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In a rapidly evolving digital landscape, small business owners in the banking sector are about to witness a significant transformation thanks to Oracle’s latest suite of AI-enhanced applications. Oracle Financial Services is leading the charge with a revolutionary agentic platform designed to enhance customer engagement, streamline operations, and introduce a new level of intelligent service. By infusing artificial intelligence into the core of banking operations, Oracle is enabling financial institutions to anticipate customer needs with unprecedented accuracy. This new capability is not just about automating routine tasks; it aims to elevate service quality through intelligent, conversational interfaces and autonomous AI agents. As Sovan Shatpathy, Oracle’s senior vice president for Product Management and Development, noted, “Our agentic platform is not just a set of applications; it’s a foundational architecture for building truly intelligent banks.” For small banking institutions, the implications are significant. The combination of domain-specific AI, human-in-the-loop governance, and enterprise-grade scalability creates a robust ecosystem from which banks can derive enhanced insights and efficiency. Here are some tangible benefits of Oracle’s platform: Hyper-Personalized Customer Interaction: By leveraging AI, banks can engage customers according to their specific preferences and behaviors. The platform supports tailored interactions whether customers engage through mobile apps, online banking, or in-person visits. Operational Efficiency: Automation of key processes is a game changer. Tools like the Product Brochure Generation agent and the Application Tracker agent provide real-time, accurate information that helps bankers expedite client service. This not only enhances customer satisfaction but also allows staff to focus on more complex interactions. Data-Driven Decision Making: Utilizing AI for credit decisioning means that banks can make faster, more reliable lending decisions. The Qualitative Analysis & Credit Decisioning agent cuts down processing times and optimizes the use of data, creating more consistent outcomes. Regulatory Compliance: With built-in compliance checks, products like the Call Compliance Check agent ensure adherence to regulations, reducing the risk for smaller banks and allowing them to serve customers more effectively without the constant worry of regulatory pitfalls. These innovations are particularly crucial for smaller banks that compete against larger institutions with larger resources. The ability to implement AI tools can help level the playing field by allowing for superior customer service and operational management. However, small business owners in the banking sector should also be aware of potential challenges when considering integration of these technologies. The initial investment in AI infrastructures, combined with the need for training staff to effectively utilize AI tools, may be daunting. Moreover, there is the ever-present concern about data privacy, especially as customer interactions become more automated. Financial institutions will need to weigh the benefits of enhanced customer engagement against potential costs and challenges. For instance, while AI can streamline operations, bankers must ensure that there is still a human touch in customer interactions, especially in sensitive situations like debt collections. The Collector Call Summarization agent and others create efficiencies but must be managed to ensure they genuinely improve customer experiences rather than creating a sense of distance. In the coming year, Oracle plans to roll out hundreds of new retail and corporate banking agents, further enriching this agentic platform, making it worthwhile for small banks to consider investing in these innovations. For small business owners in banking, the potential to harness AI for customer engagement cannot be underestimated. As Oracle leads the way in reimagining banking for the AI era, small business owners would do well to assess how these technologies can not only improve operations but also enhance customer loyalty and satisfaction. For complete details on Oracle’s offerings, visit Oracle Financial Services and see how these innovations might apply to your banking operations. More insights can be found in the original press announcement here. Image via Google Gemini This article, "Oracle Revolutionizes Banking with AI-Driven Solutions for Personalized Service" was first published on Small Business Trends View the full article

Treasury yields experienced a bullish open with the 5-year yield dropping over 15 basis points in five days, ahead of key jobs and inflation reports, as the dollar demonstrated strong adherence to technical levels, according to the CEO of IF Securities. View the full article

Media group adds ‘ticking fee’ to give shareholders additional payment for every quarter deal does not closeView the full article

The urge to tame big corporate landlords is bubbling over among locals in woodsy Paulding County, Georgia, an Atlanta exurb where church steeples and old graveyards punctuate the rolling hills, and an 18-foot fiberglass Wonder Woman waves at drivers. View the full article

