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This week, we have a status update on the ongoing Google December 2025 core update. Google also said it does not pre-announce core updates or quality updates. Gemini 3 Flash now powers Google AI Mode. Google Search...View the full article

Search and social now operate as a single ecosystem where shared signals, audience insights, and unified workflows drive stronger visibility and trust. The post Search & Social: How To Engineer Cross-Channel Synergy appeared first on Search Engine Journal. View the full article

In one of the most consequential regulatory moves yet for the future of search, the European Commission has launched a formal antitrust investigation into Google. At the center of the complaint is Google’s use of publisher content to train and power AI Overviews and other generative AI features – while potentially diverting traffic away from original sources. For anyone working in SEO, content strategy, or brand visibility, the implications are immediate. Is Google crossing a line by repurposing publisher content for AI-generated answers, or is this simply the cost of participating in an open, crawlable web? With regulators now stepping in, the industry is being compelled to reassess how machine-readable content is used, managed, and valued – and what it may cost brands, publishers, and agencies if regulation fails to keep pace with innovation. Here’s what’s happening, why it matters, and how the industry is already responding. What’s actually happening: Core allegations in the complaint This EU move comes amid a growing wave of lawsuits and policy disputes over AI training data, from high-profile publisher cases against OpenAI and others to Penske Media’s recent antitrust suit targeting Google’s AI products. Publishers increasingly describe Google’s approach as a forced choice: accept unlicensed use of their content for AI training and answers, or risk losing critical search traffic. At the same time, technical controls such as robots.txt directives, Google-Extended, and emerging noai and nopreview meta conventions reflect an industry trying to regain control over a web that was never designed for large language model training. The core dispute is whether AI training and answer generation are extensions of traditional indexing and snippet creation, or a distinct use that requires licensing, attribution, or both. Dig deeper: New web standards could redefine how AI models use your content What does the complaint target With publishers reporting traffic drops of 20–50% on informational queries, the complaint – led by a coalition of European news and specialist publishers – targets three practices: Google’s scraping of publisher content to train and ground models such as Gemini for AI Overviews and AI Mode. A lack of meaningful opt-out options that preserve search visibility. AI summaries that capture user attention above organic links, reducing clicks to original publishers. Regulators are being asked to examine three core questions: How Google trains and grounds its models on publisher content. Whether publishers have meaningful ways to opt out without sacrificing search visibility. Whether AI Overviews reinforce Google’s dominance by keeping users inside Google’s own interface. Zero-click search evolution: Is the market ready? For the SEO community, this probe marks what may be the start of the post-click era, where the battle for visibility shifts from the SERP to the LLM context window. The open question is whether Google is ready for that shift. The zero-click search experience is often discussed, but for it to work for all parties, three conditions need to be met: Users must be able to get what they need within the SERP, AI Overviews, or AI Mode. Google must seamlessly blend content types – text, images, video, products, services, and even checkout – into a coherent, useful experience. Publishers must be fairly compensated for participating in this ecosystem. At present, Google appears eager to move toward a fully zero-click experience, but is not yet able to support it end to end: Users still encounter hallucinated or outdated answers. Assistive chats remain fragmented and cannot support full discovery or purchase flows. Publishers remain unclear about how, or whether, they are compensated when their content is quoted. What is the opt-out version, and how effective is it? In its defense around content repurposing, Google points to opt-out mechanisms such as Google-Extended in robots.txt. While Google-Extended can block Gemini training, it does not prevent AI-generated answers from fetching live data from publishers’ websites. In practice, blocking LLM training has several limitations: It does not prevent content from appearing in AI Overviews. If Google has indexed a page, it can still summarize or rephrase that content in AI answers, even when Google-Extended is blocked. It is opt-out, not opt-in. Content is used by default, and publishers must be aware of Google-Extended and actively implement it to stop training. It does not provide granular control. Publishers cannot allow traditional snippets while blocking LLM training, or vice versa. Why opting out may be a bad idea Many publishers want to opt out of crawling or having their content used in AI-generated answers. However, if AI answers become the default interface as search moves further toward a zero-click experience, relying solely on direct or organic traffic may become increasingly risky. In practice, this creates a lose-lose dynamic. Blocking usage may protect intellectual property but reduce visibility, while staying open preserves presence at the cost of control. Without regulatory protections in place, publishers are largely left to play within the system as it exists today. Dig deeper: How AI answers are disrupting publisher revenue and advertising Get the newsletter search marketers rely on. See terms. The big debate: ‘Google doesn’t owe you’ vs. ‘it’s not their content’ Since websites exist, we tend to assume they are ours to control. But without search engines, their reach is limited. That tension sits at the heart of a debate that has split SEO opinion. On one side is the “Google doesn’t owe you anything” camp. Many SEOs argue that the web is open by default, and that allowing search engines to crawl a site implicitly grants permission for content use without any guaranteed return. Google enables discovery, the argument goes, but no one is promised clicks or backlinks in exchange. On the other side is the “It’s not their content” perspective. Publishers argue that: Training large language models is fundamentally different from indexing pages. Generating answers from proprietary content without attribution or compensation breaks the long-standing balance between platforms and publishers. When visibility is absorbed into AI summaries with no clear recourse or reward, the long-term implications for publishers, brands, and SEO are significant. This debate plays out daily across social media, Reddit threads, and Quora discussions. Some point to generative engine optimization, or GEO, as a potential survival path, where being quoted in AI answers replaces traditional rankings. But that approach still leaves publishers dependent on Google’s decisions about linking and on users choosing to click through. In practice, both sides have valid arguments. Still, the broader direction appears clear. Even if Google faces penalties from this investigation, search is unlikely to revert to a blue-links-only model. The shift toward a zero-click experience is already underway. The dark future of a web without unique content Before examining the potential outcomes of the complaint and what they may mean for SEOs, it is worth considering the consequences for information itself. As creators feel their work is being reused without permission or reward, the incentive to produce original, high-quality content diminishes. At the same time, the volume of AI-generated content created with minimal human input continues to grow. This trend is not marginal. Entire websites now exist with thousands of pages produced almost entirely by generative systems. Much of this material is derived from existing text that has been reworked, combined, or lightly altered, often with occasional hallucinations or inaccuracies. That content, in turn, feeds new AI answers and additional AI-generated material, creating a cycle of content reuse, error propagation, and declining informational quality due to a lack of genuinely new inputs. From that perspective, the debate over AI training and content rights is not only about traffic or monetization. It also raises fundamental questions about how the web sustains original knowledge creation – and why protecting publishers may be necessary to prevent long-term degradation of information quality. What can happen if Google loses For years, the contract between Google and publishers was simple: “I let you crawl, you give me clicks.” Generative AI has broken that contract. If the EU finds Google’s practices anticompetitive, we could see three major shifts in the search landscape: Mandatory opt-out mechanisms: Currently, blocking Google-Extended stops training but does not necessarily protect you from being summarized in real time. A regulatory win could force a granular “opt out of AI summaries without losing search rankings” mechanism. The licensing economy: Much like the music industry, we may see the rise of collective licensing. If Google is forced to pay for the training value of content, organic search may eventually split into free search and premium, licensed AI search. AEO formalization: If attribution becomes a legal requirement, citing the source may become a ranking factor. SEOs would need to optimize for entity citations rather than only traditional backlinks. Ads and the shifting economics of visibility While this is primarily a story about AI, content rights, and SEO, ads remain the elephant in the SERP. As more organic real estate is consumed by AI-generated summaries and assistive chat, the last predictable lever for visibility remains paid ads. Even if the EU forces Google to rein in its AI answers or improve attribution, the total space left for traditional blue links is unlikely to expand significantly. The available space will continue to favor Google’s revenue-generating products. If AI Overviews dominate above the fold and organic links are pushed further down, CPCs will likely rise, whether inside or outside AI answers. Advertisers will compete more aggressively for the remaining clickable positions. Regardless of how the AI future plays out for Google, the direction is clear: the price of visibility is increasing. How to adapt your SEO and content strategy Even before any formal EU decision, leading teams are shifting from “rank for the keyword” to “be the primary entity answer wherever the model looks.” That involves: Strengthening entity clarity with schema, consistent NAP, and structured data so AI systems can associate queries, topics, and attributes with your brand. Auditing how your brand appears in AI Overviews, major chatbots, and vertical AI tools, then tracking inclusion, sentiment, and factual accuracy as emerging visibility KPIs. Reviewing robots.txt. Blocking may protect IP but reduce exposure, while remaining open may increase AI visibility while raising licensing and valuation questions. Educating leadership that traffic is no longer the only outcome of visibility. Being cited, summarized, or used as a grounding source in AI outputs has value, but that value must be defined and measured internally. As legal and technical frameworks evolve, the strategic challenge is to remain machine-readable and rights-aware, asserting control over how content is used while ensuring the brand remains present wherever AI answers are trusted most. Dig deeper: How to build an effective content strategy for 2026 View the full article

