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.
Entering into the world of PPC advertising for 2026, I realize how easily we can be misled by trends. AI, creative scaling, and marketing models promised us efficiency, but often ended up costing more than delivering. So how can we reset our PPC priorities as we step into the new year?
In 2025, PPC advice revolved heavily around AI and glittering new tools, sounding both promising and expensive. We found ourselves succumbing to platform narratives rather than aligning with business needs, causing budgets to balloon without corresponding efficiency gains.
As 2026 dawns, it’s high time to break free from these outdated beliefs. This article highlights three PPC myths that looked appealing in theory and quickly spread in 2025 but often led to poor decisions.
My objective is straightforward: rethink priorities and avoid repeating costly mistakes.
Myth 1: AI Outshines Manual Targeting
We’ve been told countless times to trust AI for targeting while manual structures are deemed obsolete. But is that truly the case?
The truth depends on conditions. AI thrives on volume and quality signals. Without these, the AI delivers no meaningful results, just automated processes that mask poor performance.
For instance, ecommerce brands often find value in feeding purchase data back into Google Ads, assuming they generate enough conversions. Only then does outsourcing targeting to AI hold potential.
If your campaigns struggle with low conversions or rely primarily on lead optimization, manual intervention may still be necessary.
How to Reset Priorities
Before turning everything over to AI, there are critical questions to ask:
Are campaigns optimized against a business-level KPI like CAC or ROAS?
Do the ad platforms receive sufficient conversion data?
Are conversions reported promptly, with minimal delay?
If any answer is no, consider revisiting PPC fundamentals for 2026. Do not hesitate to apply traditional methods when needed. In 2025, I turned around a client’s fortunes by using match-type mirroring structures, even though it contradicted the common best practices.
The success was based on historical performance data:
Match Type
Cost per Lead
Customer Acquisition Cost
Search Impression Share
Exact
€35
€450
24%
Phrase
€34
€1,485
17%
Broad
€33
€2,116
18%
Here, Google Ads did exactly what it was told—focus on lower cost per lead, disregarding business impact like KPIs.
I regained control by focusing on high-performing audiences with unsaturated potential, via exact match keywords. If you’re unfamiliar with traditional structures, advanced semantic techniques can offer an excellent starting point without over-reliance on automation.
Myth 2: More Ads Lead to Better Results
This myth frustrates me as it sounds logical but rarely pans out. The argument is simple: more creative variation equates to better ad auction performance. But more often, it increases creative costs without the promised results, helping agencies more than advertisers.
Creative volume adds value only when backed by high-quality conversions. Without them, extra ads only mean more materials rotating meaninglessly.
How to Correct Course
True value still lies in creative diversification that matches messages to audiences and contexts. This isn’t a novel concept. The same principles apply:
Have a strategic approach to creative testing; testing without intent is wasteful.
Plan measurement in advance to avoid setting yourself up for failure.
Ensure business-level KPIs are present in enough volume to make a difference.
When resources are tight, rotating ads without direction is common. Focus on Conversion Rate Optimization (CRO) instead:
Enhance tracking for better performance.
Refine customer journeys to boost conversion rates and signal volume.
Align higher-margin products with more efficient spending.
Explore new networks or channels with saved creative budget.
Myth 3: MMM Will Offer Clear Clarity
Finding 10 marketers who believe GA4 is effective is challenging, indicating Google’s missteps. The misalignment with ad platform data breeds mistrust, leading to the belief that advanced solutions are needed. Yet, this often results in higher costs with average outcomes.
Most brands don’t have the scale required for Marketing Mix Modeling (MMM) to yield insightful results. Instead, it’s best to master existing tools.
The usual brand setup looks like this:
Concentrated media spend across a handful of channels, mainly Google and Meta, with YouTube, LinkedIn, or TikTok as extras.
Reliance on a narrow but consistent customer base, risking long-term stability.
Marginal marketing impact beyond the core audience.
In such settings, MMM adds abstraction, not clarity. Staying grounded in fundamentals remains vital, not modeling complexities.
Strategies to Add Value Instead
Before considering advanced tools, ensure you’re getting the basics right:
Stand out clearly from competitors.
