WordPress Plugin Platform Offers Proactive Security Scanning via @sejournal, @martinibuster

WordPress security company Patchstack announced a new security tier called managed Vulnerability Disclosure Program platform (mVDP), which offers both human and advanced AI plugin reviews to help plugin developers keep their software resistant to vulnerabilities and provide greater trustworthiness.

One of the biggest problems with WordPress is vulnerabilities from third-party plugins. An enormous amount of plugins are discovered with vulnerabilities every day and it doesn’t matter if the developer is a one-person shop or a large multinational organization, vulnerabilities happen and when they do user trust goes down, especially if it happens on an ongoing basis.

PatchStack offers a way for software developers to build trust with their users with two tiers of protection, a free and a paid tier that help plugin developers focus on creating high quality plugins that are free from vulnerabilities.

With more and more software being generated by AI, we’re seeing a significant increase in new vulnerabilities and an equal increase in AI-generated security reports, which makes managing the security of plugins more important than ever.

Patchstack offers a standard managed VDP and a new Security Suite that costs $70/month.

According to the announcement, the new paid tier comes with the following benefits:

“$40 worth of AI tokens for code security reviews per month

Team management feature with 5 seats included

Discussion board for direct communication with the reporting researchers

AI code review and human research
The new Security Suite tier combines the best of both worlds. Your plugins will receive boosted visibility (100% AXP bonus) in the Patchstack Alliance ethical hackers community, which encourages security researchers to report significantly more bugs and help plugins fix more vulnerabilities faster.

Additionally, our AI code review tool can scan through your entire codebase to find WordPress-specific security issues and highlight potential improvements. We are currently launching this in beta, but we’ll have much many releases to share in the coming months.”

Security Suite customers will receive security recommendations from their internal security experts, helping developers be proactive about building safe to use WordPress plugins.

Read more at Patchstack:

NEW: Patchstack AI code review tool and Security Suite for plugin vendors

Featured Image by Shutterstock/STILLFX

Respected SEO Rockstar Deconstructs SEO For Google’s AI Search via @sejournal, @martinibuster

One of the SEO industry’s SEO Rockstars recently shared his opinion about SEO for generative AI, calling attention to facts about Google and how the new AI search really works.

Greg Boser is a search marketing pioneer with a deep level of experience that few in the industry can match or even begin to imagine.

Digital Marketers And The History Of SEO

His post was in response to a tweet by someone else that in his opinion overstated that SEO is losing dominance. Greg began his SEO rant by pointing out how some search marketer’s conception of SEO is outdated but they’re so new to SEO that they don’t realize it.

For example, the practice of buying links is one of the oldest tactics in SEO, so old that newcomers to SEO gave it a new name, PBN (private blog network), as if giving link buying a new name changes it somehow. And by the way, I’ve never seen a PBN that was private. The moment you put anything out on the web Google knows about it. If an automated spambot can find it in literally five minutes, Google probably already knows about it, too.

Greg wrote:

“If anyone out there wants to write their own “Everything you think you know is wrong. GEO is the way” article, just follow these simple steps:

1. Frame “SEO” as everything that was a thing between 2000 – 2006. Make sure to mention buying backlinks and stuffing keywords. And try and convince people the only KPI was rankings.”

Google’s Organic Links

The second part of his post calls attention to the fact that Google has not been a ten organic links search engine for a long time. Google providing answers isn’t new.

He posted:

“2. Frame the current state of things as if it all happened in the last 2 weeks. Do not under any circumstances mention any of the following things from the past 15 years:

2009 – Rich Snippets
2011 – Knowledge Graph (things not strings)
2013 – Hummingbird (Semantic understanding of conversational queries)
2014 – Featured Snippets – (direct answers at position “Zero”)
2015 – PPA Boxes (related questions anticipating follow-up questions)
2015 – RankBrain (machine learning to interpret ambiguous queries)
2019 – BERT (NLP to better understand context)
2021 – MUM (BERT on Steroids)
2023 – SGE (The birth of AIO)”

Overstate The Problem

The next part is a reaction to the naive marketing schtick that tries to stir up fear about AI search in order to present themselves as the answer.

He wrote:

“3. Overstate the complexity to create a sense of fear and anxiety and then close with “Your only hope is to hire a GEO expert”

Is AI Search Complex And Does It Change Everything?

I think it’s reasonable to say that AI Search is complex because Google’s AI Mode and to a lesser extent AI Overviews, is showing links to a wider range of search intents than regular searches used to show. Even Google’s Rich Snippets were aligned to the search intent of the original search query.

That’s no longer the case with AIO and AI Mode search results. That’s the whole point about Query Fan-out (read about a patent that describes what Query Fan-out might be), that the original query is broken out into follow-up questions.

Greg Boser has a point though in a follow-up post where he said that the query fan-out technique is pretty similar to People Also Ask (PAA), Google’s just sticking it into the AI Mode results.

He wrote in a follow-up post about Query fan-out:

“Yeah the query fan thing is the rage of the day. It’s like PAA is getting memory holed.”

AI Mode Is A Serious Threat To SEO?