It is no secret that publishing SEO-friendly blog posts is one of the easiest and most effective ways to drive organic traffic and improve SERP rankings. However, in the era of artificial intelligence, blog posts matter more than ever. They help establish brand authority by consistently delivering fresh, valuable content that can be cited in AI-generated answers. In this guide, we will share a practical, detailed approach to writing SEO-friendly blog content that not only ranks on Google SERPs but is also surfaced by AI models. Table of contents What does an SEO-friendly blog post mean in the AI era? 9 tips to write SEO-friendly blogs for LLM and SERP visibility Bonus tips Target your readers always! Key takeaways SEO friendly blog post now means writing with search intent, ensuring content is clear and quotable for AI systems Key factors for SEO friendly blog posts include trustworthiness, machine-readability, answer-first structure, and topical authority Conduct thorough keyword research and find readers’ questions to match search intent effectively Use clear headings, improve readability, include inclusive language, and add relevant media to engage readers Write compelling meta titles and descriptions, link to existing content, and focus on building authority to enhance visibility What does an SEO-friendly blog post mean in the AI era? The way people search for information has changed, and with it, the meaning of an SEO-friendly blog post. Before the rise of generative AI, writing an SEO-friendly blog post mostly meant this: ‘Writing content with the intention of ranking highly in search engine results pages (SERPs). The content is optimized for specific target keywords, easy to read, and provides value to the reader.’ That definition is not wrong. But it is no longer complete. In the AI era, an SEO-friendly blog post is written with search intent first, answering a user’s question clearly and efficiently. It is not just about placing keywords in the right spots. It is about creating an information-dense piece with accurate, well-structured, and quotable sentences that AI systems can confidently extract and surface as direct answers. The new definition clearly shows that strong SEO foundations still matter, and they matter more than ever. What has changed is how content is evaluated and discovered. Search engines and AI models now look beyond clicks and rankings to understand whether your content is trustworthy, helpful, and easy to interpret. Here are some key factors that play a key role in determining whether a blog post is truly SEO-friendly: Trustworthiness (E-E-A-T): Demonstrating real-world experience, expertise, and credibility helps your content stand out from low-value AI-generated rehashes Machine-readability: Clear structure, clean HTML, and technical signals such as schema markup help search engines and AI systems understand what your content is about Answer-first structure: Placing concise, direct answers at the beginning of sections makes it easier for AI models to extract and reference your content Topical authority: Publishing interconnected, in-depth content around a subject is far more effective than creating isolated blog posts 9 tips to write SEO-friendly blogs for LLM and SERP visibility Now we get to the core of this guide. Below are some foundational tips to help you plan and write SEO-friendly blog posts that are genuinely helpful, easy to understand, and focused on solving real reader problems. When done right, these practices not only improve search visibility but also shape how your brand is perceived by both users and AI systems. 1. Conduct thorough keyword research Before you start writing a single word, start with solid keyword research. This step helps you understand how people search for a topic, which terms carry demand, and how competitive those searches are. It also ensures your content aligns with real user intent instead of assumptions. You can use tools like Google Keyword Planner, Ahrefs, or Semrush for this. Personally, I prefer using Semrush’s Keyword Magic Tool because it quickly surfaces thousands of relevant keyword ideas around a single topic. Here’s how I usually approach it. I enter a broad keyword related to my topic, for example, ‘SEO.’ The tool then returns an extensive list of related keywords along with important metrics. I mainly focus on three of them: Search intent, to understand what the user is really looking for Keyword Difficulty (KD%), to estimate how hard it is to rank Search volume, to gauge demand This combination helps me choose keywords that are realistic to rank for and meaningful for readers. If you use Yoast SEO, this process becomes even easier. Semrush is integrated into Yoast SEO (both free and Premium), giving you keyword suggestions directly in Yoast SEO. With a single click, you can access relevant keyword data while writing, making it easier to create focused, useful content from the start. Looking for keyphrase suggestions? When you’ve set a focus keyword in Yoast SEO, you can click on ‘Get related keyphrases’ and our Semrush integration will help you find high-performing keyphrases! Also read: How to use the Semrush related keyphrases feature in Yoast SEO for WordPress 2. Finding readers’ questions Keyword research tells you what people search for. Questions tell you why they search. When you actively look for the questions your audience is asking, you move closer to matching search intent. This is especially important in the AI era, where search engines and AI models prioritize clear, answer-driven content. For example, consider these two queries: What are the key features of good running shoes? This shows informational intent. The searcher wants to understand what makes a running shoe good. What are the best running shoes? This suggests a transactional or commercial intent. The searcher is likely comparing options before making a purchase. Both questions are valid, but they require very different content approaches. There are two simple ways I usually find relevant questions. The first is by checking the People also ask section in Google search results. By typing in a broad keyphrase, you can see related questions that Google itself considers relevant. The second method is to use the Questions filter in Semrush’s Keyword Magic Tool. This helps uncover question-based queries directly tied to your main topic. Apart from these methods, I also like using Google’s AI Overview and AI mode as a quick research layer. When I search for my main topic, I pay close attention to AI-cited sources, as they often surface broad questions people are actively seeking. The structured points and highlighted terms usually reflect the answers and subtopics that matter most to users. If I want to go deeper, I click “Show more,” which reveals additional angles and follow-up questions I might not have considered initially. Finding and answering these questions helps you do lightweight online audience research and create content that feels genuinely helpful. It also increases the chances of your blog post being referenced in AI-generated answers, since LLMs are designed to surface clear responses to specific questions. 3. Structure your content with headings and subheadings In our 2026 SEO predictions, we highlighted that editorial quality is no longer just about good writing. It has become a machine-readability requirement. Content that is clearly structured is easier to understand, reuse, and surface across both search and AI-driven experiences. How LLMs use headings AI models rely on headings to identify topics, questions, and answers within a page. When your content is broken into clear sections, it becomes easier for them to extract key information and include it in AI-generated summaries. Why headings still matter for SEO Headings help search engines understand the hierarchy of your content and the main points you are trying to rank for. They also improve scannability and usability, especially on mobile devices, and increase the chances of earning featured snippets. Good structure has always been a core SEO principle. In the AI era, it remains one of the simplest and most effective ways to improve visibility and discoverability. 4. Focus on readability aspects An SEO-friendly blog post should be easy to read before it can rank or get picked up by AI systems. Readability helps readers stay engaged and helps search engines and AI models better understand your content. A few key readability aspects to focus on while writing: Avoid passive voice where possible Active sentences are clearer and more direct. They make it easier for readers to understand who is doing what, and they reduce ambiguity for AI systems processing your content. Use transition words Transition words like “because,” “for example,” and “however” guide readers through your content. They improve flow and make it easier to follow relationships between sentences and paragraphs. Keep sentences and paragraphs short Long, complex sentences reduce clarity. Breaking content into shorter sentences and paragraphs improves scannability and comprehension. Avoid consecutive sentences starting in the same way Varying sentence structure keeps your writing engaging and prevents it from sounding repetitive or robotic. If you are a WordPress or Shopify user, Yoast SEO (and Yoast SEO for Shopify for Shopify users) can help here. Its readability analysis checks for passive voice, transition words, sentence length, and other clarity signals while you write. If you prefer drafting in Google Docs, you can use the Yoast SEO Google Docs add-on to get the same readability feedback before publishing. Use Yoast SEO in Google DocsOptimize as you draft for SEO, inclusivity, and readability. The Yoast SEO Google Docs add-on lets you export content ready for WordPress, no reformatting required. Get Yoast for Google Docs add-onOnly $5 / month (ex VAT) Good readability is not just about pleasing algorithms. It helps readers understand your message more quickly and makes your content easier to reuse in AI-generated responses. 5. Use inclusive language Inclusive language helps ensure your content is respectful, clear, and welcoming to a broader audience. It avoids assumptions about gender, ability, age, or background, and focuses on people-first communication. From an SEO and AI perspective, inclusive language also improves clarity. Content that avoids vague or biased terms is easier to interpret, digest, and trust. This directly supports brand perception, especially when your content is surfaced in AI-generated responses. Yoast SEO supports this through its inclusive language check, which flags potentially non-inclusive terms and suggests better alternatives. This feature is available in Yoast SEO, Yoast SEO Premium, and in the Yoast SEO Google Docs add-on, making it easier to build inclusive habits directly into your writing workflow. Inclusive language ensures your content is intentional, thoughtful, and clear, aligning closely with what modern SEO and AI systems value. 6. Add relevant media and interaction points A well-written blog post should not feel like a long block of text. Adding the right media and interaction points helps guide readers through your content, keeps them engaged, and encourages them to take action. Why media matters Media elements such as images, videos, embeds, and infographics make your content easier to consume and more engaging. Blog posts that include images receive 94% more views than those without, simply because visuals break up large blocks of text and make pages easier to scan. Video content plays an even bigger role. Embedded videos help explain complex ideas faster and can significantly improve organic visibility compared to text-only posts. Together, these elements encourage readers to stay longer on your page, which is a strong signal of content quality for search engines and AI systems alike. Media also improves accessibility. Properly optimized images with descriptive alt text make content usable for screen readers, while original visuals, screenshots, or diagrams help reinforce credibility and expertise. Use interaction points to guide and engage readers Interaction does not always mean complex features. Even simple elements can significantly improve engagement when used well. A table of contents, for example, allows readers to jump directly to the section they care about most. Other interaction points include clear calls to action (CTAs) that guide readers to the next step, relevant recommendations that encourage users to keep exploring your site, and social sharing buttons that make it easy to amplify your content. Interactive elements like polls, quizzes, or embedded tools further encourage participation and increase time on page. 7. Plan your content length Content length still matters, but not in the way many people think it does. A common question is what the ideal word count is for a blog post that performs well. A 2024 study by Backlinko found that while longer content tends to attract more backlinks, the average page ranking on Google’s first page contains around 1,500 words. That said, this should not be treated as a fixed benchmark. The ideal length is the one that fully answers the user’s question. In an AI-driven era, publishing long content that adds little value or is padded with unnecessary fluff can do more harm than good. If a topic genuinely requires a longer format, breaking the content into clear subheadings makes a big difference. I personally prefer structuring long articles this way because it improves readability, helps readers navigate the page more easily, and makes the content easier for search engines and AI systems to understand. Must read: How to use headings on your site If you use Yoast SEO or Yoast SEO Premium, the paragraph and sentence length checks can help here. These checks exist to prevent pages from being too thin to provide real value. Pages with very low word counts often lack context and struggle to demonstrate relevance or expertise. Yoast SEO flags such cases as a warning, while clearly indicating that adding more words alone does not guarantee better rankings. Think of word count as a guideline, not a goal. Your focus should always be on clarity, completeness, and usefulness. 8. Link to existing content Internal linking is one of the most underrated SEO practices, yet it does a lot of heavy lifting behind the scenes. By linking to relevant content within your site, you help readers discover additional resources and help search engines understand how your content is connected. Over time, this strengthens topical authority and signals that your site consistently covers a subject in depth. Good internal linking follows a few simple principles: Link only when it adds value and feels natural in context Use clear, descriptive anchor text so users and search engines know what to expect Avoid linking to outdated URLs or pages that redirect, as this wastes crawl signals Internal links also keep readers engaged longer by guiding them to related articles. This improves overall site engagement while reinforcing your expertise on a topic. From an AI and search perspective, internal linking plays an even bigger role. Modern search systems analyze content structure, metadata hierarchies, schema markup, and internal links to assess topical depth and clarity. Well-linked content clusters make it easier for search engines and AI systems to understand what your site is about and which pages are most important. For WordPress users, Yoast SEO Premium offers internal linking suggestions directly in the editor. This makes it easier to spot relevant linking opportunities as you write, helping you build stronger content connections without interrupting your workflow. A smarter analysis in Yoast SEO PremiumYoast SEO Premium has a smart content analysis that helps you take your content to the next level! Get Yoast SEO Premium »Only $118.80 / year (ex VAT) 9. Write compelling meta titles and descriptions Meta titles and meta descriptions help users decide whether to click on your content. While meta descriptions are not a direct ranking factor, they strongly influence click-through rates, making them an essential part of writing SEO-friendly blog posts. A good meta title clearly communicates what the page is about. Place your main keyword near the beginning, keep it concise, and aim for roughly 55-60 characters so it doesn’t get truncated in search results. Meta descriptions act like a short invitation. They should explain what the reader will gain from clicking and why it matters. Instead of stuffing keywords, focus on clarity and usefulness. Mention what aspects of the topic your content covers and how it helps the reader. Simple language works best. Pro tip: Using action-oriented verbs such as “learn,” “discover,” or “read” can also encourage clicks and make your description more engaging. If you use Yoast SEO Premium, this process becomes much easier. The AI-powered meta title and description generation feature helps you create relevant, well-structured metadata in just one click. It follows SEO best practices while producing descriptions and titles that are clear, engaging, and aligned with search intent. Bonus tips Once you have the fundamentals in place, a few extra refinements can go a long way. The following bonus tips help improve usability, clarity, and long-term discoverability. They are not mandatory, but when applied thoughtfully, they can make your blog posts more helpful for readers and easier to surface across search engines and AI-driven experiences. 1. Add a table of contents A table of contents (TOC) helps readers quickly understand what your blog post covers and jump straight to the section they care about. This is especially useful for long-form content, where users often scan rather than scroll from top to bottom. From an SEO perspective, a TOC improves structure and readability and can create jump links in search results, which may increase click-through rates. It reduces bounce rates by helping users find answers faster and improves accessibility by offering clear navigation. By the way, did you know Yoast can help you here too? Yes, the Yoast SEO Internal linking blocks feature lets you add a TOC block to your blog post that automatically includes all the headings with just one click! 2. Add key takeaways Key takeaways help readers quickly grasp the main points of your blog post without having to read the whole post. This is especially helpful for time-constrained users who want quick, actionable insights. Summaries also support SEO by reinforcing topic relevance and improving content comprehension for search engines and AI systems. Well-written takeaways might increase visibility in featured snippets and “People also ask” results. If you use Yoast SEO Premium, the Yoast AI Summarize feature can generate key takeaways for your content in just one click, making it easier to add concise summaries without extra effort. 3. Add an FAQ section An FAQ section gives you space to answer specific questions your readers may still have after reading your post. This improves user experience by addressing concerns directly and building trust. FAQs also help search engines better understand your content by clearly outlining common questions and answers related to your topic. While they can support rankings, their real value lies in reducing friction, improving clarity, and even supporting conversions by clearing doubts. 4. Short permalinks A permalink is the permanent URL of your blog post. Short, descriptive permalinks are easier to read, easier to share, and more likely to be clicked. Good permalinks clearly describe what the page is about, avoid unnecessary words, and include the main topic where relevant. They improve usability and help search engines understand page context at a glance. 5. Focus on building authority (EEAT aspect) Building authority is critical, especially for sites that cover sensitive or high-impact topics. Demonstrating Experience, Expertise, Authoritativeness, and Trustworthiness (E-E-A-T) helps both users and search engines trust your content. This includes citing reliable sources, showing real-world experience, maintaining consistent quality, and clearly communicating who is behind the content. Strong E-E-A-T signals are especially important for YMYL topics, where accuracy and credibility matter most. 6. Plan content distribution Writing a great blog post is only half the work. Distribution helps your content reach the right audience. Sharing posts on social media, repurposing key insights into newsletters, and earning backlinks from relevant sites can drive more traffic and visibility. Distribution also increases engagement signals and helps your content gain traction faster, which supports long-term SEO performance. Target your readers always! In AI-driven search, retrieval beats ranking. Clarity, structure, and language alignment now decide if your content gets seen. – Carolyn Shelby This perfectly sums up what writing SEO-friendly blog posts looks like today. Success is no longer just about rankings. It is about being clear, helpful, and easy to understand for both readers and AI systems. Throughout this guide, we focused on the fundamentals that still matter: understanding search intent, structuring content well, improving readability, using inclusive language, and supporting your writing with media, internal links, and thoughtful metadata. These are not new tricks. They are strong SEO foundations, adapted for how search and discovery work in the AI era. If there is one takeaway, it is this: always write for your readers first. When your content genuinely helps people, answers their questions, and respects how they search and read, it naturally becomes easier to surface across SERPs and AI-driven experiences. Good SEO has not changed. It has simply become more human. The post Tips and tricks to write SEO-friendly blog posts in the AI era appeared first on Yoast. View the full article

Google's Results about you tool now monitors Search results for government-issued IDs like passports, driver's licenses, and Social Security numbers. The post Google Can Now Monitor Search For Your Government IDs appeared first on Search Engine Journal. View the full article