Boost margins, even with simple budget plans.
Build a strong data foundation, emphasizing tracking, CRO, and conversion paths.
Expand your channel or network options.
Align creative execution with genuine customer pain points.
Smooth out any marketing execution kinks.
While advanced tools gain importance with complexity, deploying them too soon obscures accountability rather than offering real insights.
The True Issue Lies in Misuse
The thread linking these PPC myths isn’t the capabilities like AI, creativity, or analytics—it’s how they’re misused. Platforms fulfill the roles they are set for, optimizing within the provided signals and limitations.
Business fundamentals are what break in these scenarios, rather than AI fixing our problems.
Instead of pursuing the next shiny distraction, 2026 should be about focusing on core business strategies and executing with precision for profitable scaling.
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.
In my conversation with Joshua Weisberg, CEO of Lambda Finance, we explored how AI is reshaping financial research. As discovery evolves from traditional search to AI-powered insights, platforms must earn trust in an era demanding clarity, accessibility, and centralization.
First Page Sage: Financial research carries significant risks where misinformation can have severe outcomes. Joshua, why do finance sectors experience shifts in search behavior and AI-driven discovery sooner than others?
Joshua Weisberg: In finance, the repercussions of poor information are swift and quantifiable. If research lacks depth or accuracy, the impact is immediately observed in performance. This urgency pushes investors to adapt their research methods faster than other industries.
As AI shapes discovery, investors scrutinize information sources and presentation more acutely. They prefer sources demonstrating depth, consistency, and reasoning, pushing financial platforms to evolve quickly. This also provides a blueprint for trust-centric industries’ behavior.
First Page Sage: With AI underpinning research, the focus shifts from keyword matching to perceived expertise and trust. How does this affect financial platforms’ approach to visibility and authority?
Weisberg: It redefines the objective. Visibility now relies on being consistently useful rather than merely optimized for keywords.
In finance, expertise emerges from effectively linking concepts and illustrating relationships. AI favors sources that provide comprehensive answers. Platforms should focus on delivering a holistic experience that conveys thorough understanding of the topic.
First Page Sage:: Fragmented user experiences can weaken authority from an SEO/GEO perspective. Lambda Finance unifies several research functionalities. Why is this vital in an AI-driven discovery realm?
Weisberg: Fragmentation causes friction for users and affects perceived expertise. When multiple tools are needed for answers, building confidence is challenging.
Unifying insights allows them to exist contextually. Connecting technical signals, fundamentals, alternative data, and portfolio analyses enhances user comprehension and signals authoritative understanding to the users.
First Page Sage: In finance, ambiguity is costly. How does effectively explaining complex data grow user trust and digital visibility?
Weisberg: Clarity is surprisingly advantageous in financial research. Even seasoned investors benefit from understanding why something is significant, not just the event itself.
By prioritizing explanation, platforms engage users deeply, leading to sustained reliance. Over time, this trust enhances digital visibility. Platforms excelling at detailing complexities often become references for both users and AI systems seeking comprehensive answers.
First Page Sage:: What error do digital leaders in finance commonly make preparing for AI-driven search? And what should they emphasize instead?
Weisberg: A common mistake is seeing AI-driven search as merely a technical challenge. While optimization is important, it doesn’t replace substantive content, especially in complex sectors like finance.
Long-term visibility relies on depth—accurate data, insightful analysis, and clear communication. Companies focusing on these fundamentals are well-equipped as search evolves, aligning with user preferences. Authority in high-stakes industries is earned through consistent utility.
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 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.
Have you ever imagined a marketing approach where the emphasis is on outcomes rather than just the tools? Let me introduce you to Genmark Flow, a groundbreaking concept in AI marketing that is more than just software; it’s a comprehensive service.
Genmark Flow is an AI Service as Software solution that delivers results through expertly managed growth strategies. This revolutionary system prioritizes delivering tangible results over merely providing tools. AI-powered and expertly managed, it ensures your marketing goals are not just met, but exceeded.
With Genmark Flow, you’re not only accessing cutting-edge technology, but you’re also leveraging a service that supports you in achieving your growth ambitions. Get ready to transform your marketing strategies and witness significant outcomes.
