Google’s latest core update leaves publishers rattled, but its consequences are still to be determined – Digiday

Hear from execs at The New York Times, Thomson Reuters, Trusted Media Brands and many others
Last month’s Google core update was no cake walk for some publishers.
Several publishers told Digiday that unlike the March Google core update — which had minimal effects on publisher search traffic — the latest one was the more typical, Google nail-biting rollercoaster regarding search referrals and rankings/visibility. Every core update can change how publishers’ sites and pages are ranked and that impacts impressions and CTRs.
One head of audience at a news publisher said there were a few moments during the 16-day roll-out period where things were looking “grim,” as traffic tanked, albeit temporarily, though they declined to share specific figures.
Google did not immediately return a request for comment.
Publishers are well accustomed to the stomach-dropping moments they can have over traffic fluctuations during Google’s regular core updates. So much so that they have a rehearsed playbook to draw from, even during the traffic-plunging moments. “We have a responsibility to our staff to have an even keel in these moments,” said the same exec, who agreed to speak on condition of anonymity. “There’s no point in running around saying this is the death of the internet as we know it. It’s depressing and demoralizing and makes people make [rash] business decisions… which is the last thing you want to do in a core update and in a moment of industry disruption. You want to be the control and not the variable. We are keeping our newsroom calm, and our approach the same.”
Sure enough, traffic has started to stabilize after the core update completed on July 17, according to three publishers.
The core update’s completion coincided with two other major announcements last week: Google confirmed it was testing AI summaries in its Discover platform and an AI Mode button was added to its search bar.
Publishers are having a hard time figuring out just how much of an effect any of these changes are having, as they’re difficult to separate and measure, according to the three execs who spoke to Digiday. 
Core updates can impact Google’s AI tools like AI Overviews and AI Mode — which have been chipping away at publishers’ search referral traffic — as well as platforms like Discover. 
“It’s tough to separate how much going on right now is core update volatility and how much is specific to AI Overviews,” said the head of audience.
Three analytics companies told Digiday it was too soon to provide accurate numbers showing how the core update affected publishers’ search traffic.
Here are the things to know so far about Google’s latest core update:
Three publishing execs said they hadn’t seen a negative impact since Google started testing AI summaries in Discover two months ago.
“Discover continues to be one of our strongest traffic sources,” said an SEO manager at a food publisher, who requested anonymity.
One of the biggest impacts the news publisher’s head of audience has seen as a result of this core update was a “significant delay” in stories being surfaced in Discover. Typically, Google indexes their breaking news stories in three to five minutes, they said. They were seeing delays of up to 50 minutes.
While it may be too early to see a change in impressions and click-throughs on Google Discover, it’s safe to say that any new feature that puts an added layer between a user and a publisher’s site will drive down referral traffic, according to four SEO consultants and managers who spoke to Digiday.
“Google is cutting into the last remaining source of organic traffic for publishers,” said Lily Ray, vp of SEO strategy and research at performance marketing agency Amsive. “We don’t know how much they’re rolling this out, if it’s just a test, and how many publishers will be impacted.” 
Publishing execs were hesitant to share data showing the impact of the latest core update to their search visibility and click-throughs, citing continued volatility even after the update completed.
The SEO manager said some food sites had seen an impact, but their team was still working out what caused those changes. 
The news publisher’s head of audience said it had been a rough couple of weeks. “Just about every publisher I know has taken a hit,” they said.
According to Glenn Gabe, an SEO consultant and president of G-Squared, sites that were negatively impacted by this core update also saw visibility in AI Overviews drop.
However, this update seems to have helped return some of the traffic lost as a result of Google’s Helpful Content Update in September 2023 (and a related March 2024 core update), which was aimed at rewarding high-quality content in search results and demoting low-quality pages. Early data shows that some of the smaller sites that were hit hard by that update are seeing “at least a partial recovery” of 30-40% increase in click-throughs, according to Ray.
After seeing “significant volatility” and a “negative impact” to search referrals while the core update was rolling out, this has now improved, the news publisher’s head of audience said. And though they were seeing a “little trickle back” from the search referral traffic they’d lost since the rollout of AI Overviews, it wasn’t enough to offset those losses, they said.
“We’ve taken a hit, but it’s not existential,” they said.
The good news is the news publisher is gaining “topical authority” in Google’s AI Overviews, meaning their sites are the top citations in some AI topical summaries.
How did they achieve that? They’re not certain yet. There’s not enough data to draw those kinds of conclusions. “We’re in the observational phase,” the head of audience said.
Publishers’ visibility on Google search results has fallen since 2019, but this trend has accelerated sharply since April, according to a recent report by Enders Analysis. And since March, publishers’ search keywords have become over three times more likely to trigger an AI Overview. For now, the impact on publishers’ businesses is minimal, according to the analysis. Publishers’ discoverability and top-of-the-funnel brand awareness are most at risk.
Digiday’s Sara Guaglione and Seb Joseph share their reporting on IAB Tech Lab, meeting with more than 80 publishers on AI issues.
As advertising nears a double-digit revenue figure for Amazon, a Cold War between it and Google is starting to emerge. 
Model Context Protocol (MCP) is a buzzword gaining more traction, especially as publishers think about how to prepare for the agentic web. WTF is it, and why should they care?
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The New SEO Playbook: How AI Is Reshaping Search & Content – Search Engine Journal