Google announced two new ways for users to remove their sensitive information from the web Tuesday morning—or, at least, remove that data from Google Search. The first lets users request that Google remove sensitive government ID information from Search, while the second gives users new tools to request the same for non-consensual explicit images. Google's "Results about you" tool is getting an update Credit: Google First, Google is updating its existing "Results about you" tool, which helps users scour the internet for their personal information. Before today, this tool could already locate data points like your name, phone number, email addresses, and home addresses. Following the update, you can now find and request the deletion of search results containing highly sensitive information, including your driver's license, passport, or Social Security number. To launch this tool, click here. If you've never used "Results about you" before, you'll need to set it up to tell Google what to look out for. Once you do, you'll be able to add government ID numbers, such as your driver's license, passport, and Social Security number. If Google finds a match, the company will let you know. You can receive an alert from the Google app on your smartphone, which takes you to a summary of what data was found and where. From here, you can choose from "Request to remove," or "Mark as reviewed." Unfortunately, this tool won't remove the data from the websites that are hosting it, but it will eventually remove the search results—sharply reducing the chance that someone will find your data on their own. Google says these changes will roll out in the U.S. over the "coming days," while it is working on bringing them to other countries in the future. Google's simpler way to remove explicit images from Search Credit: Google In addition to these changes, Google is now rolling out a simpler tool for users to request the remove of non-consensual explicit images (NCEI) from Search. If you find such an image on Search, you can tap the three dots on that image, choose "remove result," then "it shows a sexual image of me." You'll have the choice to report whether the photo is real, or is artificially generated, as well, and you can report multiple images at once, if needed. Your requests will all appear in the Results about you hub, so you can track the progress of each. The tool lets you opt-in to an option that will filter additional explicit results in other searches. Google says it will also share links to "emotional and legal support" after you submit a request. View the full article

The terms workflow integration and workflow automation often appear interchangeably in vendor marketing, but they describe different approaches to solving related problems. Confusing them leads to buying the wrong tools or expecting capabilities that don’t exist. Workflow automation executes tasks automatically based on triggers. Workflow integration connects systems so data flows between them. The distinction matters because the tool that automates your approval process won’t necessarily keep your project management and CRM data synchronized, and the platform that syncs your tools won’t automatically send notifications or create follow-up tasks. Understanding where these categories overlap and diverge helps you build a technology stack that actually addresses your operational challenges instead of accumulating tools that almost solve the problem. What is workflow integration? Workflow integration is the process of connecting different software applications so that data and information flow between them as part of your business processes. When your sales team closes a deal in Salesforce, workflow integration ensures that customer information appears in your project management tool for the implementation team. When engineering marks a feature complete in Jira, integration updates the corresponding item in the product roadmap. The systems stay aligned without anyone manually copying information between them. ComponentWhat it doesData mappingDefines which fields in one system correspond to fields in anotherSync directionDetermines whether data flows one-way or bidirectionallyTrigger conditionsSpecifies when data should sync (immediately, on schedule, based on criteria)Transformation rulesConverts data formats between systems (e.g., status values, date formats) The goal of workflow integration is continuity. Information created in one system becomes available in other systems without manual intervention. Teams working in different tools see consistent data. Handoffs between departments don’t require copying and pasting. Workflow integration addresses the problems caused by organizations using 1,200 cloud applications on average, applications that weren’t designed to share information with each other. Without integration, each tool operates as an island, and your team becomes the bridge. Common workflow integration scenarios A product team maintains their roadmap in one tool while engineering tracks development in another. Integration keeps priorities aligned so engineering always sees current roadmap status, and the product team sees actual development progress without checking a separate system. A customer success team tracks accounts in a CRM while support manages tickets in a different platform. Integration ensures that support sees customer context when tickets arrive, and success managers see support history when reviewing account health. A marketing team runs campaigns from a marketing automation platform while sales works opportunities in a CRM. Integration keeps lead and contact data synchronized so both teams work from the same customer information without manual data entry. What is workflow automation? Workflow automation executes predefined actions automatically when specific conditions are met. It’s about removing manual steps from processes, not about connecting systems. When a support ticket reaches high-priority status, automation can notify the on-call engineer. When a form submission arrives, automation can create a task, send a confirmation email, and update a spreadsheet. When an invoice is approved, automation can trigger payment processing. ComponentWhat it doesTriggersEvents that start the automation (form submission, status change, schedule)ActionsTasks executed automatically (send email, create record, update field)ConditionsLogic that determines which actions run (if/then rules, filters)SequencesMultiple actions chained together in order The goal of workflow automation is efficiency. Tasks that previously required human intervention happen automatically. Processes that depended on someone remembering to do something now execute reliably. Manual, repetitive work gets eliminated. Workflow automation addresses the problem that knowledge workers spend 62% of their time on repetitive tasks rather than skilled work. Automation handles the routine so people can focus on what requires human judgment. Common workflow automation scenarios A sales team automates lead routing based on territory, deal size, or product interest. When a new lead enters the CRM, automation assigns it to the right rep and notifies them immediately rather than waiting for manual review. An HR team automates the onboarding sequence. When a new hire is added to the HR system, automation creates their accounts, assigns training materials, schedules orientation meetings, and notifies their manager, all without manual coordination. A finance team automates invoice processing. When an invoice arrives, automation extracts key data, routes it for approval based on amount thresholds, and schedules payment upon approval. Manual data entry and routing decisions are eliminated. How workflow integration and automation differ The distinction becomes clear when you examine what each approach actually does. AspectWorkflow IntegrationWorkflow AutomationPrimary functionConnects systems to share dataExecutes tasks without manual interventionCore problem solvedData silos between applicationsManual, repetitive workWhat it createsSynchronized records across toolsAutomated actions and notificationsRelationship between systemsOngoing connection (stateful)Trigger-action events (stateless)Typical outputSame information available everywhereTasks completed, notifications sent Integration example: A customer record created in HubSpot automatically appears in Salesforce with mapped fields. When either record is updated, the other reflects the changes. The two systems maintain alignment over time. Automation example: When a deal closes in Salesforce, an automation sends a Slack message to the implementation team, creates a project in Asana, and schedules a kickoff email. Each action fires once based on the trigger. The key difference is state. Integration maintains an ongoing relationship between records. Automation fires and forgets. Integration asks “how do we keep these systems aligned?” Automation asks “what should happen when this event occurs?” This distinction has practical implications for how you structure your operations. If you need a customer record to stay synchronized between your CRM and support platform, with updates flowing in both directions over time, that’s an integration problem. A trigger-action automation can create the initial record, but it won’t maintain alignment as both records evolve. Conversely, if you need a Slack notification when a high-priority ticket arrives, that’s an automation problem. The notification fires once when the condition is met. There’s no ongoing relationship to maintain between the ticket and the notification. Where integration and automation overlap The categories aren’t mutually exclusive, and many tools offer both capabilities to varying degrees. Automation platforms with integration features. Tools like Zapier and Make (formerly Integromat) started as automation platforms but added data sync capabilities. They excel at trigger-action workflows but can also keep simple data aligned between applications. For a deeper look at no-code workflow automation tools, several options exist beyond the major platforms. Integration platforms with automation features. Enterprise iPaaS platforms and specialized sync tools often include workflow automation as part of broader integration capabilities. You might sync data between systems and automate notifications when certain conditions are met. The overlap creates confusion because vendors position their products to capture both markets. A platform might describe itself as “workflow automation” while primarily offering integration, or vice versa. Evaluating based on your actual needs clarifies the choice: If your primary problem is data existing in multiple places with no connection between them, you need integration. If your primary problem is manual tasks that should happen automatically, you need automation. If you need both, look for platforms that handle your dominant use case well and can address the secondary need adequately. Questions that reveal which problem you’re solving: Are you tired of manually copying data between systems? That’s an integration problem. Are you tired of remembering to do the same task every time something happens? That’s an automation problem. Do you need the same record to exist and stay updated in multiple tools? Integration. Do you need a sequence of actions to execute when a specific event occurs? Automation. When you need integration vs automation Workflow integration makes sense when Different teams use different tools but need access to the same information. Your project management tool needs to reflect what’s happening in your development tracker. Your CRM data needs to stay aligned with your marketing platform. Updates made in one system should appear in others without anyone copying them manually. Workflow automation makes sense when You have manual, repetitive tasks that follow predictable patterns. Approvals that require routing to the right person. Notifications that should fire when specific events occur. Data entry that could be eliminated through automatic record creation. Sequences of actions that always happen together. You probably need both when Your operations span multiple tools AND include repetitive manual processes. Most organizations fall into this category. The question is which need is primary and which tools address each effectively. Consider a customer success team that manages accounts across a CRM and a project management tool. They need integration to keep customer data synchronized between systems so everyone sees the same information. They also need automation to alert account managers when renewal dates approach or when usage metrics cross certain thresholds. Neither capability alone solves the complete problem. Or consider an engineering team working across Jira and a product management tool. Integration keeps development status and product roadmap priorities aligned bidirectionally. Automation handles the notifications, status updates, and task creation that should happen when specific events occur. The tools complement each other rather than competing for the same job. Building an integrated and automated workflow stack The most effective approach combines integration and automation thoughtfully rather than expecting one tool to do everything. For integration needs, platforms built for two-way sync between work management tools maintain ongoing connections between your core systems. Records stay aligned. Updates flow bidirectionally. Teams work in their preferred tools while sharing consistent data. For automation needs, trigger-action platforms handle the “when X happens, do Y” workflows that don’t require ongoing data synchronization. Notifications, task creation, and process sequences work well in these tools. The combination works because each tool does what it’s designed for. Integration platforms maintain state and keep systems aligned over time. Automation platforms execute discrete actions based on triggers without maintaining ongoing relationships. Trying to force one approach to do both often creates complexity and workarounds that exceed the benefit of getting it right in the first place. Two-way sync: The future of workflow integration For teams whose primary need is keeping project management, development, and collaboration tools synchronized, two-way sync platforms solve the integration challenge without the limitations of trigger-based automation tools attempting to maintain ongoing data alignment. View the full article

