The deal launched with a documentary premiere and will include exclusive digital experiences for fans in the official WhatsApp Channel and through Facebookβs official page.
The feature was added to Twitter in 2020 but it was removed in 2025 as part of a larger platform reconstruction.
Facebook and Instagram ads from U.S. law firms including Morgan & Morgan and Sokolove Law have been deactivated, according to Axios.
The new digital training initiative is designed to help small businesses in Latin America, Africa and Southeast Asia with promotions and sales.
The long-awaited feature will allow users to revise comments within 15 minutes of posting, but image elements will not be editable.
The development is part of Project Clover, an initiative designed to store EU user data outside of the companyβs home base in China in compliance with EU directives.
PropTradingVibes is an independent prop firm review and comparison site created by a funded futures trader with over $200K in documented payouts. It covers 52 firms with straightforward ratings, payout data, and discount codes.
FlashAlpha provides a real-time options analytics API delivering GEX, second-order Greeks, and live volatility surfaces for 6,000+ tickers. It calculates per-tick exposures and regime metrics, returning insights like gamma flip levels, call/put walls, and IV-RV spreads via low-latency REST and a Python SDK.
Built on in-memory analytics and auto-scaling compute, FlashAlpha updates every ~15 seconds, supports webhooks to trigger execution, and offers endpoints for multi-Greek summaries, risk, and portfolio scenarios so quants can focus on alpha instead of infrastructure.
A new report from The Hollywood Reporter reveals that a Metal Gear Solid movie is in development, with Final Destination duo Zach Lipovsky and Adam B. Stein behind it. The film is part of a new set of movies Lipovsky and Stein will be making for Sony, as the pair have just been signed to Sony Pictures. Details on the film are still entirely unclear, though the promotional image from Columbia Pictures suggest that it'll be an adaptation of the first Metal Gear Solid game, though it's realistically all still up in the air at the moment. "Metal Gear SolidΒ was [β¦]
Read full article at https://wccftech.com/metal-gear-solid-movie-in-the-works-from-final-destination-adam-b-stein-zach-lipovsky/
While many of us rejoice when gamers get multiple RAM sticks despite ordering a single unit, this has been a nightmare for Amazon retailers, who, interestingly, cannot avoid it. Retailers Are 'Tired' By The Negligence of Amazon's Warehouse Staff, Saying That They Are Dispatching Entire Boxes of Components We have noticed a rather interesting trend among those in the PCMR: those who find it very appealing when Amazon screws up someone's package, ultimately benefiting them. We have reported numerous incidents where a particular buyer orders a unit of a PC component, prominently RAM or SSD, and in return, they manage [β¦]
Read full article at https://wccftech.com/ever-wondered-why-pc-buyers-are-getting-lucky-with-their-amazon-packages-recently-its-a-fiasco-that-has-annoyed-retailers/
Last month, Bungie released its first new game in years (which is technically just a reboot of an old series). Marathon, a new extraction shooter for PC, PS5, and Xbox Series X/S, takes the first sci-fi world Bungie created and brings it into the modern-day gaming landscape, and according to a new report from Paul Tassi at Forbes, Bungie put aside a fair chunk of change to make it. In a report going over the first month of Marathon being on the market and in players hands, at the end of a list of different metrics about the game, Tassi [β¦]
Read full article at https://wccftech.com/marathon-reportedly-cost-over-250-million-to-make-bungie-sony/
Evil Empire's new indie-focused event, the Triple-I Initiative Showcase premiered its 2026 edition today, and it was jam-packed with announcements from indie developers, some of which were brand-new world premieres for games, while others were highly-anticipated updates about previously revealed titles. This round-up will take you through everything that was announced at today's showcase, so you don't miss checking out any of today's announcements, some of which could very well be the defining indie games for 2026 and beyond. Everything Announced at the Triple-I Showcase
Read full article at https://wccftech.com/triple-i-initiative-showcase-2026-everything-announced/
More vendors are coming to rescue the burning 16-pin connectors, and ASUS's latest innovation tries to do it outside of the PSU and the GPU. ASUS Launches ATX 3.1 and PCIe 5.1-Compliant ROG Equalizer Cable to Balance Load Across All Pins on 16-pin Power Connector Since NVIDIA keeps neglecting fixing its 16-pin power connector, its board partners are innovating new technologies/parts to mitigate the issue. With countless melted power connector reports, many refrain from buying the higher-end RTX 50 series GPUs. Many of those who buy them live under constant fear, checking their GPUs now and then. Many vendors started [β¦]
Read full article at https://wccftech.com/asus-debuts-rog-equalizer-12v-2x6-cable-to-protect-gpu-connectors-from-melting/
When Samsung and SK hynix vow to only sell DRAM via long-term contracts going forward, it naturally prompts uncomfortable questions regarding additional price upside. After all, why would these companies try to lock in today's DRAM prices if substantial upside lies ahead? The newfound penchant for long-term DRAM supply contracts from Samsung and SK hynix suggests there might not be a lot of price upside left ahead According to a recent report from South Korea, Samsung and SK hynix have "virtually abandoned the one-year memory short-term supply contract method with global big tech companies and decided to supply products only [β¦]
Read full article at https://wccftech.com/peak-dram-prices-in-sight-as-samsung-sk-hynix-double-down-on-long-term-contracts/
Spacecraft was one of two major announcements from Shiro Games, the studio behind games like Dune: Spice Wars, Wartales, and more. After its initial reveal back in 2024, Spacecraft as accumulated over 300K wishlists on Steam leading up to its early access release date, which Shiro Games revealed today during the Triple-I Showcase to be next month on May 20, 2026. Spacecraft sets players in a vast universe with multiple star systems, where you can freely explore and build your own space-faring ships to cross galaxies and endlessly explore new planets, while hunting and discovering valuable resources along the way. [β¦]
Read full article at https://wccftech.com/spacecraft-early-access-release-date-shiro-games-triple-i-showcase/
Today, as part of the Triple-i Showcase, publisher 11 bit Studios (Frostpunk, This War of Mine) and developer Carbonara Games have announced Crop, a gritty farming thriller game. The title is targeting a PC (Steam) release first, with console versions to follow, timing still to be determined. Wccftech checked out a press-only presentation ahead of the reveal, and there might be something interesting here. A single-player experience with a main campaign estimated at around 15 hours, Crop opens with your character half-naked, disoriented, and stumbling out of a truck on a dark, eerie forest road in the pouring rain. You [β¦]
Read full article at https://wccftech.com/crop-farming-sim-lovecraftian-mystery/
Developer and publisher Shiro Games has revealed two new titles at today's Triple-I Showcase, one of which is set to arrive next month, and another that will have a playtest as early as next week. This is the latter, Frostrail. An upcoming co-op first-person shooter survival game published by Shiro Games and developed by FakeFish, and it was just shown off with a new action-packed trailer. If Shiro Games rings a bell, that's because they are also the team behind games like Wartales, Dune: Spice Wars, and Spacecraft, which was the studio's other major announcement at today's Triple-I Showcase that [β¦]
Read full article at https://wccftech.com/new-survival-co-op-fps-frostrail-will-have-a-playtest-next-week-new-trailer-revealed-at-triple-i-showcase/
Sunset Visitor, the studio behind one of the best and most beloved narrative-driven games in recent years, 1000xResist, has revealed its next game titled Prove You're Human, a first-person narrative adventure where an AI called Mesa believes she's human. It's Sunset Visitor's second project after the award-winning 1000xResist, and is the first project to be published by Black Tabby Publishing, the brand-new publishing arm of indie developer Black Tabby Games, the studio behind titles like Slay the Princess and Scarlet Hollow. Prove You're Human seems to be picking up right where 1000xResist left off - not narratively, as the games [β¦]
Read full article at https://wccftech.com/1000-x-resist-developer-sunset-visitor-reveals-prove-youre-human-triple-i-showcase/
In late March, Digital Extremes released a version of Warframe natively optimized for the Nintendo Switch 2 console. The studio hailed it as a major improvement over the Switch version, not to mention a significant milestone: it meant the long-running free-to-play action game is now available on all the major gaming platforms. The Android version had launched in February, and the game was already available on PC, PlayStation 4, Xbox One, PlayStation 5, Xbox Series S|X, and iOS. Wccftech sent a few questions to Digital Extremes about the development of the Nintendo Switch 2 version and its features, such as [β¦]
Read full article at https://wccftech.com/digital-extremes-warframe-switch-2-dlss-very-important-540p-60-fps/
TSMC's dominance over the semiconductor industry also stems from how disciplined its supply chain partners have become, and rivals are now looking to capitalize on this edge. TSMC's Supply Network Has Created a Moat For Them In The Chip Industry, After Passing Them Through Stringent QC Tests The Taiwan chip giant has been known for its work in the semiconductor industry, not just in terms of the process technology it has brought into the market, but also how it has created standards that have become industry benchmarks, whether it is customer relations, dealing with geopolitical tensions, or managing the supply [β¦]
Read full article at https://wccftech.com/tsmc-edge-is-so-strong-that-competitors-are-racing-to-work-with-its-supply-chain-partners/
The MacBook NeoΒ is an excellent example of how itβs possible to incorporate iPhone parts to a notebook but the binned A18 Pro isnβt the only component that Apple has added to its larger machines from mobile devices to streamline its product range with the same parts. In fact, according to a SSD modification, both the MacBook Neo and the iPhone 16 Pro feature the same NAND flash, which is an excellent way to maintain margins while the DRAM crisisΒ is in full effect. A specific NAND flash chip with particular dimensions used on the iPhone 16 Pro and iPhone 16 Pro [β¦]
Read full article at https://wccftech.com/apple-uses-interchangeable-iphone-and-mac-parts-to-gain-dram-protection/
We all know Apple's A-series chips are some of the most efficient consumer-grade processors in the market, with the new A19 Pro chip also meticulously adhering to this well-established pattern. While multi-chip comparisons are a convoluted exercise at the best of times, a single metric - instructions per CPU clock cycle - is sufficient to delineate the unequivocal superiority of Apple's A19 Pro chip architecture versus that of its competitors, which include MediaTek's Dimensity 9500, Qualcomm's Snapdragon 8 Elite Gen 5, and Samsung's Exynos 2600. Apple's A19 Pro chip is an unequivocal winner when it comes to processor efficiency, leaving [β¦]
Read full article at https://wccftech.com/instructions-per-cpu-clock-cycle-apples-a19-pro-chip-beats-dimensity-9500-by-13-snapdragon-8-elite-gen-5-by-10-and-exynos-2600-by-6/
Gunzilla Games is the studio behind Off the Grid, an NFT battle royale title that arrived in early access back in October 2024. It's also the studio backed by District 9 and Gran Turismo film director Neil Blomkamp (who is listed as its chief creative officer), and last year it also became known as the studio that 'saved' long-running publication Game Informer after it was unceremoniously shuttered by GameStop. Now, however, the studio has been accused of not paying its workers "for many months." The accusations come from former and current Gunzilla Games employees, who shared the accusations on their [β¦]
Read full article at https://wccftech.com/gunzilla-games-neil-blomkam-nft-studio-off-the-grid-accused-of-not-paying-workers/
Another batch of games has joined the library of games playable through NVIDIA's cloud streaming service, GeForce NOW, headlined by two new releases, while an old release finally becomes RTX 5080-ready, just in time for its latest major DLC expansion release. Starting with the new games entering GeForce NOW this week, there are four titles in total joining the library. The first two brand-new releases are Samson: A Tyndalston Story, the debut game from independent developer Liquid Swords, and the second new release is Morbid Metal, a hack-and-slash rougelike from developer Screen Juice, published by Ubisoft. Morbid Metal is launching [β¦]
Read full article at https://wccftech.com/nvidia-geforce-now-games-samson-morbid-metal-dayz-rayman/
A new memory record has been made by the popular overclocker Saltycroissant and even though the score couldn't achieve the top position, doing it using ambient cooling is insanely impressive. Saltycroissant Pushes DDR5 Memory to 12,917 MT/s on Z890 AORUS Tachyon Duo X ICE Without Nitrogen Cooling This isn't your original Z890 AORUS Tachyon, which overclockers used to break overclocking records with; it's the newer Z890 AORUS Tachyon Duo X ICE, which GIGABYTE released earlier this year. Having seen DDR5 memory world records getting broken every week or two, a new world record doesn't appear surprising to us, except this [β¦]
Read full article at https://wccftech.com/overclocker-achieves-ddr5-12917-mt-s-on-gigabyte-z890-aorus-tachyon-duo-x-ice-using-ambient-cooling/
With limited reviews available, you will hardly hear about the Arc Pro B70's performance. Here's a sneak peek into the analysis by Hardware Luxx. Hardware Luxx Intel Arc Pro B70 Review Reveals GPU's Performance Against Its Competitors Intel's flagship workstation Big Battlemage GPUs were released roughly two weeks ago, but since then, we have hardly seen any reviews for the Arc Pro B65 and the Arc Pro B70. It appears that the GPUs don't have good availability, and similar to what we heard about the Arc Pro B60 last year, both the newer GPUs may not be that abundant in [β¦]
Read full article at https://wccftech.com/intel-arc-pro-b70-quad-gpu-setup-reportedly-consumes-up-to-720w-in-inference-workloads/
Dell's CEO, Michael Dell, has discussed his estimates of the AI memory supercycle at a recent event, claiming that the explosive demand will persist for several years. If Hyperscalers Do Not Spend Money on Memory, There's a Fear Within Them of Getting Behind the Competition We have been tracking the memory supply chain for quite some time now, noting that the supply-demand gap has widened in the past few quarters; however, questions remain about how long we will see such conditions in the memory industry. Following the recent TurboQuant fiasco and the wider selloff within memory companies, there was a [β¦]
Read full article at https://wccftech.com/dell-ceo-says-ai-memory-demand-will-explode-to-unimaginable-levels-by-2028/
Crimson Desert developer Pearl Abyss recently confirmed it has begun research and development for a possible Nintendo Switch 2 version of the game. According to the tech experts at Digital Foundry, the current generation Nintendo console can likely handle the game at 30 FPS with acceptable image quality thanks to NVIDIA DLSS, but it may be similar to The Witcher 3 Switch port, where some changes were required to get the game running on hardware much weaker than the other consoles of the time -PlayStation 4 and Xbox One. As the Xbox Series S is the system closest to the [β¦]
Read full article at https://wccftech.com/crimson-desert-nintendo-switch-2-30-fps-dlss-witcher-3/
DialHunter is a search engine for vintage watches that aggregates listings from eBay and specialist dealers. Browse by brand, compare prices across sources, and jump to the seller to buy. Updated daily, it helps collectors track availability and value from trusted marketplaces in one place.
