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 got some exciting news for those of us tracking changes in the digital advertising space. Apple’s expanding ad opportunities within the App Store search results, offering advertisers new chances to connect with users right at the moment they’re ready to download apps.
Starting March 3rd, there will be more ad slots in the UK, and following closely, Japan will see these changes too. By the end of March, this rollout is expected to reach all Apple Ads markets.
Why is this important? With more ad slots in the App Store, we have more chances to capture installs. But, this also means heightened competition for those high-intent queries, which could drive costs upward. Since we can’t pick our ad placements, ensuring creative relevance, refining keyword strategies, and monitoring conversion tracking have never been more crucial.
What’s changing? Previously, there was just a single sponsored ad spot at the top of the search results. Now, multiple ads can show up for a search query, not only in the top spot but also further down the page.
Devices running iOS and iPadOS 26.2 or later will support these additional placements.
How eligibility works: There’s no need for us advertisers to tweak anything to tap into the new ad slots. Our existing search results campaigns are automatically eligible for these new positions.
While we can’t choose our placement or bid for a specific spot, Apple determines where our ads appear within search results.
Ad formats and pricing remain constant. Ads look the same, relying either on a standard product page or a custom one. If we want, we can even direct users to specific in-app destinations via optional deep links.
Billing remains unchanged, continuing on a cost-per-tap or cost-per-install basis.
Matching ads to searches: Ads in search results still hinge on keywords—those we choose or those suggested by Apple. According to Apple, their relevance-based matching achieves an average conversion rate exceeding 60% for top-of-search ads.
Placement is a mix of relevance and bid, but relevance remains non-negotiable. Even a high bid won’t allow an ad into auctions if it’s not a strong match for the user’s query.
What should we keep an eye on? More ad slots could lead to greater opportunities, albeit with increased competition on the same search results page. It’s prudent to keep a close eye on performance metrics, query alignment, and conversion rates as the global rollout of this feature proceeds.
Looking ahead: As March progresses, more App Store search ads will be seen in all Apple Ads markets. For those of us in app marketing, this shift represents a significant transformation in how search visibility and competition will play out within the App Store.
I’ve recently experienced a glitch in Google Ads that’s been quite the headache. It has unexpectedly removed the option for adding notes in some accounts, making change tracking and documentation far more challenging. I know how important these notes are for keeping track of optimizations and performance shifts.
This issue was initially brought to my attention by Odi Caspi, a fellow paid search consultant. Over the past couple of weeks, the problem has surfaced sporadically, causing quite a bit of disruption. Let me share what advertisers are meant to see in their dashboard:
I find it incredibly essential to understand why we care about this issue. Account notes are an invaluable tool for agencies and in-house teams to trace changes over time. When we lose the ease of access to these notes, troubleshooting performance fluctuations becomes tougher, and our collective memory weakens.
In accounts affected by this bug, the “Add note” option simply vanishes from the popup where I usually annotate changes. It’s an intermittent issue, with the functionality sometimes working perfectly and disappearing at other times.
As for workarounds, Caspi mentions that clicking on an existing note could reveal the option to add a new one. However, this method works only if there’s already a note available within the current date range we’re examining.
Another workaround I came across, suggested by Paid Media Specialist Dids Reeve, involves opening the Notes panel from the “More” menu. It seems this option still allows for adding notes in some cases.
Looking forward, it’s frustrating not knowing when Google might officially recognize or address this bug. Until it’s resolved, I’ll need to be more vigilant about documenting significant changes using alternate methods.
The first reported instance of this glitch came from Caspi himself, who shared insights from his campaign reports on LinkedIn.
I’ve always been fascinated by how companies navigate complex regulatory landscapes. Recently, TikTok made headlines with the launch of a new U.S.-controlled joint venture, a decisive move aimed at aligning with American national security rules.
To ensure that TikTok can continue serving its vast user base of over 200 million Americans, the company established TikTok USDS Joint Venture LLC. This step was officially taken following an executive order from President Trump on September 25, 2025.
The big picture. This joint venture stands out because it’s primarily owned by American interests, functioning independently concerning U.S. user data, content moderation, and algorithm security. While ByteDance maintains a 19.9% stake, this remains under the level that’s often scrutinized for national security.
This initiative leverages TikTok’s already established U.S. Data Security (USDS) program, aiming to protect sensitive information from foreign interference.
