experiences behind paid media initiatives, focusing on the challenges and insights rather than just techniques. Amy’s vast industry experience makes her perspectives invaluable for anyone steering through complex digital marketing campaigns.
Early career mistakes and learning experiences
Amy recounted an eye-opening experience from her early career while managing a fitness client’s creative assets that didn’t align with Google Ads guidelines. Despite her efforts to safeguard the account, her tactless approach during a high-stakes meeting with leadership caused friction with the creative team. Reflecting on it, Amy realized that while her decisions were valid, better communication could have preserved vital working relationships for future collaboration.
Accountability and oversight in campaign management
I also learned about another incident early in Amy’s career, where she took sole charge of a low-touch account that went inactive due to an expired insertion order. This experience underscored the importance of personal accountability, regular check-ins, and structured processes—even when managing less significant campaigns. Amy pointed out that both her oversight and the client’s lack of internal checks contributed to this oversight.
Stakeholder management and communication
Amy often emphasizes the critical nature of understanding stakeholders’ perspectives and nurturing relationships diligently. She reflects on how decisions that might seem tactical can have relational impacts, highlighting the need for empathy, strategic communication, and objectivity in managing conflicts or escalations.
Lessons on team support and leadership
Another key lesson from Amy is the value of a supportive team and managers who prioritize shared objectives over placing blame. Effective leadership, she believes, involves fostering collaboration, redistributing workload when necessary, and cultivating an environment where mistakes can be openly addressed without fear. For managers, promoting accountability and transparency within teams bolsters both performance and professional growth.
Strategic focus over tactics
Amy stresses that achieving success in paid media demands a strategic approach over purely tactical execution. Merely focusing on bid settings or platform features often overlooks the broader goal of conversion optimization and audience alignment. Amy warns that even technically perfect campaigns can falter if they aren’t aligned with overall business objectives, urging a strategic evaluation over rushing the tactical details.
Navigating AI and automation in PPC
With AI gaining importance in digital marketing, Amy highlights the risks of over-relying on automated outputs. Although AI may produce results that seem right, they often lack accuracy. Marketers need a robust foundational knowledge to critically assess these results. Strategy, judgment, and expertise are crucial in differentiating meaningful insights from the noise generated by automation.
Reflections and career philosophy
In conclusion, Amy reflects on how inevitable mistakes are a valuable part of any career in PPC. With time, marketers can understand these errors in context, learn from them, and avoid letting them define their careers. She describes her career as “practical magic,” blending technical precision with strategic insights to achieve results, knowing that true success comes from both patience and meticulous planning.
