What Google Material 3 Expressive redesigns are rolling out [Updated] – 9to5Google

Google announced its new design language in May. Material 3 Expressive redesigns have been rolling out to Google apps since then, but the Pixel 10 and Android 16 QPR1 launch really kicked things off. Here’s our list of what’s available and still to come on Android phones.
Updated 9/27: Refer to the table for what’s New and Updated.
The next phase of Gmail’s redesign is placing each message on the homepage in a container, with a narrow left/right border now existing.
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On the main browsing interface, a partitioned Material 3 progress indicator is now used. Circular containers are leveraged for the top row of actions in the overflow menu. In the Tab Grid, the new tab button and standard/Incognito/Groups switcher are placed in containers. Google is also prominently theming the frame of Tab Group cards with the color you’ve selected.
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“Wallet” has been replaced by the app logo in the top-left corner, while the list of passes below the carousel makes use of thicker cards. Containers are leveraged throughout the app including the Add to Wallet and Recent activity page.
The NFC tap-to-pay animation is getting M3 Expressive. The background is now translucent with your card jumping up and down as part of a more animated success animation. Google is also introducing a new overlay for Pixel users with the double-tap power button gesture.
Google Drive has removed the main list view container for an edge-to-edge design.
Old vs. new
The new fullscreen Quick Share experience takes full advantage of Material 3 Expressive.
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Listings in Google Maps now make use of M3 Expressive containers to better group information. Additionally, the actions carousel more consistently appears at the bottom of your screen.
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(In alphabetical order)
Just the main page for this “app” (within Settings) has been updated with M3 Expressive. Besides containers, the donut graph is thicker. This is rolling out with beta version 1.30.x.
There’s an animated Material 3 carousel on the homepage with a pill-shaped toolbar for Quick Share and document scanning, while a navigation rail is now leveraged. When opening an image, there’s a toolbar for editing and Circle to Search. List views have larger previews at the left.
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There’s a shorter bottom bar, while the sheet features more prominently rounded corners. One nice usability is how device pins are now larger.
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Your list of emails and the actual message are placed in a container, while there’s a prominent pill-shaped animation when using the swipe gestures. Meanwhile, a search app bar sees the hamburger button and profile menu move out of the pill-shaped field.
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Version 9.0 hides the row of scientific functions, while there’s now a history button (but the slide down gesture remains).
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Time slots (hours and days) are placed in their own rounded container throughout the app’s various views (Day, Week, Month). This replaces the faint lines used previously, while there’s now a solid background layer in the primary Dynamic Color. More
Additionally, a FAB menu is now leveraged for Event, Task, Out of office, and Birthday creation.
Widgets will get a pill-shaped button in the top-right corner, while most views drop the two-column layout.
Like Gmail, Google Chat makes use of a chat app bar and places the list of messages in a container. The floating toolbar leverages a pill to highlight what tab you’re currently viewing, while the chat interface places the ‘plus’ menu in a vertical pill.
Version 8.1 is rolling out with a shorter bottom bar and a new font, while it’s now a rounded square FAB at the right.
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This straightforward redesign places everything in containers, while the bottom bar is now shorter. There are also color tweaks to the app’s background.
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The updates in these three apps specifically apply to the editor interface with the new Material 3 Expressive progress indicator when waiting for documents to load. Pill-shaped buttons are used throughout, while the Format sheet is thoroughly modernized, including with the split button component.
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This redesign gets a search app bar, short bottom bar, FAB menu, and button groups, while each line item is placed in a container.
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The camera scanner is getting a redesigned editor that leverages Material 3 Expressive.
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Google Keep makes use of the new M3 Expressive search app bar component that moves the hamburger button and profile switcher outside of the search bar, which is now thicker. The other main update is on the notes page with all buttons (Archive, ‘plus’ menu, overflow, etc.) placed in containers.
Wide
Google Meet is the first app to have widely rolled out a Material 3 Expressive redesign. On the homepage, each call is placed in a large/tall card as part of M3E’s heavy use of containers.
The pre-call screen sees more M3 Expressive with very large voice and video call buttons that seem out of proportion. The name, picture, and email address of who you’re calling is placed in a pill and centered at the top. Various buttons go from circles to rounded squares.
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The list of conversations and message thread itself is now placed in containers. Google has also redesigned the ‘plus’ menu with all the buttons placed in pills. Other parts of the app getting Material 3 Expressive include New chat, Search, and Settings.
More23
The app switches to a shorter bottom bar, while the cards (and Settings) are placed in more prominent containers. Meanwhile, Google One has removed its infographics for a denser app.
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There’s a new search app bar with the Password Manager in the top-left corner. Filters for All, Passwords, Passkeys, and Network devices make a nice functionality update, while credentials are placed in containers.
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A new backup indicator at the top of the app replaces “Google Photos.” On launch, you briefly get a logo that animates into “Backup complete.” You can drag down (pull-to-refresh) to see cycling Material 3 Expressive shapes on a background layer that also notes how much you have stored in the cloud. When something is backing up, there’s a wavy progress indicator.
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The Google TV app has a short bottom bar with a white accent color that is also used in three of the four tabs for the search pill. In the For you tab, that button is themed based on the media carousel.
Meanwhile, the remote gets updated button shapes. There’s also a morphing split button at the top for the device menu.
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The Pixel Tips app is now called “My Pixel” and gets a complete overhaul that adds support options and a full Google Store.
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Compared to other apps, Phone by Google is using Material 3 Expressive as an opportunity for a complete overhaul. The bottom bar goes from four tabs to three with Favorites and Recents becoming “Home.” There’s a new “Keypad” tab that replaces the FAB, while “Voicemail” is unchanged. Contacts can now be found in a navigation drawer. All calls and lists (including Settings) make use of containers.
The Incoming and In-Call screens feature updated buttons with larger touch targets. You can pick between Horizontal swipe or Single tap.
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The big update is to the Equalizer and how you customize Bud gestures.
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This Material 3 Expressive redesign aims to greatly simplify Recorder. For example, there’s an overflow sheet for the vast majority of actions on the recording page. The capture interface has also been simplified.
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There’s now a rounded square FAB and other M3 Expressive tweaks.
Besides dropping the “preview” status, Pixel Studio 2.0 introduces a new image editor that replaces Markup in most instances. Featuring a Material 3 Expressive design, crop, draw/highlight, and caption are joined by generative AI tools. You can make stickers, erase, and change a selected part using prompts.
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Is it just me or is all of this a bit underwhelming? Looking at the presentation at I/O I expected more, bigger, bolder shapes and colors. Some of these changes are so small I really have ro squint to see any change at all :/
Pill-shaped containers replace the circular buttons.
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The Pixel Weather homepage expands the size of the city cards. You go from being able to see 10 locations to just six, but the high and low is now included. There are minor tweaks in the city view, with the big update being native homescreen widgets.
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8 SEO Courses That Actually Teach You SEO (Free + Paid) – Backlinko

