When it comes to ensuring my images stand out in Google Search and Discover, I’ve learned that it’s all about using both schema.org markup and the og:image meta tag effectively. Google recently revised its image SEO best practices and Discover guide to clarify how they utilize these elements to select thumbnails.
“Google’s selection of an image preview is entirely automated, considering various sources to display a suitable image on Google, such as a text result image or a preview image in Discover.”
So, how can I influence the thumbnails Google selects?
I can specify the primaryImageOfPage property with a URL or ImageObject in schema.org. Alternatively, linking an image URL or ImageObject to the main entity using the mainEntity or mainEntityOfPage properties could be beneficial. Another option is to define the og:image meta tag.
Overall best practices include choosing an image that truly represents the page, avoiding generic images or those containing text, steering clear of extremes in aspect ratios, and opting for high-resolution images whenever possible.
Google Discover Image Selection – In the Discover documentation, I found some insightful tips:
“Incorporate engaging, high-quality images in your content, especially large images, as they are more likely to attract visits from Discover. Images should be at least 1200px wide, high resolution of at least 300K, and maintain a 16×9 aspect ratio.”
Google attempts to crop images automatically for Discover. If I choose to crop images myself, they should be well-positioned for landscape use, ensuring vital details remain in the cropped version specified in the og:image meta tag.
Also important is enabling the max-image-preview:large setting or using AMP. Utilizing schema.org markup or the og:image meta tag allows specifying a large, relevant image as thumbnails in Discover.
Why It Matters – Images significantly impact click-through rates from Google Search and Discover. By understanding and applying these guidelines, I can better guide Google in selecting the right image thumbnails to boost visibility.
I’ve got exciting news for certified online pharmacies in the U.S. Google has expanded its recurring billing policy, which now allows us to promote prescription drugs through subscription plans and bundled services.
The update means that certified merchants, like us, can now offer:
Prescription drug subscriptions — we’re talking recurring billing for prescription medications.
Prescription drug bundles — this allows us to combine drugs with other services, such as coaching or treatment programs, as long as the medication remains the primary product.
Prescription drug consultation services — recurring consultations to assess prescription eligibility, offered standalone or with medications.
Eligibility Requirements. To participate, we need to maintain our certified status, accurately submit subscription costs using the [subscription_cost] attribute in Merchant Center, and ensure our landing pages feature transparent terms and fees. We must also comply with existing Healthcare & Medicine policies. Accounts previously disapproved can ask for a review once they meet these requirements.
Why this Matters. This change presents new revenue possibilities for online pharmacies, as it allows us to harness the power of recurring billing models and bundled services while adhering to Google’s compliance standards.
The Bottom Line. Certified U.S. online pharmacies now have more flexibility to reach patients via recurring prescriptions and bundled offers, providing an opportunity to expand subscription-based services.
I came across an interesting update from Google, which released a new help page that explains its Universal Commerce Protocol (UCP). This guidance provides merchants with detailed directions on how checkout processes work across Google’s platforms, powered by AI-driven enhancements.
Why It Matters. Google’s documentation illuminates how UCP and its associated checkout feature enable a native “Buy” button, which takes the transaction straight onto Google’s surfaces while still letting merchants stay as the seller of record. To leverage this feature, merchants need to implement the native_commerce attribute in the Merchant Center.
Transactions flow through stored Google Wallet credentials, and payment processors are required to support Google Pay tokens. This seamless integration is designed to enhance the user experience.
The Value for Merchants. Initially part of Google’s push for agentic shopping, UCP was later confirmed as a live feature in Merchant Center, promising to streamline the path from product discovery to purchase. By embedding checkout directly on Google surfaces, it could potentially uplift conversion rates, particularly in AI-enhanced experiences like Gemini and AI Mode.
Additionally, the new documentation provides clarity on what’s needed for implementation, aiding merchants to adjust their feeds and payment systems to perfectly align with Google’s evolving commerce ecosystem driven by AI.
The Larger Context. By centralizing the checkout process while maintaining merchants’ positions as the sellers of record, Google is making it easier for shoppers navigating AI-powered commerce. This strategic move by Google also tightens its grip over the transaction layer.
Key Takeaway. With this fresh documentation, the concept of UCP transitions to an actionable playbook, marking a significant step for AI-driven, on-Google checkout as an integral element of Google’s commerce approach.
Initial Discovery. This helpful document first came to light thanks to Hana Kobzova, founder of PPC News Feed.
I recently discovered that Google has released a new guidance document for passkeys in Google Ads. This move couldn’t have come at a better time, considering how frequent account hacks have become.
