I see Google’s latest Google Ads API change as another clear move away from legacy automation and toward newer AI-driven campaign types, especially Performance Max.
Beginning August 3, 2026, Google says developers will no longer be able to create new Smart Campaigns through the Google Ads API. For me, the key detail is that this change is about new campaign creation only.
Existing Smart Campaigns are not being shut down. They can keep serving ads, and advertisers and developers will still be able to update and manage those campaigns through the API.
What changes is the ability to create brand-new Smart Campaigns through API workflows. If I depend on automated campaign setup, that is the part I would review now.
I care about this because it signals where Google wants advertisers to go next. Smart Campaigns may continue running, but the path for new API-based campaign creation is moving toward newer products such as Performance Max, Search campaigns, and Demand Gen campaigns.
Google is specifically pointing advertisers toward Performance Max as the primary alternative. Since Performance Max runs across Google’s advertising inventory and uses AI to automate more of the campaign process, it fits the broader direction Google has been taking for years.
I also see this as part of a wider consolidation around automated campaign formats. Google has increasingly emphasized systems that handle bidding, targeting, and creative optimization across channels, and limiting new Smart Campaign creation reinforces that shift.
For developers, the practical next step is to audit any application that creates Smart Campaigns before the August 3, 2026 deadline. The affected requests are campaign creation operations where advertising_channel_type is set to SMART and advertising_channel_sub_type is set to SMART_CAMPAIGN.
After August 3, attempts to create new Smart Campaigns through the API will fail. In version 24 of the Google Ads API, developers will receive a SmartCampaignError.CREATION_FAILED error.
In version 23 and earlier, the same type of request will return an OperationAccessDeniedError.CREATE_OPERATION_NOT_PERMITTED error.
My main takeaway is that advertisers, agencies, and software providers should not treat this as a last-minute technical cleanup. If campaign creation is built into an internal tool, onboarding flow, or platform integration, I would start mapping the replacement path now.
Google is not ending existing Smart Campaigns, but it is removing a key creation path for new ones. To me, that is a strong signal that future campaign planning should center on Performance Max and other AI-driven Google Ads campaign types.
I’m watching a small but meaningful Google Search ads experiment that could change how people notice paid results. Google is testing labels that call out the ads it believes are most relevant to a user’s search query, which could affect both user trust and advertiser performance.
What’s happening. Google has started testing new Search ads labels such as “Strongest match” and “Strong match” on select ads in search results. Google Ads Liaison Ginny Marvin confirmed the experiment and said the labels are meant to help users quickly spot ads that closely match their search intent.
For now, I see this as a limited test. Google says it is only appearing for a small percentage of users in the U.S., so most advertisers may not notice it in the wild yet.
Why I care. This kind of visual signal could influence which ads users view as the most relevant and trustworthy. If Google expands the experiment, advertisers with stronger relevance and quality signals may gain more attention, while weaker or less aligned ads could become easier to ignore.
How it works. According to Google, these labels rely on the same ad quality and relevance signals already used inside its advertising systems. In other words, Google is not introducing a new ranking factor here. It is making its relevance assessment more visible directly in the Search results interface.
I see the goal as fairly straightforward: help users identify the ads most likely to answer what they were searching for, without making them interpret relevance entirely on their own.
Why Google is testing it. Google says the experiment is designed to improve the Search ads experience for both consumers and advertisers.
For users, the label could act as another cue that a paid result may be especially useful for their query.
For advertisers, it could help highly relevant ads stand out in front of high-intent audiences, which may lead to stronger engagement and higher click-through rates if the feature performs well.
Reading between the lines. I view this test as part of Google’s broader push to make ad relevance more visible and more understandable to searchers.
Historically, relevance signals have mostly worked behind the scenes through auctions, quality systems, and ranking logic. By showing those signals more clearly, Google may be trying to build more trust in sponsored results while also rewarding advertisers that closely match their ads to search intent.
The timing also matters. Search platforms are under ongoing pressure to prove that their ad experiences are useful, high quality, and worth users’ attention. A label like this gives Google another way to frame certain ads as more helpful, not just more prominent.
What I’m watching next. Google has emphasized that this is an early-stage experiment and has not said whether “Strongest match” or “Strong match” labels will become permanent. For now, I would treat this as another reminder that ad relevance, landing page quality, and alignment with user intent remain central to Google’s direction for Search advertising.
