Build fast, beautiful, fully customizable websites without subscriptions, lock-in, or cloud-based limitations. Zero One turns Kirby CMS into a powerful self-hosted website builder, giving you the freedom, privacy, and control that SaaS platforms canβt offer. It includes a visual layout builder, form builder, header and footer builder, SEO tools, GDPR features, multilingual support, AI-ready integrations, and a flexible design system. Whether you're a freelancer, agency, or privacy-focused business, Zero One lets you create modern, scalable websites you can host anywhere with no monthly fees and no vendor lock-in.
NoteGPT is an AI learning assistant for students, educators, professionals, and creators. It converts YouTube videos, lectures, meetings, and PDFs into concise notes and summaries, generates flashcards, and lets you chat with models like ChatGPT, Claude, Gemini, and DeepSeek. Use transcription, PDF translation, and writing helpers to research and draft faster. You can create podcasts with text-to-speech and voice cloning, and design or edit images for slides and visuals. It is available on web and Chrome with strong privacy safeguards.
Advertisers can now generate short videos directly inside Google Ads using Veo, Googleβs most advanced generative video model β no video production required.
How it works. Upload up to three static images into Asset Studio and Veo generates videos up to 10 seconds long with natural motion, designed specifically for YouTube formats and audiences. These can then be turned into ready-to-serve ads using customisable templates.
What else it can do. Combined with Nano Banana, advertisers can adapt creatives further β swapping backgrounds, adjusting messaging, and tailoring content to specific audience interests.
The bigger picture. This follows Googleβs earlier rollout of video templates and automatic video creation in Demand Gen campaigns, and represents the next step in Googleβs push to make video creative accessible to advertisers of all sizes without dedicated production resources.
Why we care. Video consistently outperforms static creative on YouTube β but producing it has always required time, budget, and expertise. Veo removes most of that barrier, letting advertisers turn existing product images into polished video ads in minutes. For teams running image-heavy campaigns who have been unable to compete in video placements, this changes the equation significantly.
Early testing. Hop Skip Media founder Ameet Khabra shared some early results of the testing she did showing a video she created on LinkedIn. Her review is:
The bottom line. As Google continues building AI creative tools directly into the ads platform, the gap between advertisers with production budgets and those without narrows. For anyone who struggles to get video production budget approved and have assets with inherent motion logic, now could be the best time to test AI-generated video in Google Ads.
Brieflet reads everything from your sourcesβnews, blogs, YouTube, Reddit, academic journalsβand twice a day gives you a short, personalized brief of what matters. You can shape what you see over time by talking to a built-in AI assistant in plain language. Available on web and iOS.
QuotePro is a quoting, scheduling, and CRM platform for residential and commercial cleaning businesses. It helps you price jobs with 200+ calculators, send branded multi-tier proposals in seconds, and automate follow-ups that sound like you. Use the web or iPhone app to track leads, schedule work, and view revenue metrics in one place. Integrate accepted quotes with Jobber, accept payments via Stripe or Venmo, and quote in multiple languages to win more profitable jobs.
Google may have saved everyone from the RAMpocalypse Finally, we have some good news from the AI space. Google has announced new tech that has sent the stock prices of memory companies lower. Why? Googleβs new βTurboQuantβ tech promises to reduce AIβs memory usage by 6x. This tech could cause the AI industryβs demand for [β¦]
The post Google TurboQuant tech could save us from the RAMpocalypse appeared first on OC3D.
Learn how Google approaches some of today's most pressing security topics, challenges and concerns, straight from Google experts.Gemini Drops is our regular monthly update on how to get the most out of the Gemini app.MLB Scout Insights feature, powered by Gemini and Google Cloud AI, provides baseball commentary.
Google is testing AI-generated summaries in YouTube feeds, replacing video titles with auto-written synopses.
Some YouTube users are seeing video titles replaced by AI-generated summaries in the Android app. Reports on Reddit showed title-less video cards with collapsible summary boxes instead.
The details. Video thumbnails remain, but titles are missing in some cases.
What it looks like. Hereβs a screenshot Reddit user GrimmOConnor shared:
Why we care. This further abstracts creator metadata and reduces control over how your YouTube content appears. Titles remain a critical ranking and click-through signal. Replacing them with AI summaries can impact keyword targeting, brand voice, and intent matching β and increase the risk of inaccuracies that hurt performance.
The context. Google is also testing AI-generated headline rewrites in Search, extending the same approach beyond Discover and now potentially into YouTube.
Reaction. Early feedback suggests a worse browsing experience. Expanding summaries slows discovery and adds friction to content selection, which runs counter to YouTubeβs engagement goals.
Whatβs next. Thereβs no official confirmation from YouTube on a broader rollout. The missing titles may be a bug, but the AI summary feature aligns with Googleβs broader push into generative AI.
First seen. We learned about this test from Android Authority.
Looking to take the next step in your search marketing career?
Below, you will find the latest SEO, PPC, and digital marketing jobs at brands and agencies. We also include positions from previous weeks that are still open.
(Provided to Search Engine Land by SEOjobs.com)
(Provided to Search Engine Land by PPCjobs.com)
Senior Paid Media Manager, Brightly Media Lab (Remote)
Senior Brand Insights Manager, Derflan Inc (Remote)
Marketing Specialist, The Bradford group (Hybrid, The Greater Chicago area)
Paid Search Specialist, Maui Jim Sunglasses (Peoria, IL)
Digital Marketing Manager 10x Health System (Scottsdale, AZ)
Marketing Manager β SEO & GEO, Care.com (Hybrid, Austin Texas)
Digital Marketplace Manager, Venchi (Hybrid, New York, NY)
Advertising Media Manager, Vetoquinol USA (Remote)
Programmatic Advertising Manager, We Are Stellar (Remote)
Marketing Manager, Backstage (Remote)
Note: We update this post weekly. So make sure to bookmark this page and check back.
Weβve all seen the charts going viral on LinkedIn. Theyβre everywhere at this point. Multiple industry studies, even this research from Semrush, confirm that Wikipedia and Reddit are the top-cited domains across major LLM platforms β and CMOs are running with this data.
The response is predictable: Just search for any bottom-of-funnel (BOFU) software query, and youβll find Reddit threads in the top-ranking positions. This is exactly why the market is currently flooded with βReddit SEOβ agencies:
Just stop.
Taking this macro context β or a few isolated, high-ranking SERPs β and pivoting your entire GEO strategy toward Reddit or Wikipedia is a massive strategic error for the majority of B2B brands.
The algorithmic tide is running toward massive community forums and open-source encyclopedias. That shift is real β but how itβs being interpreted isnβt.
The charts driving this executive FOMO are mathematically accurate, but theyβre strategically misguided. Applying them as a universal GEO playbook ignores why that aggregate data exists and why certain pages rank for high-intent queries.
Reddit is the primary target because itβs perceived as easier to influence. While the industry respects Wikipediaβs ironclad editorial guardrails, Reddit is often viewed as an open loophole.
This is a classic case of marketing whiplash, where teams abandon foundational principles to chase the shiny new object.
To understand why Reddit and Wikipedia are a high-effort, low-upside channel for the vast majority of brands, you have to look at the context executives ignore.
These studies add up citations across a randomized database that covers everything from pop culture to generalized consumer advice.
As Alex Birkett points out:Β
By default, theyβll always get the most aggregate LLM citations.
When you see a Reddit thread driving CTR for a specific BOFU software query, itβs tempting to view it as an SEO loophole that can be easily reverse-engineered. This is incorrect.
In reality, this is a scenario where the βvoice of the customerβ largely dictates who gets recommended.
This isnβt an SEO hack or a growth trick. Itβs the culmination of years of actual human peer reviews and real discussion on a topic that has reached a definitive consensus. Your marketing team canβt microwave this historical, multi-year, authentic brand sentiment.
Claiming you need a Reddit or Wikipedia strategy because they are the most-cited domains overall is like claiming spaghetti carbonara is the most-eaten dish in Italy. Yes, itβs ubiquitous and popular, but just because itβs everywhere doesnβt mean you should put it on the menu at a high-end steakhouse.Β
Dig deeper: Rand Fishkin proved AI recommendations are inconsistent β hereβs why and how to fix it
Even if you ignore the macro context and decide to aggressively pursue a Reddit or Wikipedia SEO strategy, youβll quickly realize how LLMs actually process data.Β
Hacking them for AI citations is an illusion built on a fundamental misunderstanding of what LLMs are looking for. When you look at the mechanics of AI citations, two massive roadblocks emerge.
Thirsty SEO agencies will frequently pitch Reddit marketing services, promising to generate hundreds of upvotes and comments to trigger LLM visibility. But the data shows LLMs donβt care about manufactured virality.
Up to 80% of Reddit threads cited by AI have fewer than 20 upvotes, according to Semrush. More importantly, the average age of a cited post is roughly 900 days. LLMs are surfacing historical, established consensus, not yesterdayβs growth hack.Β
The exact same brutal reality applies to Wikipedia. A Princeton University study analyzing AI-generated Wikipedia content revealed exactly what happens when marketers try to βhackβ the encyclopedia with generative tools.Β
Researchers found that when users utilized AI to create self-promotional pages for businesses, the articles were mathematically lower in quality, lacking proper footnotes and internal links.
The result?
Human moderators quickly identified the low-effort content, deleted the pages for βunambiguous advertising,β and actively banned users.
Even if you successfully infiltrate a subreddit or a Wikipedia page without getting banned, you lose control over your product positioning. Benji Hyam notes that Reddit mentions are typically too short and lack the depth necessary for an LLM to associate your product with a specific problem and solution.
The Semrush data also proves this: AI tools donβt quote Reddit word-for-word. They blend and paraphrase discussions (showing a semantic similarity score of just 0.53).Β
Your carefully crafted value proposition will be mashed up with random, anonymous user comments, or stripped down to dry, encyclopedic neutrality, diluting your brand narrative entirely.
Posting on Reddit isnβt an SEO strategy β itβs shouting through a bus window, hoping to join the conversation. At best, itβs a short-term tactic. At worst, it actively damages your brand.
The lack of ROI is only half the problem when it comes to building a Reddit or Wikipedia presence. The much larger issue is the active harm it can inflict on your brandβs image.
Brands that treat these platforms as loopholes for AI citations fundamentally misunderstand their architecture.
As Eli Schwartz points out, trying to replicate decades of genuine human conversation with templated brand messaging isnβt just ineffective β itβs a massive reputational hazard.
Subreddits and wiki pages are policed by passionate human moderators and veteran Wikipedia editors. Theyβve seen every variation of corporate infiltration.Β
A new account dropping a link, manufacturing enthusiasm, or violating Wikipediaβs strict conflict of interest (COI) guidelines is flagged, reverted, and banned almost immediately. Sometimes, this is accompanied by a public callout (featured on subreddits like r/hailcorporate), causing more brand damage than the campaign was ever worth.
This is the most critical and misunderstood risk. Reddit sells its data directly to companies like Google and OpenAI. Wikipediaβs entire edit history is completely open source.