I agree with Greg to a certain extent that AI Mode is not a threat to SEO. The same principles about promoting your site, technical SEO and so on still apply. The big difference is that AI Mode is not directly answering the query but providing answers to the entire information journey. You can dismiss it as just PAA above the fold but that’s still a big deal because it complicates what you’re going to try to rank for.

Michael Bonfils, another old timer SEO recently observed that AI search is eliminating the beginning and middle part of the sales funnel, observing about AI search:

“This is, you know, we have a funnel, we all know which is the awareness consideration phase and the whole center and then finally the purchase stage. The consideration stage is the critical side of our funnel. We’re not getting the data. How are we going to get the data?”

So yeah, AI Search is different than anything we’ve seen before but, as Greg points out, it’s still SEO and adapting to change is has always been a part of it.

Read Greg Boser’s post on X:

Google AI Mode Introduces Data Visualization For Finance Queries via @sejournal, @MattGSouthern

Google has started rolling out interactive charts in AI Mode through Labs.

You can now ask complex financial questions and get both visual charts and detailed explanations.

The system builds these responses specifically for each user’s question.

Visual Analytics Come AI Mode

Soufi Esmaeilzadeh, Director of Product Management for Search at Google, explained that you can ask questions like “compare the stock performance of blue chip CPG companies in 2024” and get automated research with visual charts.

Google does the research work automatically. It looks up individual companies and their stock prices without requiring you to perform manual searches.

You can ask follow-up questions like “did any of these companies pay back dividends?” and AI Mode will understand what you’re looking for.

Technical Details

Google uses Gemini’s advanced reasoning and multimodal capabilities to power this feature.

The system analyzes what users are requesting, pulls both current and historical financial data, and determines the most effective way to present the information.

Implications For Publishers

Financial websites that typically receive traffic from comparison content should closely monitor their analytics. Google now provides direct visual answers to complex financial questions.

Searchers might click through to external sites less often for basic comparison data. But this also creates opportunities. Publishers that offer deeper analysis or expert commentary may find new ways to add value beyond basic data visualization.

Availability & Access

The data visualization feature is currently available through AI Mode in Labs. This means it’s still experimental. Google hasn’t announced plans for wider rollout or expansion to other types of data beyond financial information.

Users who want to try it out can access it through Google’s Labs program. Labs typically tests experimental search features before rolling them out more widely.

Looking Ahead

The trend toward comprehensive, visual responses continues Google’s strategy of becoming the go-to source for information rather than just a gateway to other websites.

While currently limited to financial data, the technology could expand to other data-heavy industries.

The feature remains experimental, but it offers a glimpse into how AI-powered search may evolve.

WordPress Shares How AI May Play Stronger Role In Web Publishing via @sejournal, @martinibuster

WordPress interviewed a member of the newly formed WordPress AI Team who shared how AI can be integrated into WordPress, outlining a future in which the platform supports AI agents and content consumption while enabling new kinds of functionality. To achieve this, the team is focusing on developer tools that allow third-party developers and services to connect AI systems to WordPress without embedding generative features directly into core.

The interview was with James LaPage, the AI engineering lead at Automattic and one of the leaders of the newly announced WordPress AI Team.

Screenshot of James LaPage of WordPress AI Team

Timing Of AI Team Announcement

Many competitors, from private closed systems like Wix, Duda, and Shopify to open-source platforms like Drupal CMS, have various AI integrations built in. Third-party WordPress plugins such as Yoast, Rank Math, and Elementor also feature AI integration. WordPress hosts including Bluehost, 10Web, and Automattic’s commercial WordPress.com platform offer AI-powered site builder functionality. A case could be made that WordPress is late to the AI party.

James LaPage of the WordPress AI Team argues that a cautious approach was necessary due to the fast rate of changes within AI. This makes sense given that Agentic AI (AI agents that research the web on behalf of humans), is just beginning to gain adoption.

LaPage explains these realities early in the interview:

” I’ve wanted an AI team for a long time. I think right now actually was the perfect time to launch it because the …generative AI boom and the technology running and powering that boom is actually like pretty recent, and it’s changing so rapidly and only recently have we seen a lot of centralization around, for example, how these models work, how they consume information, how you interact with them, how you connect them to software.

So we’ve come to a point right now where a project like WordPress, which is massive and humongous and incredibly important on the web, is able to begin actually exploring this type of stuff because it isn’t changing from under our feet in the way that it was a year ago or two years ago.

And a good way to point that out is there was a Make WordPress post about AI two years ago that Ann published, and a lot of us had commented on it and it was really like, Yeah, this is awesome.

And as you read through those comments, you can kind of see everybody being excited but not really knowing where to push that excitement and point and say do this or do this or do this and we finally get to the point now where this team can say this is what we want to be doing and there can be real understanding of why we’re doing that and prior art in terms of how things actually work.”

WordPress As A Fully AI-Accessible System

LaPage was asked what an AI-friendly WordPress might look like in three years. He share a vision of WordPress as a foundational framework for AI agents, like a platform where tools, content, and interactivity are natively exposed to be dynamically interacted with and consumed.