PPC advertising for medical and mental health services comes with more restrictions than many other industries, but I still see it as one of the most effective ways to keep a steady flow of new patients and clients coming into a practice.
Whether I am managing campaigns for a client, promoting my own practice, or building a campaign from scratch, I focus on the same fundamentals: the right keywords, compliant messaging, clear landing pages, and lead-quality tracking.
Choosing keywords for medical and mental health advertising
When I choose keywords for medical or mental health advertising, I start by thinking about how real patients search. In most cases, their searches fall into three main groups.
First, some people search by symptoms or treatment options. They may not know which professional they need yet, so they search for phrases like “treatment options for depression” or “why does my ankle hurt when I run.” I do not ignore these searches, because they can still turn into new patients or clients.
Second, people often search for what they think the service is called. They may use simplified or incorrect terms, such as “therapist to manage bipolar medications” or “foot pain doctor.” These searches still show intent, even if the language is not medically precise.
Third, some searchers use the correct term because they already know what they need and are ready to contact a professional. They may search for “psychiatrist” or “endodontist near me.” Even then, I watch for confusion between similar roles, such as therapist, psychologist, and counselor.
Most of my budget usually goes toward the second and third groups, where searchers are closer to taking action and starting treatment.
If I have a larger budget, I may also test broader symptom-based or informational searches that could convert later. These can work, but I treat them carefully because informational searchers may or may not be ready to book.
I also rely heavily on negative keywords. They help me block searches for services the practice does not provide, which protects the budget and improves lead quality.
With medical and mental health ad copy, I have to be careful. I need the ad to make it clear that help is available, but I cannot write in a way that feels too direct, too personal, or too aggressive.
I expect some trial and error. An ad rejection does not automatically mean an account is in trouble. It usually means the ad was not approved, so I adjust the wording or request a manual review when appropriate.
Blunt language is often where problems happen. Instead of making strong claims, I test softer, more compliant language that still communicates the value of the service.
To stand out from competitors, I focus on practical benefits such as accepted insurance, payment options, specialized treatments, or distinctions like being family-owned, local, award-winning, certified, or licensed.
I avoid terms like “cure” and other language that implies guaranteed results. Google and Meta both have ad policies that restrict how medical, mental health, and wellness services can be promoted.
When an ad gets rejected, I rewrite it so it still explains the value of the practice without crossing policy lines.
For some psychiatrists, doctors, and other medical service providers, Google Ads may also require a LegitScript.com listing, especially for addiction treatment services.
When I build landing or service pages, I start with the information the front office already gives to patients. That is often the clearest and most useful material available.
I pull details from pamphlets, office materials, and common intake conversations. Then I highlight key points such as accepted insurance, cash payment options, payment plans, financing, and specialized treatments.
I also answer the questions patients regularly ask in person or over the phone. A strong landing page should keep improving as new questions come up.
Those questions might include whether the practice works with children, accepts Medicare, offers phone or virtual sessions, or provides a specific treatment.
I make the next step obvious. That may mean booking an appointment, scheduling an initial consultation, requesting a free phone consultation, filling out a form or questionnaire, submitting a contact request, or calling with questions.
I avoid vague forms and generic phone numbers with no instructions. Instead, I explain the process clearly from pre-treatment to treatment to post-treatment.
I also like to include a FAQ section that answers questions such as “what is the process?” and “how does treatment work?” The more uncertainty I remove, the easier it is for a patient or client to take action.
Choosing the best campaign types
For medical and mental health services, I usually build the strategy around Search campaigns.
Automated or audience-based campaign types, including Performance Max and Demand Gen, can run into privacy and targeting limits. Depending on the service, the ads may not be approved.
Remarketing is typically restricted for the same reason. Video campaigns may be possible, but targeting limits often make them better suited for local branding than direct response.
Search campaigns work well because people are actively looking for answers, treatment, or a specific type of provider. They are typing in the exact services they need.
Many providers also use directories like Psychology Today or ZocDoc for lead generation. I still like supplementing those channels with Google or Microsoft Search campaigns because they send traffic directly to the practice’s own site and give more control over patient or client flow.