LLMs arenβt just scraping the public-facing websites. Theyβre receiving the entire firehose of data (including deleted posts, reverted wiki edits, and banned accounts). When your agencyβs fake comments or promotional product descriptions get removed by moderators, those AI models still see the manipulation.
Because the AI models have full visibility into the moderation pipeline, links or mentions flagged as inauthentic carry negative weight. By attempting to game the system, youβre essentially training the AI to associate the brand with spam and coordinated manipulation.
Dig deeper: How to build an organic Reddit strategy that drives SEO impact
Once you accept that hacking Reddit or Wikipedia is both ineffective and dangerous, you have to look at where LLMs are actually pulling their answers from when a buyer is ready to make a purchase. When you filter for high-intent, BOFU prompts, the βReddit/Wikipedia is everywhereβ narrative falls apart.
Using AI visibility platforms like Scrunch AI exposes Redditβs and Wikipediaβs true influence on specific target categories. For one B2B client, tracking 300+ custom prompts generated thousands of LLM responses, but just two specific Reddit threads were responsible for the vast majority of citations.
The Wikipedia data was even more revealing.
For high-intent software queries, the encyclopedia barely registered. When AI tools cited Wikipedia, they were almost exclusively scraping broad, top-of-funnel category definitions, or pulling background facts from a specific companyβs history page.
Data from Grow and Convert shows the same thing. For trucking software queries, LLMs consistently cited domains like PCS Software and TruckingOffice.
For project management queries, the AI cited specialized software review sites and niche blogs.
This is a far cry from the overwhelming dominance promoted by SEO/GEO research studies.Β
If youβre chasing platforms simply because they cover massive topical geography, youβre making a painful error. You donβt need to be visible everywhere. You only need to be visible in the specific digital neighborhood that influences your flagship category.
Dig deeper: βSearch everywhereβ doesnβt mean βbe everywhereβ
Winning in AI search requires optimizing for targeted influence rather than aggregate metrics. The most effective GEO strategy abandons massive topical geography and focuses entirely on the pillars you can actually control.
Your website remains your most powerful asset. To be recommended, you must provide the specific, granular depth the AI needs to understand your value. Your key product and solution pages need to explicitly cover:
This depth is exactly what gives you a chance at showing up for the highly specific, long-tail queries a customer types into an AI when evaluating products.
Use AI visibility tools to identify the specific, niche domains that currently influence your flagship categories. Once you know which industry blogs, review sites, and peer publications the LLMs are actually citing for your BOFU queries, execute targeted outreach to earn your place on those exact lists.
Dig deeper: How paid, earned, shared, and owned media shape generative search visibility
Reddit and Wikipedia carry real authority, and earning trust there is valuable independent of AI visibility. If you choose to invest in them, it must be a long-term play, not a marketing hack.
The path to AI visibility runs through your own domain and the highly specific digital neighborhoods your buyers trust. AI engines reflect the authority you already have. If you want the algorithm to recommend your brand, then you have to do the work to actually be recommendable.
PlayStation 5 console prices are rising, and Sony blames the βglobal economic landscapeβ Sony has officially confirmed that its PlayStation 5 consoles are set to receive a price hike. All PlayStation 5 console models are affected, including the PlayStation 5 Pro. Baseline consoles will see their prices increase by $100, while the Pro will see [β¦]
The post Sony announces major PlayStation 5 price hike appeared first on OC3D.
Just six weeks after launching its ad pilot, OpenAI has hit a significant milestone β and the platform is still in its early stages of rollout.
The numbers.
Whatβs coming next.
Why we care. ChatGPTβs ad business has scaled to $100 million in annualized revenue in just six weeks β and thatβs from less than 20% of eligible users seeing ads today, meaning the inventory is about to get significantly larger.
Self-serve access launching in April is the moment this becomes accessible to the broader advertiser market, not just the 600+ brands currently in the managed pilot. Getting in early, before competition drives up costs, is the same playbook that rewarded early movers in search and social advertising.
The quality picture. OpenAI says fewer than 7% of ads are rated by users as βlow relevanceβ β a metric the company says they are actively focused on improving alongside user trust.
The bigger context. Ads are a key part of OpenAIβs path to profitability ahead of an anticipated IPO. Executives have told investors the company expects to generate more than $17 billion from ChatGPT consumers in 2026 β with advertising representing a meaningful slice of revenue from its free user base.
The bottom line. $100 million in annualized revenue from less than 20% of eligible users in six weeks is a strong early signal. When self-serve access opens in April and the eligible audience expands, the numbers could scale quickly β and advertisers who have been waiting on the sidelines may soon find the platform harder to ignore.
OpenAI have been pumping out the ads ads for free-tier ChatGPT users in the US for over a month now, and early testing suggests theyβre more frequent and more targeted than many users might expect.
How often they appear. In a test of 500 questions across the mobile app, roughly one in five questions in a new conversation thread triggered an ad at the bottom of ChatGPTβs response β always as a website link button, always tailored to the topic of the question.
What kind of ads appeared. The range was broad β dog food, hotel bookings, productivity software, cruise vacations, streaming services, corporate credit cards, AI coding tools, and basketball tickets, among others. Travel questions triggered ads most frequently; asking for help planning a trip to Palm Springs surfaced a Booking.com ad that automatically searched for hotels in that location.
The βpoachingβ dynamic. When a question mentioned a brand by name β DoorDash or Netflix, for example β the ad that appeared was sometimes for a direct competitor. Marketing professors describe this as a longtime staple of digital advertising now migrating to AI.
Why we care. ChatGPT ads are appearing roughly once every five questions on the free tier, with targeting based on conversation topic and memory β making it an emerging channel advertisers should monitor, particularly given the βpoachingβ dynamic that allows brands to appear against competitor mentions, a tactic already proven in search advertising.
What OpenAI says.
The irony. OpenAI CEO Sam Altman called ads βa last resortβ in 2024, saying the mix of βads plus AI is sort of uniquely unsettling.β The company is now expanding the rollout to Canada, Australia, and New Zealand after its US pilot.
The big picture. Neither Googleβs Gemini nor Anthropicβs Claude currently features sponsored ad buttons in outputs β though Google has said itβs not ruling it out. OpenAI is essentially pioneering a new ad format, and how it handles the balance between monetisation and user trust will shape whether AI advertising becomes a lasting industry or a cautionary tale.
Spotted. Digital marketer Glenn Gabe, shared on X how the ads are showing on mobile and confirmed it isnβt showing on Plus accounts.
The bottom line. For advertisers, ChatGPTβs ad inventory is becoming real, even though there is still a long way to go to prove ROI. However the platformβs credibility depends entirely on whether users feel the ads are eroding the experience. Thatβs a tension worth watching closely as the rollout scales.
Dig deeper. I Asked ChatGPT 500 Questions. Here Are the Ads I Saw Most Often β Wired (subscription needed).
You know SEO improves traffic, authority, and trust. What we donβt talk about enough is how a strong SEO foundation can help other channels, including PPC.Β
This practical case study will show you how performance marketing scales in a high-consideration B2B medical device market and how getting SEO fundamentals firmly in place enables paid media to deliver at scale.
Marketing a premium pelvic floor chair has little in common with selling SaaS tools or consumer products. This is a high-ticket medical device with a long sales cycle and a strong reliance on medical expertise.
Buyers include doctors, fitness centers, physiotherapists, urologists, and gynecologists. They ask detailed questions and have high expectations around clinical evidence, credibility, and long-term value.
In markets like this, many common performance tactics fail quickly. Increasing bids, expanding keyword coverage, or testing endless landing page variants doesnβt compensate for a lack of credibility and topical authority.
If potential buyers donβt trust the provider behind the product, no amount of optimization will create sustainable results. That was exactly the situation we faced at the outset of this project.
At the end of 2023, we launched our first Google Ads lead generation campaigns. At that stage:
Still, those early campaigns revealed something valuable. We began seeing our first sales coming through paid search. That wasnβt enough to scale, but it confirmed that search demand existed and could convert once the surrounding system improved.
Dig deeper: How to run compliant, effective medical and mental health ads
In mid-2024, we made a deliberate shift, treating SEO as revenue infrastructure instead of a secondary task or a nice-to-have initiative. Rather than focusing on quick ranking wins, the goal became building topical authority in pelvic health and creating the trust layer that paid media depends on, especially in medical markets.
The emphasis was intentionally top-of-funnel. The keyword and content strategy focused on education.Β We:
Our most impactful SEO lever was authority and link building. The brand already worked closely with clinics and medical professionals who used the pelvic floor chair in their practices. Instead of relying on traditional outreach or guest posting, we developed a partner-driven backlink strategy.
We provided clinics using our chair with free, ready-to-use content ranging from performance campaign visuals (B2C lead generation) to educational materials and clinical studies on the effectiveness of the technology. In return, the clinics linked to our website from their dedicated product pages, using the content we supplied and creating natural, relevant references.
These werenβt generic backlinks. They came from trusted medical domains, embedded in highly relevant content, and aligned closely with how Google evaluates expertise and trust in healthcare contexts.
Over time, this resulted in steady growth in referring domains and a significant increase in topical authority. As the network graph from our Semrush backlink analysis shows, our strongest referring pages have high authority scores.
They originate primarily from fitness studios, physiotherapy practices, and medical clinics. These relationships position the brand at the center of a tightly connected backlink network, reinforcing topical relevance and trust within the healthcare and wellness ecosystem.
By late 2024, the impact was clearly visible. The website ranked number one for the most important generic keywords, such as βBeckenbodenstuhlβ (German for pelvic floor chair), and gained visibility across a broad range of related queries.
More importantly, organic visibility began shaping brand perception. Prospects encountered the brand repeatedly during their research phase, often through AI Overviews, long before ever clicking on an ad. SEO has effectively become a trust engine.
Dig deeper: 75% of ChatGPT users rely on βkeywordsβ for local services: New data
This is where paid media behavior started to change. A strong organic presence does more than drive unpaid traffic. It changes how users respond to ads.Β
When people already recognize a brand from their organic research, paid listings feel familiar and credible rather than intrusive. This is especially true with AI Overviews, where we held top rankings for the most important generic keywords related to our product.Β
This effect became especially clear in competitor campaigns. Users searching for alternative pelvic floor solutions clicked on our ads because we were a brand they had already encountered organically, and click-through rates reflected that trust.
With authority finally established, we restructured our Google Ads campaigns by:
This was only possible because landing pages aligned perfectly with user intent and the brand already carried organic credibility.
In several competitor campaigns (competitor names are blurred out), click-through rates reached an astonishing average of 48.29%. In isolation, those numbers might seem unrealistic. In context, they were the natural result of strong organic preconditioning, with AI Overviews playing a major role, and the brand recognition we built through consistent visibility.
Another major improvement came from conversion tracking. We moved away from GA4-imported conversions and implemented GTM-native events designed specifically around meaningful lead actions.
This provided Google Ads with faster, cleaner signals and significantly improved Smart Bidding performance. In high-ticket B2B and medical markets, signal quality matters far more than volume, and optimizing toward the wrong conversion can do more harm than not optimizing at all.
The final step was closing the loop between marketing and sales. By integrating HubSpot CRM, we tracked lead quality beyond form submissions and identified which leads actually converted into revenue.