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Written by Ankit Vora
Most SEO courses suck.
They’re outdated, too basic, or packed with theory that falls apart in the real world.
And in 2025, when search is evolving faster than ever, wasting time on the wrong course isn’t just frustrating — it can seriously stall your growth.
Whether you’re learning SEO to grow a business, land a job, or get better at your current one, you need training that’s current, actionable, and taught by people who actually do SEO.
That’s why we spent 50+ hours testing and evaluating 20+ SEO courses (free and paid) to find the ones that are actually worth your time.
Our top pick for 2025? Semrush Academy, which offers up-to-date, expert-led SEO training at no cost.
You get both foundational skills and advanced strategies — plus a certificate for every course you complete.
Not to mention their AI SEO course is coming soon, and the Backlinko team has contributed to it. Visit the Academy to check out the other courses right now and be notified for when it launches.
In our searching for great SEO courses, we found 7 other programs — some free, some paid — that deliver, too. Each one teaches practical skills you can apply immediately, so it all comes down to what course is the best fit for your particular needs.
But first, let’s clear up a common question:
Kind of. But not for the reason you think.
An SEO certification is official recognition of your search engine optimization knowledge, earned by completing a course and passing an assessment. It’s basically proof you’ve completed a course and passed a test that says, “I understand how SEO works.”
And for some people, that is valuable — especially if you’re just starting out or applying for entry-level roles.
Bottom line: the certification itself isn’t the goal. The structure, guidance, and real-world skills you build along the way—that’s what actually matters.
Free or paid doesn’t matter — employers care about your SEO skills, not how much you spent on training.
Look for courses with hands-on projects and experienced instructors who have proven SEO results. Student reviews and community access are valuable bonuses.
Remember: A certification just shows you’ve invested time in learning SEO. Your ability to drive results is what matters.
Now, let’s explore the best SEO courses available in 2025.
We’ve narrowed down our top SEO courses and certification list to the following:
Semrush Academy is a great place to start.
It’s home to some of the most value-packed digital marketing courses on the internet.
The Semrush Academy team closely collaborates with industry leaders (both external and in-house) to produce informative, engaging, and insightful courses.
Semrush Academy offers a wide range of courses, catering to digital marketers at every level of expertise, from beginners to advanced training, ensuring they grasp core concepts and gain a deeper understanding of cutting-edge industry practices.
For example, Semrush partnered with Kevin Indig, an SEO genius who helped G2 scale their organic traffic from 3M to 5M and led a team of 25 SEOs at Shopify to produce a highly informative and actionable course on SEO strategy.
Kevin’s training is just an appetizer.
As of 2025, the Semrush Academy has more than 15 value-packed SEO courses.
Check these out:
Upon completing these courses, you can participate in their respective assessments. If you pass, you’ll receive a personalized and downloadable certificate.
Like this:
Here’s a review of Semrush Academy on LinkedIn:
“I’d highly recommend the Semrush Academy courses to anyone of any level in #marketing or who has a general interest in the area. I’ve found them to be very accessible, with short, to the point, yet informative videos with transcripts/subtitles.” – Louise Frost DipGAI
Google SEO Fundamentals is a great course for SEO beginners.
This course has been created by the University of California, Davis, and is available on Coursera.
The training comprises 28 videos divided into the following four modules:
The course takes 11 hours to complete. Meaning it requires a reasonable time investment.
However, it’s worth it. And if you’re a beginner looking to master SEO basics, you should definitely give it a try.
This course has four assessments. After passing them, you’ll receive a personalized and downloadable career certificate.
Like this:
Here’s a review on Coursera:
“Excellent course. Really breaks down all aspects of on-page, technical, and off-page SEO in an understandable, easily-digestible, and applicable way. The instructor was great and easy to follow. The additional readings, recommended resources, and suggested tools were extremely helpful if you want to dig deeper into more advanced aspects of SEO.” – Jordan Y.
HubSpot’s SEO Certification Course is ideal for you if you want to learn and understand the fundamentals.
This course comprises 26 videos divided into six modules and takes about four hours to complete.
You’ll learn:
The course also includes five quizzes to test your knowledge.
After completing the course, you’ll earn a personalized and downloadable certification like this:
A genuine customer review couldn’t be found for this course.
Alex Genadinik’s SEO Training Masterclass is one of the most popular and comprehensive paid SEO courses on Udemy, with more than 10,000 ratings and 100,000 students.
It’s a massive 18+ hour course with over 280 video lectures divided into 44 sections.
These lectures cover everything from keyword research to how to use SEO tools to URL structure for SEO, backlink strategies, local SEO and more.
Despite its comprehensive scope, Alex has skillfully structured the course.
So that you can effortlessly navigate through it or watch it without feeling lost or overwhelmed.
After completing the training, you’ll also earn a certificate of completion that you can display on professional platforms.
Like this:
The course also has dedicated sections to help you become a freelance SEO specialist, get a full-time job, or build an SEO agency.
The SEO Training Masterclass 2025 by Alex Genadinik is way better than many other courses on this list. It dives deep into the nitty-gritty of SEO and provides a practical approach.
Here’s a review of the SEO Training Masterclass on Udemy.
“This is an excellent course. It’s in-depth and provides a lot of different avenues towards improving your SEO with unique strategies and easy-to-follow instructions.” – Cassandra I.
SEO Essentials Certificate course is a six-part course offered by Moz.
If you aren’t familiar with Moz, it’s a popular all-in-one SEO platform.
It’s ideal for beginners as it covers:
Each course section has quizzes to test your knowledge along the way.
The final part of this course includes an assessment that you need to pass to earn your Moz SEO Essentials Certification.
Like this:
Moz SEO Essentials teaches you how to apply your newly learned skills using Moz’s paid SEO tool called Moz Pro. So if you’re looking to use any other tools, this course may not be the right fit for you.
Also, its $595 price tag may be just too much, especially if you have a tight budget. Many free courses on this list offer similar educational value. So that’s something to consider as well.
For this course, a genuine customer review was not available.
Matt Bailey’s Advanced SEO Certification Training is a high-value SEO course that dives deep into the fundamentals, search engine algorithms, different SEO strategies, and content marketing. It’s available on MarketMotive, a respected online marketing training and certification company.
This course offers 30+ hours of video content and 15+ hours of live instructor-led online classes.
You can get your certification by:
Here is a course review from their site:
“Now that everyone knows what the SEO factors are, we are making clear decisions that boost our online presence collectively as a team.” – Lorna Li
Backlinko isn’t technically structured as a course, but we’ve designed the content to essentially be a course replacement, providing the fundamental and up-to-date SEO knowledge you need to be an effective practitioner.
 