Download your cheat sheet and checklist to start building content that works harder.
Walk away with a clear understanding of how AI search advancements affect performance, investment decisions, and internal capabilities.
You’ll learn why traditional SEO tactics still matter, how query fanout shapes which documents are selected, and what makes content truly quotable.
This webinar challenges the “set it and forget it” myth that’s costing brands thousands, and reveals how smarter prompting and strategic oversight can transform your campaigns.
Walk away with a clear understanding of how AI search advancements affect performance, investment decisions, and internal capabilities.
Your Competitors Have Already Started
Join us as we walk you through early best practices, from re-examining your page structure to understanding how crawlers still influence visibility.
AI search is here. Traffic is down. Visibility is vanishing. The old SEO playbook? Outdated.
And many marketers are bracing for more organic traffic loss over the coming years.
With more journeys starting in AI, the dominance of traditional search tactics are in question.
So, what should you do now?
In this on-demand webinar, you’ll learn about the new SEO playbook for AI. Join Zoe Hawkins and Jeff Coyle from Siteimprove, together with James McCormick of IDC, as they walk you through: 
Plus: We’ll walk through some early best practices, from re-examining your page structure to understanding how crawlers still shape visibility.
Who should watch? CMOs, SEO professionals, and digital marketing leaders looking to stay agile in an AI-driven world and future-proof their marketing plans
View the slides below or check out the full webinar for all the details.
 

You’ll learn why traditional SEO tactics still matter, how query fanout shapes which documents are selected, and what makes content truly quotable.
Heather has over 20 years of industry experience and is the Director of Marketing at Search Engine Journal. Having worked …
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Learn how to connect search, AI, and PPC into one unstoppable strategy.
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Copyright © 2025 Search Engine Journal. All rights reserved. Published by Alpha Brand Media.

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The Dawn of Dynamic AI: How Generative Video Models Are Reshaping Content Creation – FinancialContent