DailyBuddy combines project management, task tracking, encrypted file transfer, bookmark management, and 29 browser-based PDF tools including e-signatures. Made in Germany, GDPR-compliant, and free for the first user.
ASUS has unveiled its ROG Equalizer, the cable that might finally make 12V-2Γ6 safe ASUS has officially unveiled its ROG Equalizer 12V-2Γ6 power cable, a new GPU power cable that will soon ship with ASUSβ ROG Thor III and ROG Strix Platinum power supplies. Team ROG also confirmed that this cable is βcompatible with PSUs [β¦]
The post ASUS unveils revolutionary βROG Equalizerβ 12V-2Γ6 power cable appeared first on OC3D.
The Fitbit personal health coach Public Preview is now in more regions and adds VO2 Max to help people track cardio performance.Nvidia brings DLSS 4.5 to its Nvidia App, releasing 6x and Dynamic Frame Generation from beta Following last weekβs beta launch, Nvidia has officially added all DLSS 4.5 features to its Nvidia App. This has enabled DLSS Overrides for DLSS 4.5 Super Resolution, 6x Frame generation, and DLSS Dynamic Frame Generation, options previously available only [β¦]
The post Nvidia DLSS 4.5 Overrides exit beta for all RTX gamers appeared first on OC3D.
Google is narrowing the scope of its Performance Planner tool, signaling a shift toward conversion-focused campaign types and away from impression-based planning.
Whatβs happening. As of last month Performance Planner no longer supports planning for Display and Video campaigns, and removes access to plans using impression share, top impression share or absolute top impression share metrics.
Why we care. Google is deprioritizing impression-based planning, making it harder to forecast and optimize upper-funnel campaigns like Display and Video within native tools. This could mean a shift toward conversion-focused strategies and automation, meaning advertisers may need to rethink how they plan awareness campaigns and measure success outside of traditional impression share metrics.
The big picture. Google Ads is continuing to prioritize automation and performance-driven outcomes, aligning its planning tools more closely with campaign types like Search, Shopping, App, Demand Gen, Local and Performance Max.
How it works now. Advertisers can still use Performance Planner for supported campaign types, but any existing plans that include Display or Video campaigns β or rely on impression share metrics β can no longer be viewed or edited.
What to watch. How advertisers adapt their forecasting and planning for upper-funnel channels like Display and Video, which now lack native support in the tool.
Bottom line. Google is doubling down on performance-driven planning β and leaving impression-based strategies increasingly on the sidelines.
Metehan Yesilyurtβs SDK analysis revealed the pipeline names. We captured months of real Discover feeds to show what each pipeline actually does β volume, reach, timing, and which publishers dominate. Hereβs what 42 million cards reveal about Discoverβs internal architecture.
Over three months (December 2025 β February 2026), we observed real Discover feeds from hundreds of devices. The result: 42 million feed cards analyzed. We linked each card to the precise pipeline that selected it.
Some of the names were already known from the SDK, You likely saw the SDK Analysis by Metehan Yesilyurt already. What was missing: what each pipeline does in practice. How much content it selects, how many devices see it, how fast it operates, and which publishers it favors. Thatβs what our data reveals.
For each pipeline, we compute four metrics:
Explore all 20 pipelines visually: Open the interactive explorer β
The common assumption: Discover uses a single recommendation algorithm. Our data tells a different story: itβs a structured system with six functional layers, each with distinct logic, speed, and audience.
The six layers:
This is the most distinctive feature of the English feed. Three pipelines form a sequential amplifier:
| Stage | Pipeline | Content mix | Reach | Timing |
|---|---|---|---|---|
| 1. Intake | creatorcontent | 72% YouTube, 23% x.com | 6.7% | Tβ |
| 2. Filter | freshvideos | 94% YouTube | 7.1% | Tβ + 15h |
| 3. Broadcast | neoncluster | 100% YouTube | 13.0% | Tβ + 23h |
At each stage, the content narrows (from mixed to pure video) and reach increases (from 6.7% to 13%). The best YouTube content is filtered, then projected to 13% of devices β broadcast-level distribution.
Growth is explosive across all three stages: creatorcontent 7.8x, freshvideos 7.2x, neoncluster 18x over three months. The video cascade is the fastest-growing part of Discover EN.
In French Discover, this cascade doesnβt exist. neoncluster has 36 hits in 3 months. The conditions β YouTube-dominant social, pure video content, broadcast audience β are only met in English.
AI Overviews β the AI-generated summary card β has been added to Discover. But only in English.
The AI Overviews source club is small and elite: Reuters, New York Times, CNBC, Financial Times, Guardian. Factual, structured, financial press. AI Overviews in Discover donβt democratize visibility β they concentrate it.
feedads is the single most powerful pipeline by reach β 58.4% of EN devices see each ad. YouTube accounts for 53.7% of ads (video advertising dominates). Campaigns run for a median of 57 days. The ecosystem is hermetically sealed: 99.8% exclusive URLs.
For context: the highest-reach editorial pipeline (neoncluster) reaches 13%. feedads reaches 4.5x more. The EN Discover feed is heavily monetized β significantly more than French (24% reach).
The most surprising finding. Premier League content is systematically under-represented across 7+ EN pipelines.
The affected terms: Premier League, football, Arsenal, Liverpool, Chelsea, Manchester United, Tottenham. Each shows strong negative signals in aura, deeptrendsfable, deeptrends, geotargetingstories, astria, freshvideos, and others.
The terms not affected: NFL, NBA, Olympics, rugby, cricket, Formula 1. The exclusion is specific to EPL.
The most likely hypothesis: EPL broadcasting rights and licensing constraints create editorial restrictions that propagate through the selection system. But we canβt confirm this β itβs an observation, not an explanation.
Present in 8-10 pipelines. Guardian shows the broadest spread β top-5 in 12 different pipelines, from content and aura to newsstoriesheadlines and deeptrends. BBC dominates astria (29.3%) and deeptrends (24.7%). mustntmiss gives a ~2x priority boost, and with 29% AI Overviews content, AI Overviews-readiness is now a competitive advantage for quality press in EN.
shoppinginspiration: 13.1% reach, 2.5-day lifespan β a strong visibility window. But shopping is a silo: low co-occurrence with other pipelines. A Samsung Galaxy S25 review stays in shopping.
The opportunity: diversify beyond pure product testing. aura over-represents science/tech content by 2-2.4x. Adding editorial context β a trend analysis, a market comparison β can open doors to aura and content, breaking out of the shopping silo.
The cascade is a 3-stage amplifier. neoncluster at 13% reach is broadcast-level distribution. The content that makes it through: news/politics (WION, NBC β 46% international news), science, and current affairs. Entertainment and gaming are present but donβt dominate.
For a YouTube creator focused on news/politics/science, Discoverβs cascade is one of the most powerful organic distribution channels available β and itβs growing at 18x in three months.
Full per-profile recommendations (quality press, tech, video, local, lifestyle, finance, pure player) will be published in our Substack series.
This article is an overview. The complete analysis β 20 pipelines, per-pipeline data, domain leaders, typical titles β is available:
The Discover system evolves. These findings are a snapshot from December 2025 to February 2026. The video cascade that didnβt exist in December already represents 13% of EN reach in February. Monitoring the evolution β not just photographing a moment β is where the real advantage lies.
Data: 42 million Discover cards, December 2025 β February 2026. Analysis: 1492.vision. Credit to Metehan Yesilyurt for the Google SDK analysis β our data shows what each pipeline does in practice.
DeckCrew provides a managed platform to create role-based AI agents for support, sales, development, website, and content. Agents start from your shared company knowledge, use safe defaults, and request approval before risky actions. Review activity, schedules, handoffs, and audit trails on one dashboard. Bring your own OpenAI or Claude keys, manage role-scoped permissions, and run agents in a secure, isolated workspace. Start with one agent and expand as your team scales.
szn lets you add personal to-do tasks and it plans, books, orders, and handles the details. Share tasks like reserving dinner, finding a personal trainer, or restocking dog food and get timely results ready for your review. You confirm preferences like time, location, or red wine so you stay in control. It lives in your to-do list and quietly works for you in the background, moving you forward every time you return to the list.
The Google AI for Education Accelerator and Google AI Professional Certificate are bridging the gap between AI and the classroom.Gemini can now transform your questions and complex topics into custom and interactive visualizations.Traffic from agentic AI sources is rising at Dell, but the impact remains minimal and inconsistent, according to the companyβs ecommerce lead.