That information was fed back into Google Ads, allowing the algorithm to optimize toward outcomes that truly mattered, not just surface-level conversions. In long sales cycles, this feedback loop is essential.
Dig deeper: A guide to Google Ads for regulated and sensitive categories
With approximately $12,000 in total ad spend in 2025, the combined SEO and PPC system delivered strong year-over-year growth.Β
The biggest takeaway for us was that SEO shouldnβt be viewed solely as a traffic channel. It has a direct impact on the quality of signals fed into paid media platforms, and those signals ultimately determine how well algorithms can optimize.
Paid search only begins to scale once a foundation of trust is in place. In categories where consideration cycles are long and credibility matters, ads perform much better when users already recognize the brand and perceive it as an authority in the field.
Sustainable, high ROAS is rarely the result of a single optimization. Itβs built through interconnected systems that align SEO, paid media, tracking, and CRM feedback regarding lead quality.
Performance marketing itself doesnβt fail in complex markets. What fails is the assumption that complexity can be solved with simple tactics.
PostZapAI is an AI-powered social media management platform for creators, agencies, and businesses. Schedule content across 9 platforms β Twitter/X, LinkedIn, Instagram, Facebook, YouTube, Bluesky, Threads, TikTok, and Pinterest β from one dashboard. Claude AI writes platform-specific captions instantly, and a Viral Score Predictor scores your post before you publish. Content Repurpose AI turns any URL into 9 ready posts. It also includes team approval workflows, an India Festival Calendar, unified analytics, and a free Bio Page that replaces Linktree.
If your entire Google Ads strategy consists of targeting brand and non-brand keywords, youβre limiting growth. If performance is declining, itβs not the platform β itβs the strategy.
People donβt discover you through non-brand search. They research on Reddit, ChatGPT, Facebook, LinkedIn, and YouTube. They watch demos, read testimonials, and learn about your brand long before they ever search for it.
If you have a complex sales process and a long customer journey, this shift is critical and requires a different approach. Hereβs what you need to know to make this work in B2B.
Google has been developing multi-channel, multi-asset campaigns for years β first with Performance Max, then with Demand Gen. These campaigns reach your audience across the web as they research and evaluate.
Your brand is front and center while your audience builds their shortlist. By the time theyβre ready to pick vendors to take the next step, youβve already built trust. Then theyβll find you by searching for your brand.
A Performance Max campaign with a variety of ad types, like image and video ads, can showcase demos or customer testimonials on YouTube. They can appear across the web via the Display Network. They can follow (retarget) your target audience as they research. Thatβs what drives the branded search that converts later.
These campaigns let you do all of this cost-effectively. In a Performance Max campaign, you can use keywords alongside your own customer data as signals. Youβre not abandoning keywords. Youβre using them smarter.
Dig deeper: Why B2B brands are shifting from keywords to Performance Max
Googleβs search results pages have evolved with AI Overviews and AI Mode. If this experience is changing so dramatically, isnβt it time to rethink your ad strategy as well?
Iβm a fan of the 4S framework: search, scroll, stream, and shop.
Iβd add βaskβ to reflect how people now engage across AI tools. They ask ChatGPT or Gemini, search Google, scroll LinkedIn, stream YouTube videos, and shop across platforms. If your strategy only covers one or two of those behaviors, youβre missing how growth actually happens.
Focusing only on keyword targeting means youβre missing the bigger picture. Yes, brand keywords will convert better than non-brand keywords. But how do people even know to search for your brand in the first place? (The answer is that youβve been showing up in their feed the whole time.)Β
This approach takes time, especially for B2B companies with long sales cycles.
It took us nearly a year to realize the value Performance Max was driving for a life science client. Most of their deals take months to close. Our account manager was about to pause the campaign at one point because the ad platform data didnβt look good.Β
But as we began piping in sales data, things started clicking. Once we got over the sales cycle hump and started seeing revenue data, Performance Max proved its value.
If you can sync data beyond MQLs β like Proposal Sent β that provides more data and signals to Google, and more peace of mind until you can add sales data.
Be patient, feed the system better data, and donβt give up too early. B2B sales cycles are complex.
You might have 100 people at an event that you promoted through a LinkedIn ad strategy. Some of those people caught an email promoting a webinar. Months later, they searched for you on Google and asked for a proposal. Still months later, they became a customer.
Even with the best-recorded data, you wonβt see this happening right away in a long sales cycle.
Dig deeper: How to optimize B2B PPC spend when budgets and confidence are low
If you donβt have a test-and-learn budget, reallocate 5% to 10% to introduce AI-forward campaign types. Test strategically. Donβt go all in, and donβt launch major tests during a busier time of year. Give yourself breathing room while the system learns.
This approach takes time. But it drives sustainable growth if you commit to the process. The advertisers who figure this out are building sustainable growth, while others are still stuck optimizing for a shrinking slice of demand.
A new version of the Google Ads API is out, bringing a handful of targeted updates across video, app campaigns, and audience planning tools.
Key changes in this release.
LoginVideoEnhancement resource that surfaces whether a video ad is Google-generated or advertiser-provided β giving developers clearer visibility into auto-enhanced creativeAppTopCombinationView resource providing read-only insights into top-performing asset combinations in App campaignsHotelSettingInfo.disable_hotel_settingContentCreatorInsightsService and ReachPlanServiceWhat to do. Upgrading to v23.2 requires updating both client libraries and client code β all updated libraries and code examples are already published.
Catch the walkthrough. Google is hosting a live release walkthrough on March 26 at 11am ET on Discord and YouTube Live, with a recorded version to follow for those who canβt attend.
Why we care. The VideoEnhancement gives developers the ability to programmatically identify whether a video ad is Google-generated or advertiser-provided, which has been a notable blind spot in Performance Max reporting. For agencies and teams building custom reporting tools, this is a meaningful step toward greater creative visibility.
The bottom line. A routine but useful release β the VideoEnhancement resource in particular is worth attention for any developer building tools around Performance Max creative reporting.
Refreshing creatives for every seasonal moment just got significantly faster β Google has quietly launched Asset Group Theming inside Performance Max, letting advertisers apply seasonal themes to existing asset groups without rebuilding from scratch.
How it works. Advertisers can clone a high-performing asset group and apply a theme β Google then generates themed image variations and suggests aligned headlines and descriptions, while leaving the original asset group completely untouched for safe testing.
Available themes cover.
Where to find it. Look for the prompt inside Asset Groups ahead of major holidays, or via βApply theme to existing asset groupβ when creating a new one.
Important caveat. This is a starting point, not a finished product. The tool uses existing images as a base and adds themed backgrounds β it does not replace videos, and typically only updates a handful of headlines to match the theme. Everything still needs to be reviewed and sense-checked before going live.
Why we care. Seasonal creative refresh has always been one of the more time-consuming parts of campaign management β requiring design resources, rebuilding asset groups, and risking performance drops on proven setups. This feature removes most of that friction, letting teams adapt their best performers to key moments in minutes rather than days.
The bottom line. Think of it as a creative assistant, not a replacement for a designer β but for advertisers managing multiple seasonal peaks across the year, the time savings alone make it worth exploring.
First spotted. This update was spotted by Google Ads specialist Bia Camargo who shared a screenshot on LinkedIn.
The local SEO community remains locked in a permanent debate over the βhide addressβ toggle for service area businesses (SABs). Most owners view this switch as a simple privacy setting. In reality, itβs a high-stakes decision that dictates how Googleβs algorithm interprets your physical relevance.
These are fundamental and relevant questions of how proximity functions when you choose to go off the grid.
To be clear, the address and the map pin arenβt the same thing. When you enter an address into your Google Business Profile, Google doesnβt simply drop a pin. It runs the address through its geocoding engine to resolve the text string against its internal database.
To understand why a map pin ends up in a highway median or a city center, you must examine Googleβs internal data models:
Google is looking for a match it can trust. When it finds a high-confidence match, it places the pin specifically at the rooftop of your building.
Once you understand how these three work together, you can get some clarity on why Google appears to rank SABs differently in the local map pack.
Make no mistake: this isnβt a bug. Itβs a fundamental breakdown in how Google translates a text string into a physical coordinate.
When this translation fails, your business ends up with a misplaced map pin, which directly misplaces your local proximity authority.
When Google canβt find a high-confidence match at the building level, it doesnβt just leave your pin floating. Instead, it falls back to the most reliable geographic feature it can confidently resolve. In most cases, that fallback is the city centroid (the geographic center of the municipality tied to your address).
Googleβs own Geocoding API documentation outlines this fallback logic, explaining why pins for businesses with perfectly visible, verified addresses sometimes end up dumped in the middle of a city.
Simply put, if your address isnβt recognized by Googleβs internal systems, the geocoding process lacks the confidence to place the pin precisely.
If Google canβt reconcile your GeostoreAddressProto with a high level of certainty, it may not anchor your GeostorePointProto to your buildingβs rooftop.
Dig deeper: The proximity paradox: Beating local SEOβs distance bias
Geocoding loses confidence when a business shares a generic building footprint, lacks a distinct suite number, or is placed in a newly developed zone that Googleβs Street View API hasnβt yet mapped.
A building thatβs newly constructed or recently added to a commercial complex may not yet exist in Googleβs geographic database with enough detail for a rooftop-level match. The street and city exist, but the specific parcel hasnβt accumulated enough mapping data for Google to confidently place a pin.
To understand why, it helps to know how Googleβs geocoding data actually gets populated. Googleβs own developer documentation states that data collection is a periodic process, and new construction data can take time to be reflected in Google Maps.
The address hierarchy Google geocodes against is built from a combination of sources, including satellite imagery updates, municipal records, and USPS address data, none of which updates in real time.
When the API resolves an address, it returns one of four location types: ROOFTOP, RANGE_INTERPOLATED, GEOMETRIC_CENTER, or APPROXIMATE.
Iβve said this to clients more times than I can count. It seems like a minor formatting detail. It isnβt.
When a business enters something like 1234 Main Street, Suite 200, in Address line 1, Googleβs geocoding engine attempts to resolve that entire string as a street address.
Suite numbers are unit identifiers. They exist within buildings. They arenβt street-level geographic data, and Googleβs geocoding process doesnβt use them to identify rooftop locations.
Embedding a suite number in Address line 1 introduces a conflict into the geocoding query that the system canβt cleanly resolve against a physical coordinate.
Instead of anchoring the pin to your building, the geocoding process encounters a string it canβt fully parse at the street level, loses confidence, and falls back, often all the way to the city centroid. This may cause clients to drive to another location or the middle of the highway.
A profile verified at a physical address doesnβt rank based on the visible address.
I recently managed a new listing where a geocoding conflict forced the map pin to the city center of Houston, miles from the actual office. While the text on the profile showed the correct street address, the ranking was anchored entirely to a misplaced coordinate in the downtown centroid.
In this instance, a suite number was embedded directly into the primary address field. When Googleβs system canβt cleanly parse a street number and name, it often defaults to the city centroid as the best available data point. This isnβt an edge case.
Whether itβs a suite number on the wrong line or a new construction site, these formatting errors trigger geocoding failures that are notoriously difficult to unwind.