Why it matters to me. As someone who appreciates the dynamic between technology and regulation, this joint venture is a significant test of whether TikTok can continue its operations in the U.S. without facing bans or demands to sell its U.S. assets. It effectively transfers control of key operational areas to American oversight, addressing long-standing security concerns.
For creators and advertisers like me who rely on TikTok, this development signifies a potential blueprint for future regulations of foreign tech by the U.S.
Understanding the safeguards. User data from the U.S. will be securely stored in Oracle’s cloud infrastructure in the U.S., with rigorous audits and third-party cybersecurity certifications to ensure adherence to federal and industry standards like NIST, ISO 27001, and CISA.
The content recommendation algorithm for U.S. users will also be adapted and tested using U.S. data within Oracle’s systems, ensuring robust security through continuous source code evaluations under software assurance protocols.
Trust, safety, and content moderation at the forefront. The joint venture now holds the decision-making power over trust, safety policies, and content moderation for U.S. users, further reducing foreign influence over crucial decisions.
Balancing global reach with U.S. control. While U.S.-based security and safety controls are tightened, TikTok’s global entities still handle interoperability and commercial activities like advertising and e-commerce, supporting worldwide visibility for American creators and businesses.
Governance and leadership. The joint venture is led by a seven-member board predominantly composed of Americans, including executives from Silver Lake, Oracle, Susquehanna International Group, and MGX. Adam Presser serves as CEO, with Will Farrell as Chief Security Officer, and Raul Fernandez, CEO of DXC Technology, chairs the board’s security committee.
Ownership details. Silver Lake, Oracle, and MGX are the cornerstone investors, each with a 15% stake. Other investors include entities linked to Michael Dell, General Atlantic, Dragoneer, and Xavier Niel. These safeguards also cover CapCut, Lemon8, and other TikTok-associated apps in the U.S.
What comes next. TikTok USDS Joint Venture positions itself as a definitive response to U.S. regulatory pressures. It remains to be seen whether it will fully placate lawmakers and security agencies, ultimately securing TikTok’s future in the U.S. as scrutiny begins.
Catch-up. A $14 billion arrangement keeps TikTok operational in the U.S.
A recent bug in Google Ads is causing frustration among advertisers, as it has started blocking any attempts to edit Performance Max (PMax) asset groups. I’ve personally encountered error messages when trying to update asset groups, making it impossible to save any changes directly in the platform.
Why This Matters to Us. As an advertiser, the freshness and adaptability of our assets are crucial for campaign success. Without the ability to update asset groups, there’s a risk of my campaigns running with outdated content, potentially harming their performance and efficiency.
What I’m Experiencing. Like others, I’ve faced an error message stating, “An error occurred. Please try again later. Value is required,” each time I’ve tried editing any asset group details. This error shows up in the Google Ads UI, stopping me from saving any changes even if all required fields appear to be filled.
Google’s Response. Google acknowledges this issue and is looking into it. However, they haven’t provided a timeline for a fix or any further guidance through their official channels yet.
Temporary Workaround. For now, I’ve found that using the Google Ads Editor allows me to make necessary changes and upload them directly. While this method works, it introduces additional steps that disrupt my usual workflow of managing PMAX via the web interface.
Next Steps for Advertisers. If you’re running Performance Max campaigns like I am, it’s essential to revisit recent changes to ensure they’ve been saved correctly. In the meantime, directing any necessary updates through Ads Editor may be a wise choice until Google resolves the issue.
Looking Ahead. Until Google addresses this glitch, a new level of uncertainty might accompany managing Performance Max campaigns. It’s important for us to double-check our versions and explore alternative workflows.
First to Report. PPC professional Chelsea Harding initially flagged this issue and shared her experience about the error message on LinkedIn.
I’ve watched automation quietly transform PPC management over the years with rules, scripts, and API-driven workflows in Google Ads.
Like many other marketers, I’m already very comfortable with automated bidding, data-driven optimization, and a suite of other AI-powered enhancements. But there’s a new shift on the horizon that’s set to redefine how we manage and optimize PPC campaigns.
This time, I’m talking about AI agents and vibe coding. These innovations are ushering in a more autonomous mode of working where AI takes the lead in execution, allowing marketers like me to focus on strategy and creativity.
This evolution promises unprecedented efficiency and flexibility, redefining effective PPC management.
Agentic AI: Google Ads’ Game-Changing Feature
In November 2025, Google rolled out its Agentic Ads Advisor, powered by advanced Gemini models. This tool helps advertisers like me uncover insights and boost campaign performance effortlessly.