TikTok has signed agreements with three major investors — Oracle, Silver Lake and MGX — to form a new TikTok U.S. joint venture, ensuring the popular social video platform can continue operating in the United States. The deal is expected to close on Jan. 22, according to an internal memo seen by The Associated Press. In the communication, CEO Shou Zi Chew confirmed to employees that ByteDance and TikTok signed the binding agreements with the consortium. “I want to take this opportunity to thank you for your continued dedication and tireless work. Your efforts keep us operating at the highest level and will ensure that TikTok continues to grow and thrive in the U.S. and around the world,” Chew wrote in the memo to employees. “With these agreements in place, our focus must stay where it’s always been—firmly on delivering for our users, creators, businesses and the global TikTok community.” Half of the new TikTok U.S. joint venture will be owned by a group of investors — among them Oracle, Silver Lake and the Emirati investment firm MGX, who will each hold a 15% share. 19.9% of the new app will be held by ByteDance itself, and another 30.1% will be held by affiliates of existing ByteDance investors, according to the memo. The memo did not say who the other investors are and both TikTok and the White House declined to comment. The U.S. venture will have a new, seven-member majority-American board of directors, the memo said. It will also be subject to terms that “protect Americans’ data and U.S. national security.” U.S. user data will be stored locally in a system run by Oracle. The memo said U.S. users will continue “enjoying the same experience as today” and advertisers will continue to serve global audiences with no impact from the deal. TikTok’s algorithm — the secret sauce that powers its addictive video feed — will be retrained on U.S. user data to “ensure the content feed is free from outside manipulation,” the memo said. The U.S. venture will also oversee content moderation and policies within the country. American officials have previously warned that ByteDance’s algorithm is vulnerable to manipulation by Chinese authorities, who can use it to shape content on the platform in a way that’s difficult to detect. The algorithm has been a central issue in the security debate over TikTok. China previously maintained the algorithm must remain under Chinese control by law. But the U.S. regulation passed with bipartisan support said any divestment of TikTok must mean the platform cuts ties — specifically the algorithm — with ByteDance. The deal marks the end of years of uncertainty about the fate of the popular video-sharing platform in the United States. After wide bipartisan majorities in Congress passed — and President Joe Biden signed — a law that would ban TikTok in the U.S. if it did not find a new owner in the place of China’s ByteDance, the platform was set to go dark on the law’s January 2025 deadline. For a several hours, it did. But on his first day in office, President Donald The President signed an executive order to keep it running while his administration tries to reach an agreement for the sale of the company. Three more executive orders followed, as The President, without a clear legal basis, continued to extend the deadline for a TikTok deal. The second was in April, when White House officials believed they were nearing a deal to spin off TikTok into a new company with U.S. ownership that fell apart after China backed out following The President’s tariff announcement. The third came in June, then another in September, which The President said would allow TikTok to continue operating in the United States in a way that meets national security concerns. TikTok has more than 170 million users in the U.S. About 43% of U.S. adults under the age of 30 say they regularly get news from TikTok, higher than any other social media app including YouTube, Facebook and Instagram, according to a Pew Research Center report published this fall. Shares of Oracle jumped $9.07, or 5%, to $189.10 in after-hours trading. —Barbara Ortutay, AP Technology Writer View the full article

Google reportedly has a bug that displays incorrect product reviews in Google Search for a retailer. It is now pulling from text on the page that includes the Google Business Profile reviews, despite the product reviews not being there and not being marked up on the page.View the full article

Google is testing a number of new sports-related search features within Google Search. These include a "What's new" section, "Discover more" section, a Play-by-play section, What people are saying and more. And some of these features, when clicked, take you into AI Mode.View the full article

Sam Altman addresses questions about OpenAI's losses and path to profitability. The post Sam Altman Explains OpenAI’s Bet On Profitability appeared first on Search Engine Journal. View the full article

Google Ads recently added a beta to bring in videos from your social campaigns into your ad campaigns. And now, Google is testing bringing in videos in Merchant Center.View the full article

The educator and broadcaster on the search for life beyond Earth, what we might gain from mining on the Moon — and how to divert a killer asteroidView the full article

Thank you once again for reading Fast Company’s Plugged In. A quick programming note: We will be taking the next two Fridays off. Happy holidays to all, and I look forward to resurfacing in your inbox next year. For any number of reasons, 2025 has hardly been my favorite year. But if I were to make a list of things that went well, my relationship with AI would be on it. This was the year I went from being an AI dabbler to a daily user. And while some of that usage still amounts to messing around—hello, Sora!—even more involves tasks that make me more productive. More importantly, it brings me better results, a goal I hold dear. (Sadly, not every AI enthusiast agrees.) Here, then, is a look at how I’m using AI as 2025 winds down. I covered some of this ground in a September Plugged In. But since I wrote that, the technology has become even more core to my workflow, and my AI A-team has shifted pretty dramatically to Google products for the first time. So a year-end update seemed worthwhile. First, I’ve finally figured out how to use chatbots such as OpenAI’s ChatGPT, Anthropic’s Claude, and Google’s Gemini as research tools. I remain wary of accepting anything they say as the truth, since AI still has a devious knack for hallucinating fantasies that sound like fact. But it’s dawned on me that I don’t need to take AI at its word. Starting a research quest with a detailed AI prompt is often more effective than trying to boil it down into keywords of the sort I would have typed into a search engine in the past. And every self-respecting chatbot now provides citations for its work, at least when I ask for them. They lead to web pages written by actual humans, which are far easier to assess than wordage extruded by an LLM. After spending most of 2025 weaving between ChatGPT and Claude as my chatbot of choice, I was (mostly) wowed by the new Gemini 3 Pro-powered version of Gemini that debuted in November. It’s become my default bot. But the frenzied pace of competition in the category argues against long-term loyalty: I need to spend more time with the new GPT-5.2 version of ChatGPT, which arrived last week. More than any garden-variety chatbot, I have found Google’s NotebookLM utterly essential this year. Instead of trying to be an expert on human knowledge in its entirety, it just digests files you feed to it. Then it lets you ask questions about them and responds with startlingly useful summaries and citations. They frequently lead to insights I wouldn’t have managed if left to my own devices, and have never mischaracterized anything or otherwise led me astray. For me, NotebookLM is most valuable as I spelunk through transcripts of the interviews that provide raw ingredients for articles I write. (In the case of our five-part oral history of YouTube, there were dozens of them, about 168,000 words in total.) For you, the source material might be internal documents, white papers, or something else relating to whatever you’re working on. Either way, this free tool, like most of history’s best software, is a bicycle for the mind. (Disclaimer: I’m not talking about NotebookLM’s best-known feature—podcast-like “audio overview” synthetic conversations based on your sources, which are an astounding magic trick but have never left me feeling smarter about a topic.) Finally on the AI good news front, there’s vibe coding—coming up with ideas for apps and having AI do nearly all the work of turning them into functioning software. When 2025 started, it didn’t even exist as a thing, at least under that name. Now I can’t imagine working without it. That started back in April, when I used a vibe coding tool called Replit to build the note-taking app of my dreams. The project required dozens of hours of effort and hundreds of dollars in usage fees. But eight months later, I use the app I created every day, and it still makes me unreasonably happy. Lately, I have been vibe coding with Google’s AI Studio, which is powered by Gemini 3 Pro. So far, the results have been less quirky and buggy than Replit’s sometimes are, making whipping up my own apps even more irresistible. Case in point: Last month, I bought a ScanSnap document scanner and soon discovered that its cloud service gave the resulting PDFs incomprehensible names. With Gemini’s help, I constructed a smart PDF-naming utility. It reads the files and renames them with clearer descriptions than I’d write myself. Problem solved, in about 20 minutes. Too much AI in all the wrong places For all the ways AI speeded my work in 2025, it’s been far from an unalloyed blessing. Notably, all the tools I praise above are newish and AI-first. When existing products are retooled to emphasize AI, the technology often feels bolted on. It’s not just that it isn’t dependably helpful; sometimes, it’s an obstacle to progress. For example, Google Docs, Microsoft Word, Gmail, and Outlook would all be delighted to compose text for me, a feature that has become as prominent an element of their user interfaces as the 58-year-old blinking cursor. I have no interest in turning that job over to them. And yet I can’t ignore the various icons, widgets, and promos dedicated to these tools, which stare me in the face every time I sit down with these products. It’s an ongoing mental tax levied for alleged benefits I’d prefer to avoid. In other cases, it’s obvious that AI features have been rushed to market without sufficient quality control, as if the bragging rights for having shipped them were all that mattered. I have learned to tamp down my expectations, or even assume that new functionality will perform as advertised at all. In August, for instance. I discovered that ChatGPT’s new Agent feature couldn’t perform some of the tasks in its own list of things I should try. It was also incapable of reliably determining the current date. A month later, I was intrigued enough by Perplexity’s Email Assistant to briefly spring for a $200-per-month Perplexity Max account. I never got it up and running, in part because Perplexity’s own explanation of its new tool was notably short on, you know, explanation. I might have felt less lost if it had just included a screenshot or two. Whether or not there’s an AI bubble, the industry responsible for the technology is still in the process of confronting its legacy of overpromising and underdelivering. But with the good stuff getting really good, anything that fails to live up to its own hype—or simply meet reasonable standards of utility—will only look more ridiculous. May the momentum recently seen in AI productivity’s best products continue in 2026 and beyond. You’ve been reading Plugged In, Fast Company’s weekly tech newsletter from me, global technology editor Harry McCracken. If a friend or colleague forwarded this edition to you—or if you’re reading it on fastcompany.com—you can check out previous issues and sign up to get it yourself every Friday morning. I love hearing from you: Ping me at hmccracken@fastcompany.com with your feedback and ideas for future newsletters. I’m also on Bluesky, Mastodon, and Threads, and you can follow Plugged In on Flipboard. More top tech stories from Fast Company These sites and apps will help you assemble the perfect holiday reading list Even in the AI era, bookstores and online reading communities still rely heavily on human expertise and personal recommendations. Read More → The Warner Bros.-Netflix merger could doom Hollywood film workers For media moguls, maximizing shareholder value is the only metric that counts. Read More → With Apple’s help, storytellers are figuring out Vision Pro The headset opens up immersive new opportunities for dramas, documentaries, music videos, and beyond. Some filmmakers and developers are diving right in. Read More → Robinhood knows you want to trade on everything Prediction markets boomed in 2025. Now Robinhood wants to cash in. Read More → This guy’s obscure PhD project is the only thing standing between humanity and AI image chaos A virtual watermark that’s nearly impossible to remove. Read More → Deepfakes are no longer just a disinformation problem. They are your next supply chain risk Most companies are woefully unprepared, and the traditional cybersecurity playbook isn’t enough. Read More → View the full article