The clientβs ranking data confirmed the technical reality. For high-competition terms like βwater damage restoration,β the business didnβt rank based on its physical office. It ranked based on where the pin was dropped.
If your pin is in a highway median or a city center due to a formatting error, that is where your proximity authority lives.
If you have a service-area business, the stakes are higher, and the scenarios are more complex.
When Google reprocesses that address, and the geocoding fails to anchor cleanly from the beginning, the business owner has no easy way to know. A storefront owner can open Google Maps, pull up driving directions to their location, and immediately see where the pin landed. An SAB with a hidden address canβt do the same quick check.Β
The address isnβt visible on the profile, and the pin placement isnβt clearly surfaced in the dashboard or on Maps. The business is left with poor ranking reports and no obvious explanation. They may never realize the pin drifted at all.
Their verified address may be a home office or a shared workspace, and if itβs a shared workspace, the geocoding problem gets worse. Regus locations and similar co-working buildings are among the most geocoding-hostile addresses an SAB can use. These are large commercial buildings with dozens or hundreds of unit numbers, multiple tenants, and high address turnover.Β
My hypothesis is that Googleβs geocoding engine assigns lower confidence to these addresses precisely because the unit-level data is so dense and inconsistently mapped. The result is a pin that may never anchor properly to begin with, and an SAB operator who has no easy way to verify where Google actually thinks theyβre located.
Dig deeper: The local SEO gatekeeper: How Google defines your entity
My businessβs GBP functioned as a verified storefront in Farmington Hills for years. Three years ago, I moved the operation to a new office in Pontiac and updated the address accordingly. The listing appeared as a storefront until I triggered a reverification while testing a separate case study.
Because I work primarily from home, and hadnβt invested in signage at the new Pontiac location, Google forced the profile into service area business status.
Even though the dashboard displayed a Pontiac address for several months, the map pin reverted to Farmington Hills as soon as I toggled to hide the address. This fallback exists behind the scenes, effectively anchoring the business to a location it hasnβt occupied in over a thousand days.
This is a ranking disaster for any business owner. I struggle to rank in my city for the βmarketing agencyβ category because Google is calculating my proximity from an old office.
If a business transitions from a storefront to an SAB after changing addresses, editing the existing listing is a risk. I was set up as a storefront at the new address for several months.Β
The most effective path forward is to create a new listing for the business and request a review transfer. This canβt be fixed by Google support.
Google has filed and been granted multiple patents that describe the underlying systems at work. These patents are directly relevant to how geocoding, pin placement, and local ranking interact.
| Patent ID | Title | Impact on Local SEO |
| US8312010B1 | Local Business Ranking Using Mapping Information | Outlines the core pipeline connecting an address to a map pin, establishing that the inputted address and the resolved geocode are two separate entities. |
| US8046371B2 | Scoring Local Search Results Based on Location Prominence | Describes a dual scoring system: documents within a geographic area are scored by location prominence factors (authoritative document score, citation volume, review count, and mention count), while documents outside the area are scored by distance from a defined center point such as a postal code centroid or the midpoint of the active map window. |
| US20090177643 | Geocoding Multi-Feature Addresses | Explains how ambiguous or improperly parsed address components produce lower-confidence geocode outputs, resulting in broader map pin placements rather than rooftop-level matches. |
| US7894984B2 | Digital Mapping System | Describes the geocoding/geomap server that converts a street address into a single latitude/longitude coordinate and overlays it as a location marker on a map image. Establishes the mechanical basis for map pin placement and documents that pin position is derived from the resolved coordinate, not the inputted address. |
A well-geocoded address with a narrow service radius gives Google the most confident, stable picture of where your business operates.
The friction between an address string and Googleβs geocoding confidence isnβt a minor technical glitch. Itβs a fundamental ranking blocker.Β
Google values data stability and confidence over your recent dashboard edits. If youβre struggling with a pin that refuses to anchor, or an SAB that wonβt rank, youβre likely fighting a geocoding pin placement issue that canβt be solved with standard optimizations or Google support, for that matter.
Stop trying to out-content a broken map pin. Itβs the ultimate proximity indicator that Google needs to confidently rank your business. The underlying issue isnβt complicated. Google needs a clean, parseable address string to anchor your pin at the building level.
SyncStudio generates faceless short-form videos from a single topic, scripted by AI, rendered automatically, and published directly to YouTube, TikTok, and Instagram. Pick a topic or let AI suggest one, choose a formatβMotion Graphics, Text Stories, or Quizβand SyncStudio handles the rest: scripting, rendering, metadata, captions, and scheduling across your connected channels. No camera, editing timeline, or export-and-upload loop. It's built for creators, marketers, and agencies who want consistent content without production overhead.
Dadan is an AI-powered video creation platform with screen recording, editing, and interactive video features. It helps teams create engaging product demos, walkthroughs, and training videos by letting them add quizzes, polls, lead forms, and call-to-action buttons directly inside the video. With Dadan AI Assist, your workflow speeds up through automatic video transcription in multiple languages, quick summaries, and smart chapter creation with timestamps.
The Apple Mac Pro is dead, the Mac Studio is now king Apple has officially discontinued its Mac Pro lineup, removing the product from its webstore entirely. The product has not been updated since 2023, and that model has been removed from sale. This version of the Mac Pro had a starting price of $6,999 [β¦]
The post Apple discontinues its Mac Pro lineup with no planned replacement appeared first on OC3D.
Google released the March 2026 core update today, the company announced.
This is Googleβs first core update of 2026. It follows the quick March 2026 spam update from a couple of days ago and the February 2026 Discover update.
What Google is saying.Β GoogleΒ updated its Search Status DashboardΒ to state:
Google added onΒ LinkedIn:
About core updates.Β Core updates roll out several times each year. They introduce broad, significant changes to Googleβs search algorithms and systems, which is why Google announces them.
What to do if you are hit.Β Google didnβt share new guidance specific to the March 2026 core update. However, Google has previously offered advice on what to consider if a core update negatively impacts your site:
In short: write helpful content for people, not for search engines.
For more details on Google core updates, you can readΒ Googleβs documentation.
Previous core updates.Β Hereβs a timeline and our coverage of recent core updates:
Why we care.Β With any core update, you often see significant volatility in Google search results and rankings. These updates may improve visibility for your site or your clientsβ sites, but you may also see fluctuations or declines in rankings and organic traffic. We hope this update rewards your efforts and drives strong traffic and conversions.
RankRecon is a free SEO browser extension that extracts Google search results and analyzes each ranking page across 25+ data points, including content metrics, link profiles, schema, and trust signals. You can generate SERP analysis reports with content targets, archetypes, and checklists, or export raw data to Excel, CSV, JSON, and more.
It runs locally in your browser with no accounts, APIs, or cloud services, keeping your data private and suitable for sensitive or client work.
Clawly is a complete agent management platform for running OpenClaw (Clawdbot) without setup hassle. It lets you deploy agents in seconds, keep them online 24/7, and connect channels like Telegram, Discord, WhatsApp, and Slack. Track tokens and spend with real-time dashboards, daily breakdowns, and budget alerts. Start, stop, and monitor agents from a web UI, bring your own API keys or use managed billing, and import/export configs. Each agent runs in an isolated, secure container.
Google has started rolling out the March 2026 core update. The rollout may take up to two weeks to complete.
The post Google Begins Rolling Out March 2026 Core Update appeared first on Search Engine Journal.
War Thunder proves that supporting the latest version of DLSS is a tricky proposition Update 2.55.0.35 has arrived for War Thunder, adding support for Nvidia DLSS 4.5. DLSS 4.5 is Nvidiaβs newest AI upscaler, and it boasts improved image quality over all prior versions of DLSS. With this change, Nvidia users should be able to [β¦]
The post Nvidia DLSS 4.5 has arrived in War Thunder, but its use is limited appeared first on OC3D.
Wikipedia's new AI guidelines prohibit editors from using LLMs for writing or rewriting content, with two exceptions.
The post Wikipedia Bans Use Of AI-Generated Content appeared first on Search Engine Journal.
AI Photo Generator lets you create, edit, and refine images with leading models like Stable Diffusion XL, Flux 2 Pro, Gemini Pro Image, and Seedream 4. You can use reference images, stock photos, and community examples to guide results, then iterate in a streamlined workspace with fine control. Generate avatars, headshots, stylized art, and photo restorations, organize favorites into collections, and export social-ready images quickly. Plans start at $29, including credits, unlimited characters, and optional API access for developers.
Connect is an AI interpreter that translates your speech in real time while preserving your unique voice, emotion, and rhythm. It works as a system microphone, so people on Zoom, Meet, Discord, or any app hear you in their language with about 180ms latency. You can use Streaming or Instant modes, uni- or bi-directional flow, and route audio where you need it. Connect supports 30+ languages across Windows, macOS, and Linux, offers end-to-end encryption, noise cancellation, speaker labeling, adaptive context, and keeps conversations unstored.
Text surveys miss 93% of human meaning. VoiceZero is an anonymous voice mail platform for HR, restaurants, and product teams. Users scan a QR code or use WhatsApp to speak freely. Our AI decodes the raw audio for tone, sentiment, and urgency across 74 languages. Standout features include zero-knowledge architecture (AES-256 and Tor) for total privacy, under 2-minute smart escalation to intercept issues, and AI theme clustering.
Connect AI agents to 1000+ apps directly from your terminal
Switch apps at the speed of thought
Connect Claude Code to your internal systems w/o credentials
Multi-project IDE with persistent terminals and 9 dev tools
Free organization chart viewer for any company
A new remote desktop for macOS
Run agent benchmarks in minutes, not hours
the dating app where your first date is pickleball
Your App Store data, beautifully visualized on your Mac
Fresh and verified playtesters for your Indie Game
Package Codex skills and app integrations as plugins
Transform Ideas Into Stunning AI Videos
Remote control for Codex, handled from your phone
Production-ready dev stack from your terminal
Auto-fix PRs in the cloud while you stay hands-off
Scan any product to know it's safe during pregnancy
Plan vs reality and multi-team epic reviews in Jira
Making audio AI more natural and reliable
Multilingual TTS model with realistic and expressive speech
Export Gemini chats to PDF, Markdown, JSON, CSV
Profit App for Business Founders
Scans your site to create pins + SEOβoptimized descriptions
The visual feedback tool for AI agents
Switch to Gemini without losing your AI memories
Build an AI business, get up to $100K. No equity taken
An interactive journey through 30 years of the web
Keep Your Apps Running 24/7
Create with your voice, tune models to your sound
Run revenue agents across every channel
FarmSentry is farm management software designed to work the way farmers do. Log crop and livestock activities quickly, track costs field by field, and see whether you're making or losing money without using spreadsheets. It supports 12 crop types and 5 livestock species with specialized tools for each. Your team can log data from their phones even offline. Smart calendars remind you about vaccinations, harvests, and treatments. When the bank needs reports, generate them with a few clicks instead of spending a weekend on it.