My usual approach is to target very specific terms for people who are ready to hire a professional, then test broader symptom or research-related terms when the budget allows.
Meta Ads can also be useful, but privacy laws limit targeting. I also have to be careful with ad copy, images, and landing pages so the campaign stays compliant.
I review Meta’s ad policies before launching campaigns to reduce avoidable disapprovals. Meta can support larger budgets, but for most medical and mental health marketing, Google Search remains the most reliable starting point.
With any online advertising, and especially with medical and mental health services, I need to know more than how many leads came in. I need to know which leads became real patients or clients.
A simple CRM, whether generic or built for the industry, can track incoming leads and show which ones converted.
Google Ads, Microsoft Ads, and Meta Ads all offer built-in CRM connections. I can also use a tool like Zapier to connect systems without needing a programmer.
Beyond website form submissions, I also track inbound calls generated by marketing campaigns. Phone calls often represent high-intent leads, so leaving them out can distort ROI.
Call tracking tools such as CallTrackingMetrics, CallRail, and WhatConverts can integrate with CRMs and major ad platforms to measure lead quality.
They also offer call recording and are HIPAA-compliant, which matters when tracking performance in healthcare-related campaigns.
Keeping medical and mental health ads effective
To keep medical and mental health ads effective, I focus on four things: targeting the right searches, writing compliant ads, improving landing pages, and tracking lead quality.
When those pieces work together, I can build campaigns that attract the right patients and clients more consistently.
A steady, well-structured approach is what helps a practice maintain or expand its patient flow without creating unnecessary compliance risk.
Recently, I delved into Google’s updated AI Max reporting guidance, which sheds new light on the AI-driven future of Search campaigns.
Google has revitalized its AI Max for Search reporting documentation, offering advertisers fresh insights into performance reporting, optimization best practices, and significant timelines for Dynamic Search Ads (DSA).
What’s happening? Google has expanded its help documentation for AI Max for Search campaigns, enriching the guidance on reporting and offering more details on campaign performance evaluation.
Though it doesn’t introduce new products, it clarifies how Google intends for us, as advertisers, to manage and interpret AI Max campaigns in the future.
Why this matters. This update offers insight into Google’s long-term vision for AI Max and the impending phaseout of DSA. With automatic DSA upgrades set for early 2027, it’s crucial for us to anticipate the necessary evolutions in our Search strategies.
The headline change: Google has officially outlined the transition from Dynamic Search Ads to AI Max in the help documentation.
Per the updated guidance, DSA campaigns will undergo automatic upgrades to AI Max beginning in February 2027, as Google aims to broaden the adoption of AI-powered Search campaign formats.
What’s new in reporting: Google introduced new reporting views that let us evaluate performance across several dimensions:
Search terms.
Search terms and landing pages from AI Max.
Search terms from Dynamic Search Ads.
Search terms and landing pages from Dynamic Search Ads.
They’ve clarified that search term reports reflect user destinations post-ad click and introduced options for excluding underperforming search terms or landing pages with negative keywords and URLs.
New guidance for travel advertisers: Google also introduced a section specifically for Search Campaigns related to Travel.
This documentation helps us consolidate performance data into a unified view, crucial for evaluating search terms, inventory performance, and conversion outcomes. Travel advertisers can further dissect reports by ad format to compare performance across different types of ads like Travel Promotion Ads, Booking Links, and Travel Feed-based ads.
A shift in optimization philosophy: The latest best practices emphasize targeting based on intent rather than focusing strictly on keyword matches.
Google now advises us to:
Prioritize conversion goals over mere keyword relevance.
Regularly review search term and item group performance every one to two weeks.
Use negative keywords judiciously.
Avoid over-filtering traffic to exploit AI-driven intent matching benefits.
Bottom line:Google’s documentation update serves as more than just a guide for reporting; it lays out a strategic path for us to navigate an AI Max-centric future as DSAs near their fadeout.
I’m excited to share that Google is expanding its financial services ad verification across 24 European countries. As of this summer, financial advertisers in these markets will face new compliance checks to continue running ads in the European Economic Area (EEA).
Here’s the scoop: Starting July 23rd, Google’s new requirements for financial services advertisers apply to 24 EEA countries, including Austria, Belgium, and Sweden, among others.
