Thank you to Sabrina Teyssier and Paolo Crosetto for organising the 4th Winter Workshop in Behavioural and Experimental Economics of Food Consumption. https://lnkd.in/eAZQGB38 It was good to hear a range of talks from colleagues across disciplines and career stages, to see the lovely town of Villard-de-Lans, and learn more about the fantastic research environment surrounding the Grenoble Applied Economics Lab (GAEL). Opening Keynote lecture by Jutta Roosen on social media analytics and the study of food choices. Dedicated sessions on randomised controlled trials, sustainability and change, methods, nudges and labels, natural labels, rating and ranking scales, and my closing talk on institutional aspects of behavioural change in climate settings. There are so many interesting areas evolving across measurement, causal inference, welfare evaluations, and broad ethical and institutional design in these areas and the workshop covered all this in a very stimulating and engaging way.

The 2026 NFL Draft isn't considered strong at running back, but Notre Dame Fighting Irish star Jeremiyah Love is widely viewed as a special talent.

A group of vape manufacturers and distributors are asking a California federal judge to throw out consumers' claims in antitrust multidistrict litigation, saying the allegations fail to establish either standing or the existence of a price-fixing conspiracy.

The Hall of Fame coach did not hold back when addressing the governing body's repeated failures in court, as players across the country continue seeking injunctions in state courts to bypass NCAA rulings.

Join Professor Katherine A. S. Sibley of Saint Joseph#39;s University to discuss First Lady Michelle Obama. We#39;ll explore the former First Lady#39;s early life, continuing work as a lawyer and an activist, her legacy in the White House, and the ever-evolving role of the office of First Lady within American politics. 03/13/26, 3:00 P.M. - Wynnefield Library

Discipline is strength.Continue reading on Medium »

Total worldwide shipments and digital sales for NieR: Automata have exceeded 10 million units, Square … Source

