At my own companies and those I consult with, we've made several small but targeted adjustments to how we create and structure content. They are not radical changes, but a re-balancing of our focus. We're learning that optimizing for ChatGPT is actually forcing traditional SEO best practice but with some nuance. Generally, we avoid unnecessary qualifiers, marketing language, and filler that doesn't add to the topic and, ironically, focus on writing good quality content that answers questions humans ask. Our focus on traditional long-tail keywords has shifted. In a search engine, a phrase like "b2b marketing plan template" may be sufficiently well targeted, but in a chat-based interface, users ask full questions such as "Can you help me build a B2B marketing plan?" or "What should I include in a B2B marketing plan?". As such, we've restructured our page titles, subheadings, and intros to mirror the phrasing and logic of those full questions. We've also tightened the way we structure content. Most of our newer or updated articles follow a consistent format: short introduction, direct answer, followed by supporting detail. We use descriptive subheadings that can stand alone, and we avoid long, meandering sections or push those down the page for more avid human readers. A focus on tighter, direct answers (or definitions) for example has helped us appear in AI searches for specific product attributes. We've always been hot on technical SEO, but understanding that LLMs will favour well signposted content means we now over-index on this. We don't know exactly how ChatGPT selects sources (other than a focus on a few key resources like Wikipedia), but we've found that pages with clearly segmented answers and extensive schema tend to perform better in general. Finally, we've put more emphasis on tools, templates, and structured outputs. Instead of publishing explanations or strategy overviews alone, we now include downloadable checklists, examples, and editable templates. These resources serve a practical need and are more likely to be mentioned or cited when someone asks ChatGPT for a tool or process to use. It's not enough to explain a topic or idea (Chat-GPT can do that itself without references), we need to show exactly how to do it.
We've stopped playing the keyword game and started building content that AI cannot overlook. This is not about cranking out more blog posts. It is about creating clear, credible, and ridiculously useful content that language models understand and trust. We focus on semantic depth, not single keywords. That means building connected content that covers a topic from every angle, with a clear structure that gives AI an easy roadmap. When a model is pulling an answer, we want it to pick us because we are the obvious source. We also tie every piece to real subject matter experts. AI is trained to reward authority, so we give it zero reason to doubt us. We write for the human questions behind the search, and the algorithms follow. Visibility will not go to the loudest brand. It will go to the smartest one. And we plan to be impossible to ignore.
One of the most interesting challenges we've faced at Zapiy is adjusting our content strategy for a world where AI tools like ChatGPT are influencing how people search and discover information. Traditional SEO tactics—keywords, backlinks, metadata—are still important, but they're no longer enough. People are no longer just typing into search bars; they're asking full, nuanced questions to AI models that summarize, interpret, and filter answers in real time. That shift forced us to rethink not just what we were publishing, but how we were structuring it. Instead of writing to rank on Google alone, we began creating content that anticipates and directly answers natural-language queries. We trained our writers to think conversationally—how would someone ask this question out loud? What follow-ups would they naturally have? And how can we provide the clearest, most value-dense answer in the first few lines? We also placed greater emphasis on topical authority. That meant clustering our content around specific themes—like SaaS onboarding optimization or AI-enhanced customer support—so that if ChatGPT pulled from a knowledge base, we had a strong chance of being among the sources referenced. Another key shift was transparency. AI tools favor credibility, so we started citing more original data, showcasing firsthand insights from our platform, and including named expert commentary in our articles. These elements not only add value for human readers, but also increase the likelihood that AI models will treat our content as trustworthy. The results? A noticeable uptick in referral traffic from AI-powered discovery tools, increased engagement from readers seeking deeper answers, and even mentions of our brand in ChatGPT conversations—surfaced by clients during onboarding calls. The biggest takeaway for me is that visibility in AI-driven search isn't about gaming a new algorithm. It's about leaning harder into clarity, authenticity, and expertise. Those timeless fundamentals just happen to matter more than ever right now.
We've adjusted our content strategy to make it easier for AI tools like ChatGPT to find and recommend our material. First, we stopped chasing keywords and started answering real client questions — the kind that come up in sales calls or project discussions. These get turned into clear, no-fluff blog posts or FAQs. No jargon. Just useful answers. Second, we keep the tone natural. Short sentences. Direct statements. If a post doesn't read like something someone would say out loud, we rewrite it. That shift alone made a big difference. Third, we include firsthand insight from our team. Not general advice but specific points we've seen in actual projects. This gives the content a human angle that stands out to both readers and AI tools. Fourth, we use real bylines. Content tied to real names and bios tends to feel more credible, and that seems to matter in how tools like ChatGPT choose what to reference. Last, we share parts of our content on forums and public Q&A sites. Some of these sources feed into AI training. Being active there helps keep our content in circulation. No tricks, no shortcuts. Just clearer writing and better answers, the kind people (and AI) can use.