Google positions Ads Advisor as an AI partner that enhances campaign management by understanding business contexts, simplifying tasks, and learning from interactions to deliver better outcomes.
However, the pressing question remains: What functionalities should an agentic AI tool embody?
It should function as an autonomous agent, surfacing information as needed but also operating independently. It should identify opportunities for enhancing campaign setups, assets, ad copy, and more.
An ideal agentic AI wouldn’t just make recommendations but also implement essential changes on its own.
Integrating Agentic AI in PPC Workflows
Agentic AI should ideally make decisions autonomously without needing constant human input, thereby managing, adjusting, and optimizing campaigns as they run.
Beyond just advice or reporting, its real value lies in managing bidding, ad placements, and creative testing in real-time, based on live data, seasonality, and user behavior trends.
With agentic AI handling more operational tasks, I can direct my efforts toward strategic decision-making.
The competitive edge will increasingly rely on strategy rather than tools, focusing on marketing fundamentals like positioning, value propositions, and brand awareness.
Agentic AI appeals to experienced PPC marketers like myself because it scales campaigns without compromising strategic control, proving to be a true game-changer.
With real-time optimization, data-driven creativity, and reduced human error, it redefines my role by allowing more time for strategy rather than execution.
Despite its capabilities, informed oversight is essential to ensure alignment with broader marketing objectives, highlighting the need for ongoing professional engagement.
Agentic AI isn’t replacing PPC professionals. Instead, it extends our capabilities, reduces manual effort, and facilitates better outcomes with minimal friction.
Vibe Coding: Creating Your Marketing Toolbox
In tandem with agentic AI, vibe coding is redefining how I work with AI-powered platforms, allowing me to create personalized, intuitive marketing tools and campaigns.
Tools like Cursor and AI Studio have enabled me to articulate and realize specific needs seamlessly, even without being a developer.
Incorporating vibe coding led me to build an SEO schema markup generator, an SEO audit tool, and a marketing idea generator, proving its practical value in my professional life.
The possibilities expand when combining vibe coding with agentic AI, empowering marketers to engineer their AI agents tailored for PPC work.
With this combination, I integrated these tools effectively within my marketing workflows, enhancing performance and strategy development at scale.
The Future: Navigating PPC with Agentic AI and Vibe Coding
Agentic AI and vibe coding present immense opportunities to streamline PPC operations, enhance performance, and maintain competitiveness in a fast-evolving landscape.
The future is about leveraging these technologies for more autonomous, data-driven, and personalized marketing strategies that benefit both internal teams and customers alike.
As a PPC professional, it is crucial to embrace these advancements, ensuring adaptability and continued relevance in an AI-powered future.
Follow experts like Alfred Simon, Mike Rhodes, and Ales Sturala to see practical applications of these innovative technologies in real-world scenarios.
Recently, I’ve been following a concerning development involving Google, where the tech giant is urging a federal judge to halt the Department of Justice’s antitrust remedies. The primary concern? Forced ad syndication could lay bare Google’s proprietary technology and negatively affect advertisers.
In an affidavit filed on January 16 by Google’s director of product management, Jesse Adkins, the company stresses how these measures could lead to irreversible damage. The crux of the argument is about maintaining control over proprietary ad technology, which could be jeopardized if exposed.
The big picture. In Adkins’ testimony, the likely fallout includes forced exposure of confidential technology, detrimental effects on advertisers, and a loss of authority over query and pricing data.
Mehta’s final ruling could compel Google to share its search results, features, and ads with any qualified competitor for the next half-decade under the current terms.
Google contends that employing these remedies before the conclusion of their appeal would result in immediate and unchangeable damage.
Risk to Google’s ad technology. At the center of Google’s warning is the potential exposure of its search ad auctions, developed over many years by an enormous team of engineers.
Syndication on a large scale might allow competitors or outsiders to decipher Google’s ad targeting techniques, relevance factors, and auction mechanisms, according to Adkins.
Competitors could potentially use this data to enhance their ad systems, stripping Google of its competitive edge.
Sub-syndication amplifies risk. The judgment permits competitors to further share Google ads with third parties, creating multiple layers of vulnerability to scraping and misuse.
Even the most compliant partners might lack the motivation to monitor downstream entities, effectively transforming Google’s ad system into a near-open utility with limited protection.
Advertisers could face fraud. Adkins mentions advertisers are caught in this struggle, citing tactics like “trick-to-click” that incite accidental clicks or artificially inflate expenses.