If you‘re familiar with the world of SEO, I probably don’t have to tell you there's been a serious shift in its landscape. Marketers are no longer just optimizing content for Google‘s traditional blue links; we’re now optimizing for AI. The shift is called Answer Engine Optimization, or AEO. Some practitioners also refer to it as AI engine optimization, and both terms are used interchangeably. But what does it mean to optimize your content for AI engines? I'll explain. Table of Contents What is answer engine optimization? AEO versus SEO AEO versus GEO Which Answer Engines Should You Optimize For? How to Build an AEO Plan That Works How to Measure and Report on AEO Success Frequently Asked Questions What is answer engine optimization? AEO is the practice of optimizing your content so that AI systems cite you as a source and feature your information in direct answers. AEO helps content show up in ChatGPT responses, Google's AI Overviews, voice assistant answers, and essentially anywhere an AI is serving information instead of just links. But AEO isn't here to replace your SEO program. In fact, think of them as business partners. Traditional SEO focuses on achieving high rankings in search engine results. AEO focuses on being the answer that AI systems pull from and cite. The goal shifts from “get people to click to your site” to “become the authoritative source AI systems trust and reference.” So, where does AEO actually appear? Pretty much anywhere AI is answering questions: LLM chat interfaces like ChatGPT, Claude, or Gemini — where users are having full conversations instead of searching AI Overviews in Google Search — those AI-generated summaries that appear at the top of search results Voice assistants like Siri, Alexa, or Google Assistant — which need concise, accurate information to speak back to users You‘ll find that a lot of what makes good SEO also makes good AEO, such as clear, well-structured content that answers real questions. The difference is that to use AEO, you’ll also have to think about how AI systems consume, understand, and cite information, meaning some new considerations come into play. AEO versus SEO If AEO isn't replacing SEO, what does it actually add to your workflow? Let me break down the practical differences. Entity Clarity Matters More Than Ever With traditional SEO, you optimize for keywords. With AEO, you're also optimizing for entities, such as the people, places, things, and concepts that AI systems need to understand. This means being crystal clear about who you are, what you do, and how you connect to other entities in your space. If you're a SaaS company, AI needs to know you exist and how you relate to your industry, competitors, and the problems you solve. The clearer you are, the more confidently AI can cite you. Question-and-Answer Content Becomes Your Best Friend AI systems prefer content that directly answers questions, as that's their primary purpose. This doesn't mean every blog post needs to be an FAQ (please, no), but it does mean structuring content around the questions your audience is actually asking. You want fewer posts like “10 Tips for Better Email Marketing” and more posts like “How Do I Improve My Email Open Rates?” with a clear, concise answer up front. Schema Markup Gets an Upgrade Schema helps AI systems understand the structure and meaning of your content. Things like FAQ schema, How-To schema, and Article schema provide AI with clear signals about the information you‘re providing and how it’s organized. Model Coverage vs. Search Coverage With SEO, you‘re thinking about search volume and keyword difficulty. With AEO, you’re also considering model coverage. You may wonder if you are appearing when someone asks ChatGPT or Claude about your topic. Are you cited in AI Overviews? AEO requires a slightly different content strategy where you're not just targeting high-volume keywords, but also the kinds of questions people ask conversationally to AI systems. These questions are often longer, more specific, and more natural-sounding than traditional search queries. The Zero-Click Reality AI gives users the answer directly, which means they may never visit your site. Is that frustrating? Sure. But it‘s also reality. The upside? When AI cites you, you’re building brand authority and trust. People start to recognize your name as a credible source, even if they didn't click through this time. Think of it as the long game. How Your Content Workflow Actually Evolves So, what does this mean for your content team on a day-to-day basis? The good news is that you don‘t have to overhaul your entire operation. AEO layers onto what you’re already doing, but it does require some intentional shifts. Start With Your Content Clusters (Yes, Really) Before you dive into AEO tactics, make sure your foundational SEO structure is solid. Build out your topic clusters, establish your pillar content, and create a clear content architecture. AI systems crawl and understand content the same way search engines do. So, if your site structure is a mess, AEO won't save you. Get your house in order first. Then optimize for AI. Layer in Question Mapping Once your clusters are built, map out the questions your audience asks at each stage of their journey. Not just “what keywords should we rank for,” but “what would someone type into ChatGPT about this topic?” This is where you start creating content specifically designed to be cited, in the form of clear, direct answers, credible sources, and well-structured information—the stuff AI systems love to pull from. Add Schema and Entity Work After your content and questions are in place, tackle schema markup and entity optimization. This is the technical layer that helps AI systems understand and cite your content more effectively. Mark up your FAQs. Add How-To schema to your tutorials. Use the Article schema on your blog posts. Make it as easy as possible for AI to parse and reference your information. The Priority Framework If you‘re juggling ongoing SEO, content production, and now AEO on top of it all, here’s a simple prioritization framework: Nail your core SEO first — content clusters, site structure, keyword targeting Map questions and create answer-focused content — especially for topics where AI is already answering questions Add schema and entity optimization — the technical polish that makes your content more citable Think of it like building a house. You wouldn‘t install smart home tech before you’ve framed the walls. The same logic applies here. Build your foundation first, then the AI-friendly upgrades. And look, I get it. Adding AEO to your already packed content calendar can feel overwhelming. However, the reality is that if AI systems are answering questions in your space and you're not being cited, you're missing out on visibility and authority. Better to start small and layer it in than to ignore it completely. AEO versus GEO Generative Engine Optimization (GEO) may sound like another term for AEO, but there are key differences. GEO specifically refers to optimizing for generative AI systems. Think ChatGPT, Claude, Gemini, and other large language models that generate responses based on prompts. GEO is all about getting these AI systems to cite your content when they're creating answers from scratch. AEO is the broader umbrella term. It covers optimization for any AI-powered system that surfaces answers, including generative AI, as well as AI Overviews in search, voice assistants, and other AI-augmented platforms. In other words, GEO is a subset of AEO. All GEO is AEO, but not all AEO is GEO. Think of it like this: If someone asks ChatGPT for marketing advice and it cites your blog post, that‘s GEO in action. If someone asks Google a question and your content shows up in an AI Overview, that’s AEO (but not necessarily GEO, since it's search-adjacent). If Alexa reads your recipe instructions out loud, that's also AEO. They all share the same core goal: getting AI systems to pull from and cite your content as a trusted source. Why the Distinction Matters (Sort of) Honestly? For most content teams, the distinction between