As advertisers in designated financial categories, we must undergo verification when prompted by Google. This initiative targets financial fraud and aims to ensure ads are from genuine and regulated providers.
Why it matters: If I don’t complete this verification process, my ads may no longer run in these markets. This policy impacts not just banks and insurers but also the agencies that manage their campaigns.
The big picture: This is part of Google’s efforts to improve transparency and protect consumers. If notified, I’ll receive alerts on the Google platform indicating that ad performance could be impacted unless verification is completed.
Failing to comply means I might lose the ability to serve financial services ads in these countries. It’s crucial for continued campaign success.
How does verification work? I need to complete two steps: First, I’ll verify through G2, a third-party compliance partner. Next, I’ll submit Google’s financial verification application using a code from G2.
During this process, I’ll provide details about the services offered, regulatory status, and necessary evidence of authorization or exemption from a relevant financial regulator.
Agencies, beware: These requirements also apply to agencies like mine managing campaigns for financial services clients. We’ll need to pass compliance checks before continuing operations.
A key point to note: Third-party advertisers don’t have the same freedom. If I promote services approved by a verified institution but lack direct authorization, I must rely on them to submit verification requests on my behalf.
Depending on the financial services being promoted, such as banking or credit products, I might need to undergo this verification. Google can update its list at any time, so staying informed is crucial.
Stay vigilant: As a financial brand targeting European customers, I must ensure compliance now to avoid disruptions later. This could affect agencies handling multiple clients due to administrative demands.
Dig deeper: For more details on the new requirements, I can visit Google’s support page.
When I first started looking at budget allocation, I was tempted to believe that every marketing channel followed the same path: spend a little, get a lot, but with diminishing returns.
Visually, it’s easy to assume all channels mimic this pattern.
The typical log-shaped curve illustrates that the first dollar you spend is often the most productive. With this mindset, spreading the budget across numerous channels seems like the go-to strategy.
However, I quickly learned not all channels conform to this model. Some require much more than just a sprinkle of funds to be effective. These channels start with a less efficient spend but eventually pay off if given time to warm up. This condition shifts away from the usual ‘test small, scale the winners’ strategy many marketers follow.
At the core of this difference lies a fundamental question: Is the response curve C-shaped or S-shaped?
Understanding the shape of the response curve can drastically change how I conduct channel testing and measurement, especially with Google’s increasing inclination towards S-shaped campaigns.
Let’s delve into what these two curves signify and why they are crucial.
Response curves plot conversions or revenue against spend. Typically, we encounter two main types in marketing.
A C-shaped curve means diminishing returns kick in from the first dollar spent. Meanwhile, an S-shaped curve starts slow, becomes steep at the inflection point, and finally leads to saturation.
This insight is crucial for allocation because the marginal curve—the derivative—guides budget decisions. Here, shapes diverge with significant implications.
For a C-shaped curve, the highest marginal return is from the first dollar, decreasing thereafter. Conversely, for an S-shaped curve, the initial return is low, increases up to a peak, and then declines.
This aspect of increasing marginal returns is pivotal. It’s what differentiates channels with productive small budgets from those that seem inefficient but could perform better when scaled correctly.
Mainstream marketing campaigns exhibit this principle clearly. For instance, if your CPA goal is $50, the way the S-shaped channel behaves under scaling tells a critical story.
A preliminary $10,000 test may misleadingly suggest failure, but at $20,000-$25,000, the channel might be your most cost-effective choice. Small trials in the warm-up phase mislead the eventual conclusion.
This common misconception arises as many automatically rely on ‘test small, scale what works’. Yet, without sufficient testing past the warm-up phase of an S-curve, we risk dismissing channels that could have been game-changers.
For allocation logic, in C-shaped channels, going wide is beneficial. One global optimum dictates that spreading your budget thinly across many channels generally works.
But with S-shaped channels, a small budget is inadequate. Either commit enough budget to surpass the inflection point or don’t invest at all. There is a true minimum budget to ensure viability.
In marketing, determining whether a channel requires breadth or depth is critical. Channels historically leaned towards a concave shape, although modern platform dynamics have blurred these lines.
The differences are increasingly relevant with AI-driven campaigns. For example, ‘AI Max’ necessitates sufficient conversion data to learn effectively, affirming the concave-to-sigmoid shift. Campaigns like PMax blend both response types, initially concealing inefficiencies through promising headline numbers.