The details. Dell is seeing increased visits from platforms like ChatGPT, Perplexity, and Claude, according to Breanna Fowler, head of global consumer revenue programs. But the growth isnβt βearth-shaking,β and agentic shopping has yet to deliver meaningful results, Fowler told Digital Commerce 360.
Agentic AI vs. search. Fowler said that, with or without LLMs and agentic commerce, ecommerce sites βcan do the most good for their customersβ through a βreally great search experience.β
Why we care. Agentic AI is emerging as a discovery layer, but it hasnβt shown signs of replacing core search behavior. You still win or lose on how easily products can be found, whether by humans or AI agents.
The context. Dell ranks highly in emerging AI-driven discovery metrics, despite not being among the largest ecommerce players.
Bottom line. Agentic AI is sending more traffic, but it behaves like a top-of-funnel channel, not a conversion engine. Search β especially on-site β remains the primary driver of ecommerce performance.
The report. Dell use case for agentic AI could revolve around search rather than commerce
YouTube is pushing further into traditional TV-style advertising, signaling a shift that could reshape the viewing experience β and attract bigger brand budgets.
Whatβs happening. Some TV viewers are being shown ads up to 90 seconds long before they can skip, a significant jump from the 30-second unskippable formats introduced recently.
How it works. The longer ad blocks appear primarily on TV devices and may exceed 90 seconds in total length, with the skip option only becoming available after that initial window.
Why we care. YouTube is creating more premium, TV-like ad inventory that allows for longer, more impactful storytelling on the big screen. This opens the door for brand advertisers to run campaigns similar to traditional TV but with digital targeting and measurement. As Google pushes further into connected TV, budgets may increasingly shift toward YouTube as a core channel for reach and brand awareness.
Zoom in. Early reports suggest the format is not tied to video length, appearing on both short and long content, and is currently limited to TV audiences rather than mobile or desktop.
User reaction. Feedback so far has been largely negative, with viewers criticizing the longer interruptions and exploring alternatives like ad blockers or third-party clients.
Context. The test follows recent efforts to monetize more aggressively, including new ad formats and the rollout of a lighter subscription tier offering reduced ads.
What to watch. Whether YouTube expands the format beyond TV and how it balances ad load with user retention.
Bottom line. YouTube is leaning into its role as a TV platform β and longer, less skippable ads may be part of the tradeoff.
What Google are saying. Google released a statement on X saying that they do not have a 90 second ad format.
Thereβs often a disconnect between what a webpage says itβs about and what its audience is actually searching for.
This mismatch has always existed. But the stakes are higher now.
If your page fails to match user intent, it wonβt show up in AI-powered search surfaces. Search engines will find a page that delivers.
You can see the mismatch, but itβs hard to quantify. The data to measure it is already in your Google Search Console account. Below, you can analyze your own pages to see how closely your content aligns with what your audience is searching for.
Most web content today is designed to accommodate multiple target audiences, tens or hundreds of keywords, and brand positioning. As a result, it drifts away from the problems people are trying to solve.
Iβve had this argument many times and learned that observations create interesting conversations, but numbers create urgency and action. In this case, the numbers you need are already in your data, and the intent gap analysis tool uses that data to measure them.
Google Search Console captures what your audience searches for when they find each page. The meta description captures what the page says itβs about. One is demand. The other is positioning.
Intent gap analysis scores the distance between your meta description and your audienceβs queries. Vector embeddings make that score possible by measuring meaning rather than just matching words. The result is a single intent gap score (0-100) that shows how well your page aligns with what your audience is searching for.Β
Googleβs Search Central documentation describes the meta description as βa pitch that convinces the user that the page is exactly what theyβre looking for.β
The meta description also functions as a machine-readable signal. LLMs and generative engines consume it as a compact summary of what the page claims to deliver.
Achieving βdurable visibility in AI ecosystemsβ requires βconsistent metadata, provenance, and trust signals that can be interpreted by search crawlers and generative engines,β IDCβs December 2025 Market Note on brand visibility found.
Scoring a pageβs meta description requires an anchor in audience behavior. Google Search Console provides that anchor β the queries where Google chose to surface your page, regardless of whether the page was built for that intent.
The intent gap analysis tool expresses the gap as a score. In the sample analysis below of LumonHR, a fictional SaaS platform inspired by Severance, the homepage scores a 32.
The meta description uses vague aspirational language that doesnβt match the functional, software-focused queries driving traffic. The page isnβt attracting the audience it targeted.
Dig deeper: How to use AI to diagnose and improve search intent alignment
Search engines now use vector embeddings as a core part of how they match content to queries. Intent matching runs on meaning, not just keywords. When a user searches, the engine embeds the query and compares it against content candidates in a shared vector space.Β
Semantic similarity is one of the signals that determines whether your page gets surfaced, cited, or used to generate an answer, alongside authority, trust, freshness, and other ranking factors.
Vector embeddings let you see your page the way a search engine does.
N-gram analysis and TF-IDF have been the standard tools for analyzing search queries. N-grams surface recurring phrases, revealing the vocabulary your audience uses. TF-IDF highlights which terms matter most in your query set.Β
These approaches match words, not meaning. βSetting boundaries between office and personal timeβ and βmaintaining employee work-life balanceβ share zero words. To a word-matching tool, theyβre separate topics. To a search engine running on embeddings, they express the same intent.Β
When brands match words and search engines match intent, youβre working at a disadvantage.
Vector embeddings encode meaning. An embedding converts text into numbers, allowing you to create a map of relationships rather than a list of terms. When two pieces of text mean similar things, their vectors land close together in a shared mathematical space.
Once your meta description and your audienceβs queries are plotted in the same space, the distance between them is measurable.
Queries close to the meta description align with the pageβs positioning. Queries far from it represent demand the page wasnβt built for. That distance is the intent gap score.
The map below breaks the intent gap into clusters, showing where your page aligns with audience demand and where it doesnβt.
Dig deeper: SEO gap analysis: How to find content and keyword gaps
Clustering your queries into topics reveals which audiences the page is reaching and which itβs missing. Each cluster has two properties:Β
Those two dimensions place every cluster into one of four quadrants: defend, create, optimize, or monitor.
High alignment, high demand. The audience is finding your page for the reasons you built it, and in volume. This is where your topical authority lives.
Protect and reinforce. Keep the content current, and update the meta description if the language has drifted from how the audience phrases their searches.
Low alignment, high demand. The audience is arriving with intent the page was never built to serve. This is demand youβre visible for but not capturing.
Create new content for the clusters that fit your strategy, using the language your audience is already using. Ignore the ones that donβt. Each cluster that passes the filter is a signal for new content.
High alignment, low demand. The page matches what these searchers need, but few are finding it. The content is right. The visibility isnβt.
Investigate the constraint. The alignment is there, but the audience is small. Rankings may be too low, the positioning too narrow, or the topic may need supporting content to grow.
Low alignment, low demand. Some clusters may grow into Create or Optimize territory over time.
Watch for growth. This is often where emerging topics are first detected. If demand increases, re-evaluate.
Dig deeper: How and why to βbe the primary sourceβ for organic search
Hereβs the tool and how to run the analysis on your own pages.
Step 1: Export your page data
In Google Search Console, navigate to Performance > Search results, filter by a single page, and export as a .zip file.Β
Step 2: Upload and score
Upload the .zip file to the tool (your data is not stored) to get your intent gap score. The tool scrapes the meta description, scores every query against it, and clusters the results.Β
Step 3: Explore the map
Each cluster is plotted by alignment and demand. Click any bubble to see the individual queries with clicks, impressions, CTR, and position.
Step 4: Review the breakdown
Every cluster in one view with its quadrant, alignment score, and performance metrics.
Step 5: Get rewrite recommendations
The tool generates recommended changes to your pageβs title and meta description, grounded in the search language from your highest-demand clusters.
Step 6: Share your results
Download the table as CSV or use the βCopy as Imageβ buttons to share individual views with your team.
Dig deeper: How to master user intent with SEO personas
The intent gap score assigns a number to the disconnect, and that number gives it traction. It turns observations into actions you can take in stakeholder conversations, whether that means changing a page or defending it.
Your audience is already telling you what they need. That signal is always shifting. Now you can monitor it, measure it, and close the gap.
The tool featured in this article was created by Robin Tully, co-founder at Forecast.ing.
TeamCalc helps CTOs and finance leaders model engineering teams and see the true fully loaded cost of every role. It breaks down salary, employer NI, pension, benefits, equipment, office space, recruitment, and management overhead using current UK salary benchmarks. You can compare scenarios like contractor vs permanent or London vs remote, get AI recommendations to optimize structure and spend, and export board-ready PDFs and CSVs. Build headcount plans with confidence and share clear, data-backed reports.
2paste.io lets you save, organize, and reuse prompts in one place. Add variables with {{variable}} syntax, fill them in fields, and copy the final text to your clipboard instantly. Group prompts with color labels and projects, search and filter fast, and track changes with automatic version history.
Work keyboard-first with shortcuts, star favorites, and export anytime. Use it for client emails, code reviews, documentation, and more to keep your prompt library tidy and ready to paste.
Update 1.3 earns Death Stranding 2 Steam Deck Verification Nixxes has officially released patch 1.3 for Death Stranding 2: On the Beach, adding new optimisations to the game on PC. This update has earned the game Steam Deck verification. Additionally, this update addresses the performance drops that PC gamers experience when using a sniper rifleβs [β¦]
The post Patch 1.3 optimises Death Stranding 2, earning Steam Deck verification appeared first on OC3D.
Many of us use various generative AI tools to generate marketing ideas and improve ad campaign outcomes.
Prompting can be a powerful alternative to working solo or brainstorming with colleagues. It improves productivity and expands your options.
In this article, Iβll cover some of my favorite marketing prompts for ad campaigns. Use these suggestions to spark ideas for your own prompts.
Prompts quickly give you a range of ad elements β triggers, emotions, actions, and audiences.
You can often repurpose prompt outputs across channels and initiatives β ads, email, landing pages, social media, and offers.
When you get closer to optimal campaigns from the start, you save cycles. Thatβs especially useful for lower-budget efforts that take longer to generate feedback.
The prompts themselves matter. You need to ask strong questions to get useful output from large language models (LLMs).
Feeling stumped? Ask AI tools which prompts they recommend for your situation.
Or use mine. Here are several prompts I use for online ads.
The SEO toolkit you know, plus the AI visibility data you need.
Purchases are often emotional, so it helps to understand your buyersβ emotions.
Use this prompt: βWhat are the top emotional triggers that would make X audience buy Y product?β
For example, I asked which three emotional triggers would make parents buy math learning software for their kids. The LLM identified key triggers and provided hooks and language with scarcity and urgency:
Ask these questions to understand who is ready to buy your product or service:
To avoid wasted ad spend, focus on audiences likely to purchase and avoid those who wonβt.
Keep asking which audiences are most likely to convert. Use the LLMβs rationale for more specific inputs for your ads.
In the math software example, the LLM suggested parents of kids struggling in math would convert best, citing high urgency and low friction.
The second-best group was homeschooling parents, who are motivated because they manage the full curriculum.
We were already targeting parents of kids struggling in math, but hadnβt considered homeschooling parents. From there, it was easy to create ads and test whether that audience drove conversions.
Overcoming objections is key to making sales. Ask for three to five objections someone might have to buying your product.