The landscape of digital content creation is undergoing a seismic shift with the latest breakthroughs in generative artificial intelligence, particularly in the realm of video generation. Pioneering models such as OpenAI’s (PRIVATE: OPENAI) Sora and Google’s (NASDAQ: GOOGL) Veo and V2A technology are not merely incremental improvements; they represent a fundamental redefinition of how visual narratives are conceived, produced, and consumed. These advancements promise to democratize high-quality video production, enabling creators to conjure complex, realistic scenes from simple text prompts, and even imbue silent footage with synchronized, lifelike audio.
The immediate implications of these innovations are profound, signaling a future where the barriers to entry for sophisticated video content are dramatically lowered. From independent filmmakers to global marketing agencies, the ability to rapidly prototype, iterate, and finalize video content with unprecedented efficiency is set to revolutionize workflows and unlock new creative possibilities. This technological leap is poised to reshape industries, challenge traditional production paradigms, and ignite a new era of digital storytelling.
The recent unveiling and ongoing development of advanced generative AI video models mark a pivotal moment in the evolution of artificial intelligence. At the forefront of this revolution are OpenAI’s Sora and Google’s suite of video and audio generation technologies, including Veo and V2A. These models are not just generating video; they are demonstrating an astonishing comprehension of real-world physics, nuanced human movement, and the intricate details of complex scenes, all from simple textual or visual inputs.
OpenAI’s Sora, though not yet publicly available, has captivated the industry with its ability to produce realistic and imaginative videos up to 60 seconds long from text prompts. Its remarkable capacity to interpret language accurately allows it to generate intricate scenes with multiple characters, specific motions, and precise details of subjects and backgrounds. A standout feature is Sora’s capability to extend generated videos both forward and backward in time, and even create seamless infinite loops, offering unprecedented flexibility in narrative construction. OpenAI is currently engaging in rigorous “red teaming” to identify potential harms and is developing robust tools, including detection classifiers and C2PA metadata, to ensure the responsible deployment of AI-generated content.
Google has countered with its own formidable offerings, notably the Veo series and the innovative V2A technology. Google’s (NASDAQ: GOOGL) Veo 2 generates high-quality videos with enhanced realism and an understanding of cinematography, capable of producing resolutions up to 4K and extending to minutes in length. It excels in grasping real-world physics and the subtleties of human movement and expression, and incorporates an invisible SynthID watermark for content identification. The latest iteration, Veo 3, represents a significant leap, producing 1080p HD to 4K videos directly from natural language prompts, now with synchronized native audio. This means Veo 3 can generate dialogue, ambient sounds, and background music that are perfectly synchronized with the video, creating coherent and immersive scenes. Furthermore, Veo 3 introduces a feature allowing users to create animations by drawing visual instructions directly on the first frame, offering precise animation control without complex text prompts. Complementing Veo is Google’s (NASDAQ: GOOGL) V2A (Video-to-Audio) technology, an AI-driven solution that generates rich, synchronized audio for video content. By analyzing video pixels and leveraging natural language text prompts, V2A creates soundtracks—including sound effects, music, and dialogue—that perfectly align with on-screen actions, addressing the common limitation of many video generation models that produce silent footage.
The timeline leading up to these breakthroughs has been a rapid acceleration of AI research, building upon foundational models in natural language processing and image generation. Key players include the research divisions of tech giants like Google (NASDAQ: GOOGL) and Microsoft (NASDAQ: MSFT), as well as specialized AI labs such as OpenAI (PRIVATE: N/A) and Stability AI (PRIVATE: N/A). Initial market reactions have been a mix of awe, excitement, and cautious apprehension, with content creators, filmmakers, and marketers eagerly anticipating the tools while also grappling with the ethical and practical implications.
The advent of sophisticated generative AI video models like Sora, Veo, and V2A is poised to create a new hierarchy of winners and losers across various industries, fundamentally altering competitive landscapes and business models.
Potential Winners:
Potential Losers (or those facing significant disruption):
Ultimately, the companies that embrace and strategically integrate generative AI into their core operations, rather than resisting it, will be the ones that thrive in this evolving landscape. Adaptation, innovation, and a focus on higher-level creative and strategic tasks will be crucial for navigating this transformative period.
The emergence of advanced generative AI video models like Sora, Veo, and V2A is not merely a technological upgrade; it represents a paradigm shift with far-reaching implications across industries, extending beyond the immediate realm of content creation. This event fits squarely into the broader trend of AI-driven automation and augmentation, pushing the boundaries of what machines can create and understand.
One of the most significant ripple effects will be on competitors and partners within the media and entertainment ecosystem. Traditional film studios, animation houses, and advertising agencies will face immense pressure to integrate these tools or risk becoming obsolete. Companies that develop complementary AI tools, such as those for AI-driven scriptwriting, storyboarding, or character design, will find new opportunities for partnership and integration. The competitive landscape will intensify as smaller, agile AI-first startups challenge established players with their ability to produce high-quality content at a fraction of the cost and time. This could lead to a wave of mergers and acquisitions as larger entities seek to acquire AI capabilities.