The key is recognizing the harvest versus create dichotomy. Harvest channels, like branded searches, display fast saturation and diminishing returns. Still, creating new demand—especially through platforms like Meta or YouTube—demands investment beyond superficial trials for truly incremental growth.
In conclusion, understanding whether to expand broadly or concentrate deeply in a specific channel can transform the efficiency of a marketing strategy.
Google has just unveiled some exciting AI-powered tools on YouTube. These tools are designed to reveal creator trends, enhance understanding of audience behaviors, and optimize marketing campaigns.
YouTube’s expansion of its toolset for creator marketing and campaign intelligence now includes features powered by Gemini. With these updates, I’m able to delve deep into identifying trends, understanding the creator audiences, and boosting the performance of my campaigns.
What’s happening: Google has introduced several insights and optimization tools across YouTube and Google Ads. As a marketer, these tools give me crucial visibility into trends, creator performance, and audience behavior.
The opportunity to make smarter creative and media planning decisions is more important than ever, especially in an AI-driven marketing world. That’s exactly what these new tools are designed to support.
Why I care: With deeper insights into YouTube trends, I can see which creators are resonating most with audiences and assess how my brand is performing in terms of both paid and organic content. This empowers me to make smarter choices about creator partnerships and campaign strategies.
What’s new:
More detailed trend insights: Google Ads’ Insights Finder now provides even more detailed trends in the U.S., giving advertisers like me a better view of what’s capturing attention on YouTube.
Brand Pulse data in Insights Finder: With the integration of select Brand Pulse metrics, I can now evaluate both my paid and organic efforts from a single location.
New creator insights API: The fresh Content & Creator Insights API offers agencies and partners more detailed information about YouTube creators and their audiences, enhancing my media planning and creator selection process.
Gemini-powered creative recommendations: Soon, Gemini will offer creative optimization suggestions for Demand Gen campaigns, including tips on visuals and creative elements that could boost performance.
The bigger picture: As content created by influencers plays a growing role in purchasing decisions and brand discovery, advertisers like me are keen to spot trends early and gauge creator impact effectively.
Google is banking on AI to help marketers like myself uncover insights quickly and plan more efficient campaigns.
I’ve come across important news about Google Ads that could significantly impact how we manage our campaigns. Google is on the verge of altering its target-based bidding strategies, particularly for campaigns running on limited budgets.
Mark your calendar for August 17th when these changes will take full effect. But don’t worry, a Bid Target Adjustment Tool will be available as of July 6 to help us prepare and adjust our goals accordingly.
What’s going on? Google’s update aims to closely align target-based bidding strategies such as Target CPA with our set goals, even when budget constraints come into play.
They’re introducing a new tool that allows us to tweak our targets before the updates hit, which is crucial for maintaining our campaign performance.
Why should we care? If your campaigns are currently exceeding their target CPA or ROAS goals, they might not continue to do so post-update without adjustment. This update is meant to ensure budget-constrained campaigns stay true to their targets.
For example, if my campaign is achieving a $5 CPA against a $10 target, the performance might shift towards $10 unless I make some changes.
Thankfully, the new tool is there to help us proactively update our bidding goals before the changes roll out. If we don’t take advantage of this, we might end up paying more per conversion or see our performance realign with Google’s targets instead of our historical results.
Why is Google doing this? Google wants to reduce fluctuations and provide more predictable results when we tweak or adjust our budgets.
The tool is designed to help us synchronize our bidding targets more closely with actual business outcomes before the automatic implementation begins.
What should we do? It’s a good time for us to reevaluate campaigns using target-based strategies and verify if our current targets still align with desired results.
Notifications will be sent through Google Ads accounts before the update, and the Bid Target Adjustment Tool can highlight which campaigns might be affected.
Key takeaway: For those of us with campaigns that consistently outperform their targets, maintaining current performance might require tweaking target settings instead of leaving them unchanged.
When it comes to PPC, some of the toughest lessons aren’t about bidding strategies or keywords. It’s about knowing when to walk away from a client. On a recent episode of PPC Live The Podcast, I, Laura Abreu, a performance marketing strategist, shared a pivotal experience from early in my career that taught me invaluable lessons.