If you’ve been managing PPC accounts for any length of time, you don’t need a research report to tell you something has changed. You see it in the day-to-day work: GCLIDs missing from URLs. Conversions arriving later than expected. Reports that take longer to explain while still feeling less definitive than they used to. When that happens, the reflex is to assume something broke – a tracking update, a platform change, or a misconfiguration buried somewhere in the stack. But the reality is usually simpler. Many measurement setups still assume identifiers will reliably persist from click to conversion, and that assumption no longer holds consistently. Measurement hasn’t stopped working. The conditions it depends on have been shifting for years, and what once felt like edge cases now show up often enough to feel like a systemic change. Why this shift feels so disorienting I’ve been close to this problem for most of my career. Before Google Ads had native conversion tracking, I built my own tracking pixels and URL parameters to optimize affiliate campaigns. Later, while working at Google, I was involved in the acquisition of Urchin as the industry moved toward standardized, comprehensive measurement. That era set expectations that nearly everything could be tracked, joined, and attributed at the click level. Google made advertising feel measurable, controllable, and predictable. As the ecosystem now shifts toward more automation, less control, and less data, that contrast can be jarring. It has been for me. Much of what I once relied on to interpret PPC data no longer applies in the same way. Making sense of today’s measurement environment requires rethinking those assumptions, not trying to restore the old ones. This is how I think about it now. Dig deeper: How to evolve your PPC measurement strategy for a privacy-first future The old world: click IDs and deterministic matching For many years, Google Ads measurement followed a predictable pattern. A user clicked an ad. A click ID, or gclid, was appended to the URL. The site stored it in a cookie. When a conversion fired, that identifier was sent back and matched to the click. This produced deterministic matches, supported offline conversion imports, and made attribution relatively easy to explain to stakeholders. As long as the identifier survived the journey, the system behaved in ways most advertisers could reason about. We could literally see what happened with each click and which ones led to individual conversions. That reliability depended on a specific set of conditions. Browsers needed to allow parameters through. Cookies had to persist long enough to cover the conversion window. Users had to accept tracking by default. Luckily, those conditions were common enough that the model worked really well. Why that model breaks more often now Browsers now impose tighter limits on how identifiers are stored and passed. Apple’s Intelligent Tracking Prevention, enhanced tracking protection, private browsing modes, and consent requirements all reduce how long tracking data persists, or whether it’s stored at all. URL parameters may be stripped before a page loads. Cookies set via JavaScript may expire quickly. Consent banners may block storage entirely. Click IDs sometimes never reach the site, or they disappear before a conversion occurs. This is expected behavior in modern browser environments, not an edge case, so we have to account for it. Trying to restore deterministic click-level tracking usually means working against the constant push toward more privacy and the resulting browser behaviors. This is another of the many evolutions of online advertising we simply have to get on board with, and I’ve found that designing systems to function with partial data beats fighting the tide. The adjustment isn’t just technical On my own team, GA4 is a frequent source of frustration. Not because it’s incapable, but because it’s built for a world where some data will always be missing. We hear the same from other advertisers: the data isn’t necessarily wrong, but it’s harder to reason about. This is the bigger challenge. Moving from a world where nearly everything was observable to one where some things are inferred requires accepting that measurement now operates under different conditions. That mindset shift has been uneven across the industry because measurement lives at the periphery of where many advertisers spend most of their time, working in ad platforms. A lot of effort goes into optimizing ad platform settings when sometimes the better use of time might’ve been fixing broken data so better decisions could be made. Dig deeper: Advanced analytics techniques to measure PPC Get the newsletter search marketers rely on. See terms. What still works: Client-side and server-side approaches So what approaches hold up under current constraints? The answer involves both client-side and server-side measurement. Pixels still matter, but they have limits Client-side pixels, like the Google tag, continue to collect useful data. They fire immediately, capture on-site actions, and provide fast feedback to ad platforms, whose automated bidding systems rely on this data. But these pixels are constrained by the browser. Scripts can be blocked, execution can fail and consent settings can prevent storage. A portion of traffic will never be observable at the individual level. When pixel tracking is the only measurement input, these gaps affect both reporting and optimization. Pixels haven’t stopped working. They just no longer cover every case. Changing how pixels are delivered Some responses to declining pixel data focus on the mechanics of how pixels are served rather than measurement logic. Google Tag Gateway changes where tag requests are routed, sending them through a first-party, same-origin setup instead of directly to third-party domains. This can reduce failures caused by blocked scripts and simplify deployment for teams using Google Cloud. What it doesn’t do is define events, decide what data is collected, or correct poor tagging choices. It improves delivery reliability, not measurement logic. This distinction matters when comparing Tag Gateway and server-side GTM. Tag Gateway focuses on routing and ease of setup. Server-side GTM enables event processing, enrichment, and governance. It requires more maintenance and technical oversight, but it provides more control. The two address different problems. Here’s the key point: better infrastructure affects how data moves, not what it means. Event definitions, conversion logic, and consistency across systems still determine data quality. A reliable pipeline delivers whatever it’s given, so it’d be just as good at making sure the garbage you put in also comes back out. Offline conversion imports: Moving measurement off the browser Offline conversion imports take a different approach, moving measurement away from the browser entirely. Conversions are recorded in backend systems and sent to Google Ads after the fact. Because this process is server to server, it’s less affected by browser privacy restrictions. It works for longer sales cycles, delayed purchases, and conversions that happen outside the site. This is why Google commonly recommends running offline imports alongside pixel-based tracking. The two cover different parts of the journey. One is immediate, the other persists. Offline imports also align with current privacy constraints. They rely on data users provide directly, such as email addresses during a transaction or signup. The data is processed server-side and aggregated, reducing reliance on browser identifiers and short-lived cookies. Offline imports don’t replace pixels. They reduce dependence on them. Dig deeper: Offline conversion tracking: 7 best practices and testing strategies How Google fills the gaps Even with pixels and offline imports working together, some conversions can’t be directly observed. Matching when click IDs are missing When click IDs are unavailable, Google Ads can still match conversions using other inputs. This often begins with deterministic matching through hashed first-party identifiers such as email addresses, when those identifiers can be associated with signed-in Google users. This is what Enhanced Conversions help achieve. When deterministic matching, if this then that, isn’t possible, the system relies on aggregated and validated signals rather than reconstructing individual click paths. These can include session-level attributes and limited, privacy-safe IP information, combined with timing and contextual constraints. This doesn’t recreate the old click-level model, but it allows conversions to be associated with prior ad interactions at an aggregate level. One thing I’ve noticed: adding these inputs typically improves matching before it affects bidding. Bidding systems account for conversion lag and validate new signals over time, which means imported or modeled conversions may appear in reporting before they’re fully weighted in optimization. Matching, attribution, and bidding are related but separate processes. Improvements in one don’t immediately change the others. Modeled conversions as a standard input Modeled conversions are now a standard part of Google Ads and GA4 reporting. They’re used when direct observation isn’t possible, such as when consent is denied or identifiers are unavailable. These models are constrained by available data and validated through consistency checks and holdback experiments. When confidence is low, modeling may be limited or not applied. Modeled data should be treated as an expected component of measurement rather than an exception. Dig deeper: Google Ads pushes richer conversion imports Boundaries still matter Tools like Google Tag Gateway or Enhanced Conversions for Leads help recover measurement signal, but they don’t override user intent. Routing data through a first-party domain doesn’t imply consent. Ad blockers and restrictive browser settings are explicit signals. Overriding them may slightly increase the measured volume, but it doesn’t align with users’ expectations regarding how your organization uses their data. Legal compliance and user intent aren’t the same thing. Measurement systems can respect both, but doing so requires deliberate choices. Designing for partial data Missing signals are normal. Measurement systems that assume full visibility will continue to break under current conditions. Redundancy helps: pixels paired with hardened delivery, offline imports paired with enhanced identifiers, and multiple incomplete signals instead of a single complete one. But here’s where things get interesting. Different systems will see different things, and this creates a tension many advertisers now face daily. Some clients tell us their CRM data points clearly in one direction, while Google Ads automation, operating on less complete inputs, nudges campaigns another way. In most cases, neither system is wrong. They’re answering different questions with different data, on different timelines. Operating in a world of partial observability means accounting for that tension rather than trying to eliminate it. Dig deeper: Auditing and optimizing Google Ads in an age of limited data Making peace with partial observability The shift toward privacy-first measurement changes how much of the user journey can be directly observed. That changes our jobs. The goal is no longer perfect reconstruction of every click, but building measurement systems that remain useful when signals are missing, delayed, or inferred. Different systems will continue to operate with different views of reality, and alignment comes from understanding those differences rather than trying to eliminate them. In this environment, durable measurement depends less on recovering lost identifiers and more on thoughtful data design, redundancy, and human judgment. Measurement is becoming more strategic than ever. View the full article

Americans’ hope for their future has fallen to a new low, according to new polling. In 2025, only about 59% of Americans gave high ratings when asked to evaluate how good their life will be in about five years, the lowest annual measure since Gallup began asking this question almost 20 years ago. It’s a warning about the depth of the gloom that has fallen over the country over the past few years. In the data, Gallup’s “current” and “future” lines have tended to move together over time — when Americans are feeling good about the present, they tend to feel optimistic about the future. But the most recent measures show that while current life satisfaction has declined over the last decade, future optimism has dropped even more. The finding comes from a longstanding Gallup question that asks Americans to rate their current and future lives on a scale from 0 to 10. Those who give themselves an 8 or higher on the question about the future are categorized as optimists. “While current life is eroding, it’s that optimism for the future that has eroded almost twice as much over the course of about that last 10 years or so,” said Dan Witters, the research director of the Gallup National Health and Well-Being Index. Gallup assesses people who rate their current life at a 7 or higher and their anticipated future at an 8 or higher as “thriving.” Fewer than half of Americans, about 48%, are now in that category. Democrats and Hispanic Americans, in particular, were in a darker mood last year. But even with President Donald The President back in the White House and his party in control of both houses of Congress, Republicans aren’t feeling nearly as good about the future as they were in the last year of The President’s first term. Democrats’ optimism fell significantly Americans’ attitudes toward the future tend to shift when a new political party enters the White House — generally, the party in power grows more optimistic, while the party without control is more down. For instance, Democrats became more positive about the future after Joe Biden won the presidency, while Republicans’ outlook soured. Witters notes that these changes typically happen “by roughly the same amount, same level of magnitude, so they cancel each other out.” That didn’t happen in 2025. Toward the end of Biden’s term and the start of The President’s second term, Democrats’ optimism fell from 65% to 57%. Republicans grew more hopeful, but not enough to offset Democrats’ drop. “The regime change in the White House almost certainly was a big driving factor in what’s happened,” Witters said. “And a lot of that was just because the people who identified as Democrats really took it in the chops.” But Republicans are still quite a bit gloomier about the future than they were in the last year of The President’s first term. A January AP-NORC poll found that while the vast majority of Republicans are still behind the president, his work on the economy hasn’t lived up to many people’s expectations. Hispanic adults grew more pessimistic Hispanic adults’ optimism for the near future also declined during The President’s first year in office, dropping from 69% to 63%. That decrease was sharper than among white and Black Americans, something that Witters said could be tied to overall cost concerns, health care worries or alarm about The President’s recent immigration policies. Last year, a survey by the American Communities Project found that people living in heavily Hispanic areas were feeling less hopeful about their future than in 2024. The President’s favorability fell among Hispanics over the course of 2025, according to AP-NORC polling, which also found that Hispanic adults reported higher levels of economic stress than other groups. A Pew Research Center poll conducted in October found that the administration’s tough immigration enforcement is highly visible in Hispanic communities. About 6 in 10 Latinos said they had seen or heard of Immigration and Customs Enforcement raids or arrests in their community in the past six months. “(Deportations are) something that everybody can see and look at with their own eyes,” Witters added. “But if you’re Hispanic, I think it’s fair to think that that might hit a little closer to home.” This data is a part of the Gallup National Health and Well-Being Index. The 2025 results are based on data collected over four quarterly measurement periods, totaling 22,125 interviews with U.S. adults who are part of the probability-based Gallup Panel. —Linley Sanders, Associated Press View the full article