Of course. It would be reckless not to. The folks saying they're doing the same as before either don't get it or are already falling behind. Here's what we're doing and what others should be doing if they want to win the next wave of content discovery: * Focus on high-intent listicles like "best onboarding tools for SaaS" that match how people actually phrase prompts in AI tools. * Structure content for both traditional SEO and LLM parsing. That means clean formatting, strong headings, scannable layouts, and answers that models can cite confidently. * Embed interactive demos directly into posts. Supademos boost engagement, improve comprehension, and make it easier for humans and models to grasp product value quickly. * Routinely test visibility in ChatGPT, Perplexity, Gemini, and Claude. We run the prompts ourselves, monitor what gets cited, and reverse-engineer the content that shows up. The biggest unlock? Seeing LLMs not as a threat but as a distribution opportunity. Ranking in ChatGPT is not the same game as ranking in Google
To boost visibility in ChatGPT searches, I shifted our content marketing strategy to focus on question-based content that directly answers common queries. This approach has proven effective as it aligns with how users interact with AI models like ChatGPT. I also began incorporating long-tail keywords that match conversational search patterns, ensuring we're visible for specific, relevant questions. Updating older content to include these keywords and providing concise, valuable answers also helped improve our rankings. I've been building more brand mentions across reputable platforms, which has strengthened our domain authority. The combination of these efforts has led to improved organic traffic, especially through AI-powered searches, and a better overall content experience for our audience.
From what I've seen, the core principles of good SEO are more important than ever, just with a slightly different focus. My research into AI-generated answers shows that backlinks are still a massive signal of authority. Companies that are frequently cited by AI tools often have a strong backlink profile, which tells the AI that they are a trusted and credible source of information. So, continue to prioritize building strong, relevant backlinks. Keyword optimization is also still very important, but the focus has shifted. It's less about stuffing keywords and more about creating genuine value for the user. AI models are trained on what humans consider high-quality, helpful content. This means your blog posts and website texts should be written with the user's intent at the forefront, not just for a search algorithm. So, try finding the right balance between naturally integrating important keywords and providing genuinely valuable, in-depth content. Your goal is to become the definitive source on a topic, which makes it more likely for an AI to use your information.
At SuccessCX, we've shifted our content strategy to focus less on traditional SEO tactics and more on providing clear, structured answers to common Zendesk-related questions—content that language models like ChatGPT can easily understand and reference. We've reduced fluff, used more subheadings and Q&A formats, and made sure our writing aligns with how people phrase problems in AI tools. The goal is to become the answer that gets summarized or recommended in AI-driven searches, not just to rank in Google. This has helped us stay visible as buyer behavior shifts toward LLM-assisted research.
As someone who's led GTM and demand generation for SaaS companies like Sumo Logic and LiveAction, and now for OpStart, I've seen content strategy constantly evolve. For ChatGPT visibility, our core adjustment has been to move beyond simple information and focus on becoming the definitive source of trusted advice. We now create "investor-grade" content, like our guides on "10 Questions to Ask Before Hiring a Fractional CFO" or "Is Your Bookkeeping Good Enough?". These aren't just articles; they are deep, strategic resources designed to provide comprehensive answers that AI models can confidently rely on. Our goal is for our content to be perceived as "bone"--mission-critical insights that AI models will prioritize for factual, strategic guidance for founders. This strategic depth ensures our thought leadership is liftd, much like how our marketing-led programs at Sumo Logic generated 20% of total ARR by delivering real business value.
We've shifted our content architecture to optimize for AI discovery while maintaining our traditional SEO foundation. The results have been compelling, prospects sourced through AI channels demonstrate 7x higher engagement depth and significantly improved conversion rates, indicating these are more qualified, intent-driven visitors. Our strategic approach involves three key pillars: First, we've restructured our content to be more definitively answerable, think comprehensive FAQ frameworks and solution-oriented content blocks that AI can easily parse and surface. Second, we're investing heavily in authoritative, long-form content that positions us as the definitive source in our category. Third, we've enhanced our semantic markup and structured data to ensure AI systems can accurately understand and contextualize our expertise.