Google has updated the Google Business Profiles verification issues support form. This makes it easier to pick a specific issue you had when trying to verify a business within Google Business Profiles.View the full article

Google updated its JavaScript SEO documentation for the third time this week, this time to say that "while pages with a 200 HTTP status code are sent to rendering, this might not be the case for pages with a non-200 HTTP status code."View the full article

Does it feel like your organic traffic is disappearing? You aren’t imagining it. AI Overviews and answer engines are sidelining classic SEO results. To stay visible, brands need to adapt – fast. The good news: you don’t need to rewrite your entire SEO playbook. With a few smart tweaks, you can shift from SEO to GEO and reclaim your share of search in the age of generative AI. GEO, or generative engine optimization, focuses on entities – not just pages. That means your brand, products, services, and experts. By strengthening these signals, you increase the chances your business is cited, referenced, and recommended inside AI-generated answers and conversational search results. This shift to GEO matters because AI search tools work differently from traditional engines. Instead of a list of blue links, AI delivers answers that anticipate follow-up questions and add context. Users get what they need faster, but brands get fewer clicks. Organic search demand isn’t disappearing, but traffic is drifting away from it. As clicks decline, visibility inside AI-generated responses becomes more critical than ever. What you need to do now You don’t need to reinvent your strategy to move from SEO to GEO. GEO builds on the principles you already use, with added focus on structure, clarity, and consistency. 1. Prioritize E-E-A-T (Experience, Expertise, Authoritativeness, and Trustworthiness) AI engines reward clear, authoritative content that signals real expertise. When your content aligns with established quality guidelines, it’s more likely to be used in generative answers. 2. Make your content easy for AI crawlers to read While Googlebot handles JavaScript well, many AI crawlers don’t. Fully rendered HTML, clean structure, and predictable layouts make it easier for AI systems to understand your content and reference it accurately. 3. Invest in structured data Schema markup, complete metadata, descriptive alt text, and transcripts help AI models understand your content and connect it to the right entities. These behind-the-scenes signals make it more likely your content appears in AI-generated conversations. 4. Rethink measurement Traffic is no longer the north star. Focus instead on conversions, deeper funnel impact, sentiment, and your brand’s visibility inside generative results. Want to go deeper? If you’re ready to pivot from SEO to GEO with confidence, explore proven best practices, frameworks, and real-world examples on Contentful’s GEO Hub. It’s your go-to resource for understanding the shift – and staying ahead. View the full article

Pricing is one of the most powerful growth levers a business has, yet it is still one of the most overlooked. While teams spend months refining product and brand, pricing decisions are too often rushed, emotionally charged, or guided by instinct rather than insight. Under the pressure of rising costs and competitive pressures, many leadership teams resort to the fastest fix: promotions to meet short-term targets or price increases to plug a margin leak. The companies that consistently outperform take a different approach. They treat pricing as a strategic, evidence-led discipline. They ground pricing in how customers perceive value and make decisions to deliver growth that lasts. Take two companies facing the same rising costs. One applies a uniform 10% price increase to protect margin. It works briefly, until customers notice and push back. Sales slip and the business reacts with discounts that instantly undo the uplift they were counting on. The other takes a more thoughtful approach. They identify where value is strongest, redesign how options are packaged and presented, and adjust prices selectively. A year later, revenue and gross margin are up, and customer trust remains intact. This is what happens when pricing becomes a strategic capability rather than a quick fix. Here are six levers business leaders can use to make pricing a sustainable engine of growth. 1. Position: Where do you sit in the market? Positioning shapes how customers view your product or service when compared to the alternatives. That may be another version of your offer, a competitor offer, or a completely different option that your customers believe can get the job done. Where you sit among those options shapes what customers are willing to pay. Is your offer seen as premium or budget? A “want to have” or a “need to have”? Make your positioning clear by finding out why customers choose you over the alternatives, and what role price plays in that decision. 2. Perception: How do customers assess value? Perception is how customers judge the value of your product or service. It’s how your solution meets their needs, solves a problem, or brings a moment of ease or delight. That perception forms before they buy through brand cues, third-party reviews and how clearly the benefits are communicated, and it continues to evolve based on how well the product performs in use. The mistake teams make is assuming customers see the value as clearly as they do. Instead, listen carefully to your customers to understand what they value most, and what they are willing to pay for that value. Use these insights to refine how you communicate value at every stage of the purchase journey. 3. Packaging: What choices are you offering? Packaging is the structure behind the choices you offer to customers: what’s included, how different features are bundled together, and how customers compare options. For example, streaming services use “good–better–best” packaging, with tiers ranging from a basic with ads plan up to a premium option. Give customers too many choices, and it’s overwhelming. Give them too few, and it becomes a question of “should I buy?” rather than “which should I buy?” Guide customers toward better decisions by making options intuitive, with clear trade-offs and visible benefits as they move to more premium options. 4. Presentation: How is your offer presented? Presentation is how your prices are visually communicated. Customers rely on subtle cues such as color, size, language, and layout to interpret value and compare choices. Each of these cues implicitly shapes how the price feels and can nudge customers toward one choice over another. Test and refine how pricing information is framed and displayed to build confidence and improve conversion. Experiment to measure which changes drive the best outcomes. 5. Price: Are you charging the right amount? Price is the number customers see, but it should not be the starting point for pricing decisions. When companies skip straight to the number, they end up debating numbers, not value. The price needs to align with everything that comes before it: positioning, perception, packaging, and presentation. When customers see a price that mirrors the value they feel, it strengthens trust, confidence, and conversion. Think about your price point. Is it aligned with your value, your position in the market, and the choices on offer? 6. Promotion: When and how should you discount? Promotion is the lever you pull to spark a specific behavior: trial, urgency, repeat purchase, or upsell. The challenge is that discounts are often used to chase short-term targets, which risks eroding margins and teaches customers to wait for a deal. Discounts and promotions work best when they are intentional and anchored in a clear pricing strategy. Use promotions to drive specific customer behaviors without undermining value or long-term profitability. Shift the question from “How much should we discount to hit this month’s number?” to “What behavior are we trying to drive, and is a discount the right lever to do it?” Under pressure, leaders face a choice: rely on reactive decisions or treat pricing as a strategic capability. By pulling a broader set of levers and grounding decisions in real customer value, you turn pricing into a tool that can shape demand, signal value, and lead to sustainable growth. View the full article