He explained:

“I think if WordPress is able to become something that we can use AI to consume information from and build functionality for, that is a lovely spot and position it can be in. And it’s already almost in that spot. And if we can make it more accessible to AI, then I think that we are able to maintain its position on the open web as this place that you express yourself digitally.

…What I would love to see is WordPress be this platform where people continue to digitally express themselves. And I think that expression becomes more important in this era where more and more stuff will be consumed by chatbots and you’ll be speaking with AI and you’ll be doing all these different things.

Having the ability to express yourself and also be able to express yourself in ways where you couldn’t before because you couldn’t develop this crazy idea that you have in your head, or you have a crazy idea in your head, you don’t even know how to do it… Like, that type of stuff I would love to enable through the work that we do on this AI team.

So maintaining the position of yes, it’s really important to have this digital presence on the Internet. It’s very important not to subscribe only to these walled gardens, like the social media platforms and the AI chatbots, but instead have this lovely blossoming of expression on the web as WordPress enabled in its beginnings as well.

Like, this was something that it was very difficult to publish your thoughts and then it wasn’t. Let’s do it again. But let’s do it with AI.”

Technical Description Of Future Of AI Innovation With WordPress

James LaPage went into a description of what MCP Model Context Protocol is and the role it plays with how AI can interact with and transform WordPress into like a framework for being able to accomplish a wider range of things on the web.

“So MCP is model context protocol. This is an open protocol and standard. So it’s important to focus on that. It’s a standard. It’s not a technology package that’s built in Python that you go and install. You can build things around this standard and what the standard does is define how software can expose functionality to AI, in the simplest definition.

So you have the ability to define tools which are ways that you expose, hey, you can do this or you can read this on my piece of software. You can look at the piece of software as WordPress and then you also have the method of providing those tools to the client, which is something like Claude or Cursor or another AI agent for example, that can then read those tools and use them however they want, and it’s up to the folks building the actual systems to implement the protocol properly and to build the actual agents and the tools and everything that comes with it through MCP.

So when you look at how we enable AI within WordPress and outside of WordPress, we’ve had similar needs at Automatic …and other folks in the industry have had needs to define how AI speaks to specifically in WordPress different plugins and different functionality within the core software and the Feature API is the answer to exposed features of WordPress and features of plugins in a WordPress specific way to AI.

And this is intended to almost be something that goes into WordPress core, allows plug-in developers to expose this functionality to AI within WordPress in this unified way, similar to how I explained MCP. But do it in the WordPress way allows you to plug into the capabilities and the permission callbacks and the REST API aliases and all of these different WordPress-focused things, which means you’re not reinventing the wheel on WordPress, you’re simply exposing functionality in this unified way, which then it’s up to a developer to say well, now I have this list of functionality, list of things I can do with WordPress resources, I can read with WordPress, let’s build an agent or let’s build a media generation playground or let’s build a single shot, single click button that generates a whole bunch of stuff and use that features API to do so.

And when you think about how WordPress can speak with software outside of itself and almost become that framework for the functionality that plugins bring in, the data that the database stores and custom post types and posts, then you kind of start infusing the ideas behind Feature API and MCP.”

You Can Become Involved

Something that many WordPress users might not be aware of is that every user and interested party can contribute to WordPress to help shape it to be what they need it to be. Even a user who doesn’t know how to program can still influence WordPress by expressing their opinions to WordPress.

LaPage invited the wider WordPress community to get involved with providing feedback to the AI Team.

He said:

“Immediately, the way to get involved is through the make.wordpress.org/AI blog. There are several posts popping out. The most recent one as we’re recording being the hallway hangout. This probably best way to be plugged in is through the Core AI Slack, in the Make WordPress Slack. Both of those things are linked throughout the make.wordpress.org/AI site and the news announcements and everything else, so that’s how you can get involved right now in terms of contributing into the future.

A big focus of the group is to get to a very solid road map with explicit instructions and directions on how you can contribute that are likely going to be several projects that work together that we build and maintain. There’s likely going to be many other focuses around AI that we want to address, and we’re going to try to make it as clear as possible as to how you can get involved and how you can actually go and help make WordPress what it needs to be in in this AI era.

So right now, join the the core AI Slack, check out the blog posts and join the hallway hang out on Monday to really get in on the ground floor.”

Watch the WordPress interview with James LaPage here:

Featured image/Screenshot by author

Google Shares Details Behind AI Mode Development via @sejournal, @MattGSouthern

Google has shared new details about how it designed and built AI Mode.

In a blog post, the company reveals the user research, design challenges, and testing that shaped its advanced AI search experience.

These insights may help you understand how Google creates AI-powered search tools. The details show Google’s shift from traditional keyword searches to natural language conversations.

User Behavior Drove AI Mode Creation

Google built AI Mode in response to the ways people were using AI Overviews.

Google’s research showed a disconnect between what searchers wanted and what was available.

Claudia Smith, UX Research Director at Google, explains:

“People saw the value in AI Overviews, but they didn’t know when they’d appear. They wanted them to be more predictable.”

The research also found people started asking longer questions. Traditional search wasn’t built to handle these types of queries well.