We’re striving to be on the cutting edge of AI Search, with new guides, playbooks, and helpful templates published every month.
With 9 guides about SEO fundamentals alone, as well as more than 400 resources on topics spanning from LLM seeding to content strategy development, we publish a wide breadth of content about every subtype of SEO you can imagine.
Perhaps even more useful is our templates library, where you can take what you’ve learned and get started executing ASAP. Here are some example templates we offer:
Here’s a review of Backlinko on G2:
“The blog articles, guides, and videos published on the site provide valuable insights and practical tips for improving website rankings and traffic.” – Prema Toppo
Similar to Backlinko, LearningSEO.io isn’t technically a course, but it easily could be, as it’s jam-packed with resources.
It bills itself as a comprehensive SEO roadmap, offering a structured pathway for learning SEO from the fundamentals and onward.
The site was created by Aleyda Solis, a respected international SEO consultant who has spoken at countless conferences and shared endless numbers of free resources with the greater industry. In creating LearningSEO.io, she essentially compiled resources from across the industry’s brightest minds to create an organized hub.
Take a look to see if there are any knowledge gaps you need to fill.
For this site, a genuine customer review was not available.
When evaluating SEO courses, focus on what your goal is.
If you want to dominate your local rankings, Semrush Academy’s “How to Outrank Your Competition in Local Search” is a must-watch.
Alex Genadinik’s SEO Training Masterclass is a great choice if you want to learn SEO from scratch without feeling overwhelmed.
If you’re not sure where to start, try a fundamentals course and then layer on specific subsets of SEO training.
And whatever you choose, good luck, and happy learning!
Backlinko is owned by Semrush. We’re still obsessed with bringing you world-class SEO insights, backed by hands-on experience. Unless otherwise noted, this content was written by either an employee or paid contractor of Semrush Inc.
Backlinko turns AI SEO into clear, actionable strategies with step-by-step frameworks and examples to help you rank in an AI-driven search world. Think less guessing, more visibility.
© 2025 Backlinko is a Trademark of Semrush Inc

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New Study Confirms SEO as Most Effective Digital Marketing Strategy – citybuzz –