AEO and GEO is more academic than practical. Yes, there are researchers publishing papers specifically on “generative engine optimization” and studying how to rank in LLM outputs. And yes, some practitioners use GEO when discussing ChatGPT or Claude specifically. But here‘s the thing: the tactics that make you cite-able in one AI system generally make you cite-able in others. You’re not going to optimize differently for ChatGPT versus Google's AI Overviews versus Alexa. The underlying principles are the same. So, while I‘ll use "AEO" as the catch-all term throughout this post, please note that when we’re discussing showing up in ChatGPT or other generative models, that's the GEO piece of the puzzle. One Content Architecture to Rule Them All Here‘s the best part: you don’t need separate strategies for AEO and GEO. The same content architecture that helps you show up in AI Overviews also helps you get cited by ChatGPT. Q&A Blocks Work Everywhere Whether it‘s a generative AI model or Google’s AI Overview pulling your content, both love clearly structured question-and-answer formats. When you write a section that starts with “What is email marketing?” and follows with a direct, concise answer, you‘re making it easy for any AI system to extract and cite that information. The AI doesn’t care whether it's serving that answer in a chat interface or a search result. AI just needs the information to be clear and well-structured. Schema Speaks a Universal Language FAQ schema, How-To schema, and Article schema are all structured data formats that help AI systems better understand your content. Google‘s AI uses schema to parse your content for AI Overviews. Generative models trained on web data can better understand and reference marked-up content properly. Voice assistants rely on schema to pull accurate information. It’s the same markup, serving multiple AI applications. You implement it once, and it works across the board. Entity Clarity Benefits Everyone When you clearly establish who you are, what you do, and how you connect to other entities in your space, every AI system benefits. Generative models need entity clarity to confidently cite you. Search engines need it to include you in AI Overviews. Voice assistants need it to provide accurate answers. The work you do to strengthen your entity signals — clean NAP data, consistent branding, clear about pages, authoritative backlinks — pays dividends across every AI platform. The Bottom Line Don‘t overthink the AEO vs. GEO distinction. Build content that’s clear, well-structured, and easy for AI to understand, and you'll show up across the entire ecosystem of AI-powered answer engines. One solid content architecture. Multiple AI systems. Maximum coverage. That's the sweet spot. Which Answer Engines Should You Optimize For? Okay, so you're sold on AEO. Now comes the practical question: which AI systems should you actually be optimizing for? The good news? You don't need to pick just one. The better news? A lot of the optimization work overlaps. But it does help to understand what each major answer engine tends to favor so you can prioritize your efforts. Let‘s break down the big players and what they’re looking for. Google AI Overviews (Gemini) What It Is: Those AI-generated summaries that appear at the top of Google search results, powered by Google's Gemini model. What It Favors: AI Overviews tend to pull from pages that already rank well organically, which are typically in the top 20 results. Google prioritizes authoritative, well-structured content with clear answers. If you‘re not showing up in traditional search, you’re likely not appearing in AI Overviews either. Quick Checklist: Ensure your target pages rank in the top 20 for relevant queries Use clear headers and concise answers that can be easily extracted Implement schema markup (especially FAQ and How-To schema) Bing Copilot What It Is: Microsoft's AI assistant built into Bing, Edge, and Windows, powered by GPT-4. What It Favors: Copilot tends to handle navigational and transactional queries well. It pulls from Bing's search index and favors content that clearly states what a product or service does, includes pricing or comparison information, and has strong brand signals. Quick Checklist: Optimize for navigational and product-focused queries in your space Include clear product descriptions, features, and pricing where relevant Ensure your brand entity is well-established (consistent NAP, strong backlinks) ChatGPT Search (OpenAI) What It Is: ChatGPT's newer search functionality that browses the web in real-time and cites sources in conversational responses. What It Favors: ChatGPT Search looks for credible, authoritative sources with clear entity signals. It tends to cite content that directly answers questions, comes from recognizable brands or domains, and includes proper attribution (citing other sources strengthens your own credibility). Quick Checklist: Build strong entity alignment with clear about pages, author bios, consistent branding Create content with direct, quotable answers to common questions Cite your own sources; showing you reference credible information builds trust Perplexity What It Is: An AI-powered search engine that provides synthesized answers with inline citations, kind of like a research assistant. What It Favors: Perplexity loves well-researched, comprehensive content that brings together multiple perspectives. It frequently cites academic sources, data-driven content, and articles that themselves include citations and sources. If your content looks like it was written by someone who did their homework, Perplexity is more likely to cite it. Quick Checklist: Write well-researched, data-backed content (include stats, studies, examples) Use inline citations and link to credible sources within your content Structure information in clear, scannable sections with subheadings You probably don‘t have the bandwidth to create completely different content strategies for each answer engine. And honestly, you don’t need to. The overlap is significant. Clear, well-structured, authoritative content that answers real questions? That works everywhere. Strong entity signals? Helpful across the board. Schema markup? Universal. So start with the fundamentals that benefit all engines, then layer in specific optimizations based on where your audience is actually looking for answers. If you‘re a B2B SaaS company, maybe you prioritize ChatGPT and Bing Copilot. If you’re in health and wellness, Google AI Overviews and Perplexity might be your focus. Meet your audience where they are, and optimize accordingly. How to Build an AEO Plan That Works Alright, enough theory. Let's talk about how to actually do this inside your content team. Adding AEO to your workflow takes some upfront effort, but the good news is you don't need to overhaul everything overnight. You can start small, test what works, and scale from there. Here‘s a step-by-step plan you can actually run with your team, from discovery to publishing to measuring what’s working. Step 1: Audit Where You Already Show Up (Or Don't) Before you create new content, figure out where you currently stand with AI systems. Start by testing queries related to your business in different answer engines. Ask ChatGPT questions your customers would ask. Search relevant topics in Google and see if AI Overviews appear. Try the same queries in Perplexity and Bing Copilot. Are you being cited? Are competitors showing up instead? Are AI systems pulling from outdated or inaccurate sources? This audit gives you a baseline and helps you identify quick wins, like topics where you have great content but aren‘t getting cited, or gaps where AI is answering questions and you’re nowhere to be found. Action Items: Create a list of 10-20 core questions your audience asks Test each question across Google AI Overviews, ChatGPT, Perplexity, and Bing Copilot Document which answer engines cite you (or don‘t) and what sources they’re pulling from instead Identify patterns. Ask: Are certain topics getting more AI coverage? Are competitors dominating specific question types?