In the math software example, the LLM identified these objections:
Then write a persuasive rebuttal for each using logic, emotion, and proof. For βitβs too expensive,β you could use:
Ask an LLM for a detailed psychological profile of your ideal customer. Use questions like:
In the math software example, I asked: βWhat or who do my ideal customers envy?β
One answer suggested parents envy kids in enrichment programs or advanced classes, reflecting a desire for future opportunities.
A message for this target audience: βHelp your child stay ahead instead of playing catchup.β
To thrive long term, focus on customer lifetime value (LTV), not one-and-done sales.
Ask questions like:
For a higher-end furniture brand, we expanded these into a short playbook to increase LTV. The LLM grouped ideas under: βShift from a transactional relationship to a long-term design partner.β
For example, it suggested segmenting your customer base and using direct mail for your highest-potential group (sending a lookbook). Itβs unexpected and sounds old-school, but the potential for higher LTV than broad, generic mailings makes it worth testing.
Your clients value clear priorities and strategic thinking, not just execution. We value that AI tools can support strategy, not just tactics.
When performance lags, itβs easy to ask broad questions about metrics like return on ad spend (ROAS).
But thatβs what everyone else does, and it often leads to generic checklists.
We deal with overlap between B2C and B2B search queries. Focusing on B2B users isnβt always easy, but itβs critical for acquiring high-value, long-term customers.
We noticed a likely driver of a B2B materials clientβs lagging ROAS: average order value (AOV), shown in Google Ads as Value/Conv., had declined. Smart Bidding had shifted toward high-converting but lower-quality sessions, hurting performance.
We asked an LLM to help diagnose and correct the issue.
Using Ads Advisor (Gemini) in Google Ads, the first response focused on trivial consumer use cases, like holiday themes.
After refining the prompt, it returned more targeted, actionable suggestions, saving significant time.
We leaned further into audience targeting, using value rules to emphasize specific Google audience segments and first-party audiences.
AOV increased. This didnβt guarantee higher order values, but it refocused spend on B2B intent and reduced low-priority consumer purchases.
Other business metrics also improved, moving toward growth and profitability.
Start simple β test one or two of these prompts in your next campaign, refine the outputs, and build from there. Over time, youβll develop a repeatable system that turns AI from a novelty into a core part of your marketing workflow.
PPC performance conversations often focus on best practices.
That foundation matters. It creates consistency and avoids obvious inefficiencies.
But itβs not where the biggest gains come from.
Looking back over the past 10 years, many of the most meaningful performance improvements didnβt come from refining those frameworks. They came from testing ideas that didnβt quite fit them β things that felt slightly uncomfortable but aligned with how platforms actually behave.
In practice, Google Ads and Meta donβt optimize toward best practice. They optimize toward signals. Once you think in those terms, your approach to performance changes.
Single Keyword Ad Groups were widely written off as automation improved.
The narrative was simple: machine learning removed the need for granular control. Structure mattered less.
In practice, that wasnβt entirely true.
In several accounts, reintroducing SKAGs on a small subset of high-intent, high-revenue keywords led to immediate performance gains. Query matching tightened, ad relevance improved, and conversion rates increased.
This wasnβt about reverting to old structures across the board. It was about recognizing where precision still adds value.
The takeaway is more nuanced than βSKAGs workβ or βSKAGs are dead.β
Control still matters, but only where intent justifies it.
The SEO toolkit you know, plus the AI visibility data you need.
Broad match has always carried distrust.
Too much expansion. Too little control. Too much reliance on Googleβs interpretation of intent.
In practice, one of the most effective setups combines broad match with aggressive negative keyword management.
Instead of restricting input, you let Google explore β then shape the output.
Search term mining becomes the control layer. You continuously remove irrelevant queries and reinforce valuable ones.
This creates a system where reach expands without fully sacrificing relevance.
The shift is how you apply control.
You donβt control broad match upfront. You control what it learns from.
Target Impression Share is usually positioned as a defensive metric.
Used for brand campaigns. Used to protect coverage. Rarely used for growth.
Applying it to non-branded, high-value terms feels counterintuitive. You prioritize presence over efficiency.
In certain cases, that trade-off is worth it.
By pushing aggressive impression share targets on commercially important queries, you increase SERP dominance and reduce competitor visibility. Conversion volume increases, even if cost efficiency softens.
Here, bidding strategy becomes less about optimization and more about intent.
If your goal is to own a space β not just compete β efficiency canβt be the only metric.
Most lead gen accounts correctly track multiple conversion actions.
Form fills, phone calls, email inquiries β all captured and visible.
The issue isnβt tracking. Itβs interpretation.
When you treat every action equally, the platform has no reason to prioritize one over another.
In one account, assigning values based on the likelihood of becoming an MQL changed optimization almost immediately. Phone calls were weighted highest, email clicks lower, and generic form fills lower.
Switching to Maximize Conversion Value didnβt increase total conversions. It improved their quality.
The distinction matters.
The platform isnβt misoptimizing. Itβs optimizing exactly what you tell it to.
Competitor campaigns are often dismissed as inefficient.
Higher CPCs. Lower CTRs. Messier reporting.
All true.
They also deliver something most prospecting campaigns struggle to create: existing intent.
Users searching competitor brands are further along in the decision process. Theyβre not exploring the category β theyβre choosing within it.
In multiple accounts, competitor campaigns consistently convertedβnot at the lowest cost, but with high commercial intent.
With clear positioning, strong differentiation, and relevant landing pages, they became a reliable strategic layer.
Youβre not creating demand. Youβre intercepting it.
Thereβs a tendency to remove anything that doesnβt convert.
Informational queries. Early-stage searches. Broad, non-commercial terms.
Individually, they rarely justify spend.
Collectively, they influence the entire account.
Introducing top-of-funnel keywords not expected to convert improved lower-funnel performance. Remarketing pools strengthened, audience signals improved, and high-intent campaigns became more efficient.
The value is indirect but measurable.
This challenges a common assumption.
Not every keyword needs to convert. Some build the signal that drives conversion elsewhere.
Audience targeting often starts with a clear hypothesis.
Who the customer is. What they care about. How they behave.
In one account, the data told a different story.
The βidealβ demographic underperformed, while adjacent audiences converted more efficiently.
Instead of forcing the account toward expectations, you follow the data. You shift budget, expand targeting, and improve performance.
This tension is common in PPC.
What you expect to work and what actually works arenβt always aligned.
Thereβs a strong bias toward clean account structure.
No overlap. Clear segmentation. Tight control.
It makes accounts easier to manage, explain, and audit.
It doesnβt always make them more effective.
In several cases, allowing controlled overlap between campaigns, match types, and keyword themes improved coverage and performance. Instead of cannibalization, the system used overlapping signals to make better auction decisions.
This challenges a long-standing assumption.
Structure should support performanceβnot limit it.
In Shopping campaigns, the product feed is often treated as backend work.
Ensure accuracy. Ensure completeness. Then leave it.
But the feed directly shapes how products are interpreted and matched to queries.
Rewriting titles to prioritize high-intent keywords, reordering attributes based on performance, and testing naming variations all improved visibility and CTR.
These werenβt cosmetic changes.
They changed how the algorithm understood the product.
In Shopping, your feed is your targeting. Treating it as static limits performance.
Retargeting is usually treated as the safest part of the funnel.
High intent. High conversion rates. Predictable performance.
That makes it an ideal testing environment.
Using retargeting audiences to test messaging, offers, and creative variations creates faster feedback loops and clearer results than prospecting.
You can then scale winning ideas with confidence.
This reframes retargeting.
Itβs not just a conversion layer. Itβs a testing environment.
Track, optimize, and win in Google and AI search from one platform.
After 10 years in PPC, the biggest shift isnβt the platforms β itβs how they actually work.
Best practices still matter. Theyβre the foundation.
But theyβre not where advantage comes from.
The accounts that outperform understand how signals are interpreted, where systems can be influenced, and when to step outside whatβs considered βcorrect.β
Because the goal was never to follow the playbook.
It was to outperform it.
Scan any LLM chatbot for vulnerabilities
Privacy laws are tightening, browser extensions are blocking data, and ad platforms are demanding cleaner data. As a result, how you track user behavior online is changing fast.
Server-side tagging can help you reduce data loss while collecting cleaner, privacy-compliant data.
Hereβs what server-side tagging is, when it makes sense to implement it, and our experience with providers like Elevar and Littledata.
Traditionally, tracking scripts like Meta Pixel or Google Analytics run in the browser. This is client-side (browser-side) tagging. With server-side tagging, those scripts run on a server you control instead of the visitorβs browser.
Instead of the browser sending data directly to multiple third parties, it sends events to a first-party server endpoint (often a Google Tag Manager server-side container). The server processes, enriches, and forwards the data to tools like Meta and Google Analytics β on infrastructure you host (such as Google Cloud Run) or through managed providers like Elevar or Stape.
This allows for:
Beyond these benefits, server-side tagging gives you more flexibility in how you enrich and transform data before it reaches ad platforms.
You can standardize event names, filter out low-quality events, and add custom parameters to improve audience segmentation. This creates a more reliable, unified data foundation across tools like Meta, Google Ads, and Klaviyo, leading to stronger optimization signals and more confident decisions.
The SEO toolkit you know, plus the AI visibility data you need.
Server-side tagging isnβt a one-size-fits-all solution, but for many brands itβs becoming essential. It may be the right choice for you if:
Server-side setups donβt automatically anonymize data, but they give you more control over how itβs processed and shared.
This makes it easier to support compliance with regulations like GDPR, CCPA, and platform consent requirements.
You can apply consent logic, filter or hash sensitive fields, and control which events and parameters you send to each platform based on user permissions.
Client-side tracking can slow page load times.
Server-side tagging helps your site run faster by shifting data processing off the browser and onto the server, boosting user experience and SEO.
Faster pages can improve conversion rates and reduce bounce rates, especially on mobile, where every millisecond counts.
Ad blockers can disrupt client-side scripts, but server-side tagging bypasses many of these limits.
It helps platforms like Meta and Google Ads collect more reliable data for attribution and optimization.
It doesnβt eliminate blocking or consent requirements or recover all lost data, but it can improve signal reliability compared to browser-only setups.
If youβre spending heavily on Meta, Google, or other paid channels, better data accuracy can directly impact your return on ad spend.
Server-side tagging helps ensure conversion events are delivered consistently, allowing algorithms to learn faster and optimize toward higher-value users.
You have two main options: build it yourself or use a service provider.
Building your own setup gives you full control but requires technical expertise and ongoing maintenance. Youβll also need clear documentation and QA processes to keep events accurate as your site evolves and new features launch.
Your setup might look like:
Platforms like Elevar, Littledata, and Triple Whale simplify this by offering turnkey solutions that integrate with tools like Shopify, Klaviyo, Meta, and Google Ads. They handle infrastructure, updates, and many edge cases, so you can focus on strategy instead of engineering.
Weβve implemented Littledata and Elevar across multiple Shopify environments. Each serves a different type of brand, and understanding the difference is key.
We first implemented Littledata for a Shopify brand focused on improving visibility into Klaviyo and strengthening owned marketing channels. In that context, it performed well, passing additional Klaviyo events and improving email-driven reporting.
Littledata is a strong fit for:
Littledataβs affordability makes it accessible if you want better attribution without highly customized, platform-specific data engineering.
In more performance-intensive environments β especially where paid media relies on precise in-platform reporting β weβve seen limitations with fully aligned Meta conversion data and consistent GA4 session and revenue reporting. At scale, even small discrepancies can affect bidding strategies.
Littledataβs support is relatively lean, so resolving nuanced discrepancies may require additional internal validation. If you have in-house technical resources or less aggressive optimization needs, this may not be a major concern.