Regulatory and policy implications are already a major concern. The ability to generate highly realistic “deepfakes” raises serious questions about misinformation, propaganda, and identity theft. Governments and international bodies are grappling with how to regulate AI-generated content, with discussions around mandatory watermarking, content provenance tracking (like C2PA metadata), and legal frameworks for accountability. Intellectual property rights are another contentious area, as the training of these models often involves vast datasets of copyrighted material, leading to debates over fair use and compensation for creators. The ethical use of AI, including bias in generated content and the potential for misuse, will necessitate robust policy responses and industry self-regulation.
Historically, this moment can be compared to the advent of digital video editing, computer-generated imagery (CGI), or even the printing press. Each of these innovations democratized creation, lowered production costs, and fundamentally altered the media landscape. Just as desktop publishing empowered individuals to create professional-looking documents, generative AI video empowers individuals and small teams to produce cinematic-quality video. The key difference now is the speed and scale at which this transformation is occurring, driven by the exponential growth in computational power and AI model sophistication. The shift from manual, labor-intensive processes to AI-driven automation is accelerating, forcing industries to adapt at an unprecedented pace. This also echoes the early days of the internet, where new business models emerged rapidly, and traditional industries had to quickly pivot to digital strategies.
The immediate future will see a rapid integration of generative AI video models into existing creative workflows. Short-term possibilities include widespread adoption for rapid prototyping in advertising, pre-visualization in filmmaking, and the creation of personalized marketing content. We can expect to see a surge in “AI-assisted” content, where human creativity is augmented by AI tools for efficiency and scale.
In the long term, the possibilities are even more transformative. We may witness the emergence of entirely new forms of entertainment, such as interactive narratives where viewers influence the story in real-time, or hyper-personalized content streams tailored to individual preferences. The concept of a “virtual studio” could become a reality, where entire productions, from script to final cut, are managed and executed primarily by AI, with human oversight. This could lead to a significant reduction in production costs, making high-quality video accessible to an even broader range of creators and businesses.
Potential strategic pivots or adaptations required for companies will be multifaceted. Traditional media companies must invest heavily in AI research and development, or partner with leading AI firms, to integrate these technologies into their core operations. This includes retraining their workforce to become proficient in AI prompting, oversight, and ethical considerations. Software companies providing creative tools, such as Adobe (NASDAQ: ADBE) and Autodesk (NASDAQ: ADSK), will need to rapidly incorporate generative AI capabilities into their suites to remain competitive.
Market opportunities will emerge in specialized AI services, such as AI content auditing, ethical AI consulting, and the development of niche AI models for specific industries (e.g., medical visualization, architectural walkthroughs). Challenges will include managing the ethical implications of deepfakes and misinformation, navigating complex intellectual property issues, and addressing potential job displacement in certain creative roles. The need for robust AI governance and regulatory frameworks will become paramount to ensure responsible innovation.
Potential scenarios and outcomes range from a highly democratized content landscape where anyone can be a filmmaker, to a more centralized model where a few dominant AI platforms control the means of production. The most likely outcome is a hybrid approach, where AI serves as a powerful co-creator, empowering human artists and storytellers to achieve their visions with unprecedented efficiency and scale. Investors should watch for companies that demonstrate a clear strategy for integrating AI, a strong commitment to ethical development, and the ability to adapt their business models to this rapidly evolving technological frontier.
The breakthroughs in generative AI video models, spearheaded by OpenAI’s (PRIVATE: N/A) Sora and Google’s (NASDAQ: GOOGL) Veo and V2A technology, mark a pivotal moment in the history of content creation. These innovations are not merely incremental advancements; they represent a fundamental shift in how visual and auditory narratives are conceived, produced, and consumed. The ability to generate realistic, complex, and synchronized video and audio from simple prompts democratizes high-quality production, lowers barriers to entry, and unlocks unprecedented creative possibilities across industries.
The immediate impact is already being felt, with content creators, marketers, and educators poised to leverage these tools for rapid prototyping, personalized content at scale, and streamlined workflows. While traditional production houses and certain entry-level roles may face disruption, the overall trend points towards an augmentation of human creativity, fostering new roles focused on AI prompting, oversight, and strategic direction. The broader implications extend to significant regulatory challenges concerning misinformation, intellectual property, and ethical AI use, necessitating robust policy responses and industry collaboration.
Moving forward, the market will be characterized by rapid integration of AI into existing creative tools, the emergence of entirely new forms of entertainment, and a continuous push for more sophisticated and nuanced AI models. Companies that strategically embrace and invest in AI, prioritize ethical development, and adapt their business models will be the ones to thrive. Investors should closely monitor the development of AI governance frameworks, the evolution of intellectual property laws, and the strategic pivots of major players in the media, entertainment, and technology sectors. The lasting impact of these generative AI video models will be a more dynamic, accessible, and creatively expansive digital landscape, forever changing how we tell stories and experience the world through video.