A sports betting preview of the Scottish League game between Dunfermline Ath vs Partick Thistle written by ArmchairPunter

The West Allis clinic operated by Rogers Behavioral Health is one of two in Wisconsin where employees are seeking union representation. (Rogers Behavioral Health media photo) Staff members at two Wisconsin mental health clinics are seeking union representation after what some employees describe as policy changes that have increased client caseloads and reduced one-on-one care for clients. The clinics — one in Madison and one in West Allis — are owned by Wisconsin-based Rogers Behavioral Health. The Oconomowoc-based nonprofit organization operates a network of mental health hospitals, residential treatment clinics and outpatient clinics in 10 states. Starting Monday, officials with the National Labor Relations Board will hold a hearing in Milwaukee to set union election dates for 63 employees in West Allis and 35 in Madison. The hearing is expected to take up to three days, according to documents filed with the NLRB by a lawyer representing Rogers. The case will entail “extensive testimonial and documentary evidence” about which employees at each location should be included in the vote, the attorney stated in a motion to schedule the hearing and reserve the dates. Workers at the West Allis and Madison locations want to join the National Union of Healthcare Workers. The California-based NUHW already represents Rogers employees at three locations in California as well as one in Pennsylvania. Three employees at the West Allis clinic have been fired, according to the union, which has filed an unfair labor practice charge with the NLRB. The union is accusing Rogers of violating federal labor law by retaliating against the terminated health professionals for supporting the union. The Wisconsin Examiner sent email messages to Rogers Friday morning, Feb. 20, seeking comment about the union drive, and at the invitation of the organization’s communications office sent five questions Friday afternoon. Rogers has not responded; this report will be updated with comments Rogers supplies. Clinic employees cite increased caseloads Employees involved in the union drive said in interviews that they and their colleagues enjoyed their jobs and caring for their patients. But recent changes, they said, have made their work more difficult and didn’t benefit patients. “When I first started, people were pretty happy and satisfied with their roles,” said T’Anna Holst, a therapist who works at the West Allis clinic. “As time goes on, caseloads kept increasing for therapists.” Other program changes reduced patients’ ability to have individual time with their clinicians, which “was really unfortunate for us, but also for the patients, who were expecting that when they come to our program,” Holst said. “All of the changes were about increasing the number of patients that were coming into the building,” said Stephanie Lohman, a nurse practitioner. “It did not seem to have a cohesive plan and no plan would be communicated.” Lohman said she is one of the three employees fired from the West Allis clinic, and that her termination came the Monday after she and nearly a dozen other coworkers had presented a petition seeking union recognition. When she directly asked the upper level executive who fired her, she said, she was explicitly told she was being dismissed “without cause.” “Our local leaders, including my direct boss, were not aware this was happening,” Lohman said, adding that she was not given time to prepare notes in order to transfer coverage for the patients in her care. Patient advocacy At the Madison clinic, Erin Quinlan is a behavioral specialist whose job includes assisting therapists and helping to conduct group therapy sessions. “The people that I work with are incredible,” Quinlan said. “They care very, very deeply about the work that they do and having a positive impact on the lives of patients.” After she was hired in July 2024, “Caseloads increased and individual time with patients was decreasing,” Quinlan said. “I just became concerned about how that was impacting our being able to support those patients.” Coworkers shared those concerns, she said. Employees said they were left with the impression that the changes that concerned them were coming from higher up in the organization’s hierarchy, not their local managers. Lohman said that in measuring staff productivity, the organization moved to relying on “metrics like visits per day.” That replaced a system that took into account that some patients needed more time than others, she said. Increased caseloads were presented as ways to increase the number of patients being served, Lohman said, but instead, employees were working “to their maximum capacity, ignoring actual patient or worker needs.” At the clinic level, “Rogers is run by caring professionals,” she said. “Despite the corporate push to do metric care, patient-centered care continues to be done.” All three employees said they and their coworkers believed forming a union and being able to bargain collectively would give them a stronger voice as advocates for their patients. “I take being an advocate and speaking up as a very important part of my job,” Quinlan said. She added that she routinely sought to raise concerns with “anyone who would listen, including management.” She said she got no response, however. “It was because I didn’t really see any return communication, that was when I made the decision to go to the union,” Quinlan said. Both the Madison and West Allis groups initially petitioned for Rogers to voluntarily recognize the union, citing large majorities of supporters. The organization rejected those requests, and union supporters then sent petitions for elections to the NLRB. Union represents other Rogers workers The NUHW grew out of a California health care union that was founded in the 1930s and subsequently joined what would later become the Service Employees International Union. After an acrimonious split from SEIU in 2009, the National Union of Healthcare Workers formed as an independent union. An unsigned memo from the organization urging employees to vote against the union was briefly posted at the Madison clinic in the days after members petitioned for union representation Jan. 23. The Wisconsin Examiner obtained a photograph of the memo, which employees said was later taken down. The memo describes the union as having “no experience or connection in Wisconsin.” It does not state that Rogers employees in four other U.S. clinics are now represented by the union. Employees at a Rogers mental health and addiction services clinic in Walnut Creek, California, voted for the union to represent them in 2023 and settled a first contract in 2024. “It’s an excellent contract,” said NUHW’s communications director, Matt Artz, and included “substantial salary increases and caseload limits,” according to the union’s website. After employees at Rogers clinics in Los Angeles and San Diego petitioned for union representation, the union was recognized voluntarily at those locations, which then negotiated contracts similar to the agreement at Walnut Creek, Artz said. In December 2025, a Rogers clinic in Philadelphia also voluntarily recognized the union after being petitioned by employees there. Employees at the Madison clinic operated by Rogers Behavioral Health are seeking union representation. (Rogers Behavioral Health media photo) Employees at two Wisconsin mental health clinics seek union representation was originally published by Wisconsin Examiner.