My work across decades has spanned sectors, geographies, and cultures, focusing on exploration, discovery, and innovation. My husband and I have defined our work across business, nonprofit, and philanthropy simply: “We invest in people and ideas that can change the world.” I spend much of my time exploring and sharing exciting developments that hold great promise. This work has taken me from building the Internet revolution, to working in villages and cities across the globe and America’s 50 states, to the boardroom of the National Geographic Society, where I just completed a decade of service as Chairman of the Board. It has been a true privilege to lead these efforts, and we have made a real impact in many ways. But this work can be difficult—my years of engagement in brain cancer research highlighted what an unknown frontier the brain represents. The work can also be complex—like rolling out initiatives across diverse geographies and communities, but it continues to energize and engage me. At nearly every turn, technology has been central to our quest to “find a better way,” and it has played an important part in every one of the success stories in our portfolio. But here, as we close out 2025, the reality is stark: while technology can still bring hope and promise on many fronts, the underbelly of its excessive use has become painfully clear. Americans now spend over seven hours a day looking at screens. Meanwhile, rates of anxiety, depression, isolation, and loneliness have skyrocketed, particularly among young people. Our brains are being rewired in ways none of us asked for, and the health and wellness of the population more broadly are seriously at risk. And sadly, the promise of technology to bring communities together that animated so many of us in our early tech careers has instead led to rising divisions between people and places. What can be done? So, what can be done here to address this worrisome trend? Well, it turns out a solution that might hold great promise was hiding plainly in sight: indeed, the answer doesn’t lie in abandoning technology, but rather in the simple act of logging off and getting out in nature. That’s right. It turns out nature is a powerful medicine. Recent research validates what many of us intuitively know: a Stanford meta-analysis of 449 studies found that nature exposure significantly improves mental health outcomes, including mood, stress, and anxiety. Perhaps most encouraging, researchers found that just 20 minutes in a park—even without exercising—people reported feeling better, while repeated nature exposure of as little as 10 minutes yields measurable benefits for those with mental illness. But the benefits extend far beyond individual wellness. These aren’t marginal improvements—they’re prescription-strength results from the most accessible medicine on Earth. The barrier to entry is often just putting on a pair of sneakers or hopping on a bike. The beauty of outdoor engagement is its democratic accessibility. Unlike expensive gym memberships or specialized equipment, stepping outside costs nothing and requires no particular skill. So whether you walk around the block, walk for 20 minutes in your neighborhood, or find a way to hike in a city, state, or national park, walking delivers measurable health benefits. A fork in the road We stand at an inflection point. We can continue accepting digital isolation and declining physical and mental health as inevitable byproducts of technological progress, or we can recognize that the human experience began outdoors, in communities, solving problems together—and that our health depends on experiences no app can replicate. This isn’t about returning to some romanticized past. It’s about balance. It’s about making outdoor, screen-free time as routine as checking email. It’s as simple as taking a walk, encountering neighbors or nature at a park or in your community. Where getting outdoors is the default, not the exception. The screen will always be there when you return. But the opportunity to rebuild America’s health and social cohesion by getting outdoors requires intention. We need individuals choosing strolling over scrolling, employers encouraging outdoor breaks as part of a productive workday, healthcare providers prescribing park time, and local leaders who prioritize walkable communities that enable us to meet and greet each other and Mother Nature. The question isn’t whether you have time for outdoor connection—it’s whether you can afford not to make time for the wellness program hiding in plain sight. View the full article

When it came to using frozen Russian assets as leverage, the EU blinkedView the full article

Core Web Vitals measurements reveal a significant difference between open source and proprietary CMS platforms. The post Core Web Vitals Champ: Open Source Versus Proprietary Platforms appeared first on Search Engine Journal. View the full article

AI is forcing every leader into a choice they can’t dodge: do you believe your people are fundamentally creative and motivated, or lazy and in need of control? Most leaders won’t want to answer that honestly, but their AI strategy already has. The AI mandates. AI-blamed layoffs. So-called AI-enabled “bossware.” The truth is in the tools: many leaders prefer “synthetic” employees they can control, and will treat human beings much the same way until they can be replaced. Sound hyperbolic? Just look at recent headlines. Klarna’s CEO famously bragged about AI replacing his staff after the company fired or lost 22% of its workforce a year earlier (this blew up in his face, of course). Duolingo effectively announced a hiring freeze with the introduction of AI. Elijah Clark, a CEO who advises other CEOs on AI, quipped to Gizmodo, “AI doesn’t go on strike. It doesn’t ask for a pay raise” as he expressed excitement about laying off employees in favor of AI. A 2024 review found that more than two-thirds, 68 percent, of U.S. workers report experiencing at least one form of electronic monitoring on the job. There are actual billboards running that say, “Stop hiring humans,” while a new survey found that 37% of employers would prefer hiring a robot or AI over a recent college graduate. It isn’t just that AI is replacing workers (it is), it’s that AI is reinforcing our dimmest view of workers in the process. Generation X Douglas McGregor was a social psychologist and MIT Sloan professor who, in 1960, argued that leaders don’t just manage from goals and objectives; they manage from hidden assumptions about human nature. He called one cluster of assumptions Theory X: the belief that people dislike work, avoid responsibility, and need tight control and incentives to perform. The contrasting Theory Y assumed that, given the right conditions, people will seek responsibility, exercise self-direction, and bring far more creativity and judgment than most organizations ever tap. When leaders push AI in ways that amplify surveillance, shrink autonomy, or quietly replace judgment with automation, they aren’t just “modernizing,” they’re hard-coding Theory X into the operating system of work. Here’s the thing about Theory X/Y: McGregor wasn’t arguing which was right, whether employees were fundamentally lazy or capable, but that managerial beliefs become self-fulfilling. How you think about your employees determines how they’ll act. Bossware, productivity scoring, keystroke tracking, sentiment analysis of employee chats, all of it sends the same signal: we assume you won’t do the right thing unless we’re watching. These tools teach people that initiative is risky, creativity is irrelevant, and trust is conditional. And once those assumptions are embedded in tools, dashboards, and performance reviews, they stop being a management preference and start being the default culture. It doesn’t matter that not every CEO or leader sees employees this way, enough vocal Theory X proponents will shape the narrative for everyone else. Ultimately, the more that human beings are placed in head-to-head competition with AI, the more that the workforce will respond with fear, mistrust, loafing, and even cheating. Y Not A Theory Y AI tool starts from the premise that people want to do good work when the system around them makes that possible. Unfortunately, the market isn’t offering a lot of Theory Y AI right now. We need more tools here, more competition, more billboards blaring an alternative worldview. Imagine a tool, for example, that spots duplicated efforts early. Or one that learns from and simplifies decision-making and governance over time. That helps teams compare options, highlights trade-offs, and develops their strategic thinking muscles. That could create shared situational awareness by showing how changes in one team affect others in real time. Instead of secret dashboards used to police performance, Y-style tools could give workers ownership of their data and use it for growth, not punishment. They could make invisible contributions visible—mentorship, relationship-building, problem-prevention—so the whole texture of teamwork gets its due. In short, they could expand autonomy with guardrails, rather than constrict it with algorithms. Asking the Wrong Question The real question isn’t how much productivity we can squeeze out by replacing people with AI or treating them like imperfect machines. It’s how much potential we’ve never tapped because the modern workplace was built on bureaucracy, compliance, and risk-avoidance. For decades, we’ve constrained the very things that make humans extraordinary—creativity, judgment, curiosity, connection, the spark that happens when people riff on each other’s ideas. Those capacities have never been fully measured, let alone optimized, because most organizations designed them out of daily work. AI could help us reverse that. Not by automating humans out, but by clearing away the sludge that has buried human capability for a century: redundant approvals, performative documentation, meetings that exist because the calendar said so, processes created for a world that no longer exists. The opportunity isn’t a marginal gain from policing employees harder—it’s the exponential upside from finally unleashing the talent you hired in the first place. The leaders who will win the next decade aren’t the ones who solely bet on synthetic workers, but the ones who use AI to build the first truly human organizations—places where people can think, make, collaborate, and surprise you again. View the full article

A complete guide to canonical URLs: how they affect SEO, how to add or change canonical tags, and how to fix issues in WordPress, Shopify, and more. View the full article

LinkedIn’s algorithm has always been a bit of a mystery — until now. The LinkedIn team has been pulling back the curtain on the algorithm in interviews with Entrepreneur, talking about how it works and why going viral isn't the goal. We've looked at two: On the website, with Editor-in-Chief and VP of Content Development, Dan Roth, and Alice Xiong, Director of Product Management.On the podcast, with Senior Director and Executive Editor at LinkedIn News Laura Lorenzetti.In this article, we’ll highlight the key points from the team’s interviews about the LinkedIn algorithm and share practical tips for applying this knowledge to your content. Jump to a section: How the LinkedIn algorithm works Key metrics for LinkedIn success How creators can work with the LinkedIn algorithm 7 LinkedIn tips for better content performance Frequently asked questions about the LinkedIn algorithm More LinkedIn resources How the LinkedIn algorithm worksUnlike YouTube and Instagram, which have different spaces on the platforms to discover content, LinkedIn primarily serves users content on the Feed: what someone lands on when they open the app or visit the website. The real magic is how it picks what users see. The system looks at their connections, the topics they care about, and the conversations they’re most likely to join. That’s how LinkedIn keeps people engaged with people and ideas that matter to them. With over 1 billion members and millions (some say billions) of updates posted every day, LinkedIn relies on signals like relevance, timeliness, and authenticity to decide what users see. It’s about meaningful engagement and genuine connections count more than numbers on the social media platform. Here’s what that means for brands and creators: when you create quality content that’s relevant to a specific audience, those people are more likely to see your posts. The reverse is true for your audience of LinkedIn users: what they engage with is what they’ll see. If they always engage with B2B marketing content, they’ll see more of that on their Feed. If you always post about B2B marketing, your target audience will inevitably see more of your content. And the more niche your approach is, the better the algorithm can direct your content to the top of the right Feeds. With this context in mind, all the updates are in service of getting the right content in front of the right audience. 📈Buffer's LinkedIn Analytics offers in-depth insights, allowing you to iterate and enhance your LinkedIn strategy for better reach and engagement.Virality no longer drives the algorithmLinkedIn used to prioritize whatever got the most engagement. You know, the viral stuff. Now, it’s more about meaningful connections and relevant conversations. That shift means users will likely see fewer random viral posts and more content that aligns with their interests or professional goals. Focusing on viral content isn't the best strategy now as it's unlikely to lead to real growth in the long run. Connections and followers now see your posts firstLinkedIn made this change because people kept asking for it. Turns out, most of us find posts from our existing connections way more valuable than posts from strangers. It also means that the quality of your network is more critical than ever. If you want engagement, the people you connect with need to see value in your content. This doesn't mean that your posts will live in a bubble, and that people outside your connections won't ever see them. LinkedIn's algorithm rewards knowledge-rich posts by extending their reach beyond the creator’s immediate network. Even non-connected users who might find your content valuable could see your posts if they provide value and gain meaningful engagement. LinkedIn prioritizes expert contentLinkedIn wants to surface more of the knowledge and advice that experts are sharing. The algorithm determines what expertise is relevant to a user by identifying their interests based on their profile info and activity. For creators, LinkedIn pays attention to who you are and how much engagement and sharing your content gets, then it decides how broadly to distribute your posts. That means each like, in-depth comment, or share can expand your audience — so encouraging authentic interaction is key. 📚Must-read: The Quick Guide to LinkedIn Marketing Strategy: 9 Best Practices for 2024Key metrics for LinkedIn successThe LinkedIn algorithm uses ranking signals to evaluate content: Relevance, Expertise, and Engagement. Together, they decide if your post reaches just a few people, or many more. Relevance: How closely your post matches the interests of a defined audienceExpertise: Whether you demonstrate subject matter knowledge in your postEngagement: If your post sparks meaningful comments from people who typically interact with this topicAs a creator, you should aim to design content that not only appeals to a specific audience, but also underscores your expertise and encourages genuine engagement. Here’s how. How creators can work with the LinkedIn algorithmWhether you consider yourself a creator, an influencer, or just someone building their personal brand on LinkedIn, my advice is the same: Treat LinkedIn like you would a work conference. You’re there to: Give a keynote presentation (share high-quality content built off your hard-won expertise) andNetwork with people (engage and make new connections)With that conference mindset, your posts should: Be relevant to the conference and its attendees (your niche and audience)Pack as much value as possible into those crucial first few seconds before someone keeps scrollingContain some fun personal stories or anecdotes to entertain as well as educateThis helps the LinkedIn Feed ranking algorithm accurately categorize your content and match it with the audiences most likely to value it. To help LinkedIn categorize your posts, you should: Share a unique perspective on a popular topicShow off your expertise with practical examples and adviceFormat it so that it's easy to readEncourage responses with CTAs (“comment below if...”)Use three or fewer relevant hashtagsAvoid engagement bait — posts that ask for likes, shares, or comments in a spammy way can hurt your reach.Incorporate relevant keywords from the topic niche (check out tools for finding these keywords here)Tag people when it's relevant. Remember to be respectful of how you’re bringing people in the conversation and referencing them, says Laura Lorenzetti. "[Tagging people] is a great thing to do to make sure people are connecting with you and are tagged into what is relevant to them," she says.Beyond the specific post elements, here are some bigger-picture things to keep in mind. Focus on sharing knowledge and adviceLinkedIn’s algorithm brings the platform back to its professional roots, rewarding content that sparks real conversations. If you can help others learn or grow, you’ll see better results over time. "Think about what kind of knowledge you have to offer to help people,” says Alice Xiong. “That is the kind of thing that will likely get you to reach the right audience as well.” Prioritize relevance over viralityYour content should share insights that can resonate with a specific professional audience instead of trying to appeal to a mass audience. If your passion is kitchens in Middle Eastern architecture and that’s what you choose to write about, the algorithm will make sure the right people see it. Your followers matter more than ever, but in quality over quantity In the simplest terms, if you post about a topic, the people who will see it are those who follow you, then anyone interested in that topic. So, your LinkedIn network needs to be filled with people who are most likely interested in what you share and will engage. 7 LinkedIn tips for better content performanceBeyond creating high-quality content that is relevant and useful to your audience, here’s a checklist to maximize your chances of LinkedIn success. 1. Optimize your LinkedIn profileMake sure you leave no stone unturned in completing your LinkedIn profile. Gaetano DiNardi created this handy guide of 30+ LinkedIn profile tips that’s definitely worth checking out. Here’s a summary if you’re short on time: Choose a unique profile picture and bannerWrite a catchy headline and summary — don’t be afraid to include emojis to stand out in people’s feedsWrite a detailed experience section — include bullet points of achievements in your roleAdd skills, endorsements, and recommendationsShowcase licenses and certificationsLaura Lorenzetti says your headline is something you should really pay attention to, because people will see it not only on your profile but also on your posts in their feed. “If people don’t know you, they’ll look at your name and headline, and they’ll match that to what you’re saying,” says Laura. “They’re trying to understand your credibility and expertise, so the more thoughtful you are of how that headline reflects that credibility and expertise and what you want to speak to the better.” 2. Post at the best timesWith social networks having ditched chronological newsfeeds many moons ago, timing your posts perfectly is a lot less crucial than it once was. However, considering the best time to post on LinkedIn for your audience may help give your post reach a little boost. But when works? To figure out the best times to post on LinkedIn, we assessed the engagement rates of more than a million LinkedIn posts sent through Buffer to pinpoint the sweet spot for engagement — and the results won’t surprise you. We discovered that anything posted between 7 a.m. and 4 p.m. on weekdays had the highest engagement rate — so if you’re wondering when to post, these times might be your best bet. Of course, every audience is different, so it never hurts to experiment outside those hours, too. 3. Post consistentlyThe more you share, the better LinkedIn will understand who you are, what you do, and who wants to see your posts, so publish frequently. We've got the data here, too. Buffer's analysis of more than 2 million LinkedIn posts shows that posting 2 to 5 times a week helps improve both impressions and engagement. You could absolutely post more often if you want to — our data found that the more often you post, the better your LinkedIn performance. But if that doesn't feel sustainable without burning out, aim to stay within this range. Quality is still more important than quantity on LinkedIn, so a few well-crafted, valuable posts will be a lot better for your content than aiming for a numbers game. Creating a content calendar is a great way to make this manageable and scale your output, especially if you’re posting on other social media platforms, too. 📚Must-read: 5 Tried-and-tested Strategies I’ve Used to Grow to 30K LinkedIn Followers4. Experiment with content formatsGone are the days of basic text posts. LinkedIn’s functionality allows for a host of different types of posts these days — think images, carousels, videos, text posts, newsletters, and polls. Through Buffer's analysis of the best content formats for different social media platforms, we found what works best — for LinkedIn, that's PDF carousels. Of more than 1 million LinkedIn posts analyzed, our data found that carousels greatly outperform other post formats. They earn: nearly 3x more engagement than videos3x more engagement than imagesnearly 6x more engagement than text-only postsYou can use PDF carousels to create new content, but they're also a brilliant, visual way to repurpose something you may already have shared in a text post on LinkedIn. Here are 11 LinkedIn carousel ideas to get you started. Videos are the next best performing posts. If you’re already creating videos for other platforms, consider repurposing your content — just make sure they fit what your LinkedIn audience actually wants to see. If you're starting fresh with LinkedIn video, check out the platform's Create Video newsletter for practical tips to get you going. With so many content formats to choose from, it’s worth experimenting to see which resonates the most with your audience. ⚡Make sure your carousel posts go out at the best time for engagement! Here’s how to schedule LinkedIn carousels with Buffer.5. Share links strategicallyAs you can see from the graph above, posts with links generally don’t get as much engagement as other types of content — but that doesn’t mean links are off-limits in your LinkedIn digital marketing strategy. When you share links, says Laura Lorenzetti, make sure the accompanying post also shares value. "Our algorithm is really focusing on the value and content that’s being shared in the post," says Laura. "And what we've found from talking to creators is that if you're writing great knowledge in that post, people are also more likely to be interested in what more they can get if they go to that link." Add links to your content calendar for the most essential external resources you want to share with your audience. Just make sure the post itself delivers just as much value as the page you're linking to. You could also share these resources in the comments. Sharing links this way does not appear to have a negative impact on post performance. 🔗With Buffer, you can now schedule a first comment along with your LinkedIn post — perfect for those ‘Find the link in the comments’ moments. Connect your LinkedIn Page or profile to get started.6. Pay attention to the hookIf you want people to read your post instead of scrolling by, you need to nail the hook. That's the first couple of lines they see while scrolling — and it's your shot to make them stop and pay attention. Instead of starting with an introduction or preamble, get right to the heart of the matter. "What’s the most interesting part of your post? Put it at the top," suggests Laura Lorenzetti. "Hook the people, tell them the payoff, and then get them into it." 7. Reply to commentsHere's something worth knowing: Buffer analyzed 72,000 LinkedIn posts and found that replying to comments can boost your engagement by 30%. The comments section matters just as much as what you post. Stick around to respond to people who take the time to comment. Make it easy for them to engage in the first place by ending your posts with thoughtful questions that invite real conversation. The payoff will be more engagement and a community that actually feels like one. If you're struggling to keep up with all your LinkedIn notifications and comments, Buffer can help. With the Community feature, you can reply to comments on your LinkedIn posts without ever leaving Buffer. Great news — your niche interests and knowledge are in demandThe updates to LinkedIn’s algorithm mean great things for creators with niche interests and expertise. You don’t need to try to beat it or game it — just go with its flow. Since the algorithm cares more about getting your content in front of the right people, you can be assured that you’ll grow as long as you optimize your posts and keep up your engagement through comments and replies. In other great news, scheduling content isn’t penalized — only abandoning your scheduled content. So get a head start on drafting a bunch of new, relevant content for your audience on LinkedIn through Buffer. Schedule a LinkedIn post→ Frequently asked questions about the LinkedIn algorithm1. Can I trick the LinkedIn algorithm?You really can’t “trick” the LinkedIn algorithm, and you shouldn't aim to. LinkedIn’s algorithm focuses on long-term engagement and genuine connections, so quick-fix hacks generally fall flat. 2. Does posting more often always help?Posting more often does help boost your reach, but quality, relevance, and genuine engagement will always matter more than just posting frequently. Jumping from 1 to 5 posts a week is where you'll see the biggest difference. Posting more often can still give you a lift, but the improvements are smaller, so only push for it if it feels sustainable. 3. Are hashtags still important?Hashtags can help members when they're looking for things, but overusing them can look spammy. As Laura Lorenzetti says, they're “a nice to have, not a need to have.” Stick to a few relevant ones. "Don’t use too many, and it’s ok if you don’t use them," she says. 4. Will LinkedIn penalize external links?No, LinkedIn won't penalize external links — as long as your post itself delivers real value. If you're sharing a link, make sure the post is just as helpful as the resource you're pointing people to. Give context, share insights, and make it worth their time to engage with your content first. 5. Should I boost a post?Boosting can expand your reach when done strategically, but strong organic engagement usually drives the best long-term results. More LinkedIn resourcesHow Often Should You Post on LinkedIn in 2025? Data From 2 Million+ PostsHow to Make Your LinkedIn Profile Stand Out: 30+ TipsI Started Over on LinkedIn After Deleting 7,000 Followers — and Grew Faster Than BeforeView the full article

Over the past several years, the art of the rebrand has increasingly become a spectacle sport. From cultural institutions like the Philadelphia Art Museum, which reportedly fired its CEO over a poorly received rebrand this year, to the furniture brand La-Z-Boy, which was widely praised for its modern revamp, the internet’s attention economy has meant that almost no notable rebrand is safe from social media’s deluge of hot takes. In 2025, that was more true than ever. Brands that rolled out a new look this year were scrutinized for everything from their font and color choices to the potential ideological implications of their visual pivots. In September, after the design firm Pentagram received major flack for its official branding of the city of Austin, partner DJ Stout told Fast Company, “It’s because of social media. Back when I first started about 40 years ago, nobody even knew what an identity system was.” To close out the year, Fast Company asked seven design experts to choose one rebrand that—for better or worse—will be remembered as the most influential of 2025, shaping both design and discourse in the months ahead. Here’s what they told us: Cracker Barrel’s “woke” rebrand In a testament to the major impact of Cracker Barrel’s rebrand, two of the seven designers we contacted identified the brand as their top pick. News of Cracker Barrel’s rebrand initially emerged in mid-October, when the company unveiled a new color palette, typography, and plans to revamp its restaurant interiors. But what really stood out to fans was the brand’s new logo, which removed the former rendering of an older man leaning on a barrel, known as “Uncle Herschel” or “the Old Timer,” in place of a more modernized look. “In the hope of presenting a more contemporary image to the world and attracting younger and more affluent customers, they eroded the brand’s identity and character (literally: goodbye Uncle Herschel),” says Matt Boffey, chief strategy officer at Design Bridge and Partners in the UK and Europe. Online, right-wing commentators framed the swap as a radical, “woke” move, with everyone from conservative activist Robby Starbuck to President The President himself weighing in with increasingly negative takes. The backlash was so severe that Cracker Barrel lost nearly $100 million in market value in the following days (though it later rebounded). It publicly walked back the rebrand, reinstating Uncle Herschel and assuring customers that it would no longer move forward with restaurant renovations. According to Stout of Pentagram, the unwanted attention around Cracker Barrel’s rebrand actually had ripple effects for the reception of his team’s City of Austin identity, which was unveiled around the same time and similarly became the target of criticism for what he calls the “logo mob.” “To be fair, I think the Cracker Barrel identity rebrand was nicely done and a much needed evolution,” Stout says. “The effort was unfairly judged by merely comparing the ‘before and after’ versions of a single element (the logo) of the comprehensive identity system, which is the typical online parlor game of rebrand criticism these days. The complete identity system is smart and exactly what I would have done–which is why I may need to think seriously about retiring.” Stout adds that, in his opinion, the worst part of the whole fiasco was the fact that Cracker Barrel chose to revert to their “dated, out-of-touch” identity. “That spineless decision by the parent company didn’t acknowledge the months of thoughtful deliberation and work that went into the development of their new identity system—and it threw their design partner under the bus,” Stout says. “This knee-jerk reaction and the online mob mentality it has stoked is a concerning trend and detrimental to my industry moving forward.” Walmart takes a trip into the archives Undoubtedly the largest company to rebrand this year was Walmart. The brand got its first update in two decades, courtesy of the design firm Jones Knowles Ritchie (JKR), which gave it a subtle facelift that amplifies its blue and yellow color palette and sprinkles in some callbacks to the company’s ‘60s and ‘70s archives. “My favorite part is how that custom typeface is put to work,” says Delta Murphy, an associate partner at Pentagram’s Austin outpost. “It nods to their past while still giving them room to grow, and that kind of balance is incredibly hard to pull off. I’m not sure I’d call it a trend as much as a principle of design I appreciate, but I get excited when rebrands tie into meaningful heritage and push into modernity, especially through typography.” Murphy adds that the Walmart rebrand actually hit a similar note as Cracker Barrel’s new identity—the difference being that Cracker Barrel “got tangled up in politics and internet outrage,” which stalled the roll-out before it could ever get off the ground. “If I had one wish for the future of graphic design and branding, I’d wish for more curious conversation and a lot less cynicism,” she says. Cash App is not your mom’s banking app One undersung branding hero of 2025 is Cash App, according to Kimia Fariborz, senior designer at the global creative agency Further. In March, Cash App introduced a new set of brand guidelines that brought playful motion elements and expressive graphics to the brand, making it feel more like an artsy, design-centric brand than a baking app. These broadened guidelines, Fariborz says, helped pave the way for Cash App to roll out new features throughout the year that represent how the modern customer is actually banking, like through bitcoin payment options and an AI assistant named Moneybot. “What I appreciated most is that Cash App embraces its reality instead of posturing as a traditional bank,” Fariborz says. “It recognizes the unconventional ways people use it and builds a tone that reflects that world. That honesty gives the brand permission to be vibrant and layered in a category that often defaults to seriousness.” Grammarly gets a new name Nearly two decades after its founding in 2009, Grammarly traded its brand name in October in favor of “Superhuman,” the name of a younger, less well-known AI company that it recently acquired. The swap came alongside a massive brand overhaul designed to signal Grammarly’s shift into a new era focusing on agentic AI. David Placek, CEO and cofounder of the firm Lexicon Branding, believes the change is bound to pay off. He notes that we’ve seen other companies reverting back to a component of their old name or debuting a new iteration—like MSNBC to MS NOW and Gannett to USA Today—but Superhuman’s naming shift was by far the boldest. “I expect this to be influential because Grammarly is extremely widely used today, but their name has always held them back a bit,” Placek says. “I think it’s a great call to action for companies to reflect on whether their brand name is stunting their growth and if so, to rebrand.” Apple TV loses the “+” If Superhuman represents a major brand name swap done right, then Apple TV+’s new identity as Apple TV, which was revealed in October, is an example of a small identity tweak that actually makes sense. When streaming first emerged as a new way to consume content, the “Plus” symbol became a ubiquitous way to let consumers know what kind of service a brand was offering. Today, though, streamers like Disney+ and Apple TV+ are recognizable without the extra punctuation tacked on—so, Apple made the decision to simplify things by taking it out altogether. A month later, the company also unveiled a new Apple TV branding system created using practical effects. Matt Sia, executive creative director at the design firm Pearlfisher, says the update will have an impact on branding moving forward because it demonstrates a future-facing truth: when categories become cluttered, clarity becomes the differentiator. “Instead of proliferating sub-brands and product names, adding bells, whistles (or ‘+’s), Apple pulled everything into one coherent idea,” Sia says. He believes that consolidation will spark a wave of simplification across the industry, as others begin to question how they can reduce noise in their own positioning. “Apple crafted an identity that feels more visceral and immediate. It doesn’t rely solely on software animation to convey emotion, but ensuring the logo, typography, and graphic system hold expressive power on their own,” Sia says. “Filming in an entirely practical way without relying on CGI sends a message that human touch and crafting experiences, using process and materials, still hold value.” Gap gets its groove back This year, one iconic American company didn’t rebrand in the traditional sense, but it did manage to completely turn its brand perception around: Gap, the apparel purveyor that, mere months ago, may have seemed like an outdated relic, but is now the fashion darling of Gen Zers everywhere. “Gap’s brand resurgence into the cultural lexicon this year wasn’t a story of refreshing identity but one of reclaiming ethos,” says Alexa DePasquale, head of strategy at the design agency CBX. “The brand focused less on overhauling aesthetics and more on doing things in the world that doubled down on the core equities that once made it so iconic: essential silhouettes, American optimism, and visual language engrained in memory.” Stand-out moves from Gap this year include aligning with Zac Posen, partnering with designer Sandy Liang, and bringing back the y2k jean through a collaboration with the pop group Katseye. All of these moves have resurrected the brand from the back of your childhood closet to the front of the cultural zeitgeist. “Brands are recognizing that distinctiveness matters far more than novelty, and Gap’s confident return to what only it can do proves why it is a staple,” DePasquale says. “I’m loving the clarity that comes from the brand’s conviction to buck trends. More legacy brands will realize the power that comes from moving forward without abandoning the DNA that once made them inevitable.” View the full article

Every year the world gets a little more digital—and every year we still find surprise, delight, and meaning in the physical and the material. Like books or movies, the objects we obsessed over tell a story about the year gone by. So to continue a tradition that goes back several years now, here’s my look at the objects that tell the story of 2025: the joys, the absurdities, and the difficult-to-explain. 1. “Gold” Oval Office Decor To call the second The President administration a new gilded age is less a critique than a straightforward descriptor. Most notably, the president has transformed the look of the Oval Office into a barrage of gold, from gilded statues and vases to accent pieces that Internet sleuths said were actually just painted decor from Home Depot. (The President denied this.) While mocked as tacky by many observers, the look is of a piece with a continuing embrace of brazen material opulence, from a $1 million “gold card” visa and a massive new ballroom where the East Wing used to be, to accepting a $400 jet from the Qatari government and a newly invented “peace prize” from FIFA that involved a trophy—an “oddly gruesome” object according to The New Yorker, but a shiny one, too. 2. The Wirkin Bag Walmart doesn’t usually find itself in the same conversation as luxury brands. But the discount behemoth’s $78 bag that echoed the design of the Hermès’ iconic $10,000-and-up Birkin was dubbed “the Wirkin” on social media. It quickly became a sensation—and an emblem of “dupe” culture, in which lower prices handily The President authenticity. That may threaten the value of some high-end brands, but actual Birkins remain coveted: The original, made for actress Jane Birkin, sold at auction for $10.9 million this year. 3. Starbucks Bearista Tumblers Starbucks’ attempted turnaround journey included rough patches like closing hundreds of locations and laying off employees. But the coffee giant proved it can still generate excitement—maybe more excitement than it wanted. Customers lined up at 3 a.m. to score limited-run, bear-shaped glass tumblers for $30 a pop, and sometimes getting into scuffles when there weren’t enough. But the “Bearista” cups promptly became a meme, even inspiring good-natured copycat tributes from the likes of Aldi and Walmart. Recently, Starbucks has brought the object back (on a limited basis of course) as a prize for members of its rewards program. 4. Vera C. Rubin Observatory Telescope In a year when science seemed under assault, the world’s largest telescope debuted with “jaw-dropping” views of space, including millions of galaxies and thousands of never-before-seen asteroids in our solar system. Decades in the works, the observatory is at the summit of a Chilean mountain, its telescope equipped with the biggest space camera ever built, with an unprecedented three-billion pixel sensor array. The result, from the start, has been stunning images. 5. Inflatable Frog Costumes Video of Seth Todd, a protester outside an ICE facility in Portland, Oregon, being chemical-sprayed by law enforcement went viral, one assumes, largely because he was wearing an inflatable frog costume. The absurdity was, after all, the point. The outfit’s success at making heavy-handed tactics look both bullying and clueless is why inflatable costumes—sharks, chickens, etc.—became a popular form of protest-wear. It’s an example of “tactical frivolity” as a form of resistance that defangs accusations of violent opposition. As one observer put it: It’s hard to be violent in a frog suit. 6. Wicked x Swiffer If you were looking to exemplify dubious movie-product collabs, you would have a hard time dreaming up something to top the special edition pink Wicked Swiffer. The hit Wicked movies, building on the acclaimed Broadway musical, have spawned scores of products and brand collabs, as is standard practice for blockbuster IP. But there’s something about the Swiffer sweeping its way into the spotlight of a witchy story that’s irresistibly ridiculous—picture a witch zooming away on a sponge mop instead of a broom. 7. Oasis Bucket Hat In 2025, one locus of 1990s appreciation was the lucrative reunion tour of millennial-favorite Britpop throwback rockers Oasis, making bucket hats one of the year’s Vogue-approved accessories. The floppy Gilligan-style bucket hat was part of the Gallagher brothers’ style, and apparently still is: Singer Liam clarified from the stage, “it’s a bucket hat,” to anyone mistaking his headgear for a beanie. “You’re just in a sea of bucket hats,” one concertgoer who paid $42 for an Oasis-branded hat told The Wall Street Journal, calling the effect “hilarious.” 8. L.A.B. Putter Golf is not a sport known for sudden change or progressive innovation. All the more remarkable that one of 2025’s most significant golf moments involved a weird-looking club J.J. Spaun used to sink a 64-foot putt that clinched the U.S. Open. Lie Angle Balance putters are designed to minimize torque, positioning the shaft directly into the instrument’s center of gravity, behind the head. This ends up looking like some sort of exotic barbecue tool, but their use has grown steadily on the tour and off, and this year was a breakthrough. Sales of the putter, starting at $400, are expected to triple, and a private equity fund backed by LVMH reportedly bought a majority stake in L.A.B. for $200 million. 9. AI data centers While tech pundits seem to think a desirable AI wearable is imminent (and no, the Friend ragebait ads for a product that scarcely exists don’t count), the most significant manifestation of AI mania are the data centers the technology requires. Microsoft’s Fairwater AI data center in Wisconsin has three main buildings totaling about 1.2 million square feet, its data storage systems five football fields long. Meta’s Louisiana AI campus, announced in 2025, involves over four million square feet of buildings, an industrial district of server halls, power yards, and cooling infrastructure. OpenAI’s Stargate similarly immense data center in Abilene, Texas, in progress, may ultimately require 1.2 gigawatts of power. 10. “Dust”-Free Cheetos and Doritos With skepticism of processed foods becoming a rare point of bipartisan agreement, PepsiCo is among those adding more natural, health-conscious offerings to its lineup. The most startling experiment: versions of Cheetos and Doritos without their signature orange colors—and that weird, messy, but nonetheless iconic, “dust.” The new line, dubbed Simply NKD, isn’t actually any healthier, it just doesn’t scream “industrial foodstuff” anymore. It’s a start? 11. The Button After years of swiping, tapping, and pinching, physical controls have started to show signs of a comeback. The touchscreen era has been particularly evident in auto design—and so is the recent pushback. “The data shows us physical buttons are better,” Mercedes-Benz’s chief software officer declared this year in the course of unveiling a more button-centric design strategy. Hyundai and Volkswagen are making similar moves toward bringing back buttons and knobs. The industry won’t likely swipe left on touch screens altogether, but it’s acknowledging the attraction of physical controls—at least until the robocars take over. 12. Labubu Those toothy, furry creatures hanging from everyone’s handbag weren’t a fever dream. The Labubu is very real, and the biggest collectible craze in recent memory. Created by Hong Kong artist Kasing Lung and sold by Chinese toy company Pop Mart in mystery “blind boxes,” the willfully ugly plush dolls became status symbols after K-pop star Lisa from BLACKPINK was spotted with one late last year. By 2025, celebrities from Rihanna to Kim Kardashian were clipping Labubus to their designer bags, turning the $22 accessory into a very lucrative fad. Pop Mart reported $1.9 billion in revenue for the first half of 2025—up over 200%—with Labubu accounting for a third of sales; an oversized version of the creature even joined the Macy’s Thanksgiving Day Parade. One theory of the Labubu’s appeal: the “blind box” sales strategy as an antidote to an overly algorithmic world. As one marketing professor put it: “It’s fun, it’s uncertain, and it’s social.” At least until the next trend comes along. View the full article

You can now read every article that has ever appeared in The New Yorker—from as early as February 1925—with the click of a button. For the publication’s centennial anniversary, its editorial team has spent months painstakingly scanning, digitizing, and organizing every single issue it’s ever published, or more than half a million individual pages. Each issue is artfully arranged in a chronological display under a purpose-built archive section of the website; but the content has also been incorporated into The New Yorker’s search algorithm so that readers can come across it organically. As the future of magazine journalism remains uncertain, a look back through this carefully archived material demonstrates the importance of preserving print media for the future. Digitizing a century-old archive The process of digitizing The New Yorker’s full catalog actually started back in 2005. That year, explains Nicholas Henriquez, the publication’s director of editorial infrastructure, Random House published The Complete New Yorker, a book that came with DVD-ROMs (now retro tech) containing scanned pages from all the pre-digital issues. Then, in early 2024, Henriquez’s team started to convert those scans into digital text. To start, this meant consulting with The New Yorker library, where the magazine’s physical archives are stored, to re-scan several hundreds of pages that required another pass for a number of reasons—including damage, a poor initial scan, or a corrupted file. “Some of the older issues, from the first five years or so, were basically untouched,” Henriquez says. “I had to use a letter opener to open the pages to scan some of them.” After the team had a complete collection of files, they then began the painstaking process of formatting and styling them for the web. There were the predictable challenges of making old magazine articles work online. Each needed a workable headline, description, and image. Bylines in particular were tricky, Henriquez says, as many early writers would use pseudonyms or humorous one-off pen names—or, in some cases, fail to sign their name at all. “That’s part of the value of having, as The New Yorker does, a team of technologists who are part of the editorial staff: We can build these databases and apps and scripts, and we can also look at something in that database like ‘Ogden de Sade’ and know, okay, that’s Ogden Nash, and it’s funny, and we should figure out a nice way to keep that joke online,” Henriquez says. “There were many instances where our technological approach was informed by this deep understanding of the magazine’s history and its cultural context.” Unearthing a treasure trove of early journalism Over the course of this process, Henriquez unearthed stories that he never could have expected. He came across a short, unsigned book review from 1935 of a memoir by a survivor of a Nazi concentration camp, and says he had to “triple-check that we didn’t have bad data somewhere, because that review was published in March of 1935, just two years after Hitler became chancellor. I didn’t realize those stories were out there that early, much less being translated into English and published in America.” On a lighter note, he also found a piece about going to the Newark airport at the dawn of commercial aviation in 1933, and a 1947 article that’s one of the first examples of TV criticism ever published by The New Yorker. Along the way, he says, he rediscovered what makes magazine writing special. “In a newspaper, most stories have the same framing: ‘This happened,’” Henriquez explains. “But a magazine article can do something different: It can be told in a different tense or in a different way—‘This could happen,’ ‘This happened to this person.’” Examples of this distinct genre of analysis include a 1969 article, a few months before the moon landing, that lays out how it will happen, step-by-step; or a pre-Sputnik piece about American scientists trying to launch the first satellite; or a 1961 feature on the rollout of desegregation, as witnessed by author Katharine T. Kinkead and a group of Black college students driving around Durham, North Carolina. Henriquez says: “These kinds of things, I think, make magazine journalism essential and unique.” View the full article

Review the 16 best SERP tracking tools for monitoring Google + AI search rankings to find which is right for you. View the full article

Google's Danny Sullivan says all of their ranking systems reward content that is made for humans The post Google Says Ranking Systems Reward Content Made For Humans appeared first on Search Engine Journal. View the full article