This weekend offers several remarkable opportunities to save money across various categories. For instance, you can enjoy a BOGO deal at Yogurtland, making it a great time to indulge in frozen treats. Moreover, the Shark Cyclone Pet Handheld Vacuum is available for just $25, whereas Vera Bradley Throw Blankets are marked down to $12.34. With these enticing offers and more, you’ll want to explore all the savings available this weekend. Key Takeaways Take advantage of Yogurtland’s BOGO deal on yogurt or ice cream cups available for iOS and Android users on October 27. Grab the Shark Cyclone Pet Handheld Vacuum for only $25 with free shipping, originally priced at $70, perfect for pet owners. Enjoy Vera Bradley Throw Blankets at a sale price of $12.34, offering 81% off the original price of $65, ideal for gifts or home decor. Buy Miracle-Gro Indoor Plant Food 2-Pack on Amazon for as low as $9.39, promoting healthier plant growth with convenient doorstep delivery. Experience a Luxury Head Spa Treatment for $89, or $66.75 with the HALLOWEEN promo code, rated 4.9 stars, perfect for relaxation this weekend. BOGO Yogurt or Ice Cream Cups at Yogurtland on Oct. 27 On October 27, Yogurtland is offering an enticing Buy One Get One (BOGO) deal on yogurt or ice cream cups, allowing you to enjoy twice the treats for the price of one. This promotion is available for both iOS and Android users, making it easy for everyone to participate. You can use this opportunity to try new flavors or share with friends and family. To redeem the offer, simply visit a participating Yogurtland location on the specified date. This limited-time BOGO yogurt or ice cream cups deal is ideal for those looking to indulge in delicious frozen desserts as well as maximizing savings. Don’t forget to check for food coupons today to improve your experience even further. Shark Cyclone Pet Handheld Vacuum, Just $25 Shipped at HSN If you’re looking to improve your cleaning routine after enjoying those delicious frozen treats, the Shark Cyclone Pet Handheld Vacuum is now available for just $25 with free shipping at HSN, a marked down price from its regular $70. Designed particularly for pet owners, this vacuum thrives at removing pet hair from various surfaces, making it a practical addition to your cleaning arsenal. Its compact and lightweight design allows for easy maneuverability and storage, perfect for quick clean-ups. You can conveniently shop online, avoiding the hassle of visiting physical stores. Don’t forget to check your food coupons app for other savings and explore discounts near me to maximize your weekend shopping experience. Vera Bradley Throw Blankets Dropped to $12.34 at Target Vera Bradley Throw Blankets are now available for just $12.34 at Target, considerably reduced from their original price of $65. This sale offers a remarkable 81% discount, making it an excellent opportunity to improve your home decor or find a thoughtful gift. The blankets provide both style and comfort, perfect for those chilly evenings ahead. Nonetheless, availability may vary by location, so it’s wise to check your local Target store or their website for stock. As you shop, don’t forget to look for free coupons for food today or browse online food offers to maximize your savings. This weekend, treat yourself to a cozy blanket and explore other great deals at Target. Miracle-Gro Indoor Plant Food 2-Pack, as Low as $9.39 on Amazon If you’re looking to nourish your indoor plants without breaking the bank, the Miracle-Gro Indoor Plant Food 2-Pack is a great option at just $9.39 on Amazon. This product supports healthier growth and lively foliage, making it ideal for plant enthusiasts who want to keep their greenery thriving. Plus, buying the 2-Pack means you won’t need to repurchase as frequently, providing added convenience for your plant care routine. Affordable Indoor Plant Care In relation to affordable indoor plant care, the Miracle-Gro Indoor Plant Food 2-Pack stands out as a practical choice, especially at a competitive price of as low as $9.39 on Amazon. This product promotes healthy growth and lively foliage in indoor plants, making it easier for you to nurture your greenery. Each pack contains crucial nutrients, enhancing water absorption and overall health. Customers appreciate the convenience of Miracle-Gro, simplifying the feeding process for various indoor species. By choosing this deal, you can enjoy significant savings compared to traditional prices, allowing you to maintain your indoor plants without breaking the bank. 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Originally priced at $105, this treatment is now available for $89, and using the promo code HALLOWEEN brings the cost down to just $66.75, making it an excellent opportunity to improve your spa experience. Indulge in Relaxation Indulging in relaxation has never been more accessible with the luxury head spa treatment available for both individuals and couples, featuring a soothing neck and scalp massage. Originally priced at $105, this treatment is now just $89, and with the code HALLOWEEN, you can enjoy it for only $66.75. Located conveniently at Cityplace in Dallas, only 1.8 miles away, this high-rated service boasts a 4.9 customer satisfaction score. Here’s what you can expect: A serene escape from daily stressors Highly skilled therapists providing personalized care Perfect for couples looking to unwind together Don’t forget to check for any internet coupons or free meal coupons to further improve your relaxing experience. 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Subscribing to services like brandSAVER gives you access to exclusive digital and printable coupons. Retail circulars and local newspapers often feature weekly sales and coupons, which you can clip. Furthermore, couponing apps such as Coupon24 allow you to browse offers and scan them at checkout for easy redemption. What Is the WAYDAY20 Promo Code? The WAYDAY20 promo code provides a 20% discount on select items at Wayfair during promotional events. You can apply this code at checkout for eligible purchases, allowing you to save considerably on furniture and home decor. It’s important to check Wayfair’s website for specific dates and any exclusions, as certain brands or categories may not qualify. Furthermore, you can stack WAYDAY20 with other ongoing sales for even more savings on larger purchases. What Is the Best Site for Coupon Codes? When you’re looking for the best site for coupon codes, Rakuten stands out. It offers Cash Back opportunities from various retailers, making it easy to save money as you shop online and in-store. You can access exclusive discounts through the Rakuten app’s Hot Deals section. Furthermore, using their browser extension alerts you to potential Cash Back and coupon options as you shop, enhancing your savings effortlessly. Regularly checking for new deals can further maximize your benefits. What Is the TRIPLE10 Promo Code? The TRIPLE10 promo code provides you with a 10% discount on select online purchases. To use it, simply enter the code at checkout before completing your order. It’s applicable at various retailers during special sales or promotional events. Be sure to check the specific terms and conditions, as some products may be excluded, and the code may have an expiration date. Combining TRIPLE10 with other offers can maximize your savings even further. Conclusion This weekend offers significant savings across various products and services. You can enjoy a BOGO deal at Yogurtland, purchase a Shark Cyclone Pet Handheld Vacuum for just $25, and find Vera Bradley Throw Blankets for only $12.34. Furthermore, Miracle-Gro Indoor Plant Food is available for $9.39, and the Ninja Foodi Smart XL Air Fryer is priced at $129.99. New members can likewise join Sam’s Club for just $15, making it an ideal time to save. Image via Google Gemini This article, "7 Best Coupons and Offers to Save Big This Weekend" was first published on Small Business Trends View the full article

This Ask an SEO explains how search, social platforms, and on-site content demand different optimization approaches without fragmenting strategy. The post Should I Optimize My Content Differently For Each Platform? – Ask An SEO appeared first on Search Engine Journal. View the full article

I am seeing some early signs of yet another unconfirmed Google Search ranking update with more volatility touching down today, February 10th. The chatter within the SEO community is starting to spike, and some of the third-party tracking tools are showing volatility.View the full article

Agentic AI is increasingly appearing in leadership conversations, often accompanied by big claims and unclear expectations. For SEO leaders working with ecommerce brands, this creates a familiar challenge. Executives hear about autonomous agents, automated purchasing, and AI-led decisions, and they want to know what this really means for growth, risk, and competitiveness. What they don’t need is more hype. They need clear explanations, grounded thinking, and practical guidance. This is where SEO leaders can add real value, not by predicting the future, but by helping leadership understand what is changing, what isn’t, and how to respond without overreacting. Here’s how. Start by explaining what ‘agentic’ actually means A useful first step is to remove the mystery from the term itself. Agentic systems don’t replace customers, they act on behalf of customers. The intent, preferences, and constraints still come from a person. What changes is who does the work. Discovery, comparison, filtering, and sometimes execution are handled by software that can move faster and process more information than a human can. When speaking to executive teams, a simple framing works best: “We’re not losing customers, we’re adding a new decision-maker into the journey. That decision-maker is software acting as a proxy for the customer.” Once this is clear, the conversation becomes calmer and more practical, and the focus moves away from fear and toward preparation. Your customers search everywhere. Make sure your brand shows up. The SEO toolkit you know, plus the AI visibility data you need. Start Free Trial Get started with Keep expectations realistic and avoid the hype Another important role for SEO leaders is to slow the conversation down. Agentic behavior will not arrive everywhere at the same time. Its impact will be uneven and gradual. Some categories will see change earlier because their products are standardized and data is already well structured. Others will move more slowly because trust, complexity, or regulation makes automation harder. This matters because leadership teams often fall into one of two traps: Panic, where plans are rewritten too quickly, budgets move too fast, and teams chase futures that may still be some distance away. Dismissal, where nothing changes until performance clearly drops, and by then the response is rushed. SEO leaders can offer a steadier view. Agentic AI accelerates trends that already exist. Personalized discovery, fewer visible clicks, and more pressure on data quality are not new problems. Agents simply make them more obvious. Seen this way, agentic AI becomes a reason to improve foundations, not a reason to chase novelty. Dig deeper: Are we ready for the agentic web? Change the conversation from rankings to eligibility One of the most helpful shifts in executive conversations is moving away from rankings as the main outcome of SEO. In an agent-led journey, the key question isn’t “do we rank well?” but “are we eligible to be chosen at all?” Eligibility depends on clarity, consistency, and trust. An agent needs to understand what you sell, who it is for, how much it costs, whether it is available, and how risky it is to choose you on behalf of a user. This is a strong way to connect SEO to commercial reality. Questions worth raising include whether product information is consistent across systems, whether pricing and availability are reliable, and whether policies reduce uncertainty or create it. Framed this way, SEO becomes less about chasing traffic and more about making the business easy to select. Explain why SEO no longer sits only in marketing Many executives still see SEO as a marketing channel, but agentic behavior challenges that view. Selection by an agent depends on factors that sit well beyond marketing. Data quality, technical reliability, stock accuracy, delivery performance, and payment confidence all play a role. SEO leaders should be clear about this. This isn’t about writing more content. It’s about making sure the business is understandable, reliable, and usable by machines. Positioned correctly, SEO becomes a connecting function that helps leadership see where gaps in systems or data could prevent the brand from being selected. This often resonates because it links SEO to risk and operational health, not just growth. Dig deeper: How to integrate SEO into your broader marketing strategy Be clear that discovery will change first For most ecommerce brands, the earliest impact of agentic systems will be at the top of the funnel. Discovery becomes more conversational and more personal. Users describe situations, needs, and constraints instead of typing short search phrases, and the agent then turns that context into actions. This reduces the value of simply owning category head terms. If an agent knows a user’s budget, preferences, delivery expectations, and past behavior, it doesn’t behave like a first-time visitor. It behaves like a well-informed repeat customer. This creates a reporting challenge. Some SEO work will no longer look like direct demand creation, even though it still influences outcomes. Leadership teams need to be prepared for this shift. Get the newsletter search marketers rely on. See terms. Reframe consideration as filtering, not persuasion The middle of the funnel also changes shape. Today, consideration often involves reading reviews, comparing options, and seeking reassurance. In an agent-led journey, consideration becomes a filtering process, where the agent removes options it believes the user would reject and keeps those that fit. This has clear implications. Generic content becomes less effective as a traffic driver because agents can generate summaries and comparisons instantly. Trust signals become structural, meaning claims need to be backed by consistent and verifiable information. In many cases, a brand may be chosen without the user being consciously aware of it. That can be positive for conversion, but risky for long-term brand strength if recognition isn’t built elsewhere. Dig deeper: How to align your SEO strategy with the stages of buyer intent Set honest expectations about measurement Executives care about measurement, and agentic AI makes this harder. As more discovery and consideration happen inside AI systems, fewer interactions leave clean attribution trails. Some impact will show up as direct traffic, and some will not be visible at all. SEO leaders should address this early. This isn’t a failure of optimization. It reflects the limits of today’s analytics in a more mediated world. The conversation should move toward directional signals and blended performance views, rather than precise channel attribution that no longer reflects how decisions are made. Promote a proactive, low-risk response The most important part of the leadership discussion is what to do next. The good news is that most sensible responses to agentic AI are low risk. Improving product data quality, reducing inconsistencies across platforms, strengthening reliability signals, and fixing technical weaknesses all help today, regardless of how quickly agents mature. Investing in brand demand outside search also matters. If agents handle more of the comparison work, brands that users already trust by name are more likely to be selected. This reassures leaders that action doesn’t require dramatic change, only disciplined improvement. See the complete picture of your search visibility. Track, optimize, and win in Google and AI search from one platform. Start Free Trial Get started with Agentic AI changes the focus, not the fundamentals For SEO leaders, agentic AI changes the focus of the role. The work shifts from optimizing pages to protecting eligibility, from chasing visibility to reducing ambiguity, and from reporting clicks to explaining influence. This requires confidence, clear communication, and a willingness to challenge hype. Agentic AI makes SEO more strategic, not any less important. Agentic AI should not be treated as an immediate threat or a guaranteed advantage. It’s a shift in how decisions are made. For ecommerce brands, the winners will be those that stay calm, communicate clearly, and adapt their SEO thinking from driving clicks to earning selection. That is the conversation SEO leaders should be having now. Dig deeper: The future of search visibility: What 6 SEO leaders predict for 2026 View the full article

