Imagine a world where workflows evolve beyond mere manual processes, actively collaborating with us as marketers. That’s the future Agents bring to life, seamlessly integrating with our marketing teams as valued members.
In the past month, the dedicated team behind Agents has released a series of updates, ushering in new capabilities that promise to change the way we approach marketing tasks.
Inspired by this post on Try Profound Blog.
I’ve discovered that refining our approach with both robots.txt and LLMs.txt can significantly enhance our visibility on platforms like ChatGPT, Gemini, and various answer engines. It’s fascinating how these simple files can make such a big difference in crawlability for AI bots.
Join me as I delve into the best practices for optimizing these important files. By making small yet impactful changes, we can ensure our content gets the attention it deserves in the evolving digital landscape.
Inspired by this post on HiGoodie Blog.
Exciting news! I’ve just launched brand-new Profound Data nodes within our Workflows. This makes it effortless to integrate Profound’s top-tier AEO data right into the heart of your content creation and optimization processes.
Whether you’re focused on reporting, monitoring, or refining your content strategies, these nodes are designed to enhance the efficiency and precision of your media tasks.
Inspired by this post on Try Profound Blog.
I recently discovered the potential of Google AI Max and, like many of us, wondered if my account is ready to harness its power. Google AI Max promises to unlock additional conversions if set up correctly. Before jumping in, I knew I had to ensure everything was primed and in place.
Google’s AI Max is designed to transcend traditional keyword targeting by utilizing various signals to determine ad displays. It’s a game-changer for those with a history of broad match success. However, if not optimized, it could quickly deplete your budget.
One important clarification: using AI Max is not mandatory for ad appearances in AI Overviews. Broad match keywords can place ads in AI Overviews regardless of AI Max usage. I see AI Max more as a tool to expand conversions beyond mere AI Overviews.
We’ll explore the essential steps to review before testing AI Max. These insights are crucial to ensure our campaigns are fully prepared.
Having precise conversion tracking is vital. AI Max optimizes based on our defined success metrics. Inaccurate or inflated conversions can lead to poor AI decisions. This insight made me double-check everything.
For broad match to function optimally, a conversion-centered bid strategy is necessary. Options like ‘Maximize Conversion Value’ or ‘Target CPA’ should align with your updated strategy. My experiments indicated more consistent results with target bids than max bids.
Using max bids without watching over budget and collected data might not yield the best results. I’ve learned to keep a careful eye on it.
AI Max needs sufficient data to perform well. With over 100 conversions monthly, its reliability has been strong, provided there’s a positive history with broad match. Based on this, I aimed to test in campaigns with at least 30 monthly conversions.
If budget constraints already hinder impression share, AI Max could exacerbate this issue. Prioritize spending on top keywords and let AI Max utilize remaining funds for experimentation.
AI Max treats keywords as broad match and extends beyond them. Without past success, it could be ineffective. Preparing through ad group optimization and new ad testing has been my strategy.
Enabling URL expansion allows Google to pick any webpage for landing when AI Max triggers an ad. However, indiscriminate use can be detrimental—excluding non-conversion-oriented pages mitigates risks.
Those who created landing pages for specific geographies should carefully manage page exclusions to avoid mismatching.
I’m hopeful about automatically created assets. They can significantly enhance messaging but require caution to avoid irrelevant sitelinks and incompatible callouts. Establishing clear guidelines ensures alignment with brand objectives.
Because of its performance inconsistencies with brand keywords, I’ve found it best to initially focus on non-brand keywords in AI Max tests. Starting with successful ad groups rich in conversion data offers the best chance to test its potential.
Operating AI Max at the ad group level via the Google Ads Editor proved efficient in my testing experience.
As AI Max continues to evolve, its integration into our existing systems may provide significant advantages. But, readiness involves assessing if our accounts meet all setup criteria before diving in. By following my steps, you’ll recognize its readiness and potential for success.
Inspired by this post on Search Engine Land.
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.
The bottom line: By integrating Olympic and live sports inventory into Display & Video 360, Google has made purchasing premium sports advertising more efficient, transparent, and accountable.
Inspired by this post on Search Engine Land.
As an advertiser, I’m excited to share that Microsoft is empowering Performance Max campaigns by expanding search themes to 50. This change offers us more control, allowing better alignment with high-intent customer searches.
Just ahead of next week’s major announcements, Microsoft Advertising has confirmed that we can now incorporate up to 50 search themes in our campaigns, a notable increase from previous restrictions.
Why this matters to me. Search themes serve as strategic signals that guide Performance Max toward the search queries and intent patterns that we prioritize. With this expanded capacity, I have more room to refine how automation interprets customer demand, especially for businesses with diverse product lines or complex structures.
This update also means I no longer need to compress different intents into a limited number of themes or run multiple campaigns just to portray various product offerings.
The bigger picture. Microsoft’s focus is shifting towards signal-based control rather than strict keyword targeting. By combining search themes with LinkedIn profile targeting and other audience signals, including impression-oriented remarketing, I can better target high-value customers rather than a generic audience.
What I’m looking forward to. Next week, Microsoft’s Advertising blog will feature additional updates, suggesting this change is part of a larger initiative to make Performance Max not only more flexible but also more responsive to advertisers’ needs without undermining the automation logic.
Where I first learned about this. Microsoft Product Liaison Navah Hopkins shared these insights on LinkedIn, along with hints of upcoming updates slated for next Wednesday, January 14th.