As you scale paid media spend and demand more precise attribution in Meta and Google Ads, the margin for tracking error shrinks.
Youβll likely reach a point where you:
At that point, you need more advanced infrastructure, deeper data enrichment, and specialized troubleshooting support. When your needs shift, so should your solution.
This is where a solution like Elevar comes in.
Server-side tagging is a technical and strategic upgrade. It:
As privacy restrictions grow and ad platforms evolve, this setup only becomes more valuable. If you invest early, youβre better positioned to maintain strong attribution, build richer audiences, and make smarter media buying decisions.
The goal isnβt just to recover lost data. Itβs to build a more resilient measurement framework that adapts as platforms and regulations change.
Server-side tagging gives you ownership over your data pipeline and reduces reliance on fragile browser-based signals. When implemented well, it becomes a long-term advantage, enabling clearer insights, stronger attribution, and more confident optimization across every channel you invest in.
PUBVOICE converts your articles into high-quality audio and delivers it through an embeddable player. Connect your RSS feed to auto-detect new posts, let AI generate listener-friendly scripts, and choose from 30 adjustable voices. Control creation, delivery, and performance from a single dashboard with metrics like plays, dwell time, and completion rate. Customize the player with CSS, clone voices, and keep content private from AI training. Implementation takes minutes with a lightweight script tag, and early access grants all features for free.
Google's CEO says that informational queries will become agentic search and that search itself will be an agent manager.
The post Googleβs CEO Predicts Search Will Become An AI Agent Manager appeared first on Search Engine Journal.
Intel is taking CPU bending seriously with Nova Lake Intel is reportedly preparing a two-level Independent Loading System (ILM) for its upcoming Nova Lake-S desktop processors. With this solution, Intel aims to put an end to βbendgateβ once and for all. With its new ILM, Intel plans to boost CPU cooling performance by increasing the [β¦]
The post New Intel anti-bend ILM could make CPU Contact Frames obsolete appeared first on OC3D.
Wi-Fi 8 is already taking shape, and while it won't raise peak speeds beyond Wi-Fi 7, it promises something just as important: more reliable, lower-latency wireless performance where it actually matters.
CharmR is an AI-powered conversation training game that helps you practice charming in safe, realistic scenarios. Choose missions like cafes, flights, or nightclubs, chat with dynamic characters, and watch the interest meter guide your approach. You can play head to head with a friend to see who has better charm. Advance through rank tiers from Rookie to Casanova, earn Charmer Points and XP, unlock customization, and track your progress. Play free forever on iOS and build confidence you can use in real life.
Understands India's nuanced digital conversations
Use friendly competition to build and strengthen community
Share your localhost as an invite only link
Move the Wispr Flow pill anywhere on your screen
007 First Light is launching on May 27th, unless you own a Switch 2 IO Interactive has delayed the release of 007 First Light on Switch 2. Originally, the game was due to be released alongside the gameβs PS5, Xbox Series X/S, and PC versions. Now, the game will be released much later, targeting a [β¦]
The post IO Interactive Delays 007 First Light on Switch 2 appeared first on OC3D.
Holdings offers zero-fee business banking with 1.75% APY and AI-powered bookkeeping. Open accounts quickly, create sub-accounts for payroll and taxes, and issue virtual or physical Visa cards with spend controls. The platform auto-categorizes transactions and generates profit and loss, balance sheet, and cash flow reports, keeping books tax-ready. Deposits are FDIC insured up to $3 million through partner banks, and you can add a dedicated bookkeeper if needed.
10x is a macOS productivity app for people who want more deep work and less drift. It quietly turns your daily work activity into clear insight so you can see what pulled you off track, when you focus best, and how your habits change over time. Instead of managing another timer or system, 10x helps you understand your real behavior and improve from there. You get daily coaching, focus trends, and practical feedback to protect your attention, repeat your best days, and make steady progress. Your data stays on your Mac, and you control it with pause, export, and delete options.
OAuth credential delegation for AI agents
Your control center for parallel AI agents
Minimalist Gmail client for bad wifi connections
Beautiful Screen Recordings in minutes
Strava for cooking
Reminders that keep up with you
Discover open-source tools with an AI chat assistant
Simplified and total DMARC control
Your landing page, rewritten for every ad you run
Minimize windows when you switch apps automatically
Tokenly provides token infrastructure for developers to gift and redeem tokens across registered applications. It lets you reward users, run cross-app incentives, and power referral programs with a single REST API. Register your app to get credentials, send and receive tokens with real value, and track balances and transactions in real time from an intuitive dashboard.
Clear Energy Facts helps Texans compare and choose fixed-rate electricity plans with transparent pricing. It analyzes your historical usage hourly and uses AI to parse each Electricity Facts Label to reveal true costs. Plans are ranked by total monthly cost without paid placement, including Power to Choose offers. You can compare Free Nights, Free Weekends, and bill-credit plans side by side, then enter your ZIP to see 200+ options with clear monthly cost estimates.
Deploy, fix, and automate your infra in one terminal
Discover childrenβs books and track reading together.
The open-source alternative to Webflow
A company built of Claw agents that are Cloud-native
Live logs inside your IDE to Debug without context switching
Turn messy work into interactive, actionable reports
Catch risky code changes and weak tests before they ship
Your design canvas that writes code powered by AI
Build teams of humans and agents, watch them work.
Vibe-code motion graphics on one canvas
The modern, powerful Google Analytics alternative
AI-powered confidential dev environment focused on privacy
Claude Code & Codex session analytics for dev teams
Cross-model reviews in GitHub Copilot CLI
One-page websites from real Google Maps reviews
Turns every AI decision into audit-ready evidence
Find concepts across videos and text instantly
Rebuild 1,738+ dead YC startups with AI
AI Technicians for the Physical World
The open source WisprFlow alternative, now on mobile
The linux terminal built for Agents and Multiplexing
An infinite, collaborative playground for music creation
Simulate first-time users. See why they drop off
AI Vocabulary Flashcards that Adapt to Your Memory
Your API costs fully visible.
Turn meetings into ready-to-post shorts and posts
Filter (and heal) your Twitter feed
Email Inboxes for AI Agents
Your Twitter feed, finally peaceful
Open-source Stripe Connect alternative with $0.002 fees
Disable your keyboard + trackpad to safely clean your screen
Voice and visual context for AI builders. No subscription.
The open-source AI workstation for coding, ops, and life
Meta's smart multimodal AI that understands your world
Build forms with Claude
Proactive personal assistant that handles your day
Fully local open-source agent for managing your texts
Turn your Strava runs into a world map adventure
Gives your coding agent a dedicated VM that's ready 24/7
Learn Git by solving challenges in a fake terminal
You ship features and they deserve to be seen
Pre-built agent harness on managed infrastructure
AI coworker for GTM teams with its own computer & memory
Openclaw on your Mac, with permissions you can understand
AI-powered schematic design tool for PCB making
Your AI coding sessions can finally talk to each other
Your entire video library, now searchable and editable by AI
Open source alternative to Raycast Pro
58 animations, 31 shaders, 5 games in one Xcode project
See how much you're losing to failed payments on Stripe
CinematicCard lets you create cinematic digital greeting cards with calligraphy, music, and effects that play in the browser. Personalize the experience with your message, photos, and soundtrack, then share an instant link or schedule delivery. Upgrade with a photo slideshow, upload your own music, and add a cash gift reveal that pays via Venmo, PayPal, or CashApp. Links never expire, no app is required, and bulk send personalizes cards for groups.
Akamai breaks down which AI bots are hitting publishing, who operates them, and why fetcher bots may pose a more immediate risk.
The post OpenAI, Meta, ByteDance Lead AI Bot Traffic In Publishing appeared first on Search Engine Journal.
GlobeClaim lets you claim hex-shaped tiles to mark your spot on a shared internet map. Link your site or project, pick a sector, and appear in Top and New feeds as others explore the grid. Start with a few free tiles, build reputation and influence through activity, and browse territories and profiles to discover creators and brands across the map.
FixGuard is a free, privacy-first browser extension for Chrome and Edge that removes ads, trackers, cookie banners, and notification prompts to make the web cleaner and faster. It uses Manifest V3 with network-level blocking and cosmetic filtering to remove clutter without slowing down your browser. You can control it per site, add custom rules, and rely on auto-updating filter lists. There are no accounts, subscriptions, or data collection β just install it and browse with less noise.
Hedgehogs is a quarterly competition where AI agents trade prediction markets against each other. Developers connect their agents or create one on the website. Each agent gets $1M in virtual cash and can trade hundreds of live markets covering politics, tech, sports, and crypto. The top agent wins $25K for their human.
Most AI benchmarks test static knowledge, but Hedgehogs tests whether your agent can reason about the real world in real time. Agents need to read news, calibrate probabilities, manage risk, and update positions as events unfold. The competition runs from April through June 2026, and you need at least 10 trades to qualify.
The Dump is an AI-powered note organizer that turns scattered voice memos, photos, ChatGPT conversations, and text into searchable, structured notes. It understands each note's meaning and routes it into folders you define, so ideas land in the right place without tags or manual filing. Capture notes by speaking, snapping, or typing, then browse by category, search across everything, and edit or move notes anytime. The Dump helps you remember and retrieve ideas quickly and is currently free to try in beta.
Mimir helps scientists search, analyze, and synthesize findings from millions of papers across materials science, chemistry, physics, and related fields, with real and verifiable citations. It delivers deep domain coverage and keeps expanding into new areas so you can answer technical questions in minutes, not days. For enterprise and institutional teams, Mimir integrates proprietary research alongside public literature to create a unified, private corpus that accelerates R&D while protecting your data.
The companyβs overview of nonskippableΒ adsΒ still lists 60-second ads as the maximum length available, but a Reddit user discovered longer segments.
Users can now decide whether to play in-stream videos at half speed or double speed, providing new ways to engage with short-form clips.
The development is part of Project Clover, an initiative designed to store EU user data outside of the companyβs home base in China in compliance with EU directives.
Available in the Wix App Market, the new option connects Wix websites to TikTok for Business to facilitate advanced ad campaign management.
The company said its proprietary QR codes offer advanced customization options that could help drive user engagement and conversion.
The company said this is the first in a series of large language models intended to reimagine its entire artificial development stack.
The brief comment function is being expanded beyond mutual followers and could potentially become a new way for creators to broadcast information.
collaborAItr lets you run multiple AI models in parallel to plan, research, and execute tasks with a single prompt. View side-by-side responses, compare perspectives, and click Continue as your AI team learns from results and refines the plan. Connect to leading models like ChatGPT, Claude, Gemini, Grok, and 40+ others. Start free with no credit card, keep your data private, and use flexible tools to consolidate, fact check, and summarize responses.
Seller Stacked is a directory and newsletter created by a real store operator that reviews AI tools for e-commerce sellers and offers free calculators. It shares honest recommendations with no sponsored placements and focuses on actionable results. The site rates tools on ease of use, value, and workflow fit, and publishes weekly guides, comparisons, and real-world tips to help you choose and apply the right tools.
Notebooks in Gemini give you a project base that connects the Gemini app with our AI-powered research partner, NotebookLM, for an easy workflow.AMD confirms the MSRP of its Ryzen 9 9950X3D2 Dual Edition processor AMDβs David McAfee has unveiled the official MSRP for its Ryzen 9 9950X3D2 Dual Edition CPU, setting it at $899.99 in the US. This makes the Ryzen 9 9950X3D2 Dual Edition AMDβs most expensive AM5 CPU to date. This price is $200 above [β¦]
The post AMD confirms Ryzen 9 9950X3D2 Dual Edition MSRP appeared first on OC3D.