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Samsung is rolling out the first software update for its new Galaxy foldables – 9to5Google

The Galaxy Z Fold 7, Flip 7, and Flip 7 FE were just announced, set for pre-order, and launched within the last month. Just a few days after the official, widespread launch, Samsung is pushing a software update to these devices, including the Z Fold 7.
The Galaxy Z Fold 7 and Flip 7 are Samsung’s best foldable, and they’ve done a lot to improve on a design that showcased what these phones are capable of, while bringing some key design changes that make themmore viable.
Just days after the release, Samsung is rolling out a couple of firmware updates for these devices. That includes both the standard Galaxy Z Fold 7 and Flip 7, as well as the Flip 7 FE. The updates fall under versions F966BXXS2AYGG, F766BXXS2AYGD, and F761BXXS2AYG5 (via SamMobile).
It appears the Z Fold 7 and Flip 7’s firmware updates are relatively small, and they offer little in the way of information or details. Most notably, improved security is mentioned. There’s little beyond that.
These types of updates are common right after a launch. Once the device gets into the hands of thousands, Samsung can easily identify larger security threats and start producing solutions on a wider scale. The update doesn’t offer anything in the way of new features.
It was already noted that larger updates with UX and UI features would come out during Galaxy S series launches, per previous information from the company. That’s even with foldable now being the debut device for the upcoming One UI versions.
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What’s new in Android’s August 2025 Google System Updates – 9to5Google

The monthly “Google System Release Notes” primarily detail what’s new in Play services, Play Store, and Play system update across Android phones/tablets, Wear OS, Google/Android TV, Auto, and PC. Some features apply to end users, while others are aimed at developers.
The following first-party apps comprise the “Google System”:
A feature appearing in the changelog does not mean it’s widely available. Some capabilities take months to fully launch.
Account Management
Security & Privacy
Utilities
Wallet
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Editor-in-chief. Interested in the minutiae of Google and Alphabet. Tips/talk: abner@9to5g.com

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Best Free AI Training Courses for August 2025 – tech.co

We live in the time of AI, and its power seems inescapable.
Just to list a few recent headlines about the impacts of AI on the business world: Lawyers are using the tech to (reportedly) boost productivity by 34% to 240% across six legal workflows, a huge 84% of software developers say they use or plan to use AI tools in their workflow (despite listing some trust issues), and AI investments are surging even while VC funds overall drop.
In other words, we can’t overthrow our robot rulers just yet. In the meantime, it might help to understand them a little better.
White collar workers everywhere have had a few years to pick up some AI skills, but if you’re a holdout, the good news is that you won’t have to invest very much energy into learning the basics.
Here, we’ve rounded up a wide range of online training courses. Some are just a few hours long, while others will take several months to complete. The only thing linking them all is that you can complete them in your own time, from anywhere with an internet connection, and all without paying a cent.
⏰Length: 4-8 hours
It’s right there in the title: This one’s a great starter course for AI newbies who just need to understand the basics in order to upskill and keep their career on track.
 