Target Corporation has reportedly announced that it will cut about 500 roles at the company, partially in an effort to reallocate financial resources to boost the in-store customer experience. The job cuts would be the second major wave of cuts that Target has made in the last five months, and come less than two weeks after the company’s new CEO stepped into the role. Here’s what you need to know. What’s happened? On Monday, media outlets including CNBC and MarketWatch reported on a memo sent to Target employees by the company’s chief stores officer, Adrienne Costanzo, and its chief supply chain and logistics officer, Gretchen McCarthy. In the memo, the executives announced that the chain would be initiating more layoffs—this time cutting around 500 positions. However, the majority of the job cuts will not impact store-level retail workers. Instead, the memo says that about 400 jobs will be lost across its distribution and another 100 jobs will go across its store district level. Fast Company has reached out to Target for comment. We’ll update this story if we hear back. Target’s roughly 2,000 stores are divided into geographic districts staffed by corporate regional office workers. The memo stated that the number of these districts will be reduced, and thus some corporate workers overseeing these districts will be let go. Target has around 440,000 employees, most of whom work in its retail division. Job cuts of around 500 mean Target is laying off about 1/10 of 1% of its workforce. Why is Target cutting jobs? Besides a reorganization of its geographic districts, the financial savings from job cuts will allow Target to reinvest more money into front-line in-store staffing. “This change also fuels our ability to put significantly more payroll in our stores—primarily in additional labor and hours where needed most, but also in new guest experience training for every team member at every store,” the memo stated. In recent years, Target has faced customer criticism that checkout lines have gotten longer and stores have become messier. This has been attributed to lower staffing levels in stores and to store employees being taken off the floor to help fulfill online curbside orders. But the job cuts also come less than two weeks after Target’s new CEO, Michael Fiddelke, stepped into the role at the beginning of this month. Fiddelke was named incoming CEO last year and had previously served as the company’s operating officer. Fiddelke himself is the one who notified Target employees via memo in October that the company was laying off 1,800 workers. At the time, Fiddelke said those layoffs were “a necessary step in building the future of Target and enabling the progress and growth we all want to see.” Target hit by external and self-made problems In recent years, Target has had essentially flat year-over-year sales, not helped by the fact that many of its cost-conscious consumers are cutting back on their discretionary spending and inflation surges. A majority of the goods Target sells are discretionary items. Additionally, many of Target’s products come from China and other countries in Asia that have been hit hard by President The President’s tariffs, thus raising Target’s costs when it imports those goods to the United States. The company also shot itself in the foot last year when it reversed course on its celebrated diversity, equity, and inclusion (DEI) initiatives in the wake of The President entering the White House for a second term. The reversal of its DEI policies led to fierce consumer backlash and boycotts, resulting in foot traffic falling by almost 8% in many of its stores. How has Target’s stock price reacted to the layoff news? Investors in Target Corporation (NYSE: TGT) seem unfazed by the news of more job cuts. Yesterday, TGT shares closed roughly flat to $115.52 per share. And in premarket trading this morning, TGT shares are up only about 0.4%. Given this, investors seem to think the layoffs and district changes will have little meaningful impact on Target’s finances—at least in the immediate term. The good news for Target is that, as of yesterday’s close, the company’s shares are up over 18% year to date. While the company’s stock price is still down about 12% over the past year, TGT shares have now recovered significantly since their November low of around $83. View the full article

A month ago, we reported on a new help document on Google Ads for Performance Max optimization experiments: A/B testing assets beta. Well, now some are seeing this in the wild, where you can set up these A/B tests in a controlled environment. View the full article

There are some reports coming out that Grokipedia, the AI-based Wikipedia, is now showing a decline in search visibility in both Google and even ChatGPT. This comes after both an indexing and ranking surge in Google Search.View the full article

OpenAI has officially launched ads in ChatGPT yesterday. The company announced, "Today, we're beginning to test ads in ChatGPT in the U.S. The test will be for logged-in adult users on the Free and Go subscription tiers. Plus, Pro, Business, Enterprise, and Education tiers will not have ads."View the full article

Google appears to be testing showing the citation favicon site icons at the bottom of the answer in AI Mode. This is in addition to where it normally shows those icons, at the top right of the card stack, on the side of the answer response.View the full article

Microsoft Bing is testing a dynamically loading results count under the search box. So when you enter your search phrase, the results count will dynamically count up from 0 to the number of results found.View the full article

To Dr. Richard Pan, a California-based pediatrician, the idea of living a long, healthy life should not be a partisan issue. Unfortunately, it’s become one: He knows that topics like vaccines, healthcare, and science at large are now extremely politicized, and that whoever has the power to shape our policies can have a big impact on the health of Americans. Pan has seen that firsthand in his time serving in California’s state assembly and then senate, where he authored landmark legislation around vaccines, health insurance, and even a law that led California to produce its own insulin—which paved the way for the state to offer the medicine for as low as $11. Now, Pan is running for Congress, motivated by Robert F. Kennedy Jr.’s anti-vaccine agenda and broad issues around healthcare affordability. “I swore in medical school as part of my oath to help people and improve health,” he says. “Part of my career commitment would be to say, ‘Okay, well, I tried doing that at the state [level] and succeeded. Now I need to go to the federal government.” Pan is part of a wave of experts in STEM fields (science, technology, engineering, and mathematics) who are running for Congressional seats in response to the The President administration’s attacks on science, facts, and also affordability. From doctors to scientists to math teachers, Democratic candidates, frustrated with the federal government’s actions, see an opportunity to use their STEM skills to win seats in Congress, and eventually shape policies that help the public. While some of these candidates have prior political experience, others are completely new to politics. Dr. Richard Pan RFK Jr. as a tipping point Pan first ran for California’s state assembly in 2010 after witnessing the effects of the Great Recession. The state struggled to pass a new budget, and funding shortfalls led to cuts to various health services. “I decided things were so bad that I would throw my hat in the ring and run,” he says. He flipped the Republican seat. Pan served in the State Assembly until 2014, and the state Senate from 2014 to 2022, before returning to medicine full-time. When RFK Jr. was announced as the Health and Human Services secretary, though, Pan saw it as a “tipping point.” He had already confronted RFK’s vaccine skepticism as a state lawmaker, and he saw RFK’s role in The President’s administration as something that could upend everything he worked on to help Californians. At the state level, Pan authored legislation that restricted vaccine exceptions; that law went into effect the same year California saw a massive measles outbreak. California hasn’t had such a large outbreak since. But measles cases are surging across the country, and RFK Jr. has been behind much measles vaccine misinformation. That risks everyone, Pan says. As cases increase, risks rise even for vaccinated individuals. When RFK Jr. spread false claims about vaccines during his Senate testimony, people started calling Pan—reporters, community members—asking what he was going to do about all the health protections being undone by the federal government. “I said ‘OK, then I’m going to Congress, because that’s where the problem is now,’” he says. Pan is running for the House in California’s 6th District. That seat is currently held by Democrat Ami Bera, who is challenging a Republican in the redrawn 3rd District. “Evidence and reason and the facts” Pan isn’t the only STEM expert who was asked to take action in response to the The President administration. Manny Rutinel, a microbiologist, first responder, and environmental lawyer, says community members asked him to step into the political ring for both his position in the Colorado legislature and his run for Congress. Rutinel is now running to represent Colorado’s 8th district—a seat Democrats lost by less than 1 point in 2024. The incumbent, Republican Gabe Evans, is running again, and multiple race ratings have called a “toss up” for 2026. To Rutinel, the stakes of both his campaign, and similar campaigns across the country, are clear. “To be able to put a stop to the horrors of what the The President administration and RFK Jr. are doing to our government, our institutions, our services, we need to take back Congress,” he says. He already sees his science background, along with his working-class background, reaching potential voters. In the first quarter of 2025 fundraising, his campaign raised more than $1.1 million, with an average donation of $32. “The message is resonating,” he says. “We want folks who are standing up for what’s right, who are using evidence and reason and the facts to be able to put forth legislation that actually helps people instead of hurting them.” Problem-solving mentalities Jake Johnson has taught high school math for the past 20 years. He’s never been involved in politics, but now he’s running to represent Minnesota’s 1st Congressional District—a seat currently held by Republican Brad Finstad. He knows his reasoning could sound like a cliche, but he stands by it. “I genuinely have enjoyed solving problems for two decades,” he says, “and I think that sort of spirit and mindset is something that is maybe missing a little bit in Washington these days.” The neighbors in his district seem to like that problem-solving mentality, too. Johnson’s campaign raised $100,000 the first day it launched. In both Q2 and Q3 of 2025, he outraised Finstad; Johnson’s average donation is under $50. Though he’s completely new to politics, Johnson is hopeful about his campaign; he describes himself as a “crazy optimist.” He’s also buoyed by the other STEM candidates he sees running across the country, many who are—like him, Pan, and Rutinel—backed by 314 Action, a PAC that is specifically working with STEM candidates in response to the The President administration. “We live in such a time of polarization where people get their ‘facts’ from different sources [and] when we can’t agree on basic fundamentals, we can’t have powerful, thoughtful conversations as a community,” he says. “We’ve got to get back to establishing some truths as much as we possibly can.” Public confidence in scientists Already in 2026, 314 Action is working with more than 150 STEM candidates nationwide. Many of those races are for Congress: beyond Pan, Rutinel, and Johnson, the PAC is backing Bale Dalton, former chief of staff at NASA and first-time political candidate running for Florida’s 7th District; and Audrey Denney, an agricultural scientist and educator running in California’s 1st District, among others. There are also STEM candidates running at more local levels, like Nirav Shah, who was director of the Maine Center for Disease Control and Prevention during the COVID-19 pandemic, and who is now running for Maine’s governorship. Americans’ public trust in government has been eroding. Only 17% of Americans say they trust the government in Washington to do what is right “just about always” or even “most of the time,” according to Pew Research. But they still largely trust scientists. A January 2025 Pew Research study found that 77% of U.S. adults say they have a “great deal” or “fair” amount of coincidence in scientists acting in the public’s best interest. Public confidence in scientists has dropped slightly since the start of the pandemic, but scientists continue to rank higher in confidence than elected officials or business leaders. To 314 Action, the current debates in Congress over vaccines, healthcare, and more point to a need for more STEM candidates. The PAC both recruits candidates and reaches out to candidates already running; recently, it said that all of its 150-plus STEM candidates outraised their opponents in the last quarter of 2025. The PAC has faced criticism for taking and concealing donations from the American Israel Public Affairs Committee, or AIPAC, in a 2024 Oregon Congressional race; 314 Action pushed back against the reporting at the time before campaign documents became public. “As The President and RFK Jr. ramp up their attacks on science and health care, 314 Action’s mission to recruit and elect more Democrats with science backgrounds has never been more urgent,” Erik Polyak, 314 Action’s executive director, said in a statement. “We work with a broad political coalition of individuals and organizations laser-focused on advancing winning campaigns.” To some, it might not be obvious that STEM experts would enter politics. Members of Congress tend to come from fields like law or business primarily (though education and public service are also dominant backgrounds). But to Dr. Pan, and others in STEM currently running for office, the idea makes clear sense. Pan cites Rudolf Virchow, the father of modern pathology, who said that “politics is nothing but medicine at a larger scale.” “The nature of politics right now demands that we actually enter the political field and practice medicine on a larger scale, as Virchow said, because it’s under attack,” Pan says. “One of the major sources of the problem right now is the current administration and the current people in Congress.” View the full article