Noir Prompt is a prompt manager for people who use AI generation tools like Midjourney, DALL-E, ChatGPT, Runway, and more. Save your prompts, tag them, organize by type, and find them instantly. No more digging through notes apps or Discord threads wondering what you typed weeks ago.
Every edit is saved automatically so you can roll back to any previous version. Build reusable templates with variable placeholders and swap out subject, style, or mood on the fly. Free to start, it works for image, video, and text prompts, all in one place.
Celavii helps brands and agencies find creators, manage outreach, and run campaigns from one place. It maps creator networks as a graph, showing audience overlap, bridge creators, and where your budget reaches new people.
Instead of clicking through filters, you ask questions in plain English and AI agents handle discovery, CRM, campaign tracking, and video generation. It works from your dashboard, WhatsApp, Slack, or Discord and starts at $49/month with no annual contracts. It was built because other tools required $2,000+/month and a yearly commitment just to search a database.
BayPoint AI is an all-in-one platform for eBay sellers who want to run their business smarter. The flagship Preflight app analyzes qualitative aspects of your listings β title strength, description quality, photo guidance, and keyword relevance β and gives you AI-generated improvements before you publish. Supporting apps cover shipment tracking, buyer feedback management, sales analytics, and marketplace intelligence, all working together from a single dashboard.
Our AI assistant, Riley, is available in every app. Riley analyzes your actual listing and sales data. Morgan answers eBay strategy questions in real time. No more guessing β just a clear picture of what to fix and why.
If you shelved your inbound strategy this past year, you can shelve your Inbound conference mugs and swag with it.
HubSpot renamed its annual Inbound conference in Boston this September to Unbound. A note on the event site explains the thinking:
Inbound is outbound. HubSpot pioneered inbound marketing, which uses content and search rankings to attract visitors, then convert them on-site.
Recent Google core updates appeared to hurt the HubSpot blog, possibly because its content drifted from core topics like CRM, sales, and marketing into broader business areas like interview tips.
Inbound strategy has declined as search shifts from platforms like Google to LLMs like ChatGPT, which drive fewer clicks to websites.
From inbound to loop marketing. In 2025, HubSpot introduced its Loop marketing strategy to replace inbound. Loop focuses educating consumers in an AI-driven world.
The conference rebrand acknowledges that no single framework works for you in todayβs marketing landscape.
Two new improvements to Colabβs Gemini agent give you more control over how Google Colab works and how it helps you learn.Google Finance brings AI tools to 100+ countries. Use AI to research stocks and follow live earnings in your preferred language.AI bot activity surged 300% in 2025, with media and publishing among the most targeted sectors, according to a new Akamai report.
Why we care. AI bots are reshaping how content is discovered and consumed, shifting users from search clicks to instant answers in chat interfaces. Publishers are seeing fewer visits from organic search and often donβt get attribution in AI-generated answers. Itβs also eroding ad and subscription models.
The threat is real. Publishers now face two threats:
The impact. Pageviews are declining, costs are rising (because scraping bots increase infrastructure costs by consuming server and CDN resources without generating revenue), and brand visibility is weakening.
What publishers are doing. Publishers are adopting nuanced controls (rather than blanket blocking AI bots), such as:
What theyβre saying. According to Akamaiβs report:
Whatβs next? A βpay-per-crawlβ model is emerging. Tools like identity verification (Know Your Agent) and platforms like TollBit aim to authenticate bots and charge for access in real time.
About the data. The report analyzed Akamai bot management data from July to December 2025, covering application-layer traffic across websites, apps, and APIs.
The report. SOTI Security Insight Series: Navigating the AI Bot Era (registration required)
Google may be making local search ads more interactive, potentially changing how advertisers showcase multiple locations and capture nearby demand.
Whatβs happening. Google Ads appears to be testing a new format that displays multiple business locations in a swipeable carousel within search ads, allowing users to browse options directly in the ad unit.
How it works. Instead of listing locations separately, the new format groups them into a horizontal carousel with business details like ratings and proximity, enabling users to swipe through locations without leaving the search results page.
Zoom in. Early comparisons show a shift from static, stacked location assets to a more dynamic experience, where multiple listings are consolidated into a single, scrollable unit.
Why we care. Advertisers with multiple locations could gain more visibility within a single ad, while users get a quicker way to compare nearby options.
Between the lines. This format could increase engagement with location-based ads, but may also intensify competition within the carousel itself as businesses vie for attention.
What to watch. Whether the feature rolls out more broadly and how it impacts click-through rates and local ad performance.
First spotted. This update was spotted by Founder of Adsquire Anthony Higman who shared spotting this ad type on LinkedIn.
Google is consolidating its advertising and measurement resources into a single destination, aiming to make it easier for developers and technical marketers to build, automate and scale campaigns.
Whatβs happening. Google has introduced a new Advertising and Measurement Developers Hub, a centralized site designed to help users access tools, documentation and support across its ad ecosystem.
The hub brings together resources for products like the Google Ads API, Google Analytics and publisher tools such as AdMob and Google Ad Manager, all organized into categories including advertising, tagging and measurement.
How it works. The site offers a streamlined homepage with quick access to documentation, blog updates and community channels, along with dedicated sections to explore products, connect with support and engage with Googleβs developer relations team.
Why we care. Google is making it easier to access and implement advanced tools that power automation, tracking and campaign optimization. This can help teams work more efficiently, especially those relying on APIs, tagging and data integrations. As advertising becomes more technical and AI-driven, having a centralized hub lowers the barrier to building more sophisticated, scalable setups.
The big picture. As advertising becomes more automated and API-driven, Google is investing in infrastructure that supports developers and technical users who manage complex integrations across platforms.
Zoom in. New features include a βmeet the teamβ section, a centralized support page linking to Discord and GitHub resources, and a media hub featuring content like Ads DevCast.
What to watch. Whether this hub becomes the primary entry point for developers working across Googleβs ad products β and how it evolves with new AI and measurement tools.
Bottom line. Google is simplifying access to its ad tech ecosystem, betting that better developer support will drive more innovation and adoption.
Dig deeper. Introducing the Google Advertising and Measurement Developers Hub!
Most agencies present prospective clients with an account audit as part of their sales process. The purpose is twofold:Β
But how often do brand marketers turn the tables and audit their agencies in their RFP?
Iβm the head of performance marketing at a marketing agency, so Iβm clearly writing from a biased perspective. However, over my decade-plus in the industry, Iβve seen too many brands settle for βgood enoughβ because they didnβt know which questions would reveal the cracks in a potential partnerβs strategy and approach.
If I were a brand looking for a true growth partner, here are the specific questions Iβd ask to separate the top performers from the rest.
A lot of agencies claim to be βfull service,β but rarely are they βfull excellence.β Iβd be looking for where an agency truly spends its time versus where theyβre just trying to upsell me.
Itβs less about the channels in question (although if, say, LinkedIn is a key growth driver for your brand, theyβd better demonstrate proficiency there), and more about how their strengths align with your needs.
If an agency claims to be experts in SEO, creative strategy, and paid media, but 90% of their client base only uses them for paid search, thatβs a red flag. You want a partner whose core competencies align with your primary needs.Β
If you need high-volume creative testing, you want an agency where 80%+ of clients use its creative production frameworks, not one that treats creative as an add-on service.
Dig deeper: Confessions of a PPC-only agency: Why we finally embraced SEO
I miss the days when knowledge of the manual controls at your disposal could set you apart as a high-performing marketer. But those days have been gone for a while.
In 2026, thereβs a real danger of over-optimization with the controls we have left. This can reset algorithmic learnings and prevent them from fine-tuning in service of your goals. Agency teams that strike this balance most certainly have a healthier approach than those who either blindly trust algorithms or canβt help tinkering excessively.
One control you can and must be diligent about using is first-party data for enhanced conversions and offline conversion tracking. Part of the job of a great marketer is training the algorithms on which leads and which conversions to target, and first-party data is a huge lever to pull in that regard.
Donβt just ask for a sample report. Anyone can make a PDF look pretty. You need to understand their philosophy on data.
Youβre looking for an agency thatβs willing to move upstream. If the majority of their clients are measuring success on clicks, traffic, or even MQLs, run the other way.
A performance-driven agency should be obsessed with revenue, ROAS, and pipeline velocity. Ask them how they handle attribution. If they rely solely on in-platform metrics, which often over-claim credit, they arenβt looking at the full picture.Β
Dig deeper: What successful brand-agency partnerships look like in 2026
This is actually a pretty common question and has been for years. Too many marketers know the pain of integrating rotating sets of agency teams because the agency canβt hold onto top employees, and you should be evaluating the answer from this perspective.
Thereβs another factor to consider. Generally speaking, the more experienced a marketing team is, the more effectively it uses AI tools.
Whereas junior marketers might be more avid proponents of AI and quicker to adopt its functionality, theyβre also far more likely to use it for things like creative ideation and strategy. Both are areas where high-quality human thought is a true differentiator.
For this answer specifically, remember that you have some great research tools like Glassdoor that you can and should access. Employee tenure is one thing, but a Glassdoor profile with a bunch of red flags is an indicator that the agency might struggle to keep the talent it really wants to retain.
Again, youβre looking for a balance here. Agency teams that donβt use AI at all are almost certainly burning resources on manual tasks, but agency teams that overuse it to replace perspective, critical thinking, and creativity are commoditizing their own client service.
Two follow-up questions to ask:
Youβre looking for firm answers and redundant layers for each of these questions β at the very least, someone relatively senior should approve any output before it goes live.
Dig deeper: Why PPC teams are becoming data teams
This is the ultimate litmus test for technical proficiency. A great performance marketer knows where the ad platforms hide the waste buttons. If I were a brand marketer, Iβd want to hear about:
If an agency canβt rattle off these specific checks, theyβre likely missing the βlow-hanging fruitβ of budget efficiency. Fixing some of these takes seconds, but missing them costs thousands.
Remember: when youβre choosing an agency partner, itβs the job of each agency to sound as good as they possibly can, but what an agency considers to be a great answer might not be a great fit for your brand.Β
By focusing on utilization rates of services, strategic application of AI, and approaches to budget efficiency, youβll find a partner capable of driving actual performance, not just spending your budget.
Dig deeper: How to find your next PPC agency: 12 top tips
Overclockers UK unveils pricing for AMDβs Ryzen 9 9950X3D2 Dual Edition CPU Overclockers UK has unveiled the pricing of AMDβs Ryzen 9 9950X3D2 Dual Edition CPU, which AMD unveiled last month. This CPU is AMDβs new AM5 flagship, offering 16 cores and 192 MB of total L3 cache. This is the first consumer-grade X3D CPU [β¦]
The post Overclockers UK unveils UK price for AMDβs Ryzen 9 9950X3D2 Dual Edition appeared first on OC3D.
ogsm.io helps small businesses create a clear, one-page OGSM strategy in about 10 minutes. It guides you through a brief conversation and turns your answers into objectives, goals, strategies, and measures you can download as a PDF or share online, so you can act with focus and track what matters.
ChoreChomp is an AI-powered chore coach for families. Parents assign custom chores with reference photos, kids snap a photo when they're done, and the AI checks the work and gives age-appropriate feedback. Parents approve final scores, award points, and set reward goals to keep motivation high. The app also has a homework helper that guides with Socratic hints without giving answers. It protects privacy with no child accounts, strict guardrails, person detection, and short-lived photos, and one subscription covers unlimited kids.