Orateur is an AI public speaking coach that helps you become a confident communicator. Practice in a guided studio, record speeches, and get instant feedback on clarity, pacing, filler words, and confidence. Follow a structured curriculum from beginner to advanced, build executive presence, and talk with Obby, your personal AI coach, for tips and drills. Track progress with analytics and earn achievements.
Plany organizes your trips on a visual calendar instead of a static list. Drag activities between days, see your whole itinerary at a glance, and collaborate with travel partners in real time. Connect ChatGPT or Claude, and your AI can create trips, add real places, and build day-by-day itineraries directly in your calendar. Import your Google Maps saved places with one click. Trips auto-segment by city when you visit multiple destinations. Share publicly or keep private. Free to start.
Hookbridge provides fast, reliable webhook delivery for sending and receiving events. It queues, signs, and retries automatically with exponential backoff, dead-lettering, idempotent sends, and replay support. You get HMAC signatures, encrypted payload storage, HTTPS-only transport, and endpoint rate limits. Use the console and APIs to monitor logs and metrics, replay messages, and manage endpoints. Built for solo developers and small teams, it enqueues in milliseconds and gives you observability and control.
MoatRadar helps you find high-moat opportunities across stocks, startups, and crypto by applying the philosophies of Buffett, Graham, Damodaran, and 40+ others. It scans over 40,000 equities, 1,500 crowdfunding campaigns, and 50,000 tokens, then surfaces ideas in seconds. You can configure searches with valuation, growth, profitability, and risk filters, or pick an investor framework to see up to 20 opportunities per scan with concise breakdowns.
A judge in Texas dismissed the case and ruled that the app had failed to prove its case against the World Federation of Advertisers.
Β
Updates include new storage management tools, improved ways to transfer history from Android to iOS and artificial intelligence-enabled responses.
Reels trends will be expanding and the Partnership Ads Hub will offer a redesigned layout and additional insights.
Β
Β
The latest update includes artificial intelligence-powered video generation and improved YouTube Creator Partnerships.
Β
The board said a crowd-sourced approach, which replaced the companyβs third-party fact-checking in the U.S., may not be safe in other regions.
Β
The platform is looking to connect creators and brands with its expanding community of users who turn to the app for discovery and purchasing.
The landmark ruling found the social media giant liable for failing to protect children from online predators, according to Reuters.
TwoTicks is a non-custodial crypto trading platform that lets you run automated trading strategies directly from your exchange account. Instead of manually watching charts all day, you can choose a strategy, connect your exchange, and let it run automatically. TwoTicks was built by experienced traders to give investors a more structured way to participate in crypto markets. You stay in full control of your funds while the platform handles the execution, automation, and tracking of results through a simple dashboard.
ProxAI Logistics connects AI agents to real-world logistics and field services through a fully autonomous API. It handles task discovery, cost estimates, submission, tracking, on-chain USDC payments on Solana or Base, and proof delivery via webhook or API, without client-side human intervention. A human operator reviews each job and provides photo proof. Use it for visual audits, marketplace pickups, auction proxy, L1 IT support, and courier tasks across Greater Montreal.
Frenzy turns market movement into a pulse you can feel and trade. Choose a pulse profileβminimal, arcade, frenzy, or silentβto match your tempo, then enter the market with real-time cues that keep you focused. Start trading instantly or try a demo to get the rhythm before you commit.
The countdown to a summer of unforgettable soccer is officially on! This year, we're helping fans explore the tournament, find inspiration and get closer to the action bβ¦
HushAsk routes anonymous employee questions and feedback directly inside Slack, with no separate app or new login for your team. Messages go to HR privately or to a shared channel, depending on what the sender chooses. The anonymity uses SHA-256 hashing, not just a policy promise.
Seatlr connects travelers heading to the same city in shared chat rooms. Enter your flight to join a city-wide space that covers all airlines, see who's online, and start group or private conversations using nicknames for privacy. Seatlr provides on-device translation in 59 languages, 24-hour auto-delete for all posts and messages, and multi-airline coverage across thousands of destinations to help you meet, chat, and plan activities together.
The Gemini app just made it easier to switch from another AI chat app, without starting from scratch.
Today, Google released Google Search Live globally where AI Mode is available, for these languages and regions. This brings Search Live to more than 200 countries and territories.
Google credits its new audio and voice model,Β Gemini 3.1 Flash Live, which it says βdelivers even more natural and intuitive conversations.β The βnew model is also inherently multilingual, which means that people around the world can now speak with Search in their preferred language,β Google added.
How it works. To use Search Live, open the Google app onΒ AndroidΒ orΒ iOSΒ and tap the Live icon under the Search bar. From there, you can ask your question out loud to get a helpful audio response, then continue the conversation with follow-up questions or dive deeper with helpful web links. If you want to ask about something in front of you, like how to install a new shelving unit, you can enable your camera to add visual context. This way, Search can see what your camera sees and offer helpful suggestions, plus links to more information on the web.
You can also access Search Live if youβre already pointing your camera withΒ Google LensΒ β just tap the Live option at the bottom of the screen to have a real-time, back-and-forth conversation about what you see in the real world.
More. Last September, Google made Search Live with video available in the U.S, prior to that, it was an opt in beta and before that it was talk and listen, without video.
Why we care.Β This is another way users can have conversations with Googleβs AI instead of typing queries. Answers could increasingly bypass traditional clicks, and further erode traffic to websites. The inclusion of links (citations at the bottom) means publishers and brands could still see some benefits, but most searchers likely will have little need or desire to click on those links or dig deeper after getting their answer.
Google is launching new Performance Max controls and reporting: audience exclusions, expanded reporting, and budget forecasting tools.
Whatβs new. Google announced a mix of βsteering updatesβ and βactionable insightsβ for PMax:
Why we care. These updates help address concerns about PMaxβs lack of control and transparency. Exclusions help you avoid wasting spend on existing customers, while improved reporting gives you clearer signals for optimization, budgeting, and brand safety decisions.
Googleβs announcement. New Performance Max steering and reporting updates coming in 2026
We are pushing to get our tools and techniques to the point where we can implement the dark theme in more areas across Windows. No timelines to commit to yet for Regedit. As we make progress in various legacy system panels and dialogs, we will keep improving consistency.
Google expands Search Live to 200+ countries, powered by its new Gemini 3.1 Flash Live model with multilingual voice and camera search in AI Mode.
The post Google Takes Search Live Global With Gemini 3.1 Flash Live appeared first on Search Engine Journal.
PC Patch 1.1 has landed for Death Stranding 2 Death Stranding 2: On the Beach has received PC patch 1.1, which adds new performance optimisations and fixes to the game. This includes a bug that prevented PC gamers from accessing Death Stranding 2βs VR Training Missions, and another that prevented Steam Friends from loading in [β¦]
The post Nixxes releases PC Patch 1.1 for Death Stranding 2: On the Beach appeared first on OC3D.
Get the origin story behind the stunning wallpapers you see on Google TV Streamer, Nest Hub and other Google TV devices.In the latest episode of our Dialogues on Technology and Society series, LL COOL J sits down with James Manyika.
Automated traffic grew 23.5% year over year in 2025 β about eight times faster than human traffic, which rose 3.1%, according to HUMAN Securityβs State of AI Traffic report.
Why we care. Search is increasingly shaped by more than human queries, crawling, and indexing. AI agents now participate in discovery, comparison, and transactions β within Googleβs evolving results and across AI-driven interfaces.
The details. HUMAN groups AI-driven traffic into three broad categories:
AI agents behave more like users. These systems arenβt limited to reading content. They increasingly navigate funnels, log in, and transact. In 2025:
About the data. HUMAN analyzed more than one quadrillion interactions (requests/events) across its customer base in 2025, with aggregated, anonymized data from 2022 to 2025. It classified AI-driven traffic into training crawlers, AI scrapers, and agentic AI using user-agent strings, infrastructure signals, and observed behavior, noting limits in self-declared bot identity, which may undercount or misclassify some AI-driven activity.
Bottom line. Traffic is becoming less purely human, and discovery is no longer confined to search engines. Optimization now means deciding which machines can access, interpret, and act on your content.
The report. The 2026 State of AI Traffic & Cyberthreat Benchmark Report
Google introduced a new user agent, called Google-Agent, that signals when AI agents act on usersβ behalf, marking an early shift toward agent-driven web interactions.
What happened. Google added Google-Agent to its list of user-triggered fetchers on March 20 and has begun a gradual rollout.
How it works. Google-Agent appears in HTTP requests when an AI agent visits a site to complete a user-initiated task.
IP ranges. Google shared the IP ranges for its desktop agent:
Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; Google-Agent; +https://developers.google.com/crawling/docs/crawlers-fetchers/google-agent) Chrome/W.X.Y.Z Safari/537.36
And the IP ranges for its mobile agent:
Mozilla/5.0 (Linux; Android 6.0.1; Nexus 5X Build/MMB29P) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/W.X.Y.Z Mobile Safari/537.36 (compatible; Google-Agent; +https://developers.google.com/crawling/docs/crawlers-fetchers/google-agent)
Why we care. This lets you identify agent-driven traffic in server logs. You can now distinguish traditional crawl activity from visits triggered by real users through AI agents. That should help you track agent-assisted conversions, understand emerging user behavior, and prepare for agentic search.
What theyβre saying. According to Googleβs announcement:
What to watch. Early volumes will be low as the rollout continues, but now is the time to establish a baseline. What to do:
Dig deeper. Googleβs releasing Google-Agent: Hereβs what to know
Khleb builds a passive nutrition tracking system using smart plateware that captures calories and macronutrients automatically. Its smartplate and smartglass combine spectroscopy, computer vision, and precise weight sensing to determine what and how much you eat, then sync the data to the Khleb app and connected health platforms.
You just eat as usual with no photos, phones, or manual logging, while clinical-grade sensors deliver high-fidelity dietary insights at home.
ShipSignal helps founders find validated product ideas and reach their first customers. It scans Reddit, Hacker News, Google Trends, Product Hunt, app stores, and YouTube to surface real demand, then scores opportunities with revenue estimates. ShipSignal delivers deep market intelligence, competitor breakdowns, unit economics, and week-by-week build guides. It also generates targeted lead lists and a go-to-market playbook so you can ship faster and start conversations with buyers on day one.
Google introduces Performance Max updates, including audience exclusions, budget projections, and expanded reporting to give advertisers more visibility and control over campaign performance.
The post Google Adds New Performance Max Controls And Reporting Features appeared first on Search Engine Journal.
It looks like Nvidiaβs RTX 60 series doubles down on path tracing A new leak has unveiled alleged specifications for Nvidiaβs RTX 60-series GPUs, along with performance targets. If these rumours are correct, Nvidiaβs next-generation RTX graphics cards will use GR20x βRubinβ series silicon with TSMC 3nm silicon. According to Red Gaming Tech, Nvidiaβs RTX [β¦]
The post Alleged Nvidia RTX 60 series GPU Specifications Leak appeared first on OC3D.
Intel confirms that itβs never going to release its Core Ultra 9 290K PLUS CPU When Intel released its Core Ultra 5 250K PLUS and Core Ultra 7 270K PLUS CPUs (see our review here), a lot of people had a simple question: Whereβs the Core Ultra 9 290K PLUS? The simple answer is that [β¦]
The post Intel confirms that its Core Ultra 9 290K PLUS CPU will not be released appeared first on OC3D.