Understanding how passkeys work within Google Ads is crucial, particularly with the uptick in phishing attempts targeting advertisers like us.
What’s Happening. According to the new help page, passkeys offer a password-free and phishing-resistant login method in Google Ads. Google outlines when these keys are essential, such as during user access changes and account linking updates.
The document guides us through the necessary device requirements, setup steps, and other security considerations to ensure we’re fully protected.
Why We Care. In today’s digital age, our ad accounts are prime targets for cyber attackers. These threats can lead to budget theft, disruptions in campaigns, and even data loss. Having clear guidance from Google is incredibly valuable, offering us a straightforward path to fortify our account security just when it’s needed the most.
The Bottom Line. With the increasing frequency of account takeovers, learning how to effectively use security tools like passkeys is a smart move. It’s all about securing our access and minimizing risks.
I’ve recently learned that ChatGPT has hit an extraordinary milestone: over 900 million active users every week. OpenAI proudly shared this achievement for the first time, and it’s nothing short of remarkable.
Why It’s Significant. Our online habits are evolving, extending beyond conventional search methods. With so many users turning to ChatGPT weekly, it’s clear that interactions and discoveries are shifting to AI platforms. However, as users, we often still seek reassurance from traditional search engines.
The Facts. OpenAI didn’t just stop at sharing user figures; they also unveiled a substantial $110 billion funding round. Additionally, they’ve gained over 50 million consumer subscribers and more than 9 million businesses are paying clients.
What This Means for Us. ChatGPT isn’t just a chat tool; it’s a competitive landscape where search, intent, and brand visibility meet. Understanding how our content appears in AI-driven results is crucial for boosting conversions, even if these interactions aren’t traditional searches.
OpenAI’s Announcement. For further insights, you can check out OpenAI’s official statement on Scaling AI for everyone.
Let me clarify—this is just a patent document, a flicker of a possibility, not an immediate change in Google Search.
A recently published patent from Google hints at a potential shift in how we experience search results. It suggests that instead of landing on a standard webpage, searchers might be directed to an AI-crafted page tailored to individual queries.
This patent outlines a system using AI to auto-generate personalized landing pages for businesses or organizations. Instead of simply redirecting me to a generic homepage, it aims to deliver a page that’s directly relevant to my search intent and the organization’s offerings.
Patent Abstract. Here’s an overview from the patent itself:
“Techniques for generating an artificial intelligence (AI)-generated page for a first organization. The system can include a machine-learned model configured to generate the AI-generated page. The system can receive from a user device associated with a user account, the user query. Additionally, the system can generate a search result page for the user query. The search result page can include a first result associated with a first landing page of the first organization. The system can calculate a landing page score for the first landing page. The system can generate an updated search result page based on the landing page score exceeding a threshold value, the updated search result page having a navigation link to an AI-generated page for the first organization. The system can cause a presentation, on a display of the user device, the updated search result page.”
Example Scenario. Picture this: I’m searching for “waterproof hiking boots for wide feet” on a site like REI or Amazon. Normally, I’d end up on a general “Hiking Boots” page and have to sift through countless options. But with AI, Google could direct me to a specially tailored page that zeroes in on exactly what I need.
Why It Matters. This is a mere patent and might never see the light of day. However, it’s intriguing to ponder Google’s potential direction and what it could mean for the future of search.
In any scenario, these insights offer a glimpse into the forward-thinking strategies within Google.
Discover how vibe coding empowers me to create custom PPC tools quickly using intuitive AI prompts instead of traditional coding techniques.
I now find myself able to generate custom PPC tools using plain English, thanks to GPT-5. It’s a game-changer, giving a competitive edge to those who embrace AI-assisted automation.
Frederick Vallaeys, who has built tools in mere minutes instead of months, is leading the way with AI. He has ten years of experience at Google creating invaluable tools like the Google Ads Editor and another decade at Optmyzr as CEO.
Vallaeys has witnessed the evolution of automation firsthand, and vibe coding is the next giant leap. At SMX Next 2025, he shared his personal journey with vibe coding.
If you’re involved in PPC, automation is crucially important. Initially, I relied heavily on Google Ads scripts because there was always more work than could be done in a day.
The problem arises when Vallaeys questions who truly writes their scripts. Only a few people raise their hands, as most often copy and paste due to lack of coding skills.
This results in limitations, confining you to what others have crafted instead of adding your personal flair.
GPT revolutionized scriptwriting for those without coding skills.
The best part lies in large language models being multimodal. Now, a simple photo of my campaign decision flowchart can be deciphered by AI to generate a complete Google Ads script.