One example involves a syndicator adding names of wealthier countries to queries while diverting low-cost international traffic to ads, resulting in tens of millions in click fraud within a couple of months.
As a result, users might see less relevant ads, yet advertisers would still be charged, leading to diminished conversion rates.
Pricing uncertainty. Google is also expected to offer syndication terms no less favorable than existing agreements, which are highly customized to each partner’s traffic quality and technical setup.
Imposing these terms universally could lead to suboptimal pricing and financial uncertainty linked to unpredictable query volumes.
Irreversibility is key. Throughout the affidavit, Adkins underscores the irreparable nature of the potential harm. Once proprietary ad insights are revealed, they can’t be recaptured.
Once advertisers lose confidence, it is nearly impossible to win back. Moreover, once competitors craft products based on Google’s systems, the market’s impact becomes permanent.
Google suggests that even if their appeal succeeds, it could be too late to undo the ensuing damage.
Why we care. Any court-mandated ad syndication could potentially dilute Google’s control over ad placement and targeting, resulting in irrelevant advertising and reduced conversion rates. Essentially, this affidavit highlights the risk of higher costs, lower returns on investment, and less predictable campaign performance.
What’s next. The court is set to decide whether to temporarily halt the syndication remedies while Google’s appeal is pending. Without this stay, Google might have to start licensing search ads and results to qualifying competitors under new regulations, reshaping the search advertising landscape in unexpected ways.
Dig deeper. For further reading, I recommend checking out the following resources:
I’m excited to share that Google’s Demand Gen updates are making video ads even more shoppable and measurable across platforms like YouTube and Google. With these enhancements, I can now explore new ways to engage with audiences and increase conversions.
Google is pushing more Demand Gen features into mainstream use, particularly boosting shoppable and travel ads. It’s clear to me that Google is committed to creating a comprehensive performance channel, merging discovery, video, and commerce on both YouTube and Google surfaces.
What’s new:
Shoppable CTV is now available through Demand Gen, giving viewers the option to browse and purchase products directly from YouTube ads on connected TVs. It’s a game-changer for anyone looking to enhance their advertising strategy.
Attributed Branded Searches provide advertisers, like me, with insights into how campaigns influence brand search activity on Google and YouTube. Activation requires a Google rep, and it’s a feature that promises to add tremendous value.
Travel Feeds let advertisers like me connect Hotel Center feeds to create dynamic video ads featuring real-time pricing, ratings, and availability.
By the numbers:
According to Google, Demand Gen campaigns featuring TV screens result in 7% more conversions at the same ROI. That’s a significant increase in performance for anyone leveraging these tools.
For example, LG Electronics reported a 24% higher conversion rate compared to paid social media, while reaching high-value customers at a 91% lower CPA.
Why we care. With these updates, Demand Gen becomes more competitive with paid social channels, offering actionable and measurable solutions. Shoppable CTV transforms TV impressions into direct sales opportunities, while attributed branded search proves Demand Gen’s effectiveness beyond a simple last-click model. Travel feeds, on the other hand, streamline the process from browsing to booking.
All these features offer advertisers like me the chance to drive incremental conversions, engage high-value audiences at a lower CPA, and better justify upper-funnel investments with clearer performance metrics — all within Google’s integrated ecosystem.
Between the lines. It’s evident that Google is positioning Demand Gen as a formidable alternative to paid social by utilizing premium video resources, first-party data, and enhanced measurement. This move is particularly strategic as advertisers seek scalable performance beyond traditional social media platforms.
Bottom line. With advancements like shoppable CTV, reinforced brand attribution, and travel-focused automation, Demand Gen is evolving into a versatile performance tool — a significant aspect of Google’s strategy to secure larger budgets higher up the advertising funnel.
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.
When Google introduced Demand Gen campaigns in 2023, I saw them as a promising way to boost engagement across platforms like YouTube, Discover, and Gmail.
Initially, they felt experimental, straddling the line between awareness and performance, but they’ve come a long way since.
Now, the creative flexibility and enhanced audience control make Demand Gen a go-to campaign type for my ecommerce clients.
This strategy allows me to scale revenue in a controlled manner, maintaining brand consistency while testing creative approaches to drive conversions.
I’ve found that Demand Gen delivers the best results when strategically paired with Performance Max and Search campaigns.
Advertising with Demand Gen is ideal if you crave more control.
One major drawback of Performance Max is its lack of transparency and manual control.