A comprehensive study by market research firm Digital Insights has confirmed that Search Engine Optimization remains the most critical component of digital marketing success, with 75% of surveyed marketers identifying it as their most effective strategy for customer targeting and website traffic generation. The research, which involved over 1,000 marketing professionals and business owners, underscores SEO’s continued dominance in an increasingly crowded digital marketplace where search engines serve as the primary gateway for consumer discovery.
The findings highlight that businesses prioritizing SEO transition from online obscurity to industry leadership positions, according to company president Jane Smith. ‘In today’s digital-first world, neglecting SEO is akin to shutting your doors to potential customers,’ Smith stated, emphasizing that strategic SEO investment consistently delivers superior return on investment compared to traditional marketing approaches. The study positions SEO not merely as a technical exercise but as a fundamental business strategy essential for sustained digital presence.
Critical to SEO success is the symbiotic relationship between optimization techniques and high-quality content creation. Businesses that combine robust SEO practices with valuable, audience-relevant content demonstrate significant improvements in both search engine rankings and consumer trust metrics. ‘Content is king, but good SEO is the queen that keeps it all together,’ Smith added, pointing to the interconnected nature of content quality and discoverability in achieving marketing objectives. This dual approach ensures that businesses not only attract visitors but also convert them through trustworthy, engaging material.
As organizations prepare their marketing budgets for the coming year, the study serves as a crucial reminder that SEO investment directly correlates with competitive advantage. With search engines processing billions of queries daily, optimized visibility translates to measurable business outcomes including increased lead generation, higher conversion rates, and strengthened brand authority. The research validates that companies maintaining consistent SEO efforts establish durable online footholds that withstand market fluctuations and evolving consumer behaviors. For comprehensive digital marketing resources, visit Google’s search platform for additional information on optimization techniques.
This news story relied on content distributed by Press Services. Blockchain Registration, Verification & Enhancement provided by NewsRamp™. The source URL for this press release is New Study Confirms SEO as Most Effective Digital Marketing Strategy.

© Copyright 2012 – 2023 | citybuzz | All Rights Reserved

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YouTube Shorts Remix gains AI-powered Extend feature for creators – PPC Land

YouTube introduces artificial intelligence-powered remixing tool that allows creators to generate new video segments for existing Shorts content.
YouTube announced on September 26, 2025, the launch of Extend with AI, a new feature that enables creators to add artificial intelligence-generated segments to existing Shorts videos. According to Meaghan from TeamYouTube, the feature provides creative suggestions to help users add new segments to eligible Shorts, expanding the platform’s remix capabilities beyond traditional editing tools.
The new capability allows creators to select moments from existing Shorts and choose from AI-generated prompts that describe potential continuations. Once a creator picks a video segment up to 5 seconds in length and selects a suggested prompt, the system generates a new segment that can be incorporated into their own Short. The remixed creation becomes a new Short while preserving the original creator’s video unchanged.
Most Shorts that have opted into video remix features qualify for the Extend with AI functionality. Creators who prefer to exclude their content from AI remixing can opt out following existing instructions within YouTube’s creator settings. The feature builds upon YouTube’s established remix tools, including the Cut feature that already allows creators to add their own endings to Shorts.
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The Extend with AI feature generates video segments typically lasting 8 seconds or less. Creators can trim these generated segments directly within Shorts Creation tools to achieve their desired length. During the preview stage after draft generation, users can add music from YouTube’s curated audio track library or return to the camera interface to record additional video content.
The system generates prompts based on the specific video content selected for remixing. This tailored approach ensures that suggested continuations align with the original video’s context and style. Creators can reorder clips within the editing interface and combine AI-generated segments with traditionally recorded content.
Generated videos receive an AI label in their description, consistent with YouTube’s labeling practices for other artificial intelligence tools within the Shorts ecosystem. Every Short created using Extend with AI links back to the original creator’s video from the Shorts player, providing discovery opportunities for both the original creator and the remixing creator.
Extend with AI will roll out gradually to all countries outside the European Union and United Kingdom over the coming months. Initially, the feature operates exclusively in English, with YouTube planning to expand both language and country availability in future updates. The phased rollout approach mirrors YouTube’s deployment strategy for other Shorts features, allowing for technical optimization and user feedback integration.
The feature’s exclusion from EU and UK markets aligns with recent regulatory considerations affecting AI-powered content generation tools. YouTube has faced scrutiny over AI enhancement practices that modify creator content without explicit consent, prompting more careful implementation approaches in regulated markets.
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YouTube’s introduction of Extend with AI represents the latest advancement in the platform’s artificial intelligence integration strategy. The company previously launched Dream Track, which generates instrumental soundtracks for Shorts using AI technology, and Dream Screen, enabling AI-generated video backgrounds through text prompts.
The timing coincides with YouTube’s extension of Shorts duration from 60 seconds to 3 minutes in October 2024, providing creators with expanded creative possibilities. These duration changes affected videos uploaded after October 15, 2024, with a gradual rollout process spanning several weeks.
Recent updates to Shorts editing capabilities have included layout modification features for converting long-form clips and enhanced remix options. The platform has also introduced template functionality, allowing creators to recreate popular Shorts formats while adding personal elements.
The Extend with AI feature complements YouTube’s existing remix toolset, which includes audio remixing, video cutting, green screen backgrounds, and collaboration features. Creators can already remix content from music videos, extracting audio tracks, using green screen backgrounds, or creating collaborative content alongside original videos.
YouTube’s remix capabilities have extended to official music videos from major artists, enabling creators to use snippets as soundtracks or visual elements in their own content. The platform’s integration with Official Artist Channels provides access to popular sounds sections where creators can sample audio for their Shorts.
All remixed content maintains attribution to original creators through direct linking in the Shorts player. This attribution system ensures that popular remixes can drive viewership back to source videos, creating mutual benefits for both original creators and remixing users.
The introduction of AI-generated content continuation presents new opportunities for overcoming creative blocks while maintaining personal creative expression. The feature specifically targets moments when creators experience inspiration from existing content but struggle to develop continuation concepts independently.
YouTube’s implementation emphasizes collaboration between human creativity and artificial intelligence assistance rather than complete automation of content creation. Creators retain control over prompt selection, segment timing, and final editing decisions while benefiting from AI-generated visual elements.
The feature’s impact on content discovery patterns remains to be observed as creators begin incorporating AI-generated segments into their content strategies. YouTube’s algorithm recommendations for AI-enhanced content may influence which remixed Shorts gain prominent placement within the platform’s discovery systems.
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YouTube’s expansion of AI-powered creation tools occurs alongside developments in Shorts advertising capabilities. The platform has integrated Shorts ads into efficient reach line items within Display & Video 360, automatically including Shorts inventory in advertiser campaigns seeking maximum reach.
Recent changes to Shorts view counting methodology implemented on March 31, 2025, removed minimum watch time requirements, potentially affecting how AI-enhanced content performs within YouTube’s metrics systems. However, monetization eligibility continues to rely on engaged views rather than total view counts.
The platform’s Creator Fund and revenue sharing programs for Shorts creators remain based on traditional engagement metrics rather than AI enhancement utilization. This approach maintains focus on audience interaction quality over technological tool adoption.
YouTube’s Extend with AI launch positions the platform competitively against TikTok’s AI-powered creation features and Instagram’s Reels enhancement tools. The integration of Google DeepMind’s technology provides YouTube with advanced AI capabilities that distinguish its offering from competitors relying on third-party AI providers.
The feature’s attribution requirements and opt-out mechanisms address creator concerns about unauthorized content usage that have emerged across social media platforms implementing AI features. YouTube’s approach emphasizes transparency and creator control over content utilization, potentially setting industry standards for responsible AI implementation.
The gradual rollout strategy allows YouTube to monitor creator adoption patterns and technical performance before full global deployment. This measured approach reflects lessons learned from previous feature launches that experienced scaling challenges or creator resistance.
Subscribe PPC Land newsletter ✉️ for similar stories like this one. Receive the news every day in your inbox. Free of ads. 10 USD per year.
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Who: YouTube creators and the TeamYouTube team, specifically Meaghan from TeamYouTube who announced the feature
What: Launch of Extend with AI, a new feature allowing creators to add AI-generated video segments to existing Shorts using creative prompts and machine learning technology
When: Announced on September 26, 2025, with gradual rollout beginning immediately over the coming months
Where: Available globally except in European Union and United Kingdom markets, initially in English language only
Why: To help creators overcome creative blocks, expand remix capabilities, and provide new tools for content creation while maintaining attribution to original creators and enabling new audience discovery opportunities