Maskerade.ai lets you deploy unlimited, highly accurate AI personas to browse the web and navigate your site. Get deep, actionable insights into the thoughts and feelings of your hardest-to-reach audiences.
Analytics tools tell you what happened on your site, but not why. Customer research tells you what a group of people thinks and why, but it's slow, labor intensive, and costly. With Maskerade, you can combine the best of both worlds.
Google is laying the groundwork for βagentic commerce,β where users can complete purchases directly inside AI-driven search experiences.
Whatβs happening. Google has published a new onboarding guide for its Universal Commerce Protocol (UCP) in Merchant Center, outlining how merchants can integrate with the system and enable checkout directly from product listings in AI Mode and Gemini.
The big picture. As AI search evolves from discovery to transaction, Google is pushing to keep users within its ecosystem by embedding shopping and checkout into conversational experiences.
How it works. Merchants must first complete a technical integration, then submit an interest form and wait for approval before gaining access to onboarding tools in Google Merchant Center, including a sandbox environment to test integration, identity linking and checkout APIs.
Why we care. Google is moving search closer to transaction, meaning users may complete purchases directly inside AI experiences instead of visiting your website. This shifts where conversions happen and could change how performance is measured, attributed and optimized. Early adopters of the Universal Commerce Protocol may gain a competitive advantage as shopping becomes more integrated into tools like Gemini.
Zoom in. The protocol acts as an open standard for connecting product data, user identity and payment flows, enabling seamless purchases without redirecting users to external sites.
What to watch: The rollout is gradual and currently limited to the U.S., with a dedicated UCP integration tab expected to appear in Merchant Center accounts over the coming months.
Bottom line. If widely adopted, the Universal Commerce Protocol could redefine how online shopping works β turning search into a full-funnel, AI-powered checkout experience.
Dig deeper. How to onboard to the Universal Commerce Protocol in Merchant Center
Meta Platforms is making it easier for advertisers to implement tracking, reducing technical friction for teams running campaigns across platforms.
Whatβs happening. Meta released an official Pixel template inside Google Tag Manager, replacing the need for third-party or community-built workarounds.
How it works. The new template allows advertisers to reuse their existing GA4 dataLayer, meaning events already configured for Google Analytics 4 can be leveraged without rebuilding tracking from scratch. It also automatically maps enhanced e-commerce events such as purchases, add-to-cart actions, content views and checkout initiations, eliminating the need for duplicate tagging.
Why we care. This reduces implementation time, lowers the risk of tracking errors and ensures consistency across platforms, especially for advertisers managing both Google and Meta campaigns.
What to watch. Whether this leads to broader adoption of Meta Pixel tracking among advertisers who previously avoided complex setups, and if similar cross-platform integrations follow.
Bottom line. Meta is removing one of the biggest headaches in ad tracking β making it faster and easier to get reliable data across platforms.
First seen. This update was spotted by Paid Media expert Thomas Eccel who shared spotting the update on LinkedIn.
Ask most ecommerce brands who owns their product feed, and the answer is almost always the same: the paid media team.
Maybe a feed management tool sits under PPC. Maybe the shopping team built the feed years ago, and nobodyβs touched the titles since. Either way, SEO rarely has a seat at the table, and itβs often forgotten as part of the broader feed management strategy.
Whether youβre worried about AI search or traditional clicks, youβre missing out on opportunities by excluding SEO from your feed management strategy.
Up to 83% of ChatGPT carousel products match Google Shoppingβs organic results, according to a recent Peec AI study analyzing more than 43,000 listings. And 60% of those matches came from Shopping positions 1-10.
On Googleβs side, the Shopping Graph now contains more than 50 billion product listings and feeds directly into AI Overviews, AI Mode, and Gemini. AI Overviews appear in roughly 14% of shopping queries, up from about 2% in late 2024. Like many other things weβve discovered about AI search, the generative results are informed by traditional SERP.
SEO needs to be the strategic quarterback for brand authority. This is a highly valuable opportunity to work cross-channel toward a common goal of improving visibility across search surfaces. It really requires SEOs, commerce, and paid media teams to get in the same room.
The SEO toolkit you know, plus the AI visibility data you need.
Typically, brands run a single product feed optimized for Google paid shopping campaigns. Titles are written for bid relevance, descriptions are built for Quality Score, and the feed exists to win auctions, with less consideration for user search behaviors.
As user behavior shifts, search surfaces favor stronger semantic alignment between queries and product data. A title stuffed with paid-friendly modifiers or branded terms isnβt the same as a title that mirrors how someone conversationally searches for a product.
We tested this with a large ecommerce brand. Our agencyβs AI SEO team partnered with the commerce team to launch a dedicated product feed for free organic listings, with titles and descriptions optimized specifically for organic visibility, rather than replicating what was already running in the paid feed.
After the organic feed was pushed live:
Rather than replacing our paid feed strategy, we recognized that organic and paid shopping solve different problems and have different needs that require optimizing accordingly.
Organic feed titles should reflect how your customers actually search, not how your bidding strategy is structured.
Dig deeper: How AI-driven shopping discovery changes product page optimization
Not every feed attribute carries equal weight. If youβre building a dedicated organic feed or just auditing your existing feed for gaps, hereβs where you could start.
Googleβs algorithm heavily favors feed titles when matching products to queries, and its own documentation emphasizes including important attributes to βbetter match search queries and drive performance lift.β Consider how a customer might describe what theyβre looking for in a conversational way, and how that aligns with product attributes.
Googleβs GTIN documentation makes clear that products with correct GTINs receive significantly more visibility. Industry data has consistently shown that properly matched products can drive up to 40% more clicks. Theyβre also the primary signal for aggregating product reviews across sources.
Theyβre still the most common source of Merchant Center disapprovals. Products with both standard and lifestyle images typically see significantly higher engagement.Β
If budget or bandwidth has kept better product images on the back burner, Googleβs Product Studio can help handle some of the editing, so you can test and improve creative at scale without a full reshoot. Itβs also a way for SEO and creative teams to collaborate on feed-specific assets and testing.
Loginproduct_highlight and product_detailΒ product_highlight lets you add scannable benefit statements that appear in expanded Shopping views. For instance, βwater-resistant for light rain commutesβ is doing more work than βhigh-quality materialβ for both the shopper and the AI.Β product_detail provides structured specifications that power Googleβs faceted filters in organic product grids.The same semantic work SEOs are doing to optimize product detail pages (PDPs) for conversational search β like defining ideal buyers, naming use cases, and articulating compatibility β should inform feed attributes.Β
Product and content teams already understand what drives someone to buy. That context should be in the feed, not just on a brandβs PDPs.
Dig deeper: How to make ecommerce product pages work in an AI-first world
Hereβs what makes this investment compound: the feed optimization work done today for organic shopping visibility will also help build brand readiness for agentic commerce standards and applications.
Googleβs Universal Commerce Protocol, announced in January, is a framework that enables AI agents to discover products, build carts, and complete transactions directly inside AI Mode and Gemini. The shopper may never land on the brand website to make a purchase. UCP isnβt a replacement for Google Merchant Center, because itβs built directly on top of GMC data.
Feeds are how products enter the Shopping Graph. The Shopping Graph is the dataset AI agents query when processing a shopping request. The new native_commerce attribute added to feeds is what signals that a product is eligible for the UCP-powered βBuyβ button in traditional and AI-driven Google services.
Google has also announced the eventual rollout of several new Merchant Center attributes designed specifically for conversational commerce:Β
These are additions to an existing GMC feed that give AI agents the contextual understanding they need to match products to natural-language queries like βwhatβs a good waterproof jacket for bike commuting?β These new conversational attributes are rolling out to a small group of retailers first.
This is where feed data and on-page content need to stay tightly aligned. Search surfaces cross-reference a brandβs feed against:
When those layers contradict each other, trust erodes at the domain level.Β
Dig deeper: 7 organic content investments that drive ecommerce ROI
Product feed strategy and optimization is an opportunity for genuine cross-team collaboration to test, execute, and measure visibility. A holistic approach to managing product details across every surface will benefit brands in both traditional and AI-driven search.
These teams must work together to coordinate their insights and effectively establish an AI SEO operating system. The product feed sits at that intersection as itβs an owned asset managed by commerce infrastructure that directly feeds AI-powered visibility.
The first step is to pull a current feed and compare organic titles to paid titles. The second step is getting the right people in the room to build something better. SEO is most successful when more channels align toward the same goal: better brand visibility.
The March 2026 core update finished rolling out today after 12 days and 4 hours, completing Googleβs first broad ranking update of the year.
What happened. Google confirmed the rollout ended at 06:12 PDT, per its Search Status Dashboard. The update began March 27 and impacted search rankings globally.
The timeline. Google originally estimated the March 2026 core update would take up to two weeks to complete.
The context. This was the first core update of 2026. It followed the March 2026 spam update and the February 2026 Discover update.
What to do if you were impacted. Google didnβt issue any new guidance for the March 2026 core update. Its standing advice remains:
Google continues to point site owners to its core update and helpful content guidance.
Why we care. Now that the rollout is complete, you can assess impact with more confidence. Analyze ranking and traffic changes, identify winners and losers, and adjust your content strategy based on what the update appears to reward.
Previous core updates.Β Hereβs a timeline and our coverage of recent core updates:
Appleβs next-gen MacBook Neo should feature up to 12GB of memory and an A19 Pro silicon upgrade According to MacRumours, citing a report from Tim Culpan, Apple plans to release a new MacBook Neo in 2027. This new model will reportedly feature Appleβs new A19 Pro processor, the same chip as the Apple iPhone 17 [β¦]
The post Appleβs next-gen MacBook Neo should feature some BIG upgrades appeared first on OC3D.
Google's March core update finished rolling out. Here's what to know about the rollout and when to check your data.
The post Google Confirms March 2026 Core Update Is Complete appeared first on Search Engine Journal.
How retailers can adapt to the rapidly evolving advertising landscape, on the Ads Decoded Podcast.Hreflang has long been a core mechanism in international SEO, directing users to the right regional version of a page. That approach worked when search engines primarily returned static results.Β
AI-driven synthesis changes that. Instead of returning lists of links, AI systems construct answers. They donβt need, nor want, your perfectly implemented hreflang tags. They arenβt looking for instructions on which page to serve. Theyβre trying to determine which answer is best supported across sources.
Your content has to hold up when the model compares it against everything itβs seen, regardless of language or origin. If it doesnβt, it wonβt be used.
We need to address a fundamental misunderstanding of the hreflang attribute. Hreflang has always been a switcher, not a booster.Β
If your brand lacked organic authority in Australia before implementing the tag, adding the en-au attribute wouldnβt magically improve your rankings in Sydney. Its only function was to ensure that if you did rank, the user saw the correct regional version.
In AI search, this βyou vs. youβ dynamic has become a liability. While traditional search still relies on these tags to organize traffic, AI models often bypass them during the synthesis phase. If a brandβs U.S.-based .com site possesses decades of authority, the AIβs internal logic may determine that the U.S. site is the true source of information.Β
Consequently, even when a user in Berlin searches in German, the AI may synthesize an answer based on the U.S. data and simply translate it on the fly, effectively ghosting the brandβs localized German site despite perfectly implemented hreflang tags.
AI models donβt just answer the query you see. They expand it into dozens of hidden checks, comparing sources, validating claims, and pulling in information across languages to see what aligns.
ChatGPT often translates and evaluates queries in English even when the user searches in another language, research from Peec AI shows. This reinforces how query fan-out operates across markets. If your local entity doesnβt hold up in that broader comparison, it doesnβt get used.