We know AI responses are probabilistic – if you ask an AI the same question 10 times, you’ll get 10 different responses. But how different are the responses? That’s the question Rand Fishkin explored in some interesting research. And it has big implications for how we should think about tracking AI visibility for brands. In his research, he tested prompts asking for recommendations in all sorts of products and services, including everything from chef’s knives to cancer care hospitals and Volvo dealerships in Los Angeles. Basically, he found that: AIs rarely recommend the same list of brands in the same order twice. For a given topic (e.g., running shoes), AIs recommend a certain handful of brands far more frequently than others. For my research, as always, I’m focusing exclusively on B2B use cases. Plus, I’m building on Fishkin’s work by addressing these additional questions: Does prompt complexity affect the consistency of AI recommendations? Does the competitiveness of the category affect the consistency of recommendations? Methodology To explore those questions, I first designed 12 prompts: Competitive vs. niche: Six of the prompts are about highly competitive B2B software categories (e.g., accounting software), and the other six are about less crowded categories (e.g., user entity behavior analytics (UEBA) software). I identified the categories using Contender’s database, which tracks how many brands ChatGPT associates with 1,775 different software categories. Simple vs. nuanced prompts: Within both sets of “competitive” and “niche” prompts, half of the prompts are simple (“What’s the best accounting software?”) and the other half are nuanced prompts including a persona and use case (”For a Head of Finance focused on ensuring financial reporting accuracy and compliance, what’s the best accounting software?”) I ran the 12 prompts 100 times, each, through the logged-out, free version of ChatGPT at chatgpt.com (i.e., not the API). I used a different IP address for each of the 1,200 interactions to simulate 1,200 different users starting new conversations. Limitations: This research only covers responses from ChatGPT. But given the patterns in Fishkin’s results and the similar probabilistic nature of LLMs, you can probably generalize the directional (not absolute value) findings below to most/all AIs. Your customers search everywhere. Make sure your brand shows up. The SEO toolkit you know, plus the AI visibility data you need. Start Free Trial Get started with Findings So what happens when 100 different people submit the same prompt to ChatGPT, asking for product recommendations? How many ‘open slots’ in ChatGPT responses are available to brands? On average, ChatGPT will mention 44 brands across 100 different responses. But one of the response sets included as many as 95 brands – it really depends on the category. Competitive vs. niche categories On that note, for prompts covering competitive categories, ChatGPT mentions about twice as many brands per 100 responses compared to the responses to prompts covering “niche” categories. (This lines up with the criteria I used to select the categories I studied.) Simple vs. nuanced prompts On average, ChatGPT mentioned slightly fewer brands in response to nuanced prompts. But this wasn’t a consistent pattern – for any given software category, sometimes nuanced questions ended up with more brands mentioned, and sometimes simple questions did. This was a bit surprising, since I expected more specific requests (e.g., “For a SOC analyst needing to triage security alerts from endpoints efficiently, what’s the best EDR software?”) to consistently yield a narrower set of potential solutions from ChatGPT. I think ChatGPT might not be better at tailoring a list of solutions to a specific use case because it doesn’t have a deep understanding of most brands. (More on this data in an upcoming note.) Return of the ’10 blue links’ In each individual response, ChatGPT will, on average, mention only 10 brands. There’s quite a range, though – a minimum of 6 brands per response and a maximum of 15 when averaging across response sets. But a single response typically names about 10 brands regardless of category or prompt type. The big difference is in how much the pool of brands rotates across responses – competitive categories draw from a much deeper bench, even though each individual response names a similar count. Everything old (in SEO) truly is new again (in GEO/AEO). It reminds me of trying to get a placement in one of Google’s “10 blue links”. Dig deeper: How to measure your AI search brand visibility and prove business impact Get the newsletter search marketers rely on. See terms. How consistent are ChatGPT’s brand recommendations? When you ask ChatGPT for a B2B software recommendation 100 different times, there are only ~5 brands, on average, that it’ll mention 80%+ of the time. To put it in context, that’s just 11% of all the 44 brands it’ll mention at all across those 100 responses. So it’s quite competitive to become one of the brands ChatGPT consistently mentions whenever someone asks for recommendations in your category. As you’d expect, these “dominant” brands tend to be big, established brands with strong recognition. For example, the dominant brands in the accounting software category are QuickBooks, Xero, Wave, FreshBooks, Zoho, and Sage. If you’re not a big brand, you’re better off being in a niche category: When you operate in a niche category, not only are you literally competing with fewer companies, but there are also more “open slots” available to you to become a dominant brand in ChatGPT’s responses. In niche categories, 21% of all the brands ChatGPT mentions are dominant brands, getting mentioned 80%+ of the time. Compare this to just 7% of all brands being dominant in competitive categories, where the majority of brands (72%) are languishing in the long tail, getting mentioned less than 20% of the time. A nuanced prompt doesn’t dramatically change the long tail of little-seen brands (with <20% visibility), but it does change the “winner’s circle.” Adding persona context to a prompt makes it a bit more difficult to reach the dominant tier – you can see the steeper “cliff” a brand has to climb in the “nuanced prompts” graph above. This makes intuitive sense: when someone asks “best accounting software for a Head of Finance,” ChatGPT has a more specific answer in mind and commits a bit more strongly to fewer top picks. Still, it’s worth noting that the overall pool doesn’t shrink much – ChatGPT mentions ~42 brands in 100 responses to nuanced prompts, just a handful fewer than the ~46 mentioned in response to simple prompts. If nuanced prompts make the winner’s circle a bit more exclusive, why don’t they also narrow the total field? Partly, it could be that the “nuanced” questions we fed it weren’t meaningfully more narrow and specific than what was implied in the simple questions we asked. But, based on other data I’m seeing, I think this is partly about ChatGPT not knowing enough about most brands to be more selective. I’ll share more on this in an upcoming note. Dig deeper: 7 hard truths about measuring AI visibility and GEO performance What does this mean for B2B marketers? If you’re not a dominant brand, pick your battles – niche down It’s never been more important to differentiate. 21% of mentioned brands reach dominant status in niche categories vs. 7% in competitive ones. Without time and a lot of money for brand marketing, an upstart tech company isn’t going to become a dominant brand in a broad, established category like accounting software. But the field is less competitive when you lean into your unique, differentiating strengths. ChatGPT is more likely to treat you like a dominant brand if you work to make your product known as “the best accounting software for commercial real estate companies in North America.” Most AI visibility tracking tools are grossly misleading Given the inconsistency of ChatGPT’s recommendations, a single spot-check for any given prompt is nearly meaningless. Unfortunately, checking each prompt just once per time period is exactly what most AI visibility tracking tools do. If you want anything approaching a statistically-significant visibility score for any given prompt, you need to run the prompt at least dozens of times, even 100+ times, depending on how precise you need the data to be. But that’s obviously not practical for most people, so my suggestion is: For the key, bottom-of-funnel prompts you’re tracking, run them each ~5 times whenever you pull data. That’ll at least give you a reasonable sense of whether your brand tends to show up most of the time, some of the time, or never. Your goal should be to have a confident sense of whether your brand is in the little-seen long tail, the visible middle, or the dominant top-tier for any given prompt. Whether you use my tiers of ‘under 20%’, ‘20–80%’, and ‘80%+’, or your own thresholds, this is the approach that follows the data and common sense. See the complete picture of your search visibility. Track, optimize, and win in Google and AI search from one platform. Start Free Trial Get started with What’s next? In future newsletters and LinkedIn posts, I’m going to build on these findings with new research: How does ChatGPT talk about the brands it consistently recommends? Is it indicative of how much ChatGPT “knows” about brands? Do different prompts with the same search intent tend to produce the same set of recommendations? How consistent is “rank” in the responses? Do dominant brands tend to get mentioned first? This article was originally published on Visible on beehiiv (as Most AI visibility tracking is misleading (here’s my new data)) and is republished with permission. View the full article