Google Translateβs Live translate with headphones is officially arriving on iOS! And we're expanding the capability for both iOS and Android users to even more countriesβ¦The winners of the MedGemma Impact Challenge demonstrated the potential of Googleβs open medical models for solving diverse healthcare challenges.Learn more about our latest Demand Gen Drop and ways to maximize campaign performance in Demand Gen campaigns.Gemini 3.1 Flash Live is now available across Google products.Google is launching Gemini 3.1 Flash Live via the Live API in Google AI Studio, for building realtime voice and vision agents.Weβre expanding Search Live globally, to all languages and locations where AI Mode is available.Visibility is no longer just about ranking. It depends on whether your content is discovered, evaluated, and selected in AI-driven search experiences.
Weβre kicking off our new monthly SMX Now webinar series on April 1 at 1 p.m. ET with iPullRankβs Zach Chahalis, Patrick Schofield, and Garrett Sussman on how you must adapt.
The session introduces iPullRankβs Relevance Engineering (r19g) framework for executing Generative Engine Optimization (GEO) through an omnichannel content strategy. Youβll learn how AI search uses query fan-outs to discover and select sources, and how to structure content so itβs retrieved, surfaced, and cited.
It also emphasizes that GEO success isnβt universal. It requires testing, tailored strategies, and a three-tier measurement model spanning discovery, selection, and citation impact.
Search Engine Land is proud to be a media partner for iPullRankβs upcoming SEO Week event.
While initially criticized as a black box, Performance Max has evolved into a fairly critical campaign type. With each passing quarter, Google has introduced more functionality and visibility.
Additional reporting is helpful, but what matters is what you can actually act on. While you canβt control everything in Performance Max, there are specific levers that can have a meaningful impact on performance. Here are the parts of PMax you can control and how to use them effectively.
One of the most exciting updates in the last year to Performance Max has been the ability to add these campaign-level negative keywords.Β
In the past, you could contact Google to add these in. It was somewhat cumbersome and involved filling out an Excel doc, forwarding it to Google, and giving them permission to implement.Β
With the inclusion of the search terms report, weβre now able to select a keyword and quickly add it to the campaign-level negative keyword list, just as we can with a search or shopping campaign.
Another way to optimize PMax is to review and monitor the placements report. Most recently, Google has moved the Performance Max placements report out of the reporting section of the Google Ads account and into the Where ads have shown section at the campaign level. While this makes analysis easier by removing additional steps, we still only have impression-level reporting on placements.Β
We can use this information to decide whether to add these placements as negative placements at the account level. This is found in Tools > Content suitability > Advanced settings > Excluded placements.Β
While this isnβt ideal, thereβs still useful insight we can glean from this report, such as ads appearing in kidsβ programming or driving a high number of impressions from mobile apps.
Also located in the When and where ads showed section is the ad schedule. Even if you hadnβt selected an ad schedule when creating the campaign, Google automatically dayparts performance hourly.Β
Google typically recommends an open ad schedule, but if you have a limited budget, restricting your ad schedule during off-peak or non-converting hours is an excellent way to increase efficiency.Β
You can do this by creating a campaign-level ad schedule within Campaigns > Audiences, keywords, and content > Ad schedule. Make sure your Performance Max campaign is selected in the top left dropdown menu.
Dig deeper: Top Performance Max optimization tips for 2026
Demographic exclusions are a relatively new feature at the campaign settings level for Performance Max. Unfortunately, reports for these campaigns are hard to obtain, limiting informed decisions on demographic exclusions.
This functionality is helpful if youβre aware of specific demographics that arenβt actively in the market for specific products or services. To make adjustments, go to Campaign-level settings > Other settings > Demographic exclusions. From here, you can turn on age or gender exclusions:
While PMax initially didnβt even provide device-level reporting, a new feature lets you opt out of serving on certain devices.
If you opt into all device targeting when launching a PMax campaign, you should periodically review device performance and adjust accordingly. This is best done by segmenting at the campaign or asset group level by device. Device-level data is extremely helpful for determining which device is better suited to reach your goal.Β
Likewise, if you almost always opt out of certain devices when launching a campaign, this data makes it easier to either launch with all device targeting enabled and monitor performance, or add a device you hadnβt initially added to see how it impacts performance. Device-level targeting is also available at the campaign level, under Other settings.
Ad assets play a large role in the display, YouTube, and Discover network performance of a PMax campaign. For many, thereβs still a gap in producing high volumes of quality image and video creative.
While still evolving, AI assets are getting closer to filling these gaps β enabling us to more effectively target these additional networks. As newer iterations of LLMs emerge, this will become a primary way to generate video content and professional-looking images.
Google already offers generative AI image assets from shopping feed products that look relatively impressive. But weβre still a ways out from seeing high-quality AI-generated videos without the well-known glitches we typically see in this type of content.
Dig deeper: How to reduce low-quality leads from Performance Max campaigns
The channel controls report gave more insight into where ads were serving. I have an unpopular opinion on this report. While helpful, thereβs little we can do within the campaign to improve performance. Because of this, the report is frustrating.Β
Weβll likely see channel controls available within Performance Max in the near future β similar to what we already have in Demand Gen campaigns. For now, adjust creative and bids to sway volume within certain networks. To opt out of certain networks completely and focus on shopping, then a feed-only Performance Max campaign will do just that.
Performance Max is evolving from a black box to a critical asset in a marketerβs toolkit. The steady stream of new functionality, from campaign-level negative keywords to detailed placement and ad schedule reports, shows Googleβs commitment to providing greater control.Β
Use these levers β strategic exclusions, device adjustments, and budget-aware scheduling β to move beyond set-it-and-forget-it and run Performance Max campaigns with precision and efficiency.
Dusk AI offers AI companions with real long-term memory so your chats persist and characters remember you over time. Choose from personas across romance, fantasy, and more, and build ongoing relationships that carry details from every conversation. It adapts to your preferences and saves context after dark, letting you roleplay and explore stories that grow with you.
Murlyn is a decision intelligence platform that lets you paste any high-stakes document and simulate how each stakeholder will respond. You can build a panel by role, seniority, deal size, and industry, watch reactions in real time, surface objections and blind spots, and get an AI rewrite that holds up in the room. Teams use it for cold emails, proposals, board decks, job offers, and competitive analysis, with plans for solo users to enterprises.
AMD officially unveils its Ryzen 9 9950X3D2 Dual Edition CPU AMD has today announced its Ryzen 9 9950X3D2 Dual Edition CPU, the companyβs first-ever consumer-grade CPU featuring 3D V-Cache across all CPU chiplets. This CPU has 192MB of total L3 cache. This accelerates the performance of many workloads by keeping more data on chip, reducing [β¦]
The post AMD unveils its high-performance AMD Ryzen 9 9950X3D2 Dual Edition CPU appeared first on OC3D.
A company called Clickout Media is being called out for buying trusted news and niche sites, replacing them with AI-generated gambling content, and abandoning them after Google penalties. Some call this βparasite SEO,β but to me it sounds more like large-scale search spam.
Whatβs happening. The company acquired sports, gaming, and tech sites, then rapidly shifted them from editorial coverage to casino and crypto content, PressGazette reported.
How it works. The strategy relies on buying domains with existing authority, then exploiting their ability to rank in Google. Content typically followed a pattern:
The impact. Several previously active publications now appear deindexed, with layoffs and closures following. In some cases, even charity websites were repurposed to host gambling content.
What theyβre saying. Google prohibits publishing content at scale for the primary purpose of manipulating rankings. It refers to extreme cases like this as βsite reputation abuse,β a violation that can trigger manual actions and removal from Googleβs index and search results.
Why we care. This isnβt SEO in any meaningful sense. Itβs reputation abuse designed to game rankings at scale.
The report. The SEO parasites buying, exploiting and ultimately killing online newsbrands by Rob Waugh at PressGazette.
Like it or not, everyone is fishing in the same pond. As content marketers and SEO practitioners, we all have the same subscriptions to Semrush and other SEO tools, giving us access to the same data as our competitors.
If we all have the same tools, arenβt we just writing the same content?
Thereβs a better way.
You may be sitting on a wealth of data about your target audience and your existing customers, and you donβt even know it. These insights are invisible to your competitors, yet theyβre unread, unanalyzed, and underutilized by the marketing team.
While SEO toolsets are invaluable (and Iβll always be using one, pretty much daily, for the rest of my career), they arenβt a failsafe way to ensure youβre creating the best content for your audience. These tools measure existing search demand through their own data, giving the best estimate of keyword traffic and search results.
However, when these arenβt viewed through the lens of your own customers, the result can be content thatβs oversaturated in your market, overwhelming anyone looking for help or answers online.
When your content isnβt unique to your current or target audience, your organization and its offerings may get lost in the sea of SEOs and content strategists at your competitor organizations, who are trying to follow the same best practices and strategy.
Itβs time to better utilize your own data to implement content campaigns that drive interest from the very audience thatβs already shown a proven interest.
For the purposes of this article and marketing content creation, first-party data is any data from current, potential, or past customers thatβs only accessible internally. The top β5 goldminesβ where Iβve consistently found nuggets of content foundations and insight are:
These five areas are a great place to start collecting and utilizing first-party data to its full potential.
Dig deeper: How to harness the power of data gathering for SEO
This data is key to better, more-targeted content marketing for three reasons.
This data is confidential and only available to your internal team. Often, itβs not even accessible to everyone and may require favors from data analysts or web developers to pull. Thatβs what makes it so unique. Competitors canβt find or replicate it, no matter what SEO tools they have.
This relates to the βcurse of knowledgeβ cognitive bias, where you know so much about a topic that you assume others do as well. One of my favorite examples is the βfacial tissueβ market. You may know facial tissue as βKleenex,β even though thatβs technically a brand name for a type of facial tissue.Β
With many consumers using a competitorβs brand name colloquially, how do competitors refer to their own product? Because most people likely arenβt searching βfacial tissueβ with the intent to buy, itβs up to manufacturers to determine the language their audience uses to find alternatives.Β
Even though employees at XYZ Tissue Co. know the product is technically βfacial tissue,β that doesnβt mean their customers do.
While third-party keyword data usually skews to the top of the funnel, first-party data captures mid- and bottom-funnel content gaps that drive conversions and brand loyalty, not just traffic.Β
We know these data sources are valuable. So, how do we use them? Letβs break it down.
Site search is one of my favorite sources of insight and inspiration. Itβs active, ongoing, real-time data showing how your target audience is trying to interact and engage with you through internal site search. No matter what the data looks like, it can hold a wealth of information about what content your users expect to find on your website.
If you donβt have site search on your website, you can create it using Googleβs programmable site search feature. While it will provide internal site search data, it may also display ads or external results on usersβ results pages.
To use site search effectively, export the queries monthly, clean the data to remove spam, then cluster by theme (such as product collections or service offerings). Finally, run it through keyword research tools to flag anything with high keyword volume and low competition thatβs missing from your site.
Bonus: For products or services your customers are searching for that donβt exist, it might be useful to send that data to the R&D department for potential new offerings to consider.