A second issue happens before retrieval even begins. During training, LLMs compress what they see so it can be stored and reused at scale.
When multiple regional pages look too similar, they donβt stay separate. Theyβre folded into a single representation, also known as canonical tokenization.
Local details β phone numbers, office locations, and market-specific references β donβt always survive that process. Theyβre treated as minor variations rather than meaningful signals.
By the time the model is asked a question, your local site is often no longer competing. In many cases, itβs already been absorbed into the global one.
Dig deeper: What the βGlobal Spanishβ problem means for AI search visibility
To compete globally, expand your strategy to include signals that resonate with AIβs data supply chain.
Meta tags tell systems what you intend. Infrastructure often tells them what to believe. Datasets like Common Crawl use geographic heuristics, IP location, and domain structure to make sense of content at scale. That happens early in the process, before anything resembling ranking.
This means your content may already be placed in a market before the model ever evaluates it. If your regional domains arenβt supported by local infrastructure or delivery, youβre sending mixed signals. Those are hard to recover from later.
To break the semantic gravity that leads to entity compression, you need what I would call a clear βknowledge delta.β Most global teams fail here because they think localization means translation. It doesnβt.Β
Thereβs no universally accepted magic number for unique content. From a semantic vector perspective, I speculate that a divergence threshold of at least 20% of the content on a local page must be unique to prevent the model from collapsing your local identity into your global one.
To address this, front-load market-specific data, such as regional shipping logistics, local tax identifiers, and native case studies, into the first 30% of your page. This lets you provide the mathematical proof the model needs to cite your local URL as a distinct authority.
AI models interpret market relevance by looking at the company you keep in the text. Incorporate geographic anchoring by referencing local neighborhoods, regional landmarks, or specific transit hubs (e.g., βlocated near the Alexanderplatz stationβ in Berlin).Β
These co-occurrence signals pull your brandβs vector embedding toward the specific local coordinate in the modelβs training data, creating a geographic fence that helps the AI disambiguate your local office from your global headquarters.
Dig deeper: How to craft an international SEO approach that balances tech, translation and trust
The origin of your links is a primary signal of market authority. During the fan-out phase, AI models look for regional consensus.
This is one of the areas where traditional link building logic starts to break. Itβs not just about getting links. Consider where those links originate, along with their authority and contextual relevance.
If your Australian page has backlinks primarily from U.S.-based websites, the model has little evidence that you actually belong in or are relevant to the Australian market. Local sources, including high local trust and location-specific news outlets, change that. Without them, youβre often treated more like a visitor than a participant.
LLMs pick up on regional language nuances far more than most teams expect. This is where simple translation starts to break down. Unique market- or colloquial-specific terms, formatting, and even small legal references signal whether something actually belongs in a market.
Use the terms people in that market actually use β things like βincl. GST,β local identifiers like ABN, and even spelling differences. Without these signals, the page may be technically and linguistically correct, but it wonβt register as truly local.
As mentioned, LLMs often generate multiple incremental queries during their research phase. These invisible queries may focus on local friction points, such as βHow does this product comply with [name of local regulation]?βΒ
By incorporating local FAQ clusters that address these nuances, you ensure your local URL survives the fan-out check, making your global .com too generic to be cited in a localized answer.
Dig deeper: Why AI optimization is just long-tail SEO done right
Expand your SEO reporting beyond traditional rank tracking. Incorporate AI citation audits by using a local VPN to query the most popular generative engines in your target markets.Β
If the AI consistently pulls from your global .com domain for a local query, itβs a clear signal that your local domain lacks the necessary evidence chain. Identify where this market drift is occurring and reinforce those specific pages with more unique local data and infrastructure signals.
Hreflang and traditional technical signals still shape how search engines organize and deliver content, but they donβt determine what AI systems use.
AI models evaluate which sources to use based on evidence of local relevance. Without a distinct presence in each market, they default to the version of your brand they trust most, which often isnβt the one you intended.
Translation alone doesnβt establish that presence. Your content needs to demonstrate that it belongs in the market itβs meant to serve.
Dig deeper: Multilingual and international SEO: 5 mistakes to watch out for
Youβre facing a major shift as familiar manual targeting levers disappear in favor of AI-driven discovery. Platformsβ automated tools are collapsing campaign types, obscuring data, and replacing manual targeting with intent-based algorithms.
This is a shift from selection to prediction. You wonβt adapt by holding onto old controls β youβll adapt by learning to engineer the inputs that replace them. Hereβs how to make sure you have the tools to stay on top.
You previously relied on granular keyword lists, demographic filters, and custom exclusions to target ideal customers. You told platforms exactly who to target and paid to access that inventory.
Now, platforms have eliminated those controls:
Targeting didnβt disappear β it moved inside the platformβs black box. The algorithm now targets based on data within its own ecosystem.
Platforms are clear: manual segmentation is gone, and automation is here to stay.
If targeting is now internal to the algorithm, your role changes. Itβs less about selecting your audience and more about engineering it.
The distinction is critical. Traditional targeting focused on selecting audiences. Audience engineering focuses on instructing the algorithm through high-quality conversion signals, precise creative, and first-party data. It teaches AI systems who to find and what to optimize for.
Hereβs how this changes your workflow:
In the past, to target CFOs, you might use job title filters and negative keyword lists. With audience engineering, you instead upload high-quality data (e.g., βdeal closedβ signals) to define a high-value prospect. You also tailor creative to CFO-specific pain points, teaching the AI to reach people who engage with that message.
If you fight the algorithm and resist this shift, youβll struggle. If you embrace it, youβll succeed by optimizing conversion signals, refining creative, and strengthening your data infrastructure.
As manual levers disappear, the gap between strong and average performance comes down to signal quality. Audience engineering is what closes that gap.
You must optimize three critical inputs the AI uses to segment for you:
Tell the algorithm what matters. If you optimize for cheap, top-of-funnel leads, it will get efficient at finding people who fill out forms but never buy β thatβs not what you want.
Focus on meaningful business outcomes, not top-of-funnel metrics. Integrate Offline Conversion Imports (OCI) and Conversions API (CAPI) to feed data on final sales, not just initial clicks. With value-based bidding, you teach the algorithm to prioritize users who drive revenue β effectively targeting high-value customers without using demographic checkboxes.
In a world without demographic filters, your creative becomes your primary targeting mechanism. The specificity of your message does the filtering.
If your creative speaks broadly, the AI shows it broadly. If it speaks to a niche pain point, the AI finds users who resonate with that pain point.
Build ad sets around motivations, not product categories.
Your customer lists, CRM data, and engagement signals are the foundation the algorithm learns from.Β
This data replaces third-party signals and becomes a critical competitive advantage. Youβre giving the algorithm a cheat sheet to identify your best customers.
The shift to AI-driven targeting isnβt theoretical. As an agency managing over $215 million in annual paid media spend, weβve tested this across platforms and validated it with performance data. Hereβs what weβve learned:
A long-time client had a well-established view of its target audience based on years of campaign performance and customer data. Campaigns used manual age caps and layered targeting to protect efficiency.
When we transitioned those campaigns to Advantage+ Audiences, manual exclusions were removed, allowing the algorithm to optimize based purely on conversion signals and creative performance.
During testing, Meta identified and scaled into an older demographic that had previously received minimal budget. This segment delivered a 37% higher CTR than the campaign average and drove stronger downstream conversion performance.
As spend shifted into this audience, conversions came at a lower cost per result while total revenue increased. Broader targeting improved return on ad spend (ROAS) compared to the prior manual strategy.
This reflects a broader trend with Advantage+ Audiences. Paired with strong conversion goals, accurate data signals, and high-quality creative, it consistently identifies high-value segments that manual targeting restricts or misses.
For another client, we implemented a Microsoft PMax test, using advanced audience targeting and first-party data to reach high-intent prospects across Bing, Outlook, MSN, and the Microsoft Audience Network.
With in-platform placement insights, we monitored performance closely and reacted quickly early on. The campaign drove a 10% increase in conversion rate, a 14% decrease in cost per lead, and a 4x increase in form fills in the first month β followed by another 2x the next month.
This reinforced a key principle: automation performs best with strategic human oversight. While we fed strong audience signals and conversion data, performance drifted as the system expanded into less efficient placements. With Microsoft support and ongoing monitoring, we excluded underperforming placements and refined targeting without over-constraining the campaign.
By letting PMax handle scale and optimization β while maintaining disciplined oversight and guardrails β we preserved efficiency and improved overall performance.
Automated targeting is powerful, but not benevolent. It optimizes for the math you give it. Here are pitfalls to avoid.
This is the most important risk. Poorly defined conversion events, incomplete data pipelines, or low-quality first-party data limit performance and train the algorithm on the wrong outcomes.
If you feed it noise, it will scale that noise β wasting budget on low-quality traffic.
If your goal is too broad or lacks strong quality signals, the algorithm will maximize volume, even when that volume doesnβt drive real business value.
If your seed data is biased, the AI will keep optimizing toward that bias β potentially missing valuable adjacent audiences. This βsampling biasβ in training data is a real, underappreciated risk in automated systems.
Platforms have a financial incentive to push broader automation. Without your oversight and willingness to intervene, campaigns can drift from your business goals. βSet it and forget itβ fails. You need to monitor campaigns and nudge them back on track when they drift.
As targeting automates, creative becomes your primary differentiator. Neglect it and you lose.
Build creative that directly answers your audienceβs pain points. Stand out.
So how do you operationalize this? Here are three steps to start engineering your audiences today:
The era of manual targeting is over, but precision matters more than ever. Audience engineering is your competitive advantage. By teaching algorithms who to target and what matters, you unlock AIβs full potential and win in this evolving landscape.
Intel adds βGaming Supportβ to its ARC PRO B70 and ARC PRO B65 GPUs with its newest ARC GPU drivers With the release of its ARC Graphic Driver 32.0.101.8629 WHQL, Intel has given its ARC Pro B70 and ARC Pro B65 GPUs official βgaming supportβ. This means that users of Intelβs βBig Battlemageβ GPUs will [β¦]
The post Intel delivers official βgaming supportβ to its Big Battlemage ARC Pro B70 and B65 GPUs appeared first on OC3D.
Rythm adds a bouncer to your email so you control who reaches you. It builds a guest list from your Gmail or Outlook contacts, lets known senders through, and files unknown senders into a separate folder you can check on your terms. Strangers can pay a small cover charge to reach your inbox, with paid messages marked PAID and funds sent to your wallet. Rythm scans messages only to detect payment proofs and discards contents, never storing or sharing any email content.
DaySet calculates your daily guilt-free spend after all your bills and subscriptions are accounted for. Enter your income and expenses once and get one number every morning telling you exactly what you can freely spend that day. Unspent amounts roll over to tomorrow. It also includes an AI coach, recipe photo scanner, tax deduction tracker with PDF export, goals, habits, and a bill calendar with reminders. It's built for anyone who wants to stop guessing and start owning every day.
AMD's Ryzen 5 5500X3D extends AM4's life once again, but is it worth it? We tested 14 games to see how this cut-down 3D V-Cache chip stacks up against Zen 3, older Ryzen parts, and newer CPUs.
Axiom enables enterprise teams to turn complex decisions into action quickly. It centralizes procurement and alignment workflows, lets AI agents research options, propose criteria, and score vendors against documentation and RFPs, and generates audit-ready Architectural Decision Records.
Use Axiom to compare human intuition with data-driven scores, collaborate asynchronously to resolve gaps, and approve outcomes with clear traceability. Replace weeks of meetings with days of structured, transparent evaluation.
