I’ve discovered a game-changer in how I interact with my Google ecosystem. With the beta release of Google’s new ‘Personal Intelligence’ in the Gemini app, I can now get personalized responses that take my searches, emails, photos, and YouTube history into account. This is all part of Google’s push to integrate our online experiences into one cohesive tool.
Before, Gemini could retrieve data from various Google apps; now, with Gemini 3, it reasons with the data to provide insightful recommendations proactively. This progress feels like a leap into the future.
Check it out: Here’s a video showcasing how this integration works:
Availability: This feature is being rolled out to U.S. subscribers of Google AI Pro and AI Ultra, promising full availability within the week. Once enabled, it can be used across Web, Android, and iOS platforms, expanding soon to more countries and the free user tier.
This innovation is exclusively for personal Google accounts right now, excluding Workspace users. However, with rising demand, expansion seems inevitable.
Privacy, Control, and Personalization: I’m thrilled that Google prioritizes my privacy. These features are off by default, allowing me to decide when to connect my apps. When apps are connected, personalization does not blanket all responses.
I appreciate how I can manage personalization settings: connect some apps, keep others out, and handle past chats. There’s also an option to give feedback if the personalization doesn’t quite hit the mark.
Why It Matters: The integration into AI Mode in Google Search means personalized experiences could transform how visible we are on these platforms. Tracking AI-driven results might become tricky, but the potential benefits make it worth exploring.
I’m thrilled to share some exciting news for advertisers. Google has opened the door to Olympic live sports inventory, now accessible through biddable CTV buys, capturing massive reach with enhanced control and measurement.
Live sports advertising is revolutionizing how we connect with audiences—more programmatic and measurable than ever before.
Driving the news. I’m particularly excited about Google’s latest move: introducing new abilities to bid on live sports through Display & Video 360. This includes access to NBCUniversal’s Olympic Winter Games inventory, just in time for the bustling 2026 sports calendar.
Why it matters to us. Live sports consistently engage vast and attentive audiences, and now with Google’s enhancement, advertisers like us gain more control and precision without losing reach.
What’s new. We can now reach fans directly on the big screen by merging Google audience data with NBCUniversal’s live sports CTV inventory and engage them further across YouTube and Google’s platforms. Google introduces household-level frequency management, powered by AI, to avoid ad overexposure and link CTV impressions to purchases seamlessly.
Additionally, Google has revamped its Marketplace to make accessing and activating curated sports packages a quick and easy process, saving us time and hassle.
The big picture. As viewers move across connected TV, YouTube, and social feeds, we’re challenged to maintain their attention across multiple screens. Google’s Display & Video 360 is emerging as the essential hub to capture these moments, from our living rooms to our mobiles.
Have you heard the news? Google has just launched the Universal Commerce Protocol (UCP), an innovative open standard that integrates AI agents throughout the entire shopping experience. From discovering products to making purchases and even receiving support after the sale, UCP facilitates it all.
In exciting developments for retailers, Google is also rolling out new AI tools. These include branded shopping agents and ad formats that enhance AI-driven discovery, making the shopping experience more streamlined and engaging.
About UCP
This protocol offers a common language for AI agents and commerce systems, greatly simplifying the need for custom integrations across different platforms.
UCP is compatible with existing standards like Agent2Agent and the Model Context Protocol.
The protocol was co-developed with prominent partners such as Shopify, Etsy, Wayfair, and Target.
It’s already endorsed by over 20 additional companies in the retail and payments sectors.
What’s Changing
The UCP is set to enhance the checkout experience for Google product listings via AI Mode in Search and the Gemini app. Shoppers can make purchases through Google Pay, with options to use saved payment and shipping details. Integration with PayPal is also on the horizon.
Google aims to lower cart abandonment and provide retailers with tailored integration options suited to their needs.
Upcoming features include loyalty rewards and personalized shopping experiences.
Business Agent
In tandem with UCP, Google is unveiling the Business Agent, a branded AI assistant that provides shoppers with direct interaction opportunities on Search. Think of it as a virtual sales associate offering real-time responses in your brand’s own tone.
Major retailers like Lowe’s, Michael’s, Poshmark, and Reebok are already on board. Future capabilities may include deeper customization, data training, and a seamless agent-led checkout.
Direct Offer
Google is also testing Direct Offers, a fresh initiative within Google Ads tailored for AI adoption. When AI senses that a shopper is likely to make a purchase, a special discount can be presented.
This pilot will soon expand to incorporate offers such as product bundles, complimentary shipping, and more enticing incentives.
Why It Matters
The rise of agent-led shopping reshapes where and how buying choices are made. Google’s new AI tools and protocols are taking the lead, allowing advertisers to influence these pivotal moments during an AI-driven shopping journey.