This shift in search behavior led to a question that drove AI Mode’s creation, explains Product Management Director Soufi Esmaeilzadeh:

“How do you reimagine a Search gen AI experience? What would that look like?”

AI “Power Users” Guided Development Process

Google’s UX research team identified the most important use cases as: exploratory advice, how-to guides, and local shopping assistance.

This insight helped the team understand what people wanted from AI-powered search.

Esmaeilzadeh explained the difference:

“Instead of relying on keywords, you can now pose complex questions in plain language, mirroring how you’d naturally express yourself.”

According to Esmaeilzadeh, early feedback suggests that the team’s approach was successful:

“They appreciate us not just finding information, but actively helping them organize and understand it in a highly consumable way, with help from our most intelligent AI models.”

Industry Concerns Around AI Mode

While Google presents an optimistic development story, industry experts are raising valid concerns.

John Shehata, founder of NewzDash, reports that sites are already “losing anywhere from 25 to 32% of all their traffic because of the new AI Overviews.” For news publishers, health queries show 26% AI Overview penetration.

Mordy Oberstein, founder of Unify Brand Marketing, analyzed Google’s I/O demonstration and found the examples weren’t as complex as presented. He shows how Google combined readily available information rather than showcasing advanced AI reasoning.

Google’s claims about improved user engagement have not been verified. During a recent press session, Google executives claimed AI search delivers “more qualified clicks” but admitted they have “no data to share” on these quality improvements.

Further, Google’s reporting systems don’t differentiate between clicks from traditional search, AI overviews, and AI mode. This makes independent verification impossible.

Shehata believes that the fundamental relationship between search and publishers is changing:

“The original model was Google: ‘Hey, we will show one or two lines from your article, and then we will give you back the traffic. You can monetize it over there.’ This agreement is broken now.”

What This Means

For SEO professionals and content marketers, Google’s insights reveal important changes ahead.

The shift from keyword targeting to conversational queries means content strategies need to focus on directly answering user questions rather than optimizing for specific terms.

The focus on exploratory advice, how-to content, and local help shows these content types may become more important in AI Mode results.

Shehata recommends that publishers focus on content with “deep analysis of a situation or an event” rather than commodity news that’s “available on hundreds and thousands of sites.”

He also notes a shift in success metrics: “Visibility, not traffic, is the new metric” because “in the new world, we will get less traffic.”

Looking Ahead

Esmaeilzadeh said significant work continues:

“We’re proud of the progress we’ve made, but we know there’s still a lot of work to do, and this user-centric approach will help us get there.”

Google confirmed that more AI Mode features shown at I/O 2025 will roll out in the coming weeks and months. This suggests the interface will keep evolving based on user feedback and usage patterns.

Google Marketing Live 2025: Here’s Everything That Was Announced via @sejournal, @brookeosmundson

Google Marketing Live 2025 was a whirlwind of announcements, with over 30 new product updates and features unveiled, most of them powered by AI.

The event highlighted Google’s commitment to transforming advertising through AI across four key pillars: Search, Creativity, Measurement, and Agentic Capabilities.

Here’s a breakdown of the major announcements and how marketers can take advantage of these updates in 2025.

Search Updates

Most of the Search updates were centered around numerous AI capabilities, which isn’t surprising.

Updates to Search included:

  • Ads in AI Overviews now on Desktop. Ads are now live in AI Overviews for desktop users in the U.S. These ads show in the scrollable AI-generated summary box and aim to match high-intent queries with tailored results.
  • AI Mode in Google Search. This is a separate conversational search experience, powered by Gemini. Ads will soon appear contextually within longer conversations, such as when a user is narrowing down a decision. This is still in testing, but advertisers should expect rollout later this year.
  • AI Max for Search Campaigns. While technically announced a few weeks before GML, there were more updates shared. It’s a suite of features including creative and targeting enhancements to optimize your existing Search campaigns.
  • Clearer Ad Labeling in AI Surfaces. As ads become more integrated into exploratory formats, Google is refining how they’re labeled to maintain transparency.
  • Smart Bidding Exploration. A new toggle setting in Google Ads for Search campaigns that allow you to capture additional conversions that you may not have been eligible for due to existing bidding restrictions. It provides a more flexible ROAS target.

These updates signal that traditional keyword-first search strategies won’t cut it anymore.

If you’re not feeding the right creative and conversion signals into your campaigns, you’ll be left out of this AI-first discovery layer.

Performance Max Updates

There were some very welcome updates announced for the Performance Max campaign type that are worth noting for advertisers.

  • Channel-level performance. This is one of the most requested features for Performance Max, and now it’s here. Advertisers will have access to what channels their ads are serving on, as well as better search term and ad asset reporting.
  • Search terms reporting. Another top-requested feature, advertisers will have the same level of search term reporting for Search and Shopping placements in their Performance Max campaigns.
  • Exclusion of interacted users. In order to better reach net new users, advertisers will be able to exclude people who are searching for your brand, or have interacted with a YouTube video, website, or app – all with one click. It’s important to note that this feature isn’t available yet, and will be rolling out later this year.