Like your weird uncle, nobody knows exactly how AI engines choose the sources they cite. But experiments are starting to point to ways you can get on their radar. And as consumers increasingly turn to AI search for product and service recommendations, you really want to be on their radar. (Ironically, unlike your weird uncle, who you try to avoid.) Today, I’ve got one such experiment that contributed to a 642% increase in citations by AI tools like ChatGPT. And to the delight of you word nerds, it’s all about semantics. But first, everyone’s favorite part: The disclaimer! The sum vs. the parts Before you go any further, it’s important to know that this tactic is just one piece of a wider playbook our Growth team lovingly calls the “everything bagel strategy.” “Our experimentation hasn’t [shown that] this one tactic is the key to better AI visibility,” says Amanda Sellers, HubSpot’s head of EN blog strategy. “What we’ve found is that the sum of the parts is what’s good for AI visibility.” But if I covered all of those parts at once, this would be a novel, not a newsletter — so think of this more like part 1. A little why behind the AI “A human might be able to tell you what the sentence ‘Paris is cool’ means,” Sellers says. “But an AI engine without [immediate] context wouldn’t know if we’re talking about Paris, France, or Paris Hilton.” AI tools can sound very human, but the way they understand language is very different from us. Keeping with Sellers’ example about Paris, before reading, you would know from the start whether an article you clicked on was about travel tips or one about celebrity gossip. That context would be all you needed to understand the word “Paris.” AI models need a little more handholding. One way to coddle their cold, metallic hands is with a framework called “semantic triples.” As simply as I can explain it: Semantic triples are a writing pattern that creates context using the sequence subject – predicate – object. If you also pushed third-grade English out of your brain to make room for Lord of the Rings trivia, here’s a very quick recap of what those mean: Subject: Who or what a sentence is about. Predicate: Information about (or the action of) the subject. Object: The noun or pronoun that receives that action. A real-world marketing example might look like: “HubSpot (subject) can automate (predicate) email marketing (object).” With only one sentence, I’m able to quickly guide a bot to connect HubSpot with email automation. Why does that matter? “We want HubSpot to be associated with ‘marketing automation,’ so that when someone asks ChatGPT, ‘What’s the best marketing automation platform?’ we’re mentioned in that conversation.” Semantics in action During the experiment, Sellers’ team took key information on pages that they wanted AI models to understand, and rewrote it from paragraph format into a bulleted list of semantic triples. Below is a snapshot from Sellers’ recent INBOUND presentation that highlights what that content looked like before and after the changes. Image Source In conjunction with the other “everything bagel” ingredients (like schema, backlinks, etc.), this tactic helped to increase mentions of HubSpot in AI answers by 58%, and the number of times HubSpot pages were cited by AI by 642%. Now, to some of you, this may just sound like very basic good SEO, and you’re not wrong. “It’s very important to have a stable SEO foundation to have good LLM visibility. But while semantic triples are beneficial for SEO, they’re necessary for AEO.” To others, this may sound like really annoying content for a human to read. And you’re not entirely wrong either. Done poorly, semantic triples can read like the overoptimized garbage that dominated early SEO. Luckily, Sellers offered up some practical tips on how to effectively use semantic triples without effectively alienating your audience. Triple Tips 1. A little goes a long way. “We need to find the happy medium between having the content be easily understood [by AI],” and having content that’s still enjoyable for humans to read. With a laugh, Sellers advises using the benchmark, “Would reading this as a human make me throw my phone in the pool?” Instead of cramming semantic triples all over the page, she suggests tossing in one triple for each core concept along the way. 2. Target humans and bots with the same content. You might think you could get around the need for the first tip by simply writing separate content for AI engines and for your human audience. Sellers advises against this. If AI or search engine crawlers discover your human-focused content, they may decide to penalize both pieces of content for being overly similar. But worse is what happens when your human readers stumble over your bot content. A reputation for crappy content is hard to shake. “We’re really trying to do a feed-two-birds-with-one-scone approach, because we have a massive readership that actually cares about what we write.” 3. Use answer-first phrasing. Both humans and bots like to skim, and your content, however amazing, isn’t the exception. Your job is to make sure they can quickly get key information while skimming. To that end, Sellers recommends using answer-first phrasing. So instead of a sentence like “According to recent research, pizza is delicious,” you might rewrite it as, “Pizza is delicious, according to recent research.” A warning: Both human and software editors absolutely hate this. Do it anyway. This is a structure I absolutely insisted on when I was leading the HubSpot Blog’s user acquisition program. 4. Don’t bury the lede. Similar to putting key info at the front of a sentence, you also want to make sure your semantic triples appear early within paragraphs. Again, this makes it easy for human skimmers to quickly get the information they’re looking for. But for bots, it’s even more important, because they often take chunks of content out of context. “Writers need to be conscientious about the order of sentences, so that if an LLM came and took this one paragraph, it’s enough to represent the idea.” 4. Think about mid-funnel and bottom-of-funnel content. Product reviews, product comparisons, and listicles are all great places to employ semantic triples. Readers expect this kind of content to be simple and blunt, so semantic triples don’t feel out of place. It’s also a natural opportunity to connect your brand to a product category, to certain features, or even… to your competitors. “You want your entity to be associated with similar entities. So, for example, we want HubSpot associated with Salesforce or MailChimp. That way, any time an AI engine mentions a competitor, it would be remiss to not also mention us in the same breath.” How to check your AI visibility using AEO Grader If you’re not sure where you stand in the eyes of the answer engines, it’s super easy to find out using HubSpot’s free AEO grader. I sat down to write a How-To for you, and realized it’s so easy it would almost be insulting. Just plug in four simple answers, and you’ll get ranked in areas like brand recognition, sentiment, and share of voice for the three most common AI search tools. You then have the option of providing your email address to get a detailed report of insights and recommendations.