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IBM’s long history in computing makes them a natural fit for designing and running this course, which walks its students through AI applications, use cases, and the definitions of AI concepts such as machine learning, deep learning, and neural networks.
It also discusses the ethics concerns behind AI bias and how the technology impacts broader society.
The four modules will only take a few days to work through, with no technical background required. It’s popular, too, with over a quarter of a million people enrolled at one point or another.
Head over to the edX platform to try out this free course today.
⏰Length: 2 hours
Plenty of workers already have an understanding of how to communicate with a generative AI chatbot. If that’s you, perhaps you’re hoping to gain more of an edge in the competitive “knowing how to use AI” corner of the business world. This more specific course can do the trick.
Over the course of just a couple hours, Codeacademy will teach users how to navigate the OpenAI API — the building blocks that any developer can use to create a new AI-powered app.
This particular course shows users how to use the Python coding language to discover API key authentication, gain access to API endpoints, and model configurations, among other tasks.
If you have a little bit of coding knowledge (and plenty of other free online courses can help with that), this course will help you craft a custom AI app for your company or your entrepreneurial pursuits. If you already have a vision for an app, you might be able to have a working beta turned out by the weekend.
Check out the course and get started over on Codeacademy here.
Length: 9-15 hours
Marketing and AI have an up-and-down relationship: On the one hand, 77% of Chief Marketing Officers have already adopted genAI for at least some creative development tasks, according to one study. However, another 27% of CMOs are limiting or completely avoiding the use of generative AI on their teams.
If you’re working under one of those 77% that are into the concept however, you might want this intro to digital marketing with AI. The course will take you through real-life applications and the key factors for successfully integrating AI with marketing strategies, along with a discussion of the risks and challenges that have led some CMOs to turn away from the idea.
Once you’re through with the course, you’ll even emerge with “advanced prompt engineering techniques for optimizing AI-generated content for specific marketing objectives.”
Offered through an international collaboration between Guatemala City’s Galileo University and North Carolina’s Davidson College, this course is available to all. It’s a great fit for a busy worker, too, since it should take you about 3 weeks to complete, with about 3-5 hours per week.
Check out the course on edX over here.
⏰Length: 80 hours
At a whopping 80 hours of commitment required, this is our longest course recommendation in this guide. In fact, it’s technically a three course series: The modules include “Supervised Machine Learning: Regression and Classification,” “Advanced Learning Algorithms,” and “Unsupervised Learning, Recommenders, Reinforcement Learning.”
Not only will you learn how machine learning works, but you’ll gain the “techniques to build real-world AI applications,” thanks to this collaboration between DeepLearning.AI and Stanford Online.
Best of all, your instructor is Andrew Ng, a top AI guru who cofounded and ran Google Brain, among many other AI-related accolades.
Be warned: The course is listed as “Beginner level,” but that means you’ll be expected to have a little coding knowledge before you start. If it’s for you, head over to Coursera and get started today.
⏰Length: 12-20 hours
This course isn’t solely dedicated to AI. Instead, you’ll superpower your digital marketing abilities with a whole host of tools for data analysis within the field. AI and big data applications can be included with and bundled into SEO and paid search strategies, web analytics, and online testing.
It’s another reminder that AI tools aren’t great by themselves. Only when used intelligently and combined with tried-and-true strategies can you actually glean a little extra productivity from them. Here’s how the course intro explains it:
“Businesses today have access to an increasingly large amount of detailed customer data, and this influx of “big data” is only going to continue. […] Using real-world applications from various industries, this course will help you understand the tools and strategies used to make data-driven decisions that you can put to use in your own company or business.”
Available as part of Maryland Smith’s Digital Marketing Professional Certificate, this course can be audited online here, and will just take four weeks to complete with just three to five hours per week.
Perhaps you’re a worker just hoping to retain your job as the US economy drifts closer towards a recession. If so, hopefully the selection of online courses above can do the trick.
If you own or manage your own company, however, and want to make sure you’re not missing out on AI-powered growth or cost-cutting, than maybe you’d prefer taking a look at our guide (and free template) for creating your own AI business policy.
Other guides worth checking out include our walkthrough on how to best spot AI cyber attacks, or how to stop ChatGPT from training on your data.
We’ve also rounded up other free AI training courses in the past, so check our archives for even more suggestions.
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How to build a long-term, search-first marketing strategy – MarTech