The bottom line for me. By increasing the number of available search themes to 50, Microsoft is improving our control over Performance Max, not through additional complexity, but by widening the range of pivotal signals.
Inspired by this post on Search Engine Land.
Every week, 900 million users interact with platforms like ChatGPT, yet my brand is often absent from their discussions. I wanted to understand why, and more importantly, how I could change that.
After digging into the reasons, I discovered several factors that influence brand visibility within ChatGPT’s responses. It’s not just about having a strong brand, but also understanding how to optimize for this new kind of search engine.
To make my brand appear in ChatGPT talks, I need to focus on implementing strategic optimization techniques, specifically tailored to AI-powered platforms. I’ll share these insights, so we all can benefit from increased visibility in this rapidly evolving space.
Inspired by this post on genmark.ai Blog.
Have you ever wondered why your site isn’t getting the attention it deserves from AI crawlers? I know how frustrating it can be to feel overlooked in the digital world. Often, Cloudflare might be the culprit blocking access.
Let me guide you through diagnosing these issues, providing solutions, and optimizing your site for better LLM (Large Language Model) visibility. Together, we’ll ensure your site is primed for the AI-age and ready to capture its rightful place in search rankings.
Inspired by this post on HiGoodie Blog.
Recently, I listened to a fascinating podcast featuring Nick Fox, Google’s Senior Vice President of Knowledge and Information. He shared an intriguing perspective: optimizing for AI search is fundamentally the same as traditional SEO. His advice? Focus on creating great sites with engaging content for your users.
Podcast Highlights: During the AI Inside podcast, hosted by Jason Howell and Jeff Jarvis, Nick Fox provided invaluable insights. Here’s a snippet from around the 22-minute mark:
Jeff Jarvis asked a pressing question: “For publishers wanting to participate in AI, should they view their content differently?”
Nick Fox’s response was clear and straightforward: “The short answer is no.” He emphasized that the approach to optimizing for Google’s AI experiences mirrors best practices for traditional search. Ultimately, it boils down to building outstanding sites and content. “Create what you’d want to read,” Fox advised.
If you want to dive deeper, check out the full episode around the 22-minute mark:
This perspective aligns with what other Google experts like Danny Sullivan and Gary Illyes have shared. Good traditional SEO translates to effective AI optimization. You can read more about Danny Sullivan’s thoughts and Gary Illyes’ advice on focusing on normal SEO here.
Why This Matters: As someone who’s been honing SEO skills for years, it’s reassuring to know that these skills are just as relevant in the era of AI search. We are already equipped to excel in this new landscape.
So go ahead, take advantage of your hard-earned expertise and thrive in the evolving SEO world.
Inspired by this post on Search Engine Land.
I can’t contain my excitement as Google unveils the Developer Assistant for the Google Ads API. This breakthrough tool allows us, as advertisers and developers, to leverage natural language to create, manage, and export Ads API queries effortlessly.
Google has introduced the Google Ads API Developer Assistant v1.0, an innovative Gemini CLI extension. It empowers us to interact with the Ads API seamlessly, transforming our everyday language into instant answers, functional code, and even real-time API calls.
How it works: Embedded within the Gemini CLI, the assistant utilizes project contexts from GEMINI.md and configuration files to generate precise code tailored to our specific environment. With a simple query like, “How do I filter by date in GAQL?”, I receive immediate assistance. If I describe a task, such as “Show me campaigns with the most conversions in the last 30 days,” it provides both the GAQL query and a well-optimized Python script using the google-ads-python client library.
Key features include: The ability to execute read-only API calls directly from the terminal, presenting the results in cleanly formatted tables. Plus, any tabular data can be exported to CSV, filed neatly in a dedicated directory. All code generated by the assistant is automatically organized within a saved_code/ folder for easy access.
Why it matters to us: The Google Ads API is immensely powerful yet complicated. This new Developer Assistant simplifies our workflow drastically, making it quicker and more efficient for teams to create, refine, and optimize Google Ads API workflows—the core of comprehensive campaign management and reporting.
By converting natural language into GAQL queries and operational code, it minimizes technical obstacles and speeds up our ability to glean insights that could lead to better optimization strategies. The ease of one-command execution and CSV exports means we spend less time dealing with coding complexities and more on boosting performance.
The big picture: Google positions the assistant as a dual-purpose tool—a learning aid for beginners and a productivity enhancer for experienced users. For newcomers, the use of natural language commands significantly lowers the learning curve.
For advanced users like me, features such as code generation, automatic file management, and command-line execution streamline and minimize repetitive tasks involved in daily API operations.
Getting started is straightforward: Ensuring you have a Google Ads API token, a configured google-ads.yaml, Python 3.10+, the Gemini CLI, and a local clone of the google-ads-python library is essential. A setup script handles the cloning process, with full instructions available on GitHub.
What’s next: Google invites early users to provide feedback, suggest features, and engage with the community on the Discord channel as the platform evolves with more enhancements and AI-driven tools.
The bottom line: By enabling developers to query, code, and execute using everyday language, Google is transforming the Google Ads API into a faster, more intuitive, and broadly accessible tool.
Dig Deeper: For more insights, check out Introducing the Google Ads API Developer Assistant v1.0: Interact with the API using Natural Language.
Inspired by this post on Search Engine Land.