“The boomers are all about money. Gen X is like, ‘is it all about money’? Millennials are like, ‘where is the money’? And Gen Z is like, ‘what is money’?” That’s the conclusion Parks and Recreation star Amy Poehler came to on an episode of her podcast Good Hang with Amy Poehler. Since the episode aired last year, a clip has since been shared widely of her breaking down how each generation relates to money. She adds, “That’s my bad stand-up about it.” As the clip has gained traction online, on TikTok, actor Freddie Smith said that Poehler “totally nails it.” He then took it one step further and broke it down in terms of how each generation’s economy helped shape their attitude towards money. He says that for boomers, who lived through an economic boom, accumulating wealth was easy–or at least easier than it has ever been since. Baby boomers currently hold more than $85 trillion in assets, making them the richest generation by far. Therefore, they earn the title “all about the money.” Millennials, meanwhile, were handed a map and told the exact steps to follow to find the financial success their parents enjoyed. Only when they got there “we open up the treasure chest and there’s two f-ing coins in it,” explains Smith. Now, they’re all struggling through their millennial midlife crisis trying to come to terms with all the ways they’ve been sold a dream. Then there’s Gen Z. “They’re going to work and they’re getting paid direct deposit on Fridays and as soon as that money hits the account, it just goes automatically to their bills. They don’t actually ‘touch’ money” says Smith. Disillusionomics has come to define a generation that’s lost faith in the traditional markers of stability. What once defined financial success –a house, a family, retirement – feels increasingly out of reach for the youngest working generation. “This is such a true representation of what we’re all screaming about right now,” Smith concluded. “What is going ON?” (An explanation for Gen X doesn’t appear in the video, which doesn’t do much to beat the “forgotten generation” allegations.) Poehler’s soundbite emerged from a discussion with Parks and Recreation creator Mike Schur about shifting workplace environments, particularly in Hollywood—but also beyond. Schur suggests there’s a historical belief in Hollywood that if something good comes out of a chaotic environment, then it’s taken as validation: this must be the best way to produce great work. It’s similar to how the eat-sleep-work lifestyle–akin to the infamous “996” schedule–has recently gained momentum among certain tech companies. “So we better not try to fix the chaos,” he says. “When a rational person would think, ‘let’s fix the chaos’.” If the chaos is fixed, he suggests, people will still be able to produce just as good work—but without putting up with a toxic work environment as part of the deal. Schur says this attitude has improved in Hollywood in recent years. Poehler agrees, putting this down to a push from younger generations, “who have just reminded us that we don’t need to put up with behavior that we were used to putting up with.” Thanks to Gen Z’s penchant for work-life balance, “people are just a little bit less okay with having their lives ruined at work,” she says. When Schur, 50, and Poelher, 54, were coming up in Hollywood, “you put your head down and you try to survive,” Schur recalls. “The generation behind us, and especially the one behind that generation, looks at chaos and goes like—’oh, then no, thank you’.” View the full article

When Zillow launched 20 years ago, the home-buying process happened almost entirely offline. The company’s digital listings, combined with its innovative “Zestimate”—an estimate of a home’s value, based on the kind of data typically only available to real estate professionals—marked a turning point for the housing market. Zestimates weren’t exact representations of value, but they put power back in the hands of prospective buyers (to sellers’ and agents’ chagrin). Their near-instant popularity was an early “do your research” internet moment. Fast-forward to the present day, and Zillow, which has a $13 billion market cap and reports earnings after the market close on February 10, is once again under pressure. In partnership with First Street, a provider of climate risk data, Zillow had been publishing climate risk scores for the homes on its platform. But some homeowners have balked at their scores, and some have even sued. A home that First Street labels as high-risk for flooding, for example, can quickly drop in value. Zillow CEO Jeremy Wacksman, who joined the company in 2009 and became CEO in 2024, is walking a careful line. Zillow’s brand is associated with data transparency and consumer empowerment, but an increasing share of its revenue is tied to real estate agents who pay for software tools that help them virtually stage homes and message with open house leads. On the eve of the company’s Q4 2025 earnings, which analysts estimate will be $650 million in revenue for the quarter, 17.4% growth, Wacksman sat down with Fast Company to talk about how Zillow is navigating the competing demands of its two-sided marketplace, the affordability crisis, and more. This interview has been edited for length and clarity. Zestimates weren’t perfect in Zillow’s early days, but even so, they were never taken down. Yet in the case of First Street’s climate risk scores, you’ve moved them to a separate place; people have to click through and leave the site. Walk me through the thinking there. Jeremy Wacksman When you are focused on helping the consumer, the buyer, and seller, you want to try and provide as much information as you can with the right context. That’s what the Zestimate always has been. And we show our work, right? We show what our accuracy is. It’s not an appraisal, it’s not a professional opinion, but it’s a great starting point. Our philosophy is: Information needs context. And it’s hard for it to be perfect, but more information generally, when given the right context, is better than less. Climate is the same way. We still have climate data on our site. We’ve tweaked what we show on Zillow versus what we link out to third parties, just given some of the accuracy data on some of the [climate] data sets. Get an official appraisal and figure out what you want to do, but almost every buyer and seller appreciates that data to start that conversation. It feels like part of the reason people are so sensitive to potentially a bad climate score or a bad Zestimate is just because of the state of the housing market. Inventory is tight, sales are sluggish, prices are high. There is this growing consensus that we need to make owning a home more affordable. Where do you see that tension over affordability show up on Zillow? The most stark change over the last decade has been the percentage of buyers who start with an affordability question versus start by window shopping. When I first joined, everyone just wanted to window shop. That’s how you got started. You fell in love with a home, then you hired an agent, then you figured out your financing. Now that’s flipped. About half as many buyers will say, I don’t even want to go get excited. I want to understand, can I do this? That massive shift, I think, is the best representation of the affordability crisis. You’re right: We are in a period where homes are incredibly unaffordable. Home prices have run up nearly 100% in some markets from pre-pandemic levels. Average rates obviously ran up, too, so your mortgage per home gets even less affordable. That’s why you’re seeing transaction volumes at 30-year lows. In a normal housing market, 5.5 million to 6 million homes will trade every year. We’re at 4 million. Relative to the last couple of years, it’s getting a little better, but if you zoom out, it is still dramatically unaffordable. What are the leading indicators you’re watching to see if the market is on the cusp of change? One way to track the overall picture is [to look at] what you consider an affordable home for a median-income household. With a 20% down payment, 30% of your income [going toward] a mortgage payment is affordable. At the market’s worst, we were close to 40% on average, so almost nothing was affordable. Now it’s drifting back down. I think that’s what you watch for. Zillow has been investing a lot in AI. One of the features that probably a lot of people have seen is virtual staging, or the use of software to add furniture and design elements to a listing. How do you go from conception to execution on something like that? Virtual staging as a concept is not something we invented. What we invented was the ability to do it with really modest tools. We saw this technology coming; we saw 3D tours and interactive floor plans, all these things. But they were done with very high-end, very expensive cameras and media capture. How do you get that to an average real estate agent? That’s the problem. The average real estate agent has maybe a $100 360-camera or an iPhone. So we built the technology ourselves. That’s why you now see virtual staging on 5% or 10% of listings in some markets. The agents can easily capture some media; we can generate an interactive walk-through. Zillow is trying to go from being an ad-based business to supporting transactions directly. Do those tools generate the kind of leads that you’re interested in? We are fortunate to have hundreds of millions of people on Zillow every month, shopping, dreaming, starting their transaction, using us as a companion. But we only help a very small share of those people actually buy, sell, or rent a home. Virtual staging and interactive floor plans and 3D tours: Those are tools for a listing agent to go win more business. But we spend as much time on software for agents to run their business, whether that’s book their appointments, schedule showings, run their offer processes. Sometimes, the best use cases of AI are just making that more efficient. I’ll give you an example. Agents are sending hundreds of messages a day to all their clients. Well, that’s something that generative AI can help with. We’re now sending millions of what we call smart messages. That’s something that sounds very simple, but think about the productivity gain. It helps them be a better guide, which helps them convert more business, which helps Zillow convert more business. Zillow is a partner to ChatGPT, which has been starting to encourage e-commerce through its interface. Some shopping categories are pretty simple. It’s easy to imagine, for example, that someone is going to go to ChatGPT and say, “What are the best pliers?” But a home is a little bit different, right? Buying a home and selling home, for sure, it’s a very different category than most verticals. The most interesting stat to me is that as technology gets more pervasive, and as data gets bigger, buyers and sellers feel even more paralyzed, and they want even more help. The percentage of people who say, “I want a full-service professional to help me” is higher now than it was before the internet, before the smartphone. You could think about ChatGPT and Gemini as a source of traffic for a vertical like ours, or as a technology we can build into our experience. We think the latter is really where it’s going to go. The average buyer spends six to nine months shopping, sometimes longer, sometimes years on and off. In this category, you are ultimately making a set of trade-offs between what you can afford, what’s available at the time, and all of your lifestyle situations—the commute, the school, the neighborhood. You don’t get to just pick from a shelf of endless supply. That’s why you end up hiring really good people to help you figure out how to make those trade-offs and figure out how to make sure you don’t make a financial decision that will cost you, because it’s the biggest financial decision you’ll ever make in your life. When it comes to figuring out the mortgage, figuring out which house to buy, figuring out how to sell your house, we think it will be this interweaving of professionals, professional software, buyers and sellers. And now you’re going to see LLMs [large language models] weave into all that. Twenty years in the future, what’s the one thing that will be really different about the search and the one thing that will be really different about the actual transaction? This category doesn’t work like any other category on your phone. You open your phone and you look at shopping and ride-hailing and travel and even wealth management—so much is digital. Real estate doesn’t work that way yet. We’ve made a bunch of progress, but it doesn’t. It’s very analog. It’s very paper based. It’s very asynchronous. We survey consumers every year, and the stat that always sticks out to me is that more than half of homebuyers cry during the process. I’m hopeful that in 20 years, hopefully in less than 20 years, we [can make Zillow into] more of a one-stop shop. It’s smart. It’s personal. It’s just all there for you. View the full article

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