If precise targeting, placement, or creative control is essential, Demand Gen stands out as the better option.
Performance Max auto-generates ads from your uploads, relying on Google’s AI to mix and match for the best performance.
This makes it crucial to provide top-notch creative assets.
For example, a fitness brand might create separate asset groups for products like leggings, shorts, and vests.
While this helps target relevant audiences, the control isn’t exhaustive.
However, Demand Gen offers far superior flexibility.
It allows me to upload, preview, and tweak ad combinations before launch, adapting each creative to its unique placement.
For instance, I can customize YouTube ads for in-feed, in-stream, and Shorts placements.
This control is perfect for ecommerce brands focusing on creative precision, message testing, and maintaining a strong visual identity.
Using Demand Gen alongside Performance Max can be incredibly effective if you leverage their roles within the customer journey. They enhance each other rather than compete.
Demand Gen builds awareness and sparks interest by reaching higher-funnel audiences before they actively start product searching.
Conversely, Performance Max focuses on converting lower-funnel users who are primed to purchase.
For example, a fitness retailer might utilize Demand Gen for lifestyle videos and discovery ads promoting their latest activewear.
When a potential customer begins to research or exhibit purchase intent, Performance Max engages with tailored Shopping and Search ads to finalize the sale.
I’ve set up feed-only Performance Max campaigns, providing only a product feed within the asset group.
This restricts Performance Max activities to Shopping placements, focusing it sharply on direct conversions.
Meanwhile, Demand Gen operates across platforms like YouTube, Gmail, Discover, and Shorts, covering the upper and mid-funnel with more visual, creative content focused on awareness.
This configuration minimizes overlap between campaign types while ensuring user engagement throughout the funnel, from brand discovery to purchase.
For larger accounts with flexible budgets, this dual structure drives holistic performance and clearer attribution.
In contrast, smaller accounts seeking efficiency should prioritize mastering high-intent campaigns before layering in Demand Gen once the core conversions are stable.
The diverse campaign types now offer advertisers more flexibility than ever, yet it requires understanding Google’s restructuring of video and discovery products.
It streamlines Google’s visual placements into one campaign type, including YouTube in-stream, Shorts, in-feed, Gmail, and Discover.
This change is significant. VAC was successful for ecommerce, particularly for conversion-centric video. Its removal underscores Google’s encouragement to embrace Demand Gen.
The advantage is that Demand Gen provides stronger creative control and diverse testing options across YouTube placements.
If you previously ran VAC campaigns, they are now under Demand Gen. Ensure your top-performing assets and audiences have migrated correctly, then use the new controls to optimize performance.
Audience control is a significant benefit of Demand Gen, and it’s a reason why I consistently use it for ecommerce.
Demand Gen allows precise audience creation, letting me decide who sees the ads.
I can select placements, merge audience types, and allocate the budget strategically.
It’s the only Google Ads campaign type supporting lookalike audiences, valuable for brands focused on acquiring quality leads.
While Performance Max utilizes audience signals over fixed targeting, Demand Gen excels for control, testing, and segmentation strategies.
In mid-2025, Google rolled out an open beta for advertisers to opt out of specific Demand Gen channels manually.
This means I can now control ad display, excluding Discover or YouTube Shorts if they don’t align with my objectives or creative format.
This small but significant update offers more control, a feature often lacking in many of Google’s automated campaign types.
In early 2025, Google introduced product feed integration for Demand Gen campaigns. This change allows me to link the Google Merchant Center feed, incorporating live product data directly into visual ads.
This development bridges performance and branding for ecommerce, enabling storytelling through creative visuals while displaying actual products.
For instance, a fashion retailer can showcase a new collection in a video advert while featuring shoppable product cards below.
This update positions Demand Gen as a hybrid between Shopping and Display, a much-anticipated capability among ecommerce advertisers.
Demand Gen typically demands a larger budget than other campaign types.
Google recommends starting at about £100 per day per campaign or 20 times your target CPA/tROAS, whichever is higher.
Practically, the £100-per-day baseline is a viable starting point for effective data collection and optimization. Lower budgets restrict data flow and slow progress.
Demand Gen complements your broader Google Ads strategy, rather than replacing Search or Performance Max.
It’s a premium, visually led campaign type that boosts awareness leading to conversions, particularly effective when you have accurate measurement, a clean product feed, and clearly defined audiences.
The table compares Demand Gen and Performance Max on key aspects that matter to advertisers.