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Google's Gemini 2.5 Flash Lite is now the fastest proprietary model (and there's more big Gemini updates) – VentureBeat

Google’s Gemini 2.5 Flash Lite is now the fastest proprietary model (and there’s more big Gemini updates)  VentureBeat
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What the AI Visibility Index tells us about LLMs & search – Search Engine Land

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Generative AI is reshaping how people search and discover information, making traditional SEO metrics like rankings and click-through rates incomplete. 
To address this, Semrush’s AI Visibility Index provides a holistic view of marketing visibility, layering LLM visibility data alongside traditional search. It reports on both global insights and industry-specific breakdowns, helping marketers see the bigger picture of where their brands stand.
The numbers speak for themselves: ChatGPT alone sees over 800 million active users weekly and more than 2.5 billion prompts daily, much of which is invisible to conventional analytics. That’s a lot of potential audience engagement. 
With AI-powered search experiences—from Google’s Search Generative Experience to ChatGPT, Claude, and Perplexity—brands now need to think about “LLM visibility,” or how often they surface in AI-generated responses. Understanding and optimizing for this new dimension is quickly becoming a core part of brand tracking and digital strategy.
It’s tempting to think that if you’re crushing it at E-E-A-T, you’ll see killer rankings in the SERPs and you’ll be frequently mentioned in LLMs as well as cited as a source.
Think again. You’ll need a more refined approach.
We already know that AI frequently cites lower-ranking search results. But the way AI handles specific brands is even more nuanced. That same Index found that fewer than 25% of the most mentioned brands were also the most sourced.
Take B2B SaaS leader Zapier. The Index found that it’s the #1 cited search in digital technology and software, but only #44 in brand mentions.
What are LLMs picking up on? The answer lies in the types of assets associated with the brand’s presence. Zapier maintains a large library of integration guides and tutorials, giving it strong authority for AI training since it’s effectively a repository of facts. But when people talk in reviews and discussions, competing brands tend to come up more often.
Publishing a ton of content on your site alone is not enough. LLMs also rely on specific platforms as sources they’ve identified as authorities, providing a knowledge foundation. New information is compared to and understood in terms of this foundation. Your presence on these platforms can also help your visibility.
Why does this matter? A single mention in an AI response might carry more weight than a traditional search result because it’s presented as a curated, authoritative recommendation rather than one of many options. It also might reach a more motivated audience that’s closer to conversion. 
Data also shows that the weighting of sources varies by LLM as well as by industry. For example, while ChatGPT tends to rely on Wikipedia and Reddit as major sources, Google AI Mode shows way more variation.
These snapshots of industry trends are powerful starting points for your work and can help illuminate next steps for the next 90 days. But keeping close tabs on your competitors in both the SERPs and LLMs will help you not only directly outpace them, but could also give you insights into trends and headwinds.
Your Competitors Are Already Optimizing for AI Search. Are You?
Monitor how AI platforms rank you vs competitors in real-time
Discover untapped AI visibility opportunities in your industry
Track sentiment shifts across 5+ major AI platforms
See what AI says about your brand today
This checklist highlights practical steps you can start on now to make your content and brand more discoverable in AI-powered environments. From technical SEO adjustments to content rewrites and community engagement, these actions help ensure your entity is understood, cited, and trusted by both search engines and generative AI platforms.
AI-driven crawlers such as GPTBot (OpenAI), CCBot (Common Crawl), and Claude-We (Anthropic) function similarly to traditional search engine bots, but their role is to feed information into large language models. 
If your robots.txt file accidentally blocks them, whether through overbroad disallow rules or inherited directives, you’re effectively shutting the door on your content being indexed for use in generative AI platforms. 
This doesn’t just affect training data; it also limits your chances of being surfaced in real-time responses, summaries, and AI-powered search features. 
Regularly auditing your robots.txt file, testing crawler access, and aligning permissions with your visibility goals helps ensure that your brand’s knowledge remains accessible where discovery increasingly happens: inside AI-driven engines and assistants.
Many AI systems, like traditional crawlers, still have difficulty parsing client-side rendered content that depends heavily on JavaScript. If your critical text, product information, or structured data only appears after scripts execute, there’s a strong chance it won’t be fully captured or indexed by AI crawlers. Server-side rendering (SSR) solves this by delivering pre-rendered HTML directly from the server, ensuring that the essential content is visible at the time of crawl. 
This approach not only improves accessibility for AI systems like ChatGPT or Perplexity but also enhances performance for users on slower connections. By implementing SSR for high-value pages—such as product detail pages, core service offerings, and FAQ hubs—you create a consistent, crawlable foundation that boosts visibility in both traditional search results and generative AI outputs.
Using elements like <article>, <section>, <nav>, and <header> provides explicit signals about the role and relationship of different blocks of content. For example, wrapping a blog post in <article> tells crawlers this is a standalone piece of information, while <aside> can mark supporting context.
Heading hierarchies (H1 through H6) work the same way: they create a logical outline of your content. An H1 defines the page’s core topic, H2s break it into key themes, and H3s or H4s drill into supporting points. AI crawlers use these patterns to parse and extract information accurately, which directly influences whether your content can be cited in generative responses. Pages that rely only on visual styling (bold fonts, larger text) without semantic tags risk being misinterpreted or overlooked entirely.