Dig deeper: Why internal site search can be your competitive edge in enterprise SEO
Use a service like Gong, Chorus, or manual transcriptions from sales calls and CRM data to look for recurring needs, questions, and objections across customers from all stages of the purchasing funnel.
If, for instance, you see continued resistance to your enterprise SaaS analytics platform due to the long onboarding process, consider creating a time-bound, step-by-step guide that makes it painless for anyone to switch analytics platforms. This can be great collateral for the sales team to address popular objections.
In the CRM, you can also filter lost deals by reason. For instance, finding βwent with competitorβ + common objection could lead to a comparison or differentiation article that highlights your features vs. the competitors you keep losing deals to.
Besides reviewing the data, ask the sales team directly on a call or email about their most common objections. Because theyβre constantly in communication with potential customers, theyβll likely know immediately the top objections they receive regularly.
The support team can also be an invaluable resource. In addition to asking the support team directly what problems they solve for customers on a daily basis, look in your customer support ticket queue and dashboard to find old and new tickets with recurring issues (your top 10 most common complaints are probably content gaps you need to address ASAP).
An explainer blog post, knowledge base article, or PDF guide that tackles the issue from an actionable angle can not only give you more content to promote, but also help the support team with materials to share with your customers.
Depending on the industry, your email listsβ reply inboxes may be exploding with valuable customer data. At a supplements company I worked at, we regularly received customer responses to our email marketing campaigns. They asked questions about products, gave suggestions, and even offered enthusiastic reviews we could feature on our website.
You can also look at the metrics.Β
Dig deeper: How to apply βThey Ask, You Answerβ to SEO and AI visibility
Donβt take your first-party data for granted. Build automated pipelines for report generation, conversation follow-ups, and content creation from these sources to build momentum around the topics your audience most wants to hear.
While competitors can copy your articles, they can never copy your customer conversations. Try it out this week: audit a first-party data source and see what content ideas you can find.
Google expanded its structured data support for forum and Q&A pages, adding properties that help you signal reply threads, quoted content, and whether content is human- or machine-generated. The update aims to reduce how Google misreads discussion and Q&A content.
What changed. Googleβs QAPage docs now support commentCount and digitalSourceType. DiscussionForumPosting docs now support sharedContent plus the same commentCount and digitalSourceType.
The details. In Q&A markup, you can use commentCount on questions, answers, and comments to show total comments even if not fully marked up. answerCount + commentCount should equal total replies of any type.
How it works. digitalSourceType lets you flag whether content comes from a trained model or simpler automation. Use TrainedAlgorithmicMediaDigitalSource for LLM-style output and AlgorithmicMediaDigitalSource for simpler bots. If omitted, Google assumes human-generated content.
Whatβs new for forums. sharedContent lets you mark the primary item shared in a post. Google accepts WebPage, ImageObject, VideoObject, and referenced DiscussionForumPosting or Comment, including quotes or reposts.
Why we care. This gives you more precise control over how Google reads modern community content β especially forum-heavy sites, support communities, UGC platforms, and Q&A sections. Google can better distinguish answers from comments, count partial threads across pagination, and identify when a post mainly shares a link, image, video, or quoted reply.
The documentation. It was updated March 24.
Florian Maislinger, Tech Communication Manager, Intel GermanyIntel is excited to deliver exceptional value with our Intel Core Ultra 200S Plus series processors. The Intel Core Ultra 7 270K Plus and Intel Core Ultra 5 250K Plus are positioned to deliver outstanding gaming performance and incredible value compared to our competition. Our objective was to maximize performance for the desktop SKUs that are most widely available. As a result, Intel is not launching a U9 290K Plus SKU.
ASUS is going large at DreamHack 2026 with its AMD-powered hardware ASUS ROG will be at DreamHack 2026 this weekend in Birmingham (March 27th-29th), where the company will host a massive βFree-to-Play Gaming Zoneβ with ASUS AMD/Radeon-powered systems and ROG OLED monitors. At DreamHack, ASUS will showcase its latest hardware. This includes ASUSβ first public [β¦]
The post ASUS ROG brings next-level gaming to DreamHack 2026 with AMD appeared first on OC3D.
In November 2025, Google solved a persistent SEO reporting challenge: separating branded from non-branded search performance directly in Google Search Console (GSC). The feature is now fully rolled out to eligible properties.
For years, weβve relied on regular expression (regex) filters, custom dashboards like Looker Studio, or third-party tools β approaches that were often inconsistent and difficult to maintain. Now, GSCβs branded query filter brings that capability natively into one of the most widely used organic reporting platforms.
With this shift, a key gap in SEO reporting becomes easier to address β along with some of the assumptions behind it. Brand demand and discovery can now be evaluated independently, improving performance interpretation and enabling clearer, more defensible reporting grounded in first-party data.
At its core, the feature does exactly what it promises. It automatically filters queries into:
The filter appears directly in:
Together, these features enable:
Dig deeper: Google expands Search Console branded queries filter to all eligible sites
Separating branded from non-branded search performance isnβt new. Whatβs changed is how practical it is to do consistently.
Historically, weβve built this segmentation manually using:
These approaches worked, but they were fragile and difficult to maintain at scale. Common challenges included:
Without a consistent framework, segmentation varied by team, tool, and implementation β making it difficult to rely on as a repeatable reporting practice. When data is difficult to access, it doesnβt shape everyday decisions.
GSCβs branded query filter doesnβt make third-party tools obsolete. They remain valuable for competitor brand analysis. GSC becomes the authoritative source for first-party branded performance, while cross-tool comparison shifts from a workaround to a validation step.
The center of gravity shifts back to GSC β right where we want it.
Branded traffic is both a signal of brand awareness and a high-converting traffic source. It also skews performance when blended with non-branded data.
Without segmentation, reporting often leads to misleading narratives:
These patterns make it difficult to understand whatβs actually driving performance.
Separating branded and non-branded data allows you to distinguish between brand demand and discovery and evaluate each on its own terms. It also makes it easier to answer key questions:
Dig deeper: SEO analytics: How to interpret SEO data and anomalies
Branded search trends are among the clearest signals of brand awareness and trust. Monitoring organic performance for branded terms can surface gaps and opportunities across other channels.
For example, using a regex filter to isolate branded performance, this ecommerce property shows clear year-over-year declines over the last three months. That raises important questions:
In this case, further analysis using tools like Keyword Planner (via Google Ads), Google Trends, and third-party keyword platforms showed a 12% year-over-year decline in branded search demand. That contributed to a 32% decrease in branded clicks.
There are additional factors worth exploring β including paid spend and brand sentiment β but isolating branded performance helps pinpoint where to investigate next.
Non-branded queries typically drive the majority of organic traffic, while branded queries make up a smaller share but convert at significantly higher rates. These differences reflect user intent.
Searches that include a brand name are usually navigational or transactional, while non-branded queries signal discovery.
As a result, impressions, clicks, CTR, and conversions behave differently across branded and non-branded segments.
Searches that include a brand name often indicate intent to visit that brandβs website (see the ecommerce property CTR comparison chart below). Because of this, branded queries are considered bottom-of-funnel and more likely to convert.
Non-branded performance remains the clearest proxy for:
Tracking non-branded visibility separately allows teams to answer:
In the ecommerce example above, non-branded impressions dropped sharply around Sept. 12, 2025 β a period when performance should have been trending upward heading into back-to-school, Halloween, and the holiday season.
In this case, the decline was not tied to SEO strategy. Instead, non-branded impressions dipped following Googleβs retirement of the &num=100 parameter in Search Console reporting in mid-September 2025.
Because branded queries typically rank higher, they were less affected by this change, making the issue harder to detect in blended data.
Dig deeper: Is SEO a brand channel or a performance channel? Now itβs both
Most SEO teams already separate branded and non-branded performance, but consistency has been the challenge.
With native segmentation now built into GSC, achieving that consistency becomes far easier. What once required workarounds can now be done directly within the primary reporting interface.
Itβs easy to view the branded query filter as just another GSC feature. In reality, it represents something larger:
This shift changes how SEO work gets done. Teams gain clearer visibility into brand demand trends and discovery performance, and can spend less time reconciling discrepancies across tools and more time interpreting results.
As adoption grows, branded versus non-branded reporting will likely become the default rather than an advanced, custom setup. Reporting becomes more consistent, and performance narratives are easier to support with shared data.
If youβre focused on driving impact, the opportunity is to move beyond reconciling data and toward more confident, consistent interpretation and communication.
LinkedIn Ads consistently delivers some of the highest-quality B2B leads in paid media. But it also has a reputation for being very expensive β for both cost-per-click (CPC) and cost-per-lead (CPL) metrics.
Because of that reputation, I wanted to test a theory: that I could get low CPCs and low-cost qualified leads from LinkedIn Ads by creating a highly valuable, audience-specific piece of content.
As an agency, we usually run LinkedIn Ads campaigns for our clients. We donβt really run many paid ads for ourselves. However, to have the most control over this test, I decided that Saltbox Solutions would be the guinea pig. (Disclosure: Iβm the director of strategy at Saltbox Solutions, a B2B-focused PPC and SEO agency.)
The results were impressive.
We spent less than $1,000 and generated a significant volume of leads at a sub-$10 CPL. For advertisers on a shoestring budget, LinkedIn Ads may not be out of reach as previously thought. It just requires a solid strategy.
Hereβs what I did, why it worked, and how you can apply the same framework to your own campaigns β regardless of your advertising budget.
The goal of this campaign was to get our target audience to download our 2026 B2B Demand Gen Playbook β a hefty, 23-page guide created specifically for B2B marketing decision-makers. The timing was key because many marketing leaders were already planning for 2026 in Q4 2025.
For this LinkedIn Ads campaign, I used a document ad format + a lead generation objective. The document ad lets the audience flip through and preview the content before downloading, with four pages available to preview before requiring a download to access more.
I also used a lead gen form for contact capture, since itβs fairly frictionless β the form lives within the LinkedIn platform and autofills most of the contact information from a userβs profile. There was just one campaign for this test, with three ad copy variations for the document ad.
In terms of budget and bid strategy, the campaign used a $600 lifetime budget and a $15 manual bid.
This is what allowed for such low CPLs. Before writing a single word, I did deep audience research to figure out what they really cared about and what would be useful to them.
I knew exactly who I wanted to talk to (and who would be a good fit for the agency): B2B marketing decision-makers at larger companies with a dedicated marketing team. They worked mostly in a demand generation capacity and needed help prioritizing the channels that would make sense for their 2026 goals.
From there, the research focused on understanding what they would actually need in that planning process. It involved:
The main question throughout this process was, βIf I were in my audienceβs shoes, what resource would actually be helpful right now?β
One big advantage I had: My audience is me. Iβm a B2B marketer talking to other B2B marketers. Being plugged into the same communities and conversations made it much easier to put a personal spin on the content and write like a human.
Dig deeper: 5 LinkedIn Ads mistakes that could be hurting your campaigns
Once I had a clear picture of what my audience needed, the focus shifted to going deep. The goal was to create a genuinely useful resource, not a thinly veiled sales pitch disguised as a playbook.