Tools like Direct Offers and branded agents create new pathways for advertisers to finalize sales efficiently, all while safeguarding profit margins. The balance between conversion improvements and losses in direct site traffic remains an open discussion.
Bottom Line
According to Google, agentic shopping is unstoppable. With innovations like UCP and its complementary retail tools, Google ensures that AI-driven commerce remains inclusive and accessible, keeping retailers engaged as agents transform the buying landscape.
I recently spoke with Anthony Higman, the CEO of AdSquire, on episode 336 of PPC Live The Podcast. Anthony’s remarkable journey took him from the mailroom of a law firm to the helm of his own company with a panoramic view of Philadelphia. His story exemplifies how dedication, learning from missteps, and perseverance can forge a successful career path.
Learning from Client Missteps
Anthony opened up about one of his early blunders with a client, where he allowed them to chase after quick-win promises in numerous emails. Though some were outright scams, others were genuine but unaligned with the client’s goals. His decision to let a client engage with an ineffective SEO agency resulted in subpar outcomes and a revolving door of agencies for the client.
The lesson learned was clear: building trust with clients is vital, but it’s equally important to provide them with strategic guidance. Striking a balance between educating them and respecting their autonomy is key.
A Career Lesson from ‘Cowboy Moves’
Recalling another early career incident at a large advertising agency managing car dealership accounts, Anthony described how he took independent action to correct widespread account mismanagement, considerably enhancing results. However, his proactive steps clashed with company norms, leading to his dismissal.
This taught him invaluable lessons: knowing one’s values and finding workplaces aligned with them is crucial. Moreover, balancing client success with company expectations is crucial. Today, at AdSquire, he emphasizes consistent account management and clear communication within his team.
Managing Client Expectations in a Complex Industry
Anthony highlighted the challenges of managing expectations in competitive industries like legal marketing. While clients often seek various services like SEO and social media, focusing on core strengths rather than spreading resources thin is essential for achieving the best results.
The Role of Mistakes in Growth
He believes that mistakes are fundamental to growth. At AdSquire, he encourages his team to learn from their errors without fear of losing their jobs, as long as they remain honest and aligned with the company’s vision. This approach cultivates a culture of learning, accountability, and innovation.
Common Mistakes in Modern Paid Search
With AI advancements in Google Ads, Anthony has noticed frequent mistakes such as improper search partner and location settings, automated assets misuse, and auto-apply recommendations. While AI can streamline processes, strategic oversight is essential to avoid undermining performance.
Key Takeaways from Anthony’s Stories
Anthony’s experiences offer two main insights:
Guide clients strategically, steering them away from scams while presenting genuine growth opportunities.
Understand your values and choose environments where your ethics and skills align. Never compromise on your principles.
His philosophy illustrates that mistakes can lead not to failure but to redemption, innovation, and enduring success.
Looking Ahead: AI and the Future of Google Ads
Anthony envisions continued AI integration in Google Ads by 2026. While some tools may falter or conflict with specific needs, maintaining strategic oversight and adding a personal touch will remain crucial. Misguided use of AI, such as automated video inventory creation, can yield inconsistent results and demands vigilant monitoring.
Conclusion: F-Ups Lead to Redemption
Reflecting on his career, Anthony draws parallels with The Shawshank Redemption. Every misstep contributed to future opportunities, eventually enabling him to establish AdSquire and earn recognition as a top PPC influencer. The overarching lesson: embrace your mistakes, learn from them, and let them serve as pathways to success.
I’ve noticed that Google is testing a new feature in their Performance Max campaigns that could really shake things up for us as advertisers. It seems they’re considering raising the limit on video assets from 5 to as many as 15 per Asset Group. This change could open up a whole new level of creative freedom without needing to fragment our campaigns.
Why does this matter to us? Well, video content is becoming crucial for the success of Performance Max. The current five-video limit forces us to make tough choices between different formats and ratios, which in turn restricts our reach across platforms like YouTube, Discover, and others. This new limit could lift those restrictions considerably.
With this potential update, we could include up to 15 videos per Asset Group. This means we can cover all major video ratios and formats without having to duplicate efforts or fragment campaigns. It’s an opportunity for richer, more versatile campaigns.
For those of us managing multiple video versions, this change could mean significantly streamlined campaign management. We could test more creative ideas without losing out on reach or complicating our campaign structures.
It’s still early days, with Google not yet making a formal announcement about this update. It could be in testing, or maybe it’s slowly being rolled out. Keep an eye on any new developments in this area.
This update first came to light when Growth Marketing Manager Molly Pritchard shared the new option on her LinkedIn profile. It sure caught my attention!
Bottom line? This may seem like a small tweak, but for those of us utilizing Performance Max, increasing the video cap could greatly enhance our creative strategies with minimal trade-offs.