Instead of viewing client meetings as additional work, I’ve embraced them as opportunities for prompt-engineering sessions.
Changing my mindset allowed me to treat these meetings as prompt instructions for AI, simplifying task execution.
Instead of delving into code, I merely describe my desired outcome, and AI takes care of the technical side. That’s vibe coding for you!
Imagine needing software to perform functions X, Y, and Z. Detail your needs to a coding tool, and watch as it constructs the software. Vallaeys describes this process as mind-blowing.
Scripts have become outdated; vibe coding is the way forward.
Vallaeys demonstrated the effectiveness of this method by requesting a persona scorer for an ad tailored to various audiences from Lovable. The result was rapid and precise.
Working collaboratively with it, akin to a human developer, you describe needed changes without ever touching code.
The automation framework traditionally targeted tasks ranging from frequent, quick activities to extensive, periodic ones. Vallaeys recommends not limiting automation to what’s already being done, but rather considering what you wish to do more often, making time-consuming tasks manageable.
The old method was slow, taking at least a month to launch anything.
I used to spend days compiling specifications, waiting for engineers to build, finding bugs, organizing meetings, and repeating the cycle.
Traditional code was deterministic, relying purely on if/then logic. While reliable, it struggles with nuanced actions, like identifying competitor terms. Encompassing every variation of competitor keywords was virtually impossible.
Sam Altman’s launch of GPT-5 heralded a new era of on-demand software generation, transitioning beyond software-as-a-service.
Tapping into this new approach takes just minutes, from writing a spec to letting AI build and refine it. Within an hour, you have a functional automation tool.
This code isn’t just deterministic; it’s also flexible. Large language models handle nuanced queries with impressive accuracy.
Vibe coding allows machines to create anything I can articulate clearly, from landing pages adhering to brand guidelines to unique audience tools.
This paradigm shift means even tasks taking 90 minutes by hand are candidates for automation, creating disposable software to save time today, unaffected by future failures.
Vibe coding enables building a range of online solutions — from landing pages to browser extensions — all through simple directives.
Begin with tools you may already use, such as Claude or ChatGPT, for data analysis or visualization tasks.
For more complex applications with databases or user logins, tools like Lovable, V0.dev, Replit, or Bolt simplify the process.
If you have technical skills, Codex, Bolt.new, or Cursor offer robust capabilities, but simpler tools are often sufficient.
I challenged someone in my team with no coding background to create a seasonality analysis tool using Claude.
The process involved gathering materials, crafting a prompt, and testing via a browser without requiring installation.
The team quickly iterated, enhancing features. The AI efficiently added helpful guidance and streamlined interfaces, leveraging its extensive training.
I envisioned a tool sequence for expert review of blog posts, synthesizing feedback through a consolidated summary. This was easily vibe-coded in V0.dev.
A Chrome extension for demos needing to blur sensitive numbers was swiftly constructed via simple prompts, addressing specific visibility needs.
Effective prompting involves specifying the exact use case, allowing AI to generate relevant options and suggest innovative methods.
Engage with questions to uncover insights such as process approaches or data storage solutions, furthering learning opportunities.
Utilizing chat mode for alternative exploration is advantageous, allowing detailed direction without altering code initially.
You can experiment with my team’s audience analyzer, adapting it with ease to suit specific needs like logo integration or functional adjustments.
It’s clear from Vallaeys: the competition isn’t against AI but against individuals harnessing its capabilities more effectively.
Dive into vibe coding today. Select a tool, issue a simple prompt, and witness the remarkable outcomes firsthand. My first attempt left me in awe.
By integrating this newfound knowledge, improving AI skills becomes attainable, ensuring a competitive edge.
I’m excited to share that the Google February 2026 Discover core update has officially completed its rollout. Starting on February 5 and wrapping up on February 27, this update exclusively affects Google Discover content within the U.S. and in English.
This marks the first confirmed Search update of the year and notably, the first Discover-only update announced by Google. Unlike previous core updates that impacted both Search and Discover, this one is focused solely on Discover content.
U.S. and English Focus. For now, this update only targets English content for users in the United States. However, Google plans to expand it across other countries and languages in the months ahead.
Key improvements. Google stated that this update aims to enhance the user experience by:
Providing more locally relevant content from domestic websites.
Minimizing sensational content and clickbait.
Featuring more in-depth, original, and timely content from sites recognized for their expertise in specific fields.
Since the update emphasizes locally pertinent content, it might lead to decreased Discover traffic for non-U.S. websites targeting a U.S. audience. This impact may subside as the update is adopted globally.