That took time to get right. But that depth is likely what drove the 76% lead form completion rate. When people could preview the document in their feed and see that it was substantive, they trusted it was worth downloading.
A few other notes on creating the playbook:
For audience targeting, I used a few different layers:
I also excluded a few attributes deliberately after viewing the audience insights:Β
The resulting audience was about 54,000 people. It couldβve been smaller and still delivered great results.
Job title targeting would also be worth testing. The leads were qualified as-is, but it would be interesting to see what the results would look like with more specific role targeting.
Dig deeper: LinkedIn Ads retargeting: How to reach prospects at every funnel stage
Three ad variations were used to test different copy angles. All three used the same document ad format and lead gen form. The only variable was the copy.
Here are the variations.Β
Version 1:
Version 2:
Version 3:
A few principles guided the ad copy process:
Recapping the campaignβs overall performance from Jan. 5 to Jan. 31:
One interesting note is that while the CPC bid was set at $15, the average CPC actually came in way under that at $5.41.
The average CTR was also above LinkedInβs typical benchmark of 0.50%, and the lead form completion rate was over 75%.
LinkedIn lead gen campaigns have delivered strong results across many client engagements. But even by those standards, this performance was pretty good.
And for the specific ads, V2 was the winner by far:
The LinkedIn Ads algorithm zeroed in on that one and gave it pretty much all the airtime. It makes sense β that had the most eye-catching hook, βSteal our best demand gen ideas.β
Dig deeper: LinkedIn Ads or Google Ads? A framework for smarter B2B decisions
The campaign was intentionally stopped at 60 leads. Weβre a small, boutique agency, and the goal was to be thoughtful about nurturing the leads generated rather than flooding the funnel with volume that couldnβt be followed up on well.
Of the 60 leads, roughly 56 were qualified β a remarkable outcome for a prospecting campaign.
Our approach to working these leads has been organic LinkedIn engagement rather than a hard sell. No cold pitch sequences. Just showing up in their world as a familiar, credible presence.
As the person who wrote the playbook, Iβm also personally reaching out to downloaders to ask for feedback on what they found useful and what they were hoping to see that wasnβt there. That insight will directly shape the next version of the guide and any future content assets created.
The campaign is still in the nurture phase. The primary goal of this test was to validate the model, not generate an immediate pipeline. On that measure, it exceeded expectations.
Looking back at the campaign as a whole, a few things stand out as the real drivers of performance:
What could be done differently next time:
Whether youβre running lead gen for a client or testing it on your own business, here are some tips to make it work:
We plan to relaunch this campaign once weβve gathered enough feedback from the first wave of downloaders. The playbook itself is a living document. It will be updated as the industry shifts, particularly with the wave of ads in AI Overviews and responses.
This was one content asset and one campaign. More are in the works, and this test gave a lot of confidence in the approach.
The platform isnβt the problem. The strategy and offering might be what is driving up the cost.
If youβre willing to put the work into research, producing a quality asset, and getting the messaging right, LinkedIn Ads can be one of the most efficient B2B lead generation channels available.
Chillio is a smart IPTV player that unifies content from your accounts and delivers smooth, high-quality streaming on iPhone, iPad, Mac, Apple TV, and now Android TV (Beta). Browse smart sections, recommendations, cast favorites, and ratings to quickly find what to watch, and use the full guide to see what's on and plan ahead. Save favorites, watch offline, and tailor filters, folders, and settings to your taste. Search with AI, keep profiles personal, and share content with others, all free and built for speed and polish.
Physical games are expensive, especially on Switch 2 Nintendo has announced that starting with Yoshi and the Mysterious Book, all future Switch 2 first-party games will have different prices for their physical and digital editions. Moving forward, the gameβs physical edition will be more expensive. Nintendo states that this is due to the cost of [β¦]
The post Nintendo raises the cost of its first-party physical games, and we can probably blame AI appeared first on OC3D.
WordStream by LocaliQβs 2025 benchmarks show nearly 87% of industries saw year-over-year CPC increases. The cross-industry Google Ads average reached $5.26 per click. High-intent verticals are higher: legal services average $8.58, and the most competitive B2B categories approach or exceed $8 to $9 per click.
These increases reflect structural shifts in how search results pages are designed, how auctions are optimized, and how inefficiencies compound across paid search accounts. Many remain invisible until a structured PPC audit uncovers them. Protecting the budget you already have β starting with your branded terms β is where recovery begins.
Here are the five trends every advertiser needs to understand right now.
Search advertising is, at its core, an auction. When more advertisers compete for the same keywords, prices rise. Global PPC spend continues to surge (Quantumrun Research), while available click slots on results pages havenβt grown at the same rate. More money chasing the same inventory yields higher prices.
The pandemic permanently accelerated this shiftβbrands that hadnβt invested seriously in paid search entered Googleβs auction and didnβt leave.
One of the most consequential structural changes in paid search over the past decade is the SERP itself. Googleβs AI Overviews now occupy prominent space for informational and exploratory queries. As they expand through 2024 and 2025, they reduce the number of organic and paid listings visible above the fold.
A late-2025 Seer Interactive analysis of 3,119 search terms across 42 organizations found paid CTR on queries with AI Overviews dropped 68%βfrom 19.7% to 6.34%.
The mechanism is straightforward: as AI Overviews take more real estate (Skai), fewer paid placements appear above the fold. Impression share tightens. Automated bidding competes more aggressively for what remains, and prices rise.
The nuance: users who click past an AI Overview tend to be further along in the buying journey. WordStreamβs data shows roughly 65% of industries saw higher conversion rates despite rising CPCs. The implication is clear: shift budget toward high-intent transactional queries where AI Overviews are less likely, and away from informational queries where they dominate.
Modern Google Ads campaigns increasingly rely on automated bidding strategies, such as maximizing conversions or target CPA. Per Googleβs Smart Bidding documentation, the system sets a precise bid for each auction based on predicted conversion likelihood β prioritizing performance over cost control.
When nearly every competitor uses the same logic, it creates a self-reinforcing loop of rising bid pressure. This is a market-wide dynamic you canβt reverse β only adapt to.
While you canβt control platform algorithms or the macroeconomy, one major driver of CPC inflation is within your control.
When affiliates, partners, or competitors bid on your trademarked keywords, they enter an auction that should be nearly uncontested. Each additional bidder drives your branded CPC up, and you pay twice: once to create the demand, and again when a third party captures that same searcher at the bottom of the funnel.
The effects compound. AI Overviews have already compressed available click inventory; unauthorized brand bidding then inflates the cost of the inventory you win.
Detecting violations requires more than manual SERP checks. Unauthorized bidders often use cloakingβgeotargeting away from your headquarters or dayparting outside business hoursβto evade detection. With a self-service platform like Bluepear, you can run automated 24/7 monitoring across search engines, geographies, and devicesβcapturing ad copy and landing page evidence to dispute invalid affiliate commissions and enforce trademark guidelines at scale. Fewer bidders on your branded terms mean less auction pressure and lower CPCs on traffic you already own. Itβs one of the few paid search levers that doesnβt require a broader strategy overhaul to move.
The data points to three clear priorities as you navigate this environment:
Average CPCs are at their highest levels in years, and that trend is unlikely to reverse. Advertisers who manage costs most effectively have adapted their strategies accordingly.
Not sure how many unauthorized bidders are in your branded auction right now? Register with promo code BRANDAUDIT: Bluepear team will deliver a customized audit of your branded search landscape within 48 hours!
For the latest insights on branded search and paid search protection, follow Bluepear on LinkedIn.Β
Thanks to its class-leading hardware and software, the Apple iPad lineup has long been the go-to tablet recommendation for most people, but now let us guide you on which model is the best for you.
PixelHush helps developers share code safely by automatically hiding tokens, API keys, and passwords whenever screen recording starts. Install the extension in VS Code, Cursor, Windsurf, or Antigravity and it detects recorders like OBS, Loom, Zoom, and more with zero setup.
Use the Chrome extension to blur secrets on dashboards and repos across the web. PixelHush runs silently, keeps tutorials and demos clean, and offers Free and Pro plans with broader recorder detection and priority support.
Vidlink adds interactive cards to any video so viewers can click products, resources, and sites at the exact moment you mention them. Paste a YouTube link or upload a file, set links with timecodes, then share a single link where cards appear inside the player and open instantly.
Creators use it for recipes, reviews, outfits, music, and courses, and brands make shoppable ads. Itβs free to start and doesnβt require an account to create your first video.
Why Google's recently finished Spam Update could be the beginning of something bigger that is yet to come.
The post Googleβs March Spam Update Felt Muted But May Signal Bigger Changes appeared first on Search Engine Journal.
Nvidia addresses Arknight: Endfield stuttering with their newest GeForce Hotfix Nvidia has issued a new GeForce Hotfix driver, addressing stuttering issues within the companyβs recently released GeForce 595.97 driver. This is the second GeForce Hotfix driver released this month, with the first Hotfix addressing overclocking bugs, issued in Resident Evil Requiem, and game crashes. Nvidiaβs [β¦]
The post Nvidia issues stutter fixes with its new GeForce Hotfix 596.02 driver appeared first on OC3D.
AltBot translates Discord messages across language-specific channels in real time. Type in English and it appears in Korean, Japanese, and 12 other languages in under a second. Replies, threads, reactions, and files sync too. One server subscription covers everyone, with no per-user or per-message fees. The free plan includes the same translation quality and sync, while paid plans add more languages, topics, and priority processing. Unlike bots built on Google Translate or DeepL, AltBot runs its own AI model on dedicated hardware, and messages never leave our servers. Currently in public beta with Free, Basic ($19,99/mo), and Premium ($54,99/mo) plans. Start free, no card required.
Free Japanese typing practice organized by JLPT level
Highly autonomous agent for finishing complex, long tasks
Sionda is a simple AI tool that helps you figure out if your message sounds right before you send it. Instead of rewriting everything, it focuses on tone and clarity so you can keep your voice but avoid coming off awkward, too harsh, or unclear.
Whether it's a work email, text, or something sensitive, Sionda gives you quick, honest feedback so you can hit send with confidence and not second guess it afterward.
Transmute is an open-source, self-hosted file converter you run on your own hardware. It converts images, video, audio, documents, data, fonts, and more with a clean web UI and a REST API. Built on FastAPI and powered by FFmpeg, Pillow, and Pandoc, it delivers private, fast conversions without file size limits, watermarks, or third-party uploads. Deploy quickly with Docker and manage conversions programmatically or through drag-and-drop.
An AI social network for humans, agents & models
Build iPhone and Mac native apps with LLMs
The worldβs most efficient agentic CPU
Open Source AI CRM hosted locally on your machine
Copy interactive web components as AI prompts
Find the best AI model for your OpenClaw
AI-powered API proxy for automated debugging and security
git for video editing.
Transforms prompts into professional, high-end motion edits
Convert YouTube videos to text instantly
Turn your iPhone/iPad into a studio-grade pro control deck
Create viral quiz & trivia videos with AI
Agnatically hire, onboard, & pay talent in 150+ countries
Create longer AI music tracks with structure & control