I’ve recently learned that Google carefully analyzes user engagement to determine when to feature AI Overviews in search results. According to Google VP Robby Stein, these features are only shown if they truly add value for us, the users.
Stein shared in a CNN interview that Google’s approach to AI-driven results is evolving as they expand ads, personalization, and visual search options within their services.
Engagement drives AI Overviews. Google conducts tests with AI Overviews for different types of queries, retaining them only when we, the users, find them beneficial. If we don’t interact with these features, they are removed, and Google applies the insights to similar queries.
Stein explained, “The system will learn — so it’ll try it — and then see if people engage with it for certain kinds of questions… If it doesn’t work, it won’t show up again.”
Why it matters. As someone interested in SEO, I understand that appearing in AI Overviews is significant. However, it’s becoming clear that maintaining those spots hinges on user engagement. If we don’t interact with these overviews for certain queries, Google may choose not to display them, affecting AI visibility for different brands and publishers.
AI and personalization. While Google incorporates some personalization in AI search, Stein mentioned that these are smaller adjustments rather than extensive reshaping of results:
“For instance, if you’re someone who frequently clicks on videos, those results may appear higher for you. However, the adjustment is minor because we want the user experience to remain consistent.”
Ads and monetization in AI search. It’s interesting to note that Google is actively experimenting with ads within AI-powered search experiences, including AI Overviews and AI Mode.
Stein explained that ads will appear “when helpful,” in line with Google’s longstanding ad philosophy. He also noted that “the vast majority of Google searches do not have ads.” Key use cases for AI-driven ads include shopping, comparisons, and product research.
Furthermore, Stein emphasized transparency in distinguishing sponsored content as a priority.
Visual search growth. Visual search is apparently exploding in popularity, with usage up 70% year over year. Around 1 billion of us are now using visual search tools like Google Lens to find information visually, such as discovering products, matching outfits, and solving real-world queries.
Google has rolled out a new Beta feature that allows us, Performance Max advertisers, to A/B test asset sets. This expansion takes last year’s retail experiment to an exciting new level, now available for all campaigns.
With this update, I can compare two sets of assets while keeping the ‘common assets’ steady across both versions. By accessing the Experiments page under the Assets sub-menu, I can determine which creative combinations yield the best results.
I saw a similar experiment rolled out for retail campaigns last year, and I’m thrilled to see it expand to all Performance Max campaigns.
Why it matters to me. Performance Max campaigns rely heavily on automation, often making it difficult for me to test specific creative assets. This new capability gives us more control over asset-level performance without compromising the integrity of the entire campaign.
The big picture. From my perspective, tests must run for at least four weeks to consider the learning phase of P-Max and ad delivery stabilization. While the results aren’t immediate, they’ll allow me to make more informed choices about which images, headlines, and videos drive engagement.
Between the lines. Asset-level A/B testing could be a pivotal factor in enhancing my Performance Max ROI, particularly when managing diverse creative and asset formats.
First seen. This update caught my attention when web marketer Dario Zannoni highlighted it on LinkedIn.
The bottom line. Although still in Beta, this experiment type offers a new degree of transparency and control over automated campaigns, potentially transforming how I approach asset strategies in Performance Max.
I recently discovered that Google is enhancing Vehicle Ads with a click-to-call feature. This update gives potential car buyers a direct and seamless way to connect with dealers, turning search behavior into swift, live conversations.
Why does this matter? Vehicle Ads typically attract buyers who are already showing a strong intent to purchase. Removing obstacles with the new click-to-call feature meets shoppers at the precise moment they’re ready to engage with a dealership.
The big picture reveals a shift in automotive advertising towards instant human interaction. Buyers are more interested in real-time conversations rather than filling out additional forms. With call-enabled Vehicle Ads, connecting search to dialogue has never been easier.
In this evolving landscape, advertisers now bear a greater responsibility. Since the ad itself has become a conversion point, the quality of call handling, as well as staffing levels, can greatly affect performance. Dealers who prioritize phone interactions as a main conversion method will prevail, while those who do not may experience a decline.
Credit goes to Google Ads specialist Thomas Eccel for spotting this update first and sharing it on LinkedIn.
The bottom line is simple: Vehicle Ads have not only gained more visibility but have also come closer to facilitating actual sales.
Google just introduced a beta integration for the Google Tag Gateway, allowing advertisers, like myself, to deploy it effortlessly through the Google Cloud Platform (GCP). The process is now simplified with a new one-click workflow available in Google Tag Manager and Google tag settings.
What’s really exciting is how the GCP integration leverages Google Cloud’s Global External Application Load Balancer. This tool routes tag traffic through our own first-party domain before sending it off to Google, which enhances the deployment process. This strategic approach not only improves data signal quality but also boosts resilience against ad blockers and features like Apple’s Intelligent Tracking Prevention.