By consistently applying semantic HTML and clear heading structures, you make your site more machine-readable, improve content extractability, and increase the odds that both search engines and AI platforms pull your information into summaries, snippets, and conversational answers.
When you test your priority topics in AI platforms such as ChatGPT, Claude, or Perplexity, you’re essentially auditing the sources those systems deem trustworthy and authoritative. Pay close attention to which competitors, publications, or data sets are consistently cited in responses. This reveals the knowledge graph you’re competing against—the ecosystem of entities, sources, and relationships that AI models use to assemble answers.
If your competitors’ blogs, research reports, or even forum contributions appear but your brand does not, that’s a signal of a content or authority gap. It may mean you need to produce more in-depth resources, pursue stronger backlinks and citations, or distribute expertise across third-party sites that AI systems favor. Over time, this type of monitoring shows patterns: which types of sources (academic studies, media outlets, niche blogs, Q&A forums) carry the most weight and where you can strategically position your brand to earn visibility.
In practice, this exercise turns AI outputs into a form of competitive intelligence, helping you benchmark your brand’s presence in generative ecosystems and prioritize the content formats and authority signals that AI models actually reward.
AI optimization (AIO) tools like the AI SEO Toolkit extend beyond traditional SEO analytics by tracking how your brand shows up inside generative platforms. Instead of just measuring keyword rankings or backlinks, these tools reveal your presence across AI assistants and AI-powered search, showing how often your brand is cited compared to competitors, what topics are working for you, and what prompt opportunities are out there. They also surface mentions in AI-generated outputs, letting you see whether platforms like ChatGPT, Claude, or Perplexity are pulling your brand into responses, and in what context.
Equally important is sentiment analysis. AIO tools can detect whether your brand is described positively, negatively, or neutrally within these generative answers. This helps you understand not only how visible you are, but also how you’re being framed in the conversations that influence decision-making. 
For example, if competitors are cited more frequently or framed more favorably, it highlights opportunities to strengthen your authority signals through better content, reviews, or media coverage.
You also see Share of Voice alongside sentiment. In traditional marketing and SEO, Share of Voice measures what percentage of the overall conversation or visibility your brand commands compared to competitors. In the world of AI optimization tools, it works the same way, but the “conversation” is happening inside generative platforms like ChatGPT, Claude, Gemini, or Perplexity.
For example, if you ask an AI assistant 100 queries in your category (say, “best project management software” or “how to reduce cloud costs”), and your brand is cited or mentioned in 20 of those answers, your Share of Voice would be 20%. The tools automate this at scale: They track how often your brand appears, how it’s positioned (top citation vs passing mention), and how that compares to key competitors.
This metric is powerful because it tells you how much space your brand occupies in AI-driven discovery ecosystems, where traditional ranking reports can’t reach. A rising Share of Voice means AI platforms increasingly trust and surface your content, while a declining one is an early warning that competitors are capturing attention in generative results. In the AI SEO Toolkit, you can dive deeper into what’s driving positive or negative sentiment and figure out what’s needed to put your brand in the best light, authentically.
In short, these tools give you a new layer of competitive intelligence—one that reflects the realities of AI search. By monitoring visibility, mentions, and sentiment, you can benchmark your standing, identify gaps, and adapt your strategy to stay discoverable and credible in the spaces where users are increasingly finding answers.
LLMs  are designed to surface clear, factual, and verifiable information. When content leans too heavily on buzzwords or vague promises—“industry-leading,” “cutting-edge,” “best-in-class”—AI systems have little substance to work with and are less likely to extract or cite it. What resonates instead are specifics: quantifiable data, well-attributed statistics, expert commentary, and case studies that provide evidence.
For example, instead of writing “Our platform improves efficiency,” you might say “Our platform reduces average processing time by 37%, based on a study of 500 enterprise clients.” Similarly, weaving in expert quotes from industry leaders or referencing reputable sources signals to AI that your content is trustworthy and grounded in fact. This not only increases your odds of being cited in AI-generated responses but also builds credibility with human readers who demand more than marketing spin.
Ultimately, the more concrete, evidence-backed language you embed in your content, the more LLMs will view it as useful material to pull into conversational answers, summaries, and overviews—directly boosting your visibility in generative search.
Adding FAQ sections to your most important pages—such as product, service, and topic hubs—bridges the gap between how people ask questions and how AI systems deliver answers. Users often type or speak their queries in a natural, conversational way (“How much does this cost?” “Is this safe for beginners?”), and AI platforms are built to recognize and respond to this Q&A structure. By anticipating these questions and embedding them into your content, you make it easier for generative models to parse, extract, and cite your information.
FAQs also help you capture long-tail queries that may not justify standalone pages but are still valuable for traffic and visibility. When optimized with clear, concise answers—and, where relevant, enriched with structured data markup—they can feed directly into AI Overviews, featured snippets, and conversational responses. This not only boosts your chances of being quoted but also positions your site as a reliable resource when users are in research or decision-making mode.