MONDAY, Feb. 23, 2026 — Side effects like nausea or vomiting are common among folks taking Ozempic/Wegovy, but they’ll grin and bear it if they think they’re losing weight, a new study finds. The drugs’ perceived...

A sports betting preview of the English Non-League game between Halifax vs Rochdale written by ArmchairPunter

Great to continue our series of LSE/Warwick PhD Behavioural Science events this week. Twice-annual event bringing together PhD students and faculty in behavioural science working in Warwick and LSE. Having rich spaces between internal presentations and full international conferences is important for research development. Looking forward to continuing to developing this with PhD researchers and staff over the next few years. Thanks in particular to our PhD manager at LSE Karine Gay for organising this one and all presenters and faculty attendees.

Arc System Works has released an 11-minute behind the scenes video for action game DAMON … Source

Garrett Podell joins CBS Sports HQ to discuss 5 moves the Dallas Cowboys need to make this offseason.(0:00) Intro(1:00) 1. Free up $100M in cap space(2:15) 2. Re-sign George Pickens(3:28) 3. Bring in defensive free agents(4:23) 4. Re-sign Jadeveon Clowney(5:24) 5. Re-sign Brandon AubreySUBSCRIBE TO OUR CHANNEL:https://www.youtube.com/user/CBSSportsWATCHCBS Sports HQ: https://www.cbssports.com/live/Paramount Plus: https://www.paramountplus.com FOLLOW US ON:Facebook - https://www.facebook.com/CBSSports/Instagram - https://www.instagram.com/cbssports/Twitter - https://twitter.com/CBSSports#nfl #cowboys #nfloffseason #nflfreeagency #dallascowboys