Why does this matter to us? As third-party tracking faces increasing limitations from browsers and platforms, advertisers like us need reliable ways to protect measurement signals. By directing Google tags through our infrastructure, we can maintain the integrity of our measurement signals against ad blockers and browser privacy constraints.
For those of us already using Google Cloud, this one-click setup significantly reduces the barriers to achieving more resilient and future-proof tracking.
What are others saying? Digital marketer and Simmer co-founder Simo Ahava highlighted this advancement on LinkedIn. According to him, the integration facilitates a seamless GCP deployment. It automatically configures an External Application Load Balancer with rules to direct Google Tag Gateway traffic to our backend services handling these requests.
Ahava also noted that Google Tag Gateway positions Google’s tagging infrastructure behind a same-site, same-origin first-party host, ensuring that tags endure in restrictive browser environments.
The broader perspective here is that previously, Cloudflare was the only automated option for deploying Google Tag Gateway, with other CDNs requiring manual setups. By adding GCP, Google reduces the friction for us advertisers already committed to their cloud ecosystem, thus promoting first-party tagging strategies.
The bottom line? Google is simplifying first-party tagging deployment, and while the GCP integration is still in its beta stage, it represents a significant stride toward robust measurement solutions in our increasingly privacy-focused digital landscape.
I’ve been closely following OpenAI’s journey as they pause ChatGPT ads to focus entirely on optimizing the user experience. It’s a daring decision, and I see it as a strategic move to challenge Google’s Gemini’s dominance in the AI landscape without distractions.
For years, as the forefront of AI innovation with ChatGPT, OpenAI seemed unbeatable, especially with their partnership with Microsoft. However, tables have turned, and the competition is heating up with Google’s Gemini gaining ground and even surpassing in vital areas.
When OpenAI CEO Sam Altman announced an internal “code red,” I realized this was a wake-up call to prioritize ChatGPT’s quality over everything else. This pause meant putting their advertising plans on hold, not forgoing them entirely.
It’s fascinating to me how OpenAI is handling this situation. The focus is on fixing fundamental issues related to speed, reliability, and reasoning to retain their user base. Despite the pause, advertisements are still part of the long-term strategy.
This leads me to wonder: what steps is OpenAI taking to catch up, and what does this delay mean for the future of AI advertising? Understanding these aspects is crucial for predicting OpenAI’s path forward.
Examining the performance shift, I see that OpenAI and Microsoft weren’t slowing down. Instead, Google’s investment in infrastructure paid off, exposing weaknesses in OpenAI’s alliance. The key lies in model architecture, as Google’s Gemini 3 is built as a “native multimodal” model, unlike ChatGPT’s combined approach, which feels less cohesive over time.
Google’s advantage of owning the technology that powers Gemini offers them unbeatable optimization and cost control. OpenAI faces challenges with their reliance on costly Nvidia GPU integrations.
This lack of an all-encompassing ecosystem is contributing to the shift in user sentiment towards Google. Users experience Gemini as a unified assistant embedded into their daily work routine, in contrast to the slightly disjointed feel of Microsoft’s Copilot.
I find it telling that Gemini now outperforms ChatGPT in benchmarks for reasoning and speed, highlighting the effectiveness of Google’s integrated machine approach over the Microsoft-OpenAI alliance.
Considering how ChatGPT and Gemini tackle the same problems differently, it’s intriguing to see Gemini’s practical approach compared to ChatGPT’s fact-providing nature. Gemini offers real-time solutions by integrating with Google Maps and Workspace, crafting an end-to-end experience that truly solves user problems.
The “code red” response from OpenAI highlights their understanding that without a solid foundation, introducing new features is futile. This realization is driving the development of GPT-5.2, aimed at closing the gap with Gemini in complex reasoning and coding.
OpenAI is focused on stopping hallucinations, improving speed, and making the interaction feel intuitive and personal again. They aim to move from a passive chatbot to a reliable executor of complex tasks, an area where Google currently leads.
For Microsoft, the challenge is to unify the Copilot experience, solving data silo issues. They need to leverage Office 365 data more effectively, akin to Google’s personalization using user data.
The pause on ad deployment serves as a significant indicator of OpenAI’s strategic priorities. Introducing paid ads amid current challenges would risk user loss, and OpenAI understands the necessity of retention before revenue.
OpenAI recognizes that to introduce advertising successfully in the future, the product must stabilize against Gemini’s advancements. When trust is restored, only then can monetization through ads be pursued.
The delay allows OpenAI to craft ad formats that are integrated and contextually relevant, ensuring they enhance rather than disrupt user experience. I believe that properly executed ads will become an essential revenue stream.
Overall, pausing ChatGPT ads reflects a necessary strategy to refine its core capabilities and challenge Google’s dominance effectively. In doing so, OpenAI hopes to reclaim its position and eventually introduce ads that align seamlessly with user expectations.