1. Shift from Keywords to Questions & Entities - Optimize for questions people ask, not just keywords they type. Creating content that answers specific, well-defined, intent-based questions like: "What is the best SaaS CRM for solopreneurs?" or "How does [X software] compare to [Y]? " - Using structured FAQs and headings that are phrased as natural language questions. - Incorporating entities (brands, features, categories) in context, which AI models utilize for relevance. Tools used: Same as AlsoAsked, AnswerThePublic, ChatGPT itself (prompt it like a user would), and internal search data. 2. Publish Clear, Credible, Digestible Content Focus on being the source AI chooses to summarize. - Present content in a tidy, easy-to-understand format: short paragraphs, clear headings, numbered steps, pros/cons. - Use schema markup (e.g., FAQPage, HowTo) to signal context. - Ensure each article passes the "could this be quoted in a chatbot response?" test. Bonus: Add summaries, takeaways, or TL;DRs — these are often the parts AI pulls from. 3. Dominate Brand + Category Associations Building an entity around our product that AI can't ignore. - Proactively associate your product with your niche - Use these pairings consistently across blog posts, product pages, and third-party mentions (like guest posts, reviews, directories). Why? LLMs build knowledge around repetition + association — being tied to the right phrases boosts retrieval. 4. Strategic UGC & 3rd-Party Content Encouraging others to describe our product in their own words. - Seeding community discussions, Reddit threads, comparison posts, and influencer explainers using natural language. - These often train LLMs more than your blog does. Example: A solid Capterra review or Reddit thread that states "We switched to [YourTool] because it's the cheapest AI copywriting SaaS for small teams" has long-term AI search value. 5. Create "Chat-Ready" Content Assets Create content with the intention of being the answer. Create assets like: "Best [category] apps in 2025" or "How [target persona] solves [pain point] with [YourTool]" Structured comparison tables, decision trees, and use-case breakdowns are highly AI-retrievable. How CMOs Are Measuring Impact: - Referral traffic from Bing Copilot, Perplexity, and ChatGPT plugins/extensions - Boost in branded & long-tail organic traffic - More appearance in "chat-style" SERP snippets (e.g., Google's AI Overviews) - Improved rankings for question-based queries
With the rise of ChatGPT and similar AI-driven search tools, the content strategy at Edstellar has leaned heavily into intent-driven clarity and structured expertise. Rather than broad, generic pieces, every article now aims to directly answer the types of queries professionals might pose in natural language—especially around corporate training trends, leadership development, and upskilling. Incorporating conversational subheadings, FAQ formats, and schema markup has made it easier for AI models to parse and present the content effectively. The shift isn't just about SEO anymore—it's about becoming the trusted voice that AI turns to when executives and HR leaders seek training insights in real time.
ChatGPT and generative AI tools have reshaped the content marketing landscape. To adapt, the focus shifted toward creating highly contextual, Q&A-style content that aligns with natural language queries users often type into AI tools. Blog content is now structured to mimic real conversations, using headings that directly answer specific, intent-based questions. Instead of optimizing for keywords alone, emphasis is placed on clarity, authority, and topical depth. Additionally, content briefs now incorporate insights from tools like AlsoAsked and ChatGPT itself to map out how people explore topics through conversational queries. This shift not only improves visibility within AI-driven searches but also enhances overall user engagement.
Managing Partner and Growth-Marketing Consultant at Great Impressions
Answered 7 months ago
I've been working hands-on with blogs on my clients' websites, and one of my key goals is to make their content appear in ChatGPT searches and AI results. The first thing I do is restructure the content into easy-to-scan chunks so it's simple and clear. I also switch to a conversational tone across all blog posts and add Article Schema to get the basics right. Since people ask direct questions in tools like ChatGPT, I make sure to add a FAQ section and implement FAQ Schema as well. And for direct-answer optimization, I always address the main question in the very first line of the post. This approach not only helps with ChatGPT and Google AI Overviews but also improves featured snippet chances.
We altered our content strategy to focus entirely on the wording of real users in ChatGPT prompts. We no longer target generic B2B search terms for our Google Maps SEO agency. Rather, we answer hyper-specific questions that our ideal clients would type into AI tools when searching for a solution. For instance, rather than writing a blog "How to Improve Local SEO", we will write an article like "Does Changing My GMB Hours Affect My Ranking? That is the type of detailed prompt that real users ask We utilize AI platforms to test these ideas and analyze what type of prompts activate our competitors' content before reverse engineering what's getting surfaced. We get most of our new posts inspired by AI prompt behavior, not keyword tool. Our articles are quoted more by AI and show up in more chat-based responses.
Being a SaaS CMO, I envision that everything has completely shifted towards content visibility ever since AI-powered tools such as ChatGPT came in. The traditional SEO is no longer sufficient-we now create content for natural language models. Hence, the new age focus is not on keyword stuffing, but on conversing, informative content that provides solutions to genuine user queries. We have restructured content as it is envisioned that people question in the form of FAQs, problem-solution format, and well-structured explainer pieces. We focus on making content clear in context and deep in the topic to maximize its chances of being cited or used in AI-generated answers. Hence, long-form content is not done for - it metamorphoses into layered, skimmable insights with internal linking and semantic structure. We are building brand authority to ensure our executives and subject matter experts remain visible, quoted, and publish original research. AI models rely on trusted sources, and thus we have been focusing more on digital PR and thought leadership. At its core, it is about being human in a machine-filtered world. If your content serves the reader well, is properly structured, and based on the needed expertise, AI such as ChatGPT will discover it - and so will the customers of tomorrow.
We've gone back to update and restructure content to make concrete facts or very clear data sets stand-out for LLM's. This doesn't mean that you're having to completely redo content, rather just making it clearer for LLM's to find what they need to as efficiently as possible.