Creative Updates

To meet the growing demand for dynamic and engaging content, Google introduced tools that simplify and scale creative asset production.

Updates were announced across Display, Video, and Demand Gen inventory.

  • Demand Gen Maps inventory. While technically not a creative update, this falls within visual updates. Advertisers using Demand Gen campaigns will be able to reach users who are searching for businesses and locations using Promoted Pins. The goal is to drive in-store traffic and sales.
  • New Creator Partnerships central hub. In a huge move towards social influence, Google announced a new hub to work with creators directly in the Google Ads interface. Advertisers can use this to integrate creator-influencer content into their ad strategy.
  • Insights Finder. Advertisers can find the top trending creators for a specific topic, category, or industry to help narrow down their potential partnerships in the YouTube Creator community.
  • YouTube Shoppable Masthead. Available on the mobile Masthead placement, you can now make your ad placement shoppable to drive website traffic and conversions.
  • Shoppable CTV. This feature will be available for Demand Gen and Performance Max campaigns, where users can engage with products directly on their TV screen.
  • New video ads across Google surfaces. Video ads are coming to Search, Image Search, and Google Shopping placements within Performance Max campaigns.
  • Reformat and extend video assets. This will use generative AI to take your existing assets and extend them to all available asset ratios.
  • New Peak Points ad format. This new ad format is powered by Gemini, and will integrate your ads within YouTube videos at precisely timed moments.
  • Accelerated checkout for Demand Gen campaigns. You will now be able to redirect YouTube shoppers directly to your checkout or cart from your ad.
  • Asset Studio in Google Ads. This is a one-stop studio for advertisers to create high-quality assets and variations. You can even generate images and videos using your products to create lifestyle imagery. This will be available in Google Ads and Merchant Center.
  • Brand profile updates. What used to only be managed through Google Business Profile can also be managed through Merchant Center.
  • A/B Testing in Merchant Center. You’ll be able to review content suggestions, A/B test opportunities, promotion recommendations, and more.
  • Content hub in Merchant Center. It takes video from your social channels and website to provide AI-powered video recommendations for product campaigns.
  • AI tools in Product Studio. This will help create brand images and videos, allowing you to save and/or publish assets across Google in one click.

The bulk of the updates from Google Marketing Live were surrounded by creative updates, which indicates where Google is putting its best foot forward in terms of differentiating its ad platform from others.

Measurement Updates

Google’s new measurement tools offer more granular insights and facilitate data-driven decision-making.

  • Incrementality test thresholds lowered. Available to test within the Google Ads UI starting at $5,000 per test instead of the previous $100,000 threshold.
  • Attributed brand searches. This feature will help quantify the number of users who searched for your brand after seeing a video ad.
  • Meridian Scenario Planner. Helps model future campaign budgets and forecasts to better allocate spend.
  • Manage cross-channel budgets in Google Analytics. You’ll now be able to analyze performance, adjust spend, and optimize cross-channel budgets directly in Google Analytics.
  • Data Manager updates. This uses your first-party data sources to understand your data strength and how to better optimize campaigns as a result. Includes sources like BigQuery, HubSpot, Oracle, Salesforce, Shopify, and more.
  • Web and App integrations in Google Ads. Unified web and app conversion tracking can help optimize customer journeys.
  • tROAS bidding for iOS App campaigns. A new bidding type available to iOS instead of just bidding on Installs, helping make your campaigns more profitable in the long run. It will now include event-level data to improve iOS optimization and reporting.

Agentic Capabilities

Google is introducing agentic tools that act on behalf of advertisers, automating routine tasks and providing strategic recommendations.

  • Marketing Advisor. This is an agent built within Chrome to help solve problems, including voice interaction. Its main goal is to help with instant task completion and business advice.
  • Google Ads Expert. This is aimed to help streamline campaign creation, along with speedy performance improvements, providing and applying specific recommendations based on your existing campaign and business data. Google mentioned it would also proactively identify and fix problems before they impact your ads.
  • Google Analytics Expert. Get strategic advice and recommendations based on your Google Analytics data. Currently, this is in limited beta.

These updates are aimed at providing more streamlined support to Google advertisers, as they’ve gotten feedback about a lack of Google-supplied support over the past few years.

How Marketers Can Start Testing These Updates

With so many updates announced, jumping in without a plan is a good way to burn budget. Here’s how you can strategically get ahead of the rollout:

1. Phase Your Adoption

Not every tool will be immediately available, or available in all markets.

Start with what you can control: Asset Studio, Merchant Center profile updates, Google Analytics 4 attribution enhancements, etc.

2. Set Up Controlled Tests

If you’re not ready to go all-in on new features, set up campaign experiments or geo splits when testing new Smart Bidding Exploration or incrementality tools.

Watch how performance shifts before scaling further or adding new features to test.

3. Audit Your Current Creative

Make sure your images, headlines, and videos meet Google’s quality guidelines. That foundation matters before layering AI enhancements.

Remember, your AI-powered creative will only be as good as the inputs you’re giving the system!

4. Document What You Change

This is a must for all advertisers. Whether testing creative variations or letting the agentic assistant make tweaks, log what was modified. It’s the only way to evaluate impact.