Despite my initial thoughts on leveraging bite-sized content for LLM and AI search mentions, Google has made it clear that this approach is not sustainable in the long run.
Recently, Danny Sullivan, who once served as Google’s Search Liaison, advised against breaking down content into small chunks to cater to AI systems. Comments from Google’s engineers confirmed his stance, emphasizing, “we don’t want you to do that” for LLMs.
More insights. In the latest Search Off the Record podcast, Danny spoke about the misconceptions and guidance surrounding LLM optimization.
“One common piece of advice is to turn your content into bite-sized chunks because LLMs prefer that format,” Danny observed, but immediately warned against adopting this method.
He reiterated, “We really don’t want you to think you need to craft content specifically for search. We maintain that position and discourage creating dual versions of your content – one for LLMs and another for general audiences.”
What about scenarios where it seems effective? Danny acknowledged, “In some edge cases, or perhaps more, you might notice certain advantages.”
However, he stressed that any gains would be short-lived. As Google’s ranking systems evolve, they will shift towards rewarding content authentically written for humans, rendering bite-sized content strategies obsolete.
Danny explained, “Systems improve by prioritizing human-centric content. Past tactics designed to exploit LLM systems might not hold up over time.”
The advice I took away was akin to the strategy of “Skating to where the puck is going, not where it has been.”
The podcast. Check out the 18-minute mark of the podcast for in-depth details.
Why this matters. Sure, even this platform has praised content chunking in the past, but SEO has consistently evolved towards delivering what users genuinely want. Creating a loyal audience independent of Google and LLMs is crucial. While there might be short-term wins, sacrificing user trust isn’t worth it.
Ultimately, as an SEO, continuous testing is necessary. Yet, today’s effective strategies might fail tomorrow.
Hey there! Navigating the ever-evolving landscape of Google Ads can be quite the adventure. I’ve gathered some important insights to help us optimize our PPC campaigns by addressing common pitfalls like inconsistent tracking, outdated negative keywords, and an over-reliance on AI.
Google Ads is in a constant state of evolution. This means new challenges and mistakes often pop up as we optimize and manage our PPC campaigns. Let me share some insights on the most prevalent Google Ads mistakes in 2026, so we can dodge them effectively this year.
Optimization decisions hinge on conversion data. If our conversion tracking is inconsistent, it skews the entire account’s data, making it difficult to draw accurate insights.
Converting varying attribution methods, count types, and conversion windows means data is applied unevenly across our account, complicating any assessment of click value.
Occasionally, we might override tracking settings at the campaign level, achieving accuracy there but inconsistent data at the account level. Ensuring consistent application of conversion data is something I prioritize in my management tasks.
I’ve noticed many people losing sight of ‘exact match’ keywords as Google encourages broad match by making it the default setting in their interface. Yet, exact match is invaluable, consistently proving to be the highest-converting match type for many of us.
When campaigns vary widely in excluded regions, ad schedules, and bid strategies, it’s crucial to re-evaluate our settings. Consistency in campaign settings is vital to keeping everything running smoothly.
Ad strength directly affects how much control Google has over our ad content. Lower ad strength means more control for us, which I’ve found leads to higher conversion rates despite common misconceptions about its impact on quality scores.
The flexibility of match types has loosened in recent years, leading to search terms triggering multiple keywords. This duplication, without exact matches, can cause inconsistent messaging. I always make sure our keyword list includes top-performing search terms.
Broad match keywords can lead to different results based on our bidding strategies. I learned the importance of matching bid strategies with the right keyword types. After all, different goals require different approaches.
Blinded by our auto-pilot tendencies, we might use outdated negative keyword lists without review, which leads to keyword blocking and lost opportunities. It’s essential to review these regularly to prevent conflicts.
Having auto-apply turned on in Google Ads can lead to unexpected changes like added keywords or modified bid strategies. Turning it off gives me the power to make well-thought-out decisions instead.
Finally, while AI offers tremendous capabilities, believing it’s wiser than us can be a major pitfall. I always remember that it’s best used as a tool that complements our judgment and expertise in ensuring successful campaigns.