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“There are roughly three and a half billion Google searches made every day,” said Craig Dunham, CEO of enterprise SEO platform Deepcrawl, at our recent MarTech conference. “According to research from Moz, 84% of people use Google at least three times a day, and about half of all product searches start with Google. The way that consumers are engaging with brands is changing, and it’s doing so rapidly.”
He added, “Consumers begin their journey with the tool that many of us use hundreds of times a day. Thus, the connection to revenue becomes clear — it starts with search.”
The concept of digital transformation has been around for years, but it’s taken a whole new form in the wake of recent societal shifts. New technologies and the 2020 pandemic have led to a “greater focus on the need to drive optimal digital experiences for our customers,” says Dunham.
A brand’s website is often the first, and most lasting, impression customers will have of your organization. Here are some strategic actions he recommends marketers take to ensure their online properties are optimized for the search-first age.
“The website is a shared responsibility and it requires proper strategic leadership,” Dunham said. “The first step is to take some time and educate yourself, your leadership, your board and your organization so they more broadly promote organic KPIs as business-wide objectives.”
“There’s great data out there on the impact of the efficiency of SEO as a low-cost acquisition channel,” he added.
Aside from sharing communication from Google on the importance of search from a business perspective, marketers can look for case studies from reputable organizations to encourage search prioritization. This can help higher-ups start seeing organic traffic as a key business metric.
“I was in a meeting recently and I had a digital leader say to me that you know website performance should not be an SEO metric — it has to be a business metric,” he said.
“Much of the data and insight generated by CEOs and their tools today are rarely utilized to their full potential,” Dunham said. “This is in part due to SEO not being seen as a business priority. As a result, it’s been siloed — pulling in teams from across the organization breaks down those silos.”
The more team members are involved with search processes, the more they’ll see its impact. People from each department will have more opportunities to contribute to growing online visibility using their unique skillsets.
“We know that businesses that are able to implement these organizational-wide search operations systems and practices — connecting a range of perspectives and search activities that are happening — are going to be the ones that will have a competitive advantage,” said Dunham.
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More and more brands are turning to automation tools to streamline tasks. According to Dunham, these solutions can be used for search-related activities as well.
“Automation can be well-deployed within web development processes,” Dunham said. “Until recently, this technology didn’t exist.”
Brands now have access to a wide variety of automation tools to streamline SEO-related tasks. The key is to pick solutions that align with your organization’s goals and give you full control over their deployment: “There are additional risk mechanisms that can be put in place to ensure you don’t release bad code that will result in large traffic losses, ultimately driving down revenue across your critical web pages,” said Dunham.
If brands can optimize their internal process, teams and tools around organic search, they’ll increase their chances of achieving long-term success in the search-first digital landscape.
Watch the full presentation from our MarTech conference below.
What is SEO? Search engine optimization encompasses a wide range of marketing activities, including content marketing, user experience strategy, technical analysis, and more, all with the goal of increasing the traffic websites receive from search engines.
What do the tools do? SEO platforms help marketers draw more insights from their work. They offer capabilities such as rank-checking, advanced keyword research, competitive intelligence, and backlink analysis. What’s more, enterprise-level platforms take these functions to new heights with extensive auditing and analysis of page performance, making it easier to find key areas needing improvement.
Why we care. SEO has remained one of the key foundations of digital marketing for years. Search drives roughly 50% of website traffic on average, according to a study on SimilarWeb data by Growth Badger. And while marketers have developed strategies to keep up, SEO’s growing complexity has made this a more complicated marketing discipline that companies cannot afford to ignore.
Dig deeper: What do SEO platforms do and how do they help marketers get found on search engines?
Contributing authors are invited to create content for MarTech and are chosen for their expertise and contribution to the martech community. Our contributors work under the oversight of the editorial staff and contributions are checked for quality and relevance to our readers. MarTech is owned by Semrush. Contributor was not asked to make any direct or indirect mentions of Semrush. The opinions they express are their own.
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Google addresses six vulnerabilities in August’s Android security update – CyberScoop

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Google addressed six vulnerabilities affecting Android devices in its August security update, marking a months-long lull in the number of software defects disclosed and patched in the mobile operating system this summer.
The company issued no security patches in its update last month. Yet, monthly Android security bulletins typically address dozens of vulnerabilities. Google’s Android security update covered 34 vulnerabilities in June, 47 defects in May, 62 in April and 43 in March.
The summer break suggests Android partners and customers have experienced a temporary respite from a larger pool of vulnerabilities. Google notifies Android partners of all software defects affecting the mobile operating system at least a month before public disclosure.
Google said the most severe defect in this month’s security update — CVE-2025-48530 — is a critical remote code execution vulnerability in the Android system that doesn’t require user interaction or additional execution privileges for exploitation. 
The advisory also addressed two high-severity vulnerabilities — CVE-2025-22441 and CVE-2025-48533 — affecting the Android framework. Google said user interaction and additional privileges aren’t required to exploit the elevation of privilege defects.
None of the vulnerabilities addressed in this month’s security update are under active exploitation, according to Google. The company hasn’t included an actively exploited defect in its monthly batch of patches since May.
The Android security update contains two patch levels — 2025-08-01 and 2025-08-05 — allowing Android partners to address common vulnerabilities on different devices.
The second patch includes fixes for a high-severity vulnerability affecting Arm components and two vulnerabilities in Qualcomm components.
Third-party Android device manufacturers release security patches on their own schedule after they’ve customized operating system updates for their specific hardware.
Google said source code patches for all six vulnerabilities addressed in this month’s security update will be released to the Android Open Source Project repository by Wednesday.

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Forget What You Know About Search. Optimize Your Brand for LLMs. – hbr.org


Over the past year, consumers have migrated en masse from traditional search engines to Gen AI platforms including ChatGPT, Gemini, DeepSeek, and Perplexity. In a survey of 12,000 consumers, 58% (vs. only 25% in 2023) reported having turned to Gen AI tools for product/service recommendations. Another study reported a 1,300% surge in AI search referrals to U.S. retail sites during the 2024 holiday season.
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