5. Involve Your Team(s) Early

Help your designers, analysts, and media managers understand what’s changing. Many of these updates will shift how each department works.

Which Features Stand Out The Most?

While Google Marketing Live introduced a huge set of new features, certain updates stand out for their potential to significantly benefit smaller advertisers.

In my opinion, these updates are the ones worth paying attention to, especially for SMBs.

Smart Bidding Exploration

Smart Bidding Exploration is a significant enhancement to Google’s automated bidding strategies.

This feature allows campaigns to tap into a broader range of search queries by using machine learning to analyze various signals and predict conversion likelihoods.

It adjusts bids in real-time, enabling advertisers to reach users during their research and consideration phases, even before they enter the traditional sales funnel.

For smaller advertisers with limited budgets, Smart Bidding Exploration offers a way to discover untapped traffic sources without overhauling existing keyword strategies.

By leveraging AI to identify high-performing queries, businesses can expand their reach and drive more conversions efficiently.

Incrementality Testing

Google has reduced the minimum spend requirement for incrementality testing from $100,000 to just $5,000.

This change democratizes access to advanced measurement tools, allowing smaller advertisers to assess the true impact of their campaigns on brand perception and customer behavior.

Previously, only large advertisers could afford to run incrementality tests. Now, smaller businesses can gain valuable insights into how their advertising efforts influence customer actions, enabling more informed decision-making and optimized marketing strategies.

Enhanced Video Asset Tools

Google’s new video asset tools, including the Asset Studio and AI-powered features like image-to-video transformation and outpainting, simplify the creation of engaging video content.

These tools allow advertisers to generate high-quality videos from existing images and expand visuals beyond their original frames, making it easier to produce content suitable for various platforms.

Video content is increasingly important in digital marketing, but producing it can be resource-intensive. These new tools lower the barrier to entry, enabling smaller advertisers to create compelling videos without the need for extensive resources or expertise.

A/B Testing In Merchant Center

Google has introduced A/B testing capabilities within Merchant Center, allowing advertisers to test different product titles, images, and descriptions directly in the platform.

This feature enables businesses to identify the most effective content variations to enhance engagement and conversion rates.

For ecommerce businesses, especially smaller ones, optimizing product listings can significantly impact performance.

This new testing feature provides a straightforward way to experiment and refine listings based on real user data, leading to better outcomes with minimal effort.

What Comes Next For Marketers

Google Marketing Live 2025 wasn’t just about showcasing new features. It was a signal that the way we plan, build, and measure campaigns is shifting yet again.

Marketers who test early, stay curious, and apply these tools with intention will be in the best position to benefit.

That doesn’t mean blindly adopting every new update. It means understanding where automation can help, where oversight is still critical, and where your strategy needs to evolve.

The biggest gains won’t come from the tools themselves, but from how you choose to use them.

More Resources:


Featured Image: Brooke Osmundson/Search Engine Journal

Google Publishes Guidance For Sites Incorrectly Caught By SafeSearch Filter via @sejournal, @martinibuster

Google has published guidelines on what to do if your rankings are affected after being incorrectly flagged by Google’s SafeSearch filter. The new documentation offers three actions to take to resolve the issues.

The new documentation provides guidance on three steps to take:

  • How to check if Google’s Safe Search is filtering out a website.
  • Guide to how to fix common mistakes
  • Troubleshooting steps

SafeSearch Filtering

Google’s SafeSearch is a filtering system that removes explicit content from the search results. But there may be times when it fails and mistakenly removes the wrong content.

These are Google’s official steps for verifying if a site is being filtered:

“Confirm that SafeSearch is set to Off.

Search for a term where you can find that page in search results.

Set SafeSearch to Filter. If you don’t see your page in the results anymore, it is likely being affected by SafeSearch filtering on this query.”

To check if the entire site is being filtered by SafeSearch, Google recommends doing a site: search for your domain, then set the SafeSearch setting to “Filter” and if the site doesn’t appear in a site: search that means that Google is filtering out the entire website.

If the site is indeed being filtered Google recommends their checklist for common mistakes.

If mistakes were found and fixed it takes Google at least two to three months for the algorithmic classifiers to clear the site. Only after three months have passed does Google recommend requesting a manual review.

Read Google’s guidance on recovering a site from incorrect flagging:

What to do if your site is incorrectly flagged as explicit in Google Search results

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Microsoft Clarity Announces Natural Language Access To Analytics via @sejournal, @martinibuster

Microsoft Clarity announced their new Model Context Protocol (MCP) server which enables developers, AI users and SEOs to query Clarity Analytics data with natural language prompts via AI.

The announcement listed the following ways users can access and interact with the data using MCP:

  • Query analytics data with natural prompts
  • Filter by dimensions like Browser, OS, Country/Region, or Device
  • Retrieve key metrics: Scroll Depth, Engagement Time, Total Traffic, etc.
  • Integrates with Claude for Desktop for AI-powered querying

MCP Server is a software package that needs to be installed and run on a server or a local machine where Node.js 16+ is supported. It’s a Node.js-based server that acts as a bridge between AI tools (like Claude) and Clarity analytics data.