Over time, well-crafted FAQs strengthen your site’s role as a conversational authority, ensuring that both search engines and AI-driven platforms recognize your content as aligned with the way people actually ask questions.
Active participation in niche online communities like Reddit, Quora, and GitHub not only builds trust with human audiences but also increases your footprint in the sources that AI systems frequently draw from. These platforms are rich with Q&A-style content, practical solutions, and peer-to-peer insights, which are exactly the kind of material large language models index and surface in generative answers.
The key is to engage authentically. Instead of dropping links or promotional soundbites, focus on answering questions thoroughly, sharing unique perspectives, or contributing code snippets and documentation where relevant. Over time, your contributions can gain upvotes, visibility, and citations, signaling authority both to users and to AI models trained on that content.
By embedding your expertise into these high-signal communities, you effectively plant seeds of authority across the web. These contributions not only drive referral traffic and brand recognition but also increase the likelihood that your insights will be quoted, paraphrased, or referenced in AI-generated responses, extending your reach well beyond your owned channels.
Reviews act as social proof not only for people but also for AI systems. Generative models scan sentiment signals from platforms like Google, G2, Trustpilot, Yelp, or industry-specific directories, and they often incorporate those perspectives into summaries and recommendations. If most of the visible reviews about your brand are negative or if you lack reviews altogether, AI may interpret your entity as less credible, reducing the likelihood of being favorably cited in conversational search.
The solution is to proactively encourage authentic reviews from satisfied customers and manage feedback consistently. Prompting clients at the right moment in their journey, simplifying the review process, and addressing complaints constructively all help shift sentiment in your favor. Positive patterns of feedback create a reputation signal that both users and AI can trust, while thoughtful responses to negative reviews demonstrate accountability.
Over time, this builds a reputation moat: a body of credible, third-party validation that AI systems draw from when generating answers. In practice, that means your brand isn’t just trusted by human audiences; it becomes algorithmically trusted, increasing your chances of being surfaced, recommended, and cited across AI-driven platforms.
Media coverage functions as a high-value trust signal in both traditional SEO and AI-driven discovery. Mentions in reputable outlets—whether through press articles, interviews, podcast appearances, or industry features—are disproportionately influential because AI models weigh these sources more heavily than self-published content. When your brand is cited by journalists or discussed in respected media, that reference becomes part of the authoritative data pool models use to generate responses.
Strategically, this means pursuing earned media partnerships should go beyond PR vanity—it’s a visibility play in the era of generative AI. Pitching thought leadership pieces, offering expert commentary, or collaborating on podcast discussions not only introduces your brand to new audiences but also creates durable citations that AI systems are more likely to trust and replicate.
By cultivating these relationships, you build a citation footprint that extends across different formats (articles, transcripts, audio summaries). Each mention increases the probability that your brand surfaces in AI overviews, conversational answers, and knowledge graph associations, reinforcing your authority in the spaces that matter most.
Entity-based clustering takes the traditional SEO concept of topic clusters and adapts it for the AI-first search environment. Instead of treating each page as a standalone asset, you organize content around well-defined entities—people, products, industries, or concepts—that map directly to how AI systems structure knowledge. A strong cluster typically includes a pillar page that defines the entity, supported by subpages, FAQs, and related resources that cover its attributes, use cases, and connections to other entities.
This structure makes it easier for AI systems to understand relationships and context. For example, a cybersecurity brand that builds a cluster around “Zero Trust Security” would include subtopics like authentication methods, case studies, regulatory standards, and common FAQs. By interlinking these assets, you give both search engines and LLMs a clear semantic map, reinforcing your expertise in that domain.
The payoff is twofold: Your brand is more likely to be recognized as an authoritative source within that knowledge space, and your content becomes more extractable, meaning AI platforms can easily pull accurate, well-structured snippets into summaries, answers, and generative search results. In short, entity-based clusters teach AI systems exactly who you are and why you’re credible.
The shift toward AI-mediated information discovery represents the most significant change in search behavior since the advent of Google. Developing competency in LLM visibility tracking and optimization will ensure your brand remains discoverable and authoritative in the new landscape of AI-powered information consumption.
As these tools and methodologies continue to mature, the brands that invest early in understanding and optimizing for LLM visibility will have significant competitive advantages in the AI-first world that’s rapidly approaching. Dive deeper into the AI Visibility Index or go straight into exploring your LLM visibility.
Andrea Pretorian
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© 2025 Search Engine Land is a Trademark of Semrush Inc.
Third Door Media operates business-to-business media properties and produces events, including SMX. It is the publisher of Search Engine Land, the leading digital publication covering the latest search engine optimization (SEO) and pay-per-click (PPC) marketing news, trends and advice. The company headquarters is 800 Boylston Street, Suite 2475, Boston, MA USA 02199.