My first client was launching an ecommerce store featuring beauty products from well-known brands. On paper, it looked promising, but deep down, something felt off. The products were available at the same price elsewhere, giving consumers little reason to choose our store. Despite this, I ignored my instincts and accepted the project.
Despite our team’s best efforts with search campaigns, Meta ads, seasonal offers, and product bundles, we didn’t manage a single sale over three months. The issue wasn’t with our marketing strategies—it was the lack of a unique value proposition in the business model itself.
I’ve learned that great marketing won’t fix a weak business proposition. Engaging with a new client now involves ensuring they’ve done market validation before investments in advertising.
This experience also revealed the importance of not letting personal preferences cloud judgement in marketing. We focused heavily on creating visually appealing content without realizing that resonating with customer needs and desires is what truly drives sales.
The emotional turmoil from this misstep was profound, affecting my confidence to the point where I took a break from PPC clients. I realized I was unfairly shouldering the blame for a structural business issue beyond my control.
Setting clear expectations from the start with every client has become another cornerstone of my practice. I ensure advertising is positioned as a way to test assumptions instead of promising immediate growth. This approach helps in maintaining honest conversations and prevents misunderstandings.
I’ve also decided never to mix business with personal relationships. Working with friends and family often involves emotional challenges that can interfere with objective decision-making.
Protecting one’s reputation is crucial, especially when campaigns don’t meet expectations. Honest dialogue, even if it means discussing failures or refunding fees, is necessary to build trust, which is invaluable in our referral-driven industry.
Through auditing various PPC accounts, I often encounter the mistake of treating campaigns as “set and forget.” It’s vital to constantly refresh ad copy, scale winning creatives, and streamline lead-generation processes for better conversion rates.
AI has become a significant asset in automating routine tasks, allowing more time for strategic thinking and client interactions. However, I advise marketers to maintain human oversight to avoid the pitfalls of poor-quality AI outputs.
In a significant move, Google Ads has launched a beta feature that allows advertisers like me to connect additional data sources directly to website conversion actions. This innovative step gives us a chance to enhance tag-based measurements using our backend conversion data.
The new feature equips advertisers to merge conversion signals gathered through Google tags with transactional data from various platforms, such as CRMs, order databases, and e-commerce systems.
What’s new. Now, I can append an additional data source to an existing website conversion action via Google Ads Data Manager or through the Data Manager API.
Designed to enhance—not replace—website tagging, this beta allows us to send conversion data from backend systems into the same conversion action utilized for campaign measurement and optimization.
Why we care. This beta is crucial for filling conversion measurement gaps by fusing Google tag data with our first-party data from backend structures like CRMs. It helps us capture conversions that might be overlooked due to browser limits, privacy settings, or ad blockers, providing a fuller view of campaign performance.
Why Google launched it. Google indicates that combining tag-based measurement with backend conversion data allows advertisers to construct a more comprehensive picture of conversions, subsequently boosting campaign performance.
Here’s what this feature helps achieve:
Recover conversions that may escape website tags.
Enhance measurement resilience.
Deliver more exhaustive data for automated bidding.
Simplify data integration through the Data Manager.
How it works. The system combines website conversion data captured by Google tags with conversion records uploaded from an advertiser’s backend systems.
To avoid duplicate reporting, Google utilizes transaction IDs to identify and de-duplicate conversions between the tag and the supplementary data source within the same conversion action.
What advertisers need to know. The beta is currently restricted to website conversion actions that implement Google tags or Google Tag Manager.
It’s not available for:
Google Analytics imported conversions.
URL-based conversion actions.
Google advises attaching an additional data source to an existing conversion action rather than initiating a new one to eschew potential double-counting across campaign goals.
Data requirements. Each upload must encompass:
Transaction ID.
Conversion date and time.
Advertisers need to supply at least one attribution identifier, like hashed customer data or a Google click identifier.
Google suggests that I upload conversion data as swiftly as possible and ensure the conversion values match the currency format utilized by website tags.
Bottom line. This beta signifies Google’s ongoing effort to bolster conversion measurement by integrating backend transaction data directly into Google Ads. As we seek more comprehensive performance insights, this feature provides a streamlined means to enhance website measurement using first-party business data.