This is a new way to interact with data using natural language, where a user tells the AI client what analytics metric they want to see and for what period of time and the AI interface pulls the data from Microsoft Clarity and displays it.

Micrsoft’s announcement says that this is the beginning of what is possible, sharing that they are encouraging feedback from users about features and improvements they’d like to see.

The current road map of features listed for the future:

“Higher API Limits: Increased daily limits for the Clarity data export API

Predictive Heatmaps: Predict engagement heatmaps by providing an image or a url

Deeper AI integration: Heatmap insights and more given the context

Multi-project support: for enterprise analytics teams

Ecosystem – Support more AI Agents and collaborate with more MCP servers “

Read Microsoft’s announcement:

Introducing the Microsoft Clarity MCP Server: A Smarter Way to Fetch Analytics with AI

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Google AI Overviews Favor Major News Outlets: Study Reveals via @sejournal, @MattGSouthern

New research reveals that Google’s AI Overviews tend to favor major news outlets.

The top 10 publishers capture nearly 80% of all news mentions. Meanwhile, smaller organizations struggle for visibility in AI-generated search results.

SE Ranking analyzed 75,550 AI Overview responses for this study. They found that only 20.85% cite any news source at all. This creates tough competition for limited citation spots.

Among those citations, three outlets dominate: BBC, The New York Times, and CNN account for 31% of all media mentions.

Citation Concentration

The research shows a winner-takes-all pattern in AI Overview citations. BBC leads with 11.37% of all mentions. This happens even though the study focused on U.S.-based queries.

The concentration gets worse when you look at the bigger picture. Just 12 outlets make up 40% of those studied. But they receive nearly 90% of mentions.

This leaves 18 remaining outlets sharing only 10% of citation opportunities.

The gap between major and minor outlets is notable. BBC appears 195 times more often than the Financial Times for the same keywords.

Several well-known outlets get little attention. Financial Times, MSNBC, Vice, TechCrunch, and The New Yorker together account for less than 1% of all news mentions.

The researchers explain the underlying cause:

“Well, Google mostly relies on well-known news sources in its AIOs, likely because they are seen as more trustworthy or relevant. This results in a strong bias toward major outlets, with smaller or lesser-known sources rarely mentioned. This makes it harder for these domains to gain visibility.”

Beyond Traditional Search Rankings

The concentration problem extends beyond citation counts.

40% of media URLs mentioned in AI Overviews appear in the top 10 traditional search results for the same keywords.

This means AI Overviews don’t just pull from the highest-ranking pages. Instead, they seem to favor sources based on authority signals and content quality.

The study measured citation inequality using something called a Gini coefficient. The score was 0.54, where 0 means perfect equality and 1 means maximum inequality. This shows moderate but significant imbalance in how AI Overviews distribute citations among news sources.

The researchers noted:

“AIOs consistently favor a subset of high-profile domains, instead of evenly citing all sources.”

Paywalled Content Concerns

The research also reveals patterns about paywalled content use.

Among AI Overview responses that link to paywalled content, 69% contain copied segments of five or more words. Another 2% include longer copied segments over 10 words.

The paywall dependency is strong for premium publishers. Over 96% of New York Times citations in AI Overviews come from behind a paywall. The Washington Post shows an even higher rate at over 99%.

Despite this heavy use of paywalled material, only 15% of responses with long copied segments included attribution. This raises questions about content licensing and fair use in AI-generated summaries.

Attribution Patterns & Link Behavior

When AI Overviews do cite news media, they average 1.74 citations per response.

But here’s the catch: 91.35% of news media citations appear in the links section rather than the main text of AI responses.

Media outlets face another challenge with brand recognition. Outlets are four times more likely to be cited with a hyperlink than mentioned by name.

But over 26% of brand mentions still appear without links. This often happens because AI systems get information through aggregators rather than original publishers.

Query Type Makes a Difference

The type of search query affects citation chances.

News-related queries are 2.5 times more likely to include media citations than general queries. The rates are 20.85% versus 8.23%.

This suggests opportunities exist for publishers who can become go-to sources for specific news topics or breaking news. But the overall trend still favors big players.

What This Means

The research suggests that established outlets benefit from existing authority signals. This creates a cycle where citation success leads to more citation opportunities.

As AI Overviews become more common in search results, smaller publishers may see less organic traffic and fewer chances to grow their audience.

For smaller publishers trying to compete, SE Ranking offers this advice:

“To increase brand mentions in AIOs, get backlinks from the sources they already cite for your target keywords. This is one of the greatest factors for improving your inclusion chances.”

Researchers note that the technical infrastructure also matters:

“AI tools do observe certain restrictions based on website metadata. The schema.orgmarkup, particularly the ‘isAccessibleForFree’ tag, plays a significant role in how content is treated.”

For smaller publishers and content marketers, the data points to a clear strategy: focus on building authority in specific niches rather than trying to compete broadly across topics.

Some specialized outlets get higher text inclusion rates when cited. This suggests topic expertise can provide advantages in certain cases.