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Review of Prestashop SEO Optimizer Module-Advance SEO Expert Module [2025] – vocal.media

Review of Prestashop SEO Optimizer Module-Advance SEO Expert Module [2025]  vocal.media
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Utilizing AI and Software for More Effective Marketing Campaigns – MarTech Outlook

Utilizing AI and Software for More Effective Marketing Campaigns  MarTech Outlook
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How AI Is Reshaping Digital Marketing in 2025 – South Florida Reporter

Artificial intelligence has moved from being a buzzword to becoming the backbone of modern marketing strategies. In 2025, businesses across industries are finding that AI is not just useful, it is essential. From optimizing campaigns to personalizing customer experiences, AI is redefining how digital marketing works.
AI adoption has accelerated rapidly. According to Fantasy AI, 78% of organizations now use AI in at least one business function. This highlights the technology’s shift from experimental to mainstream, with businesses relying on it for everything from analytics to customer engagement.
Georgi Dimitrov, CEO and Founder of Fantasy AI, explains:
“AI is not here to take creativity away from marketers. It is here to amplify it. By combining human insight with AI’s speed and precision, companies can scale personalization, predict trends, and execute campaigns more effectively than ever before.”
Content creation and search engine optimization have been transformed by AI tools. Platforms can now generate outlines, analyze keywords, and suggest improvements in real time. This enables marketers to publish more high-quality content while saving time and resources.
SEO strategies are also becoming more predictive. AI tools can identify new opportunities, spot gaps in competitor strategies, and forecast performance. This allows businesses to be proactive rather than reactive.
Social media campaigns demand constant attention, and AI tools are making them easier to manage. Automated caption generation, optimized posting schedules, and real-time engagement analysis ensure that brands remain consistent.
Personalization is another area where AI excels. By tailoring ads, product recommendations, and emails, companies can build stronger relationships with their audiences. What was once reserved for enterprises with large budgets is now available to small and medium businesses through affordable AI tools.
AI is also changing how paid campaigns are run. Automated bidding, audience segmentation, and creative testing have become standard features in modern ad platforms. This reduces waste and increases return on investment, giving marketers more confidence in their campaigns.
Analytics powered by AI go beyond tracking results. They predict customer behavior, suggest next steps, and uncover hidden opportunities. This empowers businesses to make smarter, data-driven decisions.
AI’s role in digital marketing will only continue to grow. We are likely to see real-time personalization across every customer interaction, smarter automation in advertising, and AI-driven creative tools entering the mainstream.
As Dimitrov points out, “The companies that embrace AI now will not just compete, they will lead. AI is no longer optional for digital marketing, it is the foundation for the next generation of business growth.”
AI is transforming digital marketing in 2025. From SEO to social media, from personalization to predictive analytics, the technology is empowering businesses to reach audiences more effectively.
The message is clear: those who adapt to AI will stay ahead, while those who resist will fall behind. For marketing teams, AI is not the future, it is the present — and the smartest companies are already making it central to their strategy.
 

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The Google Home app is getting a new look. Here’s what’s changing. – Mashable

A sneak peek of Google’s new Google Home app design reveals that Gemini will be front and center as the company transforms its new products with artificial intelligenceSmart House, you will always be famous.
Google Home v3.41.50.3, a forthcoming app update, includes a significant UI overhaul, according to an exclusive by Android Authority. The app will now feature Gemini and Gemini Live (not Google Assistant) front and center, which allows users to fully automate their Google Home settings using the AI assistant. Simply “Ask Home.”
Users will be able to use the new Ask Home search bar to do just that, and can oversee their preferred devices, automations, and environmental feedback on a revived “favorites” page. Google’s also added tiles for expected video and thermometer add-ons. The app comes with fresh icons, cleaner pages, and important privacy disclosures for Gemini Home’s data collection, too — keep your eyes peeled.
Google is set to announce a new line of smart products in October, including a new Nest speaker with built-in Gemini, a new Nest doorbell, and a series of Nest cams for a fully rounded smart home setup. In April, Google announced it would be ending support for first—and second-generation Nest Thermostats, which was explained as a necessary move to focus on supporting newer hardware.
In addition to the hardware upgrades, Google Home users can expect new AI-powered functions and features, such as daily summaries and AI event descriptions, first demoed at the company’s Made by Google event in August.
Topics Google Home
Chase joined Mashable’s Social Good team in 2020, covering online stories about digital activism, climate justice, accessibility, and media representation. Her work also captures how these conversations manifest in politics, popular culture, and fandom. Sometimes she’s very funny.

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