Selecting an email marketing automation platform goes far beyond choosing where marketers will send emails. The right tool becomes the backbone of lifecycle marketing — powering personalized workflows and driving revenue. Email marketing automation platforms help businesses send targeted, personalized emails at scale by automating workflows, segmenting audiences, and integrating with CRM and ecommerce tools. Today’s marketing teams need platforms that offer predictive analytics, journey-based targeting, drag-and-drop journey builders and behavioral triggers, unified customer data for accurate segmentation, AI-powered content and optimization features, strong deliverability and compliance safeguards, and transparent pricing and easy migration support. They also need software that’s durable enough to support long-term growth. To choose the best fit, map your needs by team size, use case, and required integrations. In this guide, learn how to evaluate email automation tools, where AI fits in, and how the top email marketing automation platforms stack up. Table of Contents What is an email marketing automation platform? How to Choose the Right Email Marketing Automation Tool Top Email Marketing Automation Software How to Use AI With Email Automation Tools Best-fit Picks by Use Case and Team Size Frequently Asked Questions About Email Marketing Automation Platforms What is an email marketing automation platform? Email marketing automation platforms automate sending targeted, personalized emails based on user behavior and customer data. These tools help teams: Trigger emails when users take specific actions (like viewing a page or abandoning a cart). Build automated customer journeys with branching logic. Segment audiences using unified behavioral, demographic, and transactional data. Personalize content at scale with tokens, rules, and AI-driven recommendations. Report on engagement, conversions, revenue, and lifecycle performance. Unlike traditional email marketing software, which focuses on manual list sends, automation platforms like HubSpot’s email marketing software deliver continuous, context-aware communication powered by workflows and integrations. How to Choose the Right Email Marketing Automation Tool The right email automation tool depends on factors like revenue goals, team capacity, existing tech stack, and compliance requirements. Personally, as a fractional content strategist, I appreciate an email marketing tool that fits within my clients’ budgets and offers stress-free onboarding. But because every marketing team is different, here’s how to evaluate the best options on the market. Be sure to follow these best practices to avoid automation mistakes. 1. Start with your business goals. Ask: What outcomes must this tool drive? Common goals for using an email marketing automation tool include: Lead nurturing. Ecommerce recovery. Strengthening retention programs. Sending lifecycle emails. Partner marketing. Automated onboarding. Pro tip: Look for platforms that support these use cases with pre-built workflow templates, strong segmentation, and native integrations. 2. Evaluate your team’s workflow and capacity. Some email marketing services require specialists. Others are designed for lean teams who need AI assistance, intuitive drag-and-drop builders, and fast implementation. If the goal is to ship campaigns regularly, prioritize platforms with: Native AI writing and optimization. Easy-to-use journey builders. Clear reporting and troubleshooting. Pro tip: Migration to a new platform requires asset inventory, data export/import, domain authentication, and deliverability monitoring. Ensure your team has enough hands on deck to support migration efforts. 3. Map your tech stack and data sources. CRM integration enables unified customer profiles and accurate segmentation. For a non-technical marketer, integrations — such as those with the CRM — provide easy access to the data sources that make email marketing effective. Common integrations for email marketing platforms include pairing with: CRMs. Ecommerce systems, including Shopify, WooCommerce, or custom catalogs. Ads and social tools. Customer support systems. Product usage or event tracking platforms. Pro tip: CRM-native platforms like HubSpot’s email marketing software offer the strongest advantage. They eliminate data syncing issues and reduce tool fatigue, making it easier to maintain an email marketing strategy. 4. Prioritize compliance and deliverability safeguards. If an email lands in the spam box, the chances that the recipient reads it dramatically decrease. Deliverability is a deal-breaker, and the right email marketing automation tool can get an email through spam filters. Look for tools with: Automatic DKIM/SPF/DMARC prompts. Built-in permission management. Bounce handling. Spam testing. Dedicated IP options. Real-time health monitoring. Pro tip: Verifying and authenticating an inbox takes time and can be tricky. The best email marketing automation tools offer guides and one-to-one personalized setup to help guide marketers through authentication and onboarding. 5. Understand total cost of ownership. Transparent pricing models help users avoid hidden costs and plan budgets. However, pricing varies widely across the market and may increase as features become more in-depth. Consider: Contact-based plans. Send limits. Feature add-ons. Required support tiers. Migration costs. Deliverability add-ons (e.g., dedicated IPs). Pro tip: Transparent, all-in-one pricing prevents surprises as an audience grows. Choose an email automation tool with clear pricing for specific outcomes. Top Email Marketing Automation Software Marketers can choose from many email automation tools, but only a select few are worth the investment. Below are six top platforms, evaluated on features, usability, extensibility, and total cost of ownership. 1. HubSpot Marketing Hub + AI Email Writer Source HubSpot is an all-in-one marketing automation platform built on a unified CRM, which means every email, workflow, and personalization rule is powered by a single, consistent customer record. Instead of stitching together disconnected data sources, teams can build segmentation, triggers, and reporting directly from the CRM. What differentiates HubSpot is how quickly teams can get up and running. The email editor, automation builder, asset manager, and reporting tools all share a common interface. Deliverability safeguards, domain authentication prompts, and permission settings are built directly into the onboarding process, reducing the risk of mistakes that harm performance. HubSpot’s AI Email Writer, included with Marketing Hub, is a powerful addition for lean teams. The AI Email writer helps marketers: Generate net-new campaigns. Rewrites underperforming content. Adapts copy to different tones or segments. Run instant variations for testing. Because the AI is connected to the CRM, it can reference lifecycle stages, product data, or behavioral properties to create more personalized messaging. For teams that want powerful automation without the complexity of enterprise systems, HubSpot offers both sophistication and speed in a single platform. Key Features: Drag-and-drop email builder. AI Email Writer for campaign creation and optimization. Behavioral, transactional, and demographic segmentation via CRM. Workflow automation with branching logic. Personalization tokens from any CRM property. A/B testing and multivariate optimization. Transactional email (with add-on). Revenue and lifecycle reporting. Automatic deliverability setup guidance. Pricing: HubSpot Email Marketing is included in Marketing Hub plans, with a free tier available. Starter is $9 per seat/month, Professional $800/month, and Enterprise is $3,600/month. Paid plans offer automation, advanced segmentation, collaboration tools, and AI-powered features. What I like: HubSpot’s automation is CRM-native, meaning every workflow, trigger, and personalization token is powered by a unified data source. That means no syncing required. It’s also one of the fastest tools to adopt for teams that need to scale quickly without a complex setup. How to use AI to Write an Email with HubSpot 2. Mailchimp Mailchimp remains one of the most recognized tools for small to mid-size teams. It offers strong templates, ecommerce-focused journeys, and beginner-friendly automation features. Key Features: Drag-and-drop builder. Pre-built ecommerce automations. Basic journey builder. AI subject line options. Audience segmentation. Reporting dashboards. Pricing: Free tier available. Paid plans scale with contact count and feature depth. What I like: Mailchimp is easy to start with and offers strong templates for ecommerce brands, though teams often outgrow it as their data needs become more complex. 3. Klaviyo Klaviyo specializes in ecommerce automation with deep Shopify and WooCommerce integrations. It uses real-time product and behavioral data to fuel hyper-personalized journeys. Key Features: Strong ecommerce data sync. Dynamic product recommendations. SMS + email automation. Predictive AI: churn, next order date, lifetime value. Advanced segmentation. Pricing: Usage-based pricing. Pricing scales with email + SMS volume. What I like: Klaviyo is excellent for ecommerce brands needing granular, SKU-level personalization and predictive analytics. 4. ActiveCampaign ActiveCampaign blends email automation with lightweight CRM functionality, making it popular for mid-sized B2B teams needing robust workflows. Key Features: Advanced automation builder. Lead scoring. Conditional content. Basic CRM pipelines. Event + site tracking. Split automation paths. Pricing: Tiered plans are available: Starter starts at $15/month, Plus at $49/month, Pro at $79/month, and Enterprise at $145/month. ActiveCampaign offers automation at higher tiers. What I like: Its workflow builder is one of the most flexible on the market. It’s great for teams that rely on complex, multi-branch automation sequences. 5. Brevo Brevo offers accessible pricing and a combined messaging suite, including SMS and WhatsApp alongside email. Key Features: Email + SMS + WhatsApp automation. Transactional email via API. Basic segmentation. Drag-and-drop builder. Send-time optimization. Pricing: Free tier with send limits. Paid plans are based on monthly email volume. What I like: Brevo is a cost-effective option for lean teams or early-stage companies needing cross-channel messaging. 6. Customer.io Customer.io is built for product-led companies and developers who want maximum flexibility in workflow logic and event-triggered automation. Key Features: Real-time event tracking. Advanced workflow builder. Liquid templating. API-triggered campaigns. Mobile push + in-app messaging. Data pipelines. Pricing: Core plans are available at $100/month, $1,000/month, or custom pricing. However, advanced features and data tools are priced separately. What I like: Customer.io’s event-based automation is very powerful for SaaS companies needing usage-based lifecycle emails. Platform Best For Standout Features Pricing Model HubSpot Teams needing unified CRM + automation AI Email Writer, CRM-native workflows, advanced segmentation, reporting Free tier + tiered plans Mailchimp Small teams, quick campaigns Templates, simple journeys Contact-based Klaviyo Ecommerce brands Product recommendations, predictive AI Usage-based ActiveCampaign B2B automation depth