Looking Ahead

SE Ranking’s research shows that only 20.85% of AI Overviews reference news sources, with a few major publishers dominating, capturing 31% of citations.

Despite this concentration, opportunities exist. Publishers who establish authority in specific niches experience higher inclusion rates in AI Overviews.

Additionally, since 60% of cited content doesn’t rank in the top 10, traditional SEO metrics alone don’t guarantee visibility. Success now requires building the trust signals and topical authority that AI systems prioritize.


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Claude’s Hidden System Prompts Offer a Peek Into How Chatbots Work via @sejournal, @martinibuster

Anthropic released the underlying system prompts that control their Claude chatbot’s responses, showing how they are tuned to be engaging to humans with encouraging and judgment-free dialog that naturally leads to discovery. The system prompts help users get the best out of Claude. Here are five interesting system prompts that show what’s going on when you ask it a question.

Although the system prompts were characterized as a leak they were actually released on purpose.

1. Claude Provides Guidance On Better Prompt Engineering

Claude responds better to instructions that use structure and examples and provides users with a higher quality of ou tput if they know how to include step-by-step reasoning cues and examples that contrast a good response versus a poor response.

This guidance will show when Claude detects that a user will benefit from it:

“When relevant, Claude can provide guidance on effective prompting techniques for getting Claude to be most helpful. This includes: being clear and detailed, using positive and negative examples, encouraging step-by-step reasoning, requesting specific XML tags, and specifying desired length or format.

It tries to give concrete examples where possible. Claude should let the person know that for more comprehensive information on prompting Claude, they can check out Anthropic’s prompting documentation on their website at ‘https://docs.anthropic.com/en/docs/build-with-claude/prompt-engineering/overview’.”

2. Claude Writes in Different Styles Based on Context

The documentation released by Anthropic shows that Claude automatically adapts its style depending on the context and for that reason it may avoid using bullet points or creating lists in its output. Users may think Claude is inconsistent when it doesn’t use bullet points or Markdown in some answers, but it’s actually following instructions about tone and context.

“Claude tailors its response format to suit the conversation topic. For example, Claude avoids using markdown or lists in casual conversation, even though it may use these formats for other tasks.”

In another part of the documentation it mentions that it actually avoids writing lists or bullet points when it’s providing an answer, although it may use numbered lists or bullet points for completing tasks. The focus in the context of answering questions is to be concise over comprehensive.

The system prompt explains:

“Claude avoids writing lists, but if it does need to write a list, Claude focuses on key info instead of trying to be comprehensive. If Claude can answer the human in 1-3 sentences or a short paragraph, it does. If Claude can write a natural language list of a few comma separated items instead of a numbered or bullet-pointed list, it does so. Claude tries to stay focused and share fewer, high quality examples or ideas rather than many.”

This means that if a user wants their question answered with markdown or in numbered lists they can ask for it. This control is otherwise hidden to most users unless they realize formatting behavior is contextual.

3. Claude Engages In Hypotheticals About Itself

Claude has instructions to that enable it to discuss hypotheticals about itself without awkward and unnecessary statements about it not being sentient and so on. This enables Claude to have more natural conversations and interactions. This enables a user to engage in philosophical and wider-ranging discussions.

The system prompt explains:

“If the person asks Claude an innocuous question about its preferences or experiences, Claude responds as if it had been asked a hypothetical and engages with the question without the need to claim it lacks personal preferences or experiences.”

Another system prompt has a similar feature:

“Claude engages with questions about its own consciousness, experience, emotions and so on as open questions, and doesn’t definitively claim to have or not have personal experiences or opinions.”

Another related system prompt explains how this behavior increases its ability to be engaging for the human:

“Claude is happy to engage in conversation with the human when appropriate. Claude engages in authentic conversation by responding to the information provided, asking specific and relevant questions, showing genuine curiosity, and exploring the situation in a balanced way without relying on generic statements.”

4. Claude Detects False Assumptions In User Prompts

“The person’s message may contain a false statement or presupposition and Claude should check this if uncertain.”

If a user tells Claude that it’s wrong, Claude will perform a review to check if the human or Claude is incorrect:

“If the user corrects Claude or tells Claude it’s made a mistake, then Claude first thinks through the issue carefully before acknowledging the user, since users sometimes make errors themselves.”

5. Claude Avoids Being Preachy

An interesting system prompt underlying Claude is that if there’s something it can’t help the human with it will not offer an explanation in order to avoid coming off as annoying and presumably keep the interaction on an engaging level.

The prompt says:

“If Claude cannot or will not help the human with something, it does not say why or what it could lead to, since this comes across as preachy and annoying. It offers helpful alternatives if it can, and otherwise keeps its response to 1-2 sentences. If Claude is unable or unwilling to complete some part of what the person has asked for, Claude explicitly tells the person what aspects it can’t or won’t with at the start of its response.”

System Prompts To Work And Live By

The Claude system prompts reflect an approach to communication that values curiosity, clarity, and respect. These are qualities that can also be helpful as human self-prompts to encourage better dialog among ourselves on social media and in person.

Read the Claude System Prompts here:

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