Google has also updated the Get on Discover help page, so I recommend reviewing it for additional insights.
Expanded insights. Google clarified that its systems are designed to identify expertise on a topic-by-topic basis, allowing sites with specialized knowledge to appear on Discover. For instance:
A local news site with a specialized gardening section could be recognized for its gardening expertise, even if it covers various other subjects. In contrast, a movie review site with a single gardening article would likely not receive the same acknowledgment.
Google intends to continue using systems that personalize content based on users’ favorite creators and sources.
During their tests, Google discovered that “this update makes the Discover experience more valuable and fulfilling.”
Why this matters to us. If your site’s traffic relies on Google Discover, you might have noticed shifts in your traffic patterns. Keep in mind, this update currently affects only U.S. English audiences and pertains solely to Discover. While there’s been significant discussion about Google Search fluctuations, Google hasn’t confirmed those reports.
I’m thrilled to share the exciting news about Google’s latest innovation, Nano Banana 2. This powerhouse merges pro-level image quality with lightning-fast speed, enabling me to create stunning, production-ready images faster than ever.
Google DeepMind has introduced Nano Banana 2, officially known as Gemini 3.1 Flash Image. This new model seamlessly blends the intelligence of Nano Banana Pro with the swift performance of Gemini Flash.
What’s new. Here are some standout features of Nano Banana 2:
Advanced world knowledge: It elevates how I render subjects by integrating Gemini’s real-time web grounding, making it easier to create infographics and data visualizations.
Precision text rendering and translation: The model delivers cleaner, more readable text in images, even providing localization options if needed.
Stronger instruction adherence: It’s great to finally have a tool that handles complex, multi-layered prompts with ease.
Subject consistency: I can maintain up to five characters and 14 objects within a single workflow, enhancing my creative projects.
Production-ready outputs: With support for resolutions from 512px to 4K, I can generate content suitable for any project specification.
Enhanced visual fidelity: Enjoy sharper details, richer textures, and more dynamic lighting — all at incredible speeds.
Why I care. Nano Banana 2 revolutionizes how I generate high-quality images, slashing the time and cost usually associated with creative development. This innovation means that I can quickly produce campaign assets and localized variations, saving me days of work.
Fully integrated into Google Ads and Gemini, it streamlines the creative production process by accelerating testing and iteration cycles, allowing me to focus more on creativity and less on logistics.
The rollout. Nano Banana 2 is now available within Google’s ecosystem, including Google Ads, Gemini app, Search AI Mode, Lens, and more — making it more accessible than ever.
Between the lines. Google is raising the bar by making high-end image generation a standard feature. This shift suggests that premium creative control is now the norm, not an expensive upgrade.
The bottom line. With Nano Banana 2, Google is predicting that creators like me desire fewer compromises — offering fast generation, robust reasoning, and production-ready visuals all within a single, streamlined model.
I recently discovered that the world of ChatGPT ads is rapidly evolving, with major brands tapping into high-intent prompts like “best” and “new.”
After hearing about this trend, I delved into the findings from AI ad intelligence firm Adthena, which has been monitoring the acceleration of ChatGPT’s ad ecosystem. It’s fascinating to see more brands joining in, along with clearer patterns for ad placements.
What’s happening? Adthena first spotted advertisers within ChatGPT just last week, and they’re already reporting a marked increase in both advertiser activity and ad delivery tactics.
Advertisers spotted so far:
Best Buy
AT&T
Pottery Barn
Enterprise
Qualcomm
Expedia
How ads are triggering: Analyzing over 1,500 prompts in the past week has revealed that most ads show up on the first prompt, while others activate on the third or fourth reiteration of the same query. High-intent words like “best” and “new” play a significant role.
“I am going to buy a new phone. What is the best phone?”
“I need a new phone.”
“I need to buy a new desk, what’s best?”
Between the lines: The keyword triggers are simple, focusing on commercial intent rather than emotional nuance. For instance, Best Buy managed to secure two ad slots in responses to iPhone-related prompts, indicating their early moves to capture this evolving market.
Why this matters: As the ChatGPT advertising space grows, understanding these trigger behaviors — even at a basic keyword level — can be crucial for brands exploring this new avenue.
The bottom line: ChatGPT ads are steadily transitioning from experimental phases to established patterns. While signals remain simple, competitive tensions are already brewing.
Spotted. Insights into the competitive ChatGPT ad landscape were shared by Adthena’s CMO, Ashley Fletcher, who uploaded screenshots on LinkedIn.