In a past work life, I stole search rank positions #1 and zero and even featured snippets from much larger companies, including HubSpot. That’s why I firmly believe bootstrapped small-to-medium-sized businesses (SMB) can compete with big-budget corporations. Strategies like SEO, social media, and generative engine optimization for small business make it possible. I know what you’re thinking, “GEO for small business? Not another thing to add to my plate." But generative engine optimization (GEO) doesn’t actually mean a complete overhaul of your marketing. It‘s an evolution of what you’re likely already doing with SEO — just adapted for a world where AI referral traffic to SMB websites increased by 123% in just a matter of months. GEO doesn't demand more time; it demands smarter use of the time you already have. This guide will show you exactly how, without draining your budget or hiring a specialized team. Table of Contents TLDR What is generative engine optimization for small business? Why Generative Engine Optimization Matters Now for Small Businesses How to Do Generative Engine Optimization for Small Business Generative engine optimization best practices for small business Generative engine optimization for local content Recommended generative engine optimization software on a budget FAQs about Generative Engine Optimization for Small Business Do small businesses need GEO? TLDR Generative engine optimization (GEO) helps small businesses get cited in AI-generated answers from ChatGPT, Perplexity, and Google's Gemini without requiring big budgets or new skills. If a small business is already doing well with SEO, leaning into schema markup, optimizing their Google Business Profile, creating FAQ pages, encouraging customer reviews, and ensuring name, address, and phone number (NAP) consistency across their web presence will set them up for GEO success. Most can start with free tools and see results within 4-8 weeks, with local businesses having a particular advantage since they can dominate geographic-specific queries more easily than national competitors. HubSpot Marketing Hub has several free tools to help you structure, publish, and optimize your content in your GEO efforts, while our free AI search grader can help you audit how you’re currently doing. What is generative engine optimization for small business? Generative engine optimization (GEO) for small business is the practice of making your content easy for AI-powered search tools to find, understand, and cite when generating answers to user questions. Here‘s how it works in plain English: When someone asks a generative engine (like ChatGPT, Perplexity, or Google’s Gemini) a question, these AI systems scan the web to gather information. Instead of showing a list of links (like traditional search), they create a synthesized answer and cite sources they consider reliable and authoritative. GEO ensures your small business becomes one of those cited sources. GEO vs. SEO: What SMBs Need to Know Traditional SEO for small businesses focuses on ranking your website in search engine results pages (SERPs) so people can click through, browse, and take action. GEO focuses on getting your business mentioned directly in AI-generated answers, even if users don't always click through. – Wait, no click? What’s the point then? GEO is still extremely valuable for small businesses. Let me explain with an example. Say you’re an event planner, and a potential customer is looking for information on their opens. SEO: “Here are 10 event planners near you” → User clicks your listing → Visits your website GEO: “Based on reviews and service offerings, here are the top event planners in your area...” → Your business gets mentioned with key details → User may visit your site OR contact you directly, but they still become aware of your business and its expertise. Both awareness and traffic matter. In fact, BrightLocal's 2025 SMB Marketing Report found that 72% of SMBs say SEO has a significant impact on growth, and now GEO is extending that reach to AI platforms. The most important thing to understand: If you‘re doing SEO well, you’re already the majority of the way to effective GEO. The foundations are the same: quality content, credible information, and technical soundness. GEO just adds a few targeted optimizations on top. (Plus, you should regularly revisit your search strategy anyway.) Why Generative Engine Optimization Matters Now for Small Businesses Shift from Rankings to Multi-surface Visibility Search engines are certainly not dead, but consumer search behavior is changing. Getting found isn’t just about search engine rank anymore; it’s about being visible across multiple platforms, and that includes AI engines. A study by GWI found 31% of Gen Zers already use AI platforms or chatbots most frequently to find information online, while research from Semrush predicts that LLM traffic will pass traditional Google search by the end of 2027. If small businesses are going to stay competitive, they need to take note of these changes and adapt their strategies accordingly. Early adoption benefits Our 2026 State of Marketing found over 92% of marketers plan on or are already using SEO optimization for traditional and AI-powered search engines. At the same time, nearly 24% are exploring updating their SEO strategy for generative AI in search (e.g. ChatGPT, Gemini, Claude). That means it's likely your competitors are already showing up in AI search results. For small businesses, this creates both opportunity and urgency. Early adopters who optimize for AI search are establishing authority before the space becomes saturated. But don’t worry, you don't need months to start seeing GEO benefits. 7 Day Quick-Win Checklist for GEO for Small Business Here's what you can accomplish in the next week: Day 1-2: Audit your Google Business Profile — ensure all information is complete, accurate, and includes detailed service descriptions. Learn more about what this looks like in our article, “Google My Business Guide: Complete Overview & Expert Tips.” Source Day 3: Add FAQ schema to your most important pages using a free schema generator. More on that and schema markup in general in our article, “How to Use Schema Markup to Improve Your Website's Structure.” Day 4-5: Update your homepage and key service pages with clear, direct answers to common customer questions in the first 2-3 paragraphs. Pro Tip: Also, make sure to highlight your location. Local SEO can be a very influential part of AI search. (More on that later.) Day 6: Add author bios and credentials to blog posts and service pages. Day 7: Check if your site appears in ChatGPT or Perplexity for your core services (search “[your service] in [your city]”) We’ll expand on this process further in our next section. Want to know where you stand right now? Use HubSpot's AI Search Grader to check your AI search visibility and get personalized recommendations. How to Do Generative Engine Optimization for Small Business 1. Audit your AI visibility and foundations. Before optimizing anything, you need to understand where you currently stand. HubSpot’s free AI Search Grader is a great place to start. It’ll give you a detailed competitive analysis, brand sentiment score, and strategic recommendations to optimize your brand's AI visibility, but don’t stop there. Search for your business name + service in ChatGPT, Perplexity, and Google (with AI Overviews enabled). Complete your Google Business Profile. Run your website through Google's Rich Results Test. Use Google PageSpeed Insights to check site performance (i.e., speed). Source As you do this, ask yourself: Does your business appear when you search for your category + location? Is the information accurate? Do you have basic schema markup in place? Is your site mobile-friendly and fast? This baseline audit takes 30-45 minutes and will show you exactly where to focus your efforts. 2. Research what/who LLMs are already citing in your niche. Large language models (LLMs) have citation patterns. They look for certain types of sources and content structures get referenced more frequently — though I’ve noticed they’re not always the biggest or most well-known sources. (If you’re still debating if GEO is worth it for a small business, I’d say that’s an encouraging sign, but I digress.) Take some time to research which sources, companies, and even competitors are getting cited for the questions your customers typically ask. Type each question into each AI tool individually, and note which businesses come up. Visit those sites and analyze: How they structure their content What credentials do they display How they answer questions (format, length, specificity) What schema markup do they use (check with Schema Markup Validator) This will give you insight into what content formats AI prefers (i.e., listicles, Q&A, detailed guides), content lengths, and common elements such as customer reviews, specific data points, and local references. This research is free and should take about 1-2 hours. Pro Tip: If you don’t know what questions your audience is asking. Check out AnswerThePublic and the “People Also Ask” boxes in Google search results. You can also check with your sales and customer service reps to see which questions come up most often in their conversations. 3. Optimize your existing content to be LLM-friendly. You don't need to hire writers or create dozens of new pages, at least not right off the bat. Start by optimizing what you already have with these techniques: Lead with direct answers (first 200-300 words): State the answer to the target question immediately Include your business name, service, and location in the first paragraph Use natural, conversational language For instance, don’t say “In this post, we'll share various templates for planning your events.” Say, "Ramona’s Elite Events offers high-end party and event planning services in downtown Boston. Our seasoned planners typically respond within 24 hours to requests regarding Boston-area birthdays, weddings, engagement parties, and corporate events." Add clear structure: Use descriptive H2 and H3 headings that include target keywords and questions Include a table of contents for longer pages Include comparison tables to organize important data Add FAQ sections with schema markup (use a free FAQ schema generator) Include credibility signals: Author names with brief credentials Publication/update dates Customer review counts and ratings, Certifications, licenses, or industry affiliations Specific service details (response times, service areas, pricing ranges) HubSpot's Content Hub has a host of free tools to help you accomplish these tasks. You can also try free tools like Google Docs, Grammarly, and Hemingway Editor to simplify complex language 4. Plan question-led content and entity coverage. With your format and structure insights handy, you can start planning your content. AI systems are designed to answer questions, so keep your content organized around the actual questions your customers ask. Follow these simple steps to get started: List 10-15 core questions Note which ones you already answered on your website Identify gaps where you need new content Prioritize based on search volume and business impact Pro Tip: Be mindful of specificity, especially when it comes to “entity coverage.” Entity coverage means being specific about who/what/where you're discussing. Instead of “we offer services,” write “Ramona’s Elite Events offers party and event planning services in downtown Boston.” AI systems need this specificity to confidently cite your content. 5. Publish across multi-platform channels. We touched upon this lightly earlier, but search is no longer just about your website. In fact, GEO especially looks for sources that have established authority across a variety of different platforms people turn to for information. Similar to social media, the goal isn't to be everywhere, though. The goal is to be visible on the platforms your audience (in this case, AI systems) use as sources for your industry. This includes, but is not limited to: Google Business Profile YouTube: Short how-to videos and service explanations get indexed by AI systems LinkedIn: Share expertise through posts and articles Industry directories (i.e. Houzz for the construction industry): Ensure consistent NAP (Name, Address, Phone) across all listings Local news/blogs: Pitch expert commentary to get quoted and linked Review Sites: Make sure your profile is complete and address all your reviews. Pro Tip: