Your competitors are named in Google AI Overviews when a pet owner asks about joint supplements for a senior dog. […]
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Your location pages rank on page one. Your Google Business Profiles are claimed and optimized. And yet, when a renter […]
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What do you do when inspiration for your umpteenth blog post is low? What’s the solution to writer’s block or a general lack of ideas? Every writer will encounter a lack of inspiration from time to time. You’ll be staring at your screen, not knowing what to write about. Nevertheless, you are determined to write those blog posts regularly. Today, AI tools like LLMs or Yoast AI Content Planner can spark ideas when you’re stuck. Luckily, there are many other ways to get inspired!
If your blog has a comment section for your audience to leave comments or you have a contact form, you’ll receive feedback. While most of the reactions you get will just be positive or negative statements, you might receive questions as well. Perhaps some of these questions are easy to answer in a reply, but other questions will be off-topic or need elaboration. You can also send a questionnaire to your readers to gather input and feedback. Those kinds of questions are excellent starting points for your next post. You could try keeping a list of relevant questions whenever you come across them, so you have a place to look when inspiration is low.
Read more: How to handle comments on your blog »
Google Search Console is still one of the best tools to find new blog post ideas. It shows you the exact search terms people use to find your site. This helps you spot topics your audience cares about, but you haven’t fully covered yet.
The Performance Report is where you’ll find these insights. It lists the search queries that bring visitors to your site, along with clicks, impressions, and average rankings. Look for queries where your content ranks but doesn’t fully answer the question. For example, if people find your site by searching “how to keep toddlers busy without screens” but you don’t have a dedicated post on that topic, it’s a clear sign to write one.
If you use Yoast SEO with Google Site Kit, you can access Google Search Console data directly in your WordPress dashboard. This integration saves time because you don’t have to switch between tools. Just open the dashboard, click on the Yoast SEO tab, and open the General section. You’ll see your top search queries and performance metrics right there.
While tools like Ahrefs or Semrush offer deeper competitive analysis, Google Search Console provides direct data from Google. It’s free, reliable, and still one of the best ways to find information about what your audience is searching for. Use it alongside Yoast SEO’s tools to ensure you cover all the topics that matter to your readers.
You know you need to publish, but deciding what to write about can sometimes take forever. To help you overcome this, we built the Yoast AI Content Planner. It scans your existing content, identifies gaps, and suggests five relevant blog ideas.
When you open a new post, Yoast SEO analyzes your site’s content and generates ideas tailored to your niche. These aren’t generic suggestions because they’re based on what your audience is already reading and what’s missing from your blog. For example, if you run a food blog and have written about meal prep but not quick vegetarian lunches, that might suggest that topic.
Once you pick an idea, Yoast SEO creates a structured draft with a suggested title, headings, and even a meta description. You get a clear outline so you can start writing immediately. If the first set of ideas doesn’t feel right, you can generate a new batch with one click.
Yoast AI Content Planner is included in all our Yoast SEO Premium products. It’s designed for anyone who writes regularly and wants to publish consistently without running out of fresh ideas. This tool helps you create content that fills real gaps for your audience. Give it a try the next time you’re stuck for ideas.
Your keyword research document contains many potential blog ideas. But don’t just pick a keyword and start writing, because digging deeper helps you find the best angle.
What’s the search intent behind a keyword? Are people looking for a how-to guide or an opinion piece? Tools like Yoast SEO’s Semrush integration, or Google’s autocomplete can help you figure this out. Don’t forget to check what appears in Google’s AI Overviews or AI Mode answers when you research these keywords and topics.
For example, if your keyword is “best running shoes for flat feet,” ask:
Each of these could be its own post:
This way, you’re not simply writing about a keyword, but answering the exact question your audience is asking. Plus, if you set up Wincher in Yoast SEO, you can track how well your posts perform for these keywords over time.
Pinterest is still a useful place to find inspiration, especially if your blog covers visual topics like food, DIY, fashion, travel, or home decor. But it’s not just for pretty pictures, because you can use it to spot trends and gaps in your niche. Search for keywords such as [blog post ideas], [blog ideas], or [what to blog about]. To get even more inspiration fast, include your niche in your search. For example: [blog post ideas for parents], or [blog post ideas for lifestyle bloggers]. Be sure to check the top-pinned post for the topics.
It’s a good idea to be cautious as well, because Pinterest is clickbait heaven. Falling into the trap of quantity over quality is easy. Keep your focus, or you’ll lose track of time.
To be clear, the Content Idea Generator won’t give you ready-to-go article ideas. At best, it will point you in the right direction; at worst, it will provide you with a few good laughs to clear your head. For example, you can enter the term [house plant]. Content Idea Generator could give you the following title: ‘The 15 biggest house plant blunders’. A content idea about [wine]: ’17 unexpected uses for wine’. Enter [baby] and a suggestion that might come up: ‘20 ideas you can steal from babies’.
So, while the Content Idea Generator won’t give you what you want immediately, it’s sure to get your creativity flowing. Taking the previous examples, you could expand on that and get the following blog ideas:
AI tools and chatbots like ChatGPT, Claude, or Gemini can help when you’re stuck. But don’t just ask for generic ideas, and always provide context about your blog and your audience. Here’s how to get the most out of them:
Ask for specific angles, so instead of “Give me blog ideas about parenting,” try:
Always try to refine vague ideas, so if you have a broad topic, ask AI to narrow it down. For example:
Reverse-engineer competitors by feeding AI a competitor’s blog URL and asking:
Try to avoid producing commodity content, because AI often suggests ideas that feel generic or overdone. Always add your own perspective, your experience, or data, as this can truly make your content stand out from the crowd. For example, if AI suggests “10 tips for better sleep,” make it unique:
Days Of The Year is a website that offers inspiration for all kinds of blogs. This website collects all the fun, bizarre, and nice holidays the world has to offer. You can easily lose a couple of hours while scrolling through that site. Keep your pen and notepad at hand, though, because it is bound to give you tons of inspiration. There are days available for every niche. Are you a fan of mythical creatures? April 9th is ‘Unicorn Day’. There’s also a ‘Leprechaun Day’ and a ‘Howl at the Moon Day’. May 25th is ‘Towel Day’, which can give travel bloggers and lifestyle bloggers ideas for posts. Think of blog posts such as: ‘How to keep your towels soft’ or ‘With this information you will never buy the wrong towel again’.
The internet is full of inspiration for blog ideas, and there are many places to look. Perhaps you follow other bloggers who inspire you. A great way to come up with blog post ideas is to read other posts or just scroll through post feeds. Similarly, you can join Facebook groups related to your niche or for bloggers. Discussing ideas with fellow bloggers will surely get your creative juices flowing! Make sure you do not copy people’s ideas, though, and give credit where credit is due.
Current events can give you great blog ideas if you connect them to your niche. The trick is to link the news to what your audience cares about in a way that feels natural. For example, if you run a parenting blog, a new study on screen time could inspire a post like “How much screen time is too much? What the latest research says.” If you write about personal finance, a change in tax laws might lead to “Three ways the new tax rules affect your savings (and what to do about it).” The key is to add value, so don’t just repeat the news, but explain what it means for your readers.
Set up Google Alerts for keywords related to your topic to stay updated. When something relevant pops up, think about how it affects your audience. For instance, if you blog about sustainable living, a new recycling policy could lead to a post titled “How to adjust your recycling habits under the new rules.” Avoid sensitive topics unless you can handle them thoughtfully. If you do cover them, focus on helping your readers, not just exploiting the trend. The goal is to turn news into high-quality content that fits your blog’s purpose.
Situations from your own work could also be great inspiration for blog posts. You can write about things that happen in your day-to-day life, and how you go about them. Or even about what you do if your clients or colleagues are faced with a certain problem. It’s quite possible that others encounter the same problem and are seeking input.
If you write about real-life situations, you should always make sure that you respect the privacy of your clients, friends, or colleagues and ask for permission to use their cases on your blog. For example, a therapist with a blog offering mental health tips might want to use examples from their practice. In that case, it’s vital to change names and details to protect clients’ privacy and the practice’s future!
Sitting at your desk for too long can drain your creativity. If you’re staring at a blank screen, step away and do something that shifts your focus. A short walk, or even washing the dishes, can help reset your mind. The goal isn’t to force ideas but to give your brain space to wander. Often, the best thoughts come when you’re not trying too hard.
If you need a more structured break, try a ten-minute brainstorming sprint. Set a timer and ask yourself: “What are twenty blog ideas about [your topic]? Make five weird, five practical, and ten in between.” Don’t overthink it and just write down whatever comes to mind. When the timer goes off, pick the most interesting idea and freewrite about it for another five minutes. This exercise forces you to think outside your usual patterns and often leads to unexpected angles. When you return to your desk, you’ll likely feel more focused and inspired.
The solution can be very simple: some days, you have plenty of blog post ideas, some days you don’t. So, prepare for days when you have no inspiration and keep a list of blog ideas. It doesn’t matter whether it’s a list on your mobile phone or on paper. Every time you have a good idea, write it down. You can use these ideas on days you’re feeling uninspired.
Don’t let a lack of inspiration derail your publishing schedule. Whether you use Yoast AI Content Planner or take a break to clear your head, there are always ways to find new topics. The best approach combines structure and creativity, using tools to generate ideas, then refining them with your own insights and voice.
The next time you’re stuck, pick one method from this list and give it a try. Maybe it’s deep-diving into your keyword research or setting a timer for a quick brainstorming session. Each of these strategies can help you break through writer’s block and keep your content flowing.
Keep reading: SEO copywriting: the ultimate guide »
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If you run marketing for a multi-location campground or RV resort group, you have likely watched the same pattern repeat. […]
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A prospective member opens ChatGPT and types “best private golf club near me.” An event planner asks Google’s Gemini-powered Ask […]
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Today, we’re excited to announce the launch of new Search Generative AI performance reports
in Search Console, including dedicated reports for Search and Discover, to help you understand your
site’s visibility within generative AI features on Search.
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Referral traffic is down, and smaller publishers are absorbing the sharpest declines. Some have seen traffic drop by as much as 60 percent over the past two years. That is not a temporary dip from an algorithm update. It is a directional change in how audiences find and consume content online.
The driving force is straightforward: AI-generated answers are satisfying queries that used to produce clicks. Users get what they need from a synthesized summary and never visit the source. The publisher who ranked for that query, optimized for it, and built content around it gets nothing.
Understanding why this is happening and what to do about it is urgent for any publisher or content-driven brand relying on search as a primary traffic source.
It used to be that answering a search query meant earning a click. A user typed something into Google, saw a list of results, and visited a site. Publishers built their entire distribution model around capturing those visits.
AI Overviews, ChatGPT, Perplexity, and similar platforms have disrupted that chain. Instead of surfacing a list of links, they deliver a synthesized answer assembled from multiple sources. The user gets what they came for. The click never happens.
The data on this is significant. According to Similarweb, zero-click searches increased from 56 to 69 percent between May 2024 and May 2025. For queries where a Google AI Overview appears, the zero-click rate hits between 80 and 83 percent. Pew Research found that users clicked on results only 8 percent of the time when AI summaries appeared, compared to 15 percent when they did not. That is a nearly 47 percent relative reduction in click-through from the presence of AI summaries alone.
Smaller publishers absorb the impact more severely than larger outlets. Chartbeat data reported in March 2026 breaks this down clearly: small publishers with fewer than 10,000 daily page views saw 60 percent declines in search referral traffic over two years. Medium publishers with up to 100,000 daily page views saw 47 percent declines. Large publishers saw 22 percent declines.
Scale and brand recognition provide a partial buffer, but even major names have not been immune. Business Insider saw organic search traffic fall 55 percent between 2022 and 2025. HuffPost lost half of its search referrals over the same period.
Ranking at the top of search results used to mean something close to guaranteed visibility. That relationship has broken down. Visibility no longer guarantees influence.
The formula that drove publisher growth for the past decade was consistent: create content that ranks, capture organic traffic, monetize that traffic. SEO was the engine and search was the distribution channel.
That engine is still running, but far less reliably than before. Reuters Institute survey data from early 2026, covering 280 media leaders across 51 countries, found that most publishers now expect to put less effort into traditional Google search this year. Media executives worldwide fear search engine referrals will fall another 43 percent over the next three years.
The publishers navigating this period well are not the ones with the best keyword strategies. They are the ones with direct audience relationships that do not depend on any algorithm to survive. Strong email lists, consistent social presences, and loyal readerships keep them stable when search referrals drop. Publishers without those foundations are feeling the decline most acutely.
Continuing to optimize exclusively for traditional search while ignoring how AI discovery works is a compounding mistake. The channel has already shifted, and waiting for it to shift back is not a strategy.
The response requires action on two fronts simultaneously: protecting your direct audience relationships and adapting your content for how AI surfaces information.
Build owned channels as your primary distribution. Email is the most durable investment you can make. A subscriber who gets your content in their inbox is completely insulated from AI summaries, algorithm changes, and shifts in how Google decides to handle any given query type. The data supports this: publishers sent 28 billion emails in 2025, reaching over 255 million readers, with average open rates exceeding 41 percent. That outperforms most social media content by a significant margin. Build your list. Send consistently. Give people a genuine reason to keep showing up.
Social media supports direct distribution, but the goal is consistent presence that builds recognition, not chasing reach. Regular posting across the platforms where your audience already spends time keeps you visible through channels that do not depend on search referrals. Chartbeat data shows social referrals were flat or slightly up in 2025, with X up 15 percent and Facebook up 9 percent year over year. Those are not transformative numbers, but they represent channels that are holding while search declines.
Earned media and press relationships matter here too. Coverage in credible third-party publications builds the kind of authority signals that make your content more likely to be cited in AI-generated responses, which is the new version of organic discoverability.
Optimize your content for AI citation, not just search ranking. There is a real upside to the AI traffic story that most coverage misses. Brands cited in AI Overviews earn 35 percent more organic clicks and 91 percent more paid clicks than non-cited brands for the same queries, according to Seer Interactive data.
Being cited by AI systems is not a consolation prize. It is becoming a primary visibility driver.
Clear structure, direct answers to specific questions, and accurate, current information make your content easier for AI systems to pull from and surface. Practical, utility-focused content (guides, how-to articles, explainers) generates more page views per article from AI referrals than other content types, suggesting that practical resource content is more likely to earn a citation from an AI system.
Think about what questions users in your category are asking AI tools right now. If your content is not appearing as a cited source for those queries, that is a gap to close through targeted content work. Google added dedicated AI search tracking to Search Console in mid-2025: use the Search Appearance filter to see your performance in AI Overviews specifically, and let that data guide your content priorities.
Monitor your AI presence actively. Check regularly what major AI platforms say when users ask questions your content should be answering. Track changes over time. If you are being misrepresented, omitted, or replaced by less accurate sources, you have a visibility and reputation problem that content strategy needs to address. Platforms like Writesonic have a sentiment feature to help gauge how your brand or a client’s brand is being portrayed.
The 60 percent traffic decline some publishers have experienced did not happen overnight, and it has not reversed. AI platforms generated over a billion referral visits in mid-2025, a 357 percent year-over-year increase. Even so, AI referrals still account for less than 1 percent of total web traffic, because the volume of search traffic absorbed by AI is so large.
The brands and publishers that adapt their distribution mix now, investing in owned audiences while making their content AI-discoverable, will be in a far stronger position over the next two to three years than those holding out for a search traffic recovery that may not come.
Not gone, but fundamentally changed. Certain query types will always generate clicks: transactional searches where users intend to purchase, navigational searches for specific sites, and research queries requiring depth beyond what AI summaries provide. The shift is in emphasis: optimizing for AI citation and direct audience relationships is now a higher priority than chasing organic keyword rankings, particularly for smaller publishers without the domain authority to compete in contested niches.
Practical, utility-focused content generates more AI referrals than editorial or opinion content. Guides, how-to articles, and detailed explainers are more likely to earn AI citations. Transactional content tied to specific purchase intent also continues to drive clicks because AI summaries do not fully satisfy the need to complete a purchase.
In Google Search Console, go to Performance, then Search Results, and use the Search Appearance filter to select AI Overviews. This shows impressions and clicks specifically for queries where AI summaries appear. Impressions holding steady while clicks decline is the clearest signal of AI Overview impact.
Yes. AEO and traditional SEO share significant overlap: content structure, technical optimization, and authority building all remain relevant. The shift is in emphasis. Clear structure, direct answers, factual accuracy, and third-party credibility signals are the factors that most influence AI citation.
The 60 percent decline in search referral traffic for smaller publishers is not a fluctuation. It is a signal of where information discovery is going. The publishers still performing have strong brands, direct audience relationships, and content that AI systems want to cite.
Building those same assets is the path forward for any content-driven brand. Diversify your distribution, optimize for AI discoverability, and treat owned channels as your foundation rather than your backup plan.
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SEO has expanded beyond conversion into the operational side of the business, because that’s where the signals AI engines increasingly rely on get created.
When AI systems decide whether to recommend a brand, they evaluate post-sale signals like onboarding accuracy, performance outcomes, integration depth, and customer advocacy. Most of that information lives inside sales, support, customer success, and delivery teams, not inside marketing calendars or publishing workflows.
That creates a major SEO opportunity. Much of the evidence that could influence AI visibility still dies in CRMs, support platforms, and quarterly retrospectives rather than being codified into machine-readable form.
Bots and algorithms need to understand your business: what you offer, how you deliver it, and what customers think about it, in as much detail as possible. Here’s how.
OPIDC stands for onboarded, performed, integrated, devoted, and codified.
The first four stages map to the customer-success lifecycle most service and SaaS businesses already run: onboarding, adoption, retention, and advocacy.
Codified is the addition. It describes the work of turning post-sale experiences into machine-legible evidence that AI systems can evaluate, compare, and recommend.
| My term | What everyone else calls it |
| Onboarded | Onboarding |
| Performed | Adoption, first value, time-to-value |
| Integrated | Retention, expansion, stickiness |
| Devoted | Advocacy, loyalty |
| Codified | No established term |
The first four stages — onboarded, performed, integrated, and devoted — describe what the business already does as part of its operations. The fifth stage — codified — describes what SEO does with what the business produces.
Together, those five stages form the people phase, which sits after the first 10 gates of the AI engine pipeline: discovered, selected, crawled, rendered, indexed, annotated, recruited, grounded, displayed, and won.
Combined, the 15-gate sequence extends the AI assistive agent optimization approach I was exploring when I first coined AEO.
The SEO toolkit you know, plus the AI visibility data you need.
The four OPID stages are the active core of business operations, and they’re where the business actually makes money.
Onboarded is the operational practice of getting new clients from sale to delivery. Performed is the operational practice of achieving measurable outcomes against a baseline. Integrated is the operational practice of becoming structurally embedded in clients’ lives. Devoted is the operational practice of earning unprompted advocacy.
The people who run these stages are the sales, service, support, customer success, and delivery teams. Marketing shapes the message, but the raw material comes from the people doing the delivery. What’s changed is that SEO now has work to do inside that operational core: harvesting from it.
Frame the work as harvesting the output of other teams, and the service team turns from gatekeeper into collaborator. You walk away with large amounts of raw material to publish, codify, and distribute, where AI engines can read it.
Walk into a customer-success meeting saying, “I need content for my blog,” and nobody pays attention. Walk in saying, “The evidence your team produces every week influences whether AI recommends us to the next prospect, and I want to help you capture it,” and they’ll engage and help you.
Run OPIDC properly, and the work benefits the entire business. James Dooley told me his sales team now mostly fills in onboarding forms because AI has already done much of the selling before anyone picks up the phone. Inquiry volume is down, sales are up, and buyers often arrive already convinced.
That’s what OPID looks like once you harvest it, codify it, and distribute it.
Whether your next customer is a person or an agent, the work is the same: engineer the business to serve both, then make sure machines can see, ingest, and evaluate the quality of what you do.
Here’s the trap: OPID is some of the most persuasive evidence you can generate, and it’s invisible to everyone except the client being served in that moment. Every other prospect, and every agent weighing you against a competitor, stands outside the room while your best work happens inside it.
The agent is the exception. In agential mode, the agent sees the delivery, evaluates it against the promised terms, and decides whether to return. That means you now have a second audience to satisfy, and the agent may control repeat transactions.
Please the human and lose the agent, and you risk losing the repeat business the agent influences. Please the agent, and you may earn a customer who reselects you every cycle without a sales call.
Dave Davies at Weights and Biases has explored this idea through the lens of “my client is an agent, how do I provide after-sales service for a machine?”
The catch is that the agent sits inside a walled garden. It evaluates the quality of what you delivered, but when an experience disappoints, it may return to the open web to verify whether it got you wrong. It looks for public evidence that supports or contradicts its experience with your brand.
If the open web reinforces your credibility, the agent may treat the bad experience as an exception and continue recommending you. If the open web confirms weaknesses or inconsistency, the agent may conclude it backed the wrong brand and quietly switch to a competitor. You never see that decision happen.
An agent’s loyalty is shaped by its direct experience with you, but public proof still matters when it goes looking for validation.
And it goes deeper than that. The agent runs on a model trained on the open web, built from the same public record you’re either feeding or neglecting. Your digital footprint shapes what the machine thinks about you long before any individual query. It’s what the model learned from, what the agent checks against, and one of the few assets you can actively build.
Neglect it, and you become invisible in training data and difficult to verify in the moment. Build it, and you’re known before the conversation starts and reinforced when it does. This helps with both humans and assistive engines: your digital footprint supports both discovery and trust.
Here’s the part that matters more than the labels themselves: OPID isn’t a marketing program bolted onto the business. It’s the business, the way companies operate to make money, whether they’re B2B, B2C, ecommerce, or SaaS. Every one of these companies onboards customers, performs against a promise, embeds itself into customer workflows, and earns advocacy, because that’s what operating a business requires.
The new requirement is codifying those experiences and distributing them back into the open web. That’s the flywheel, and it applies across business models.
Onboarded is what you do to take a customer from the moment they pay to the moment they get what they paid for, and get them there without the wheels coming off. Whatever you sell, the job is the same: close the gap between what you promised in the sale and what the customer actually experiences when delivery begins.
That’s the satisfaction gap. You close it before the contract is even signed by asking two questions many businesses skip:
If you don’t ask the second question, your team and the customer end up measuring success against different scorecards, and the relationship starts breaking down in the first few weeks because you were working toward different outcomes.
So you get the answer up front, write it down, and carry it across every part of the business that touches the account. You’ve defined what success looks like in the customer’s own words before you deliver a thing. Get that right, and you can codify it and distribute it as proof of delivery.
Harvest: When the client tells you the first win landed, capture it in their words, include the date, then codify it and distribute it.
Performed is doing the thing you were paid to do and proving it made a difference. You increase the client’s revenue, reduce their processing time, solve the problem they hired you to solve, and deliver the result they came in wanting. Then you do the part many businesses miss: show the difference from where they started.
“Reduced support tickets by 43% in six months against a baseline of 1,200 a month” is proof that a machine can evaluate confidently. “We helped them grow” is a claim every human and every engine will question.
The trap is measuring only what the customer happens to notice — the project finished, the order shipped, the feature launched — while never capturing the comparison against the prior state. That comparison is the proof. Capture it, and you have evidence machines can evaluate and support.
Harvest: Results only matter in context, so capture the before and after to create evidence instead of unsupported claims.
Integrated is earning a permanent place in how the customer operates, not by trapping them, but by becoming the answer they reach for every time the need comes around again. This is the customer who has stopped shopping. They have a recurring job, you’re the one they call, and they’re happy keeping it that way.
When you sell something ongoing, it’s the account that renews without a conversation because you’ve become how a particular thing gets done. When you sell something bought once, it’s the buyer who comes straight back without comparing, the brand an agent drops into the basket because it already ran the comparison and you won.
Different shape, same outcome: you become the use case they’ve assigned to you, and you keep earning it so they never feel the need to reopen the question. Win that, and the renewal happens before anyone thinks to reconsider.
Harvest: Listen for lines like, “I can’t imagine XYZ without them.” That’s the customer telling you you’ve become a repeatable use case worth keeping.
Devoted is turning a happy customer into one who says so publicly. It’s one of the strongest signals in the model because engines can distinguish earned advocacy from manufactured promotion. A manufactured testimonial carries little weight. A customer praising you independently carries much more.
The B2B client naming you on a panel, the SaaS user posting a workflow to their network, the ecommerce buyer leaving an unsolicited review, and the B2C customer recommending you to a friend are all doing the same thing: describing what you do in their own words, in language the next buyer actually needs to hear.
That phrasing often carries more weight than brand messaging because it serves as independent corroboration rather than self-description. The challenge is that customers rarely do it on their own, so part of the work is creating opportunities for them to share those experiences publicly.
Harvest: Encourage customers to share their experiences publicly, capture those stories, publish them on your own channels, and encourage customers to publish them on theirs.
Here’s the thing many SEOs have been getting half-right for years. You create content to satisfy machines, and always have, but too much of it gets created at a desk instead of being extracted from how the business actually serves its customers. You end up talking to the machines without gathering the material they actually need.
That material doesn’t live in your head or your content calendar. It lives in the business: in sales calls, support desks, account managers, founders taking difficult calls, and the day-to-day reality of delivering the right thing to the right people. Your job is to extract it, codify it, and feed it back into the ecosystem.
That’s the foundation under everything else, because codifying isn’t about writing content and guessing what people want to hear. It’s about pulling sales calls, FAQs, success stories, and product attributes from a central source and consolidating them.
The unique marketing content you create still matters — the pieces where you demonstrate topical authority and show you know what you’re talking about — but that’s one stream, not the whole river.
This is where much of the SEO community has it backward. We overlook the bigger truth sitting in plain sight: businesses are already delivering the right products and services to the right people every day. That delivery is what convinces both machines and humans. You don’t have to invent it. You have to codify it and make it visible.
And this extends beyond AI assistants. The model we’re discussing includes assistive engines like Google, ChatGPT, Perplexity, and Copilot, but codifying isn’t an AI-specific tactic. It’s the discipline of making what you do legible to any machine that reads content, which is exactly what marketing teams already try to do on LinkedIn, Facebook, Instagram, and other platforms.
The moment they codify content for those channels, they’re feeding assistive engines too, because those systems read many of the same sources. One discipline supports every machine, and marketing teams have already been laying much of the groundwork.
So stand where your audience is looking. Show them how well you serve people they recognize as themselves, invite them down the funnel by demonstrating you can solve their problem, and let them see the proof in your delivery.
Track, optimize, and win in Google and AI search from one platform.
Codifying gives SEO a coordinating role across the business. The business creates value every day, serves customers, and delivers results. Someone has to extract that evidence, turn it into something machines can read, and distribute it into the world. Increasingly, that responsibility falls to SEO.
And here’s the broader shift: machine-driven distribution now shapes nearly every major platform. Google, ChatGPT, LinkedIn, YouTube, Facebook, and Instagram all rely on systems deciding what gets surfaced. That means every platform increasingly depends on structured, machine-readable content.
Marketing teams can publish raw posts and hope they land, but machines can’t reliably interpret unstructured information. Distribution works better when someone codifies the message first, turning it into structured proof that can travel across search, assistive engines, and social platforms.
That content has to come from the business itself: real delivery, real customer feedback, and real proof, not marketing copy invented to fill a calendar. That’s why business operations, marketing, and SEO increasingly depend on each other. Business teams generate the evidence. Marketing shapes the message. SEO codifies and distributes it in ways machines can understand.
Because increasingly, once communication moves through a screen, a machine helps determine whether people see it. Codify for that machine, and you do more than feed search and AI systems. You organize information in a way that also makes it easier for humans to understand. The structure that helps algorithms interpret content also helps people process it.
The takeaway is simple: codify the real business. Use real delivery, real customer feedback, and real proof, then distribute it where your audience is already looking. Machines increasingly mediate what people see online, so feeding those systems has become part of reaching humans in the first place. That’s why codifying matters, and why SEO is well positioned to lead it.
This is the 16th piece in my AI authority series.
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It’s one of the best “problems” you can have in paid media.
You’re running a campaign that delivers on every front. Cost per acquisition is strong. Return on ad spend is exceptional. Lead quality meets expectations. Average order value is exactly where it should be.
Then the ask comes in: Double the budget and keep the momentum going.
Before you take that step, pause. Increasing budget can unlock more performance, but only if there’s real room for that budget to be productive. If you’ve already maximized what the campaign can deliver on its own, adding budget can lead to higher costs without meaningful incremental revenue gains.
There are times when increasing budget is the right choice, and those are covered later. First, it’s important to understand when not to increase spend.
(Disclosure: I’m a Microsoft Ads employee, and while I’ll share some Microsoft insights, this is intended to be a platform-agnostic piece.)
Before you increase spend, make sure the campaign can support more scale without sacrificing efficiency.
Any meaningful change to budget, target CPA, or target ROAS can trigger a learning period.
In Microsoft Advertising, changes exceeding approximately 15% are likely to introduce performance volatility. This can result in short-term fluctuations in efficiency and volume while the system recalibrates.
If you increase budget too aggressively, you risk disrupting a high-performing campaign. A more stable approach is to increase budgets incrementally week over week. It’s also important to set expectations with stakeholders that growth will be gradual rather than immediate.
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High return on ad spend only matters if it reflects real business value. Before increasing investment, confirm that:
Document any changes to conversion tracking or values, and clearly communicate what’s being measured and why.
Doubling down on a single audience or geography can lead to diminishing returns.
If you increase budget without expanding reach, you may oversaturate the available audience. This can drive up costs without expanding opportunity. Effective scaling often requires:
There’s a natural trade-off between efficiency and scale. At higher volume, it’s difficult to maintain peak return on ad spend. If stakeholders expect the same efficiency at significantly higher spend, misalignment is likely.
Be explicit about the objective:
Clarity here prevents frustration later.
Impression share and share of voice are critical indicators of growth potential.
In those cases, you may be dealing with:
If impression share lost due to rank exceeds 50%, increasing budget is unlikely to drive incremental value because there’s either a structural issue or you’re underbidding. Raising the budget might solve the latter problem. However, you need to be prepared for higher CPCs.
Before increasing budget, audit the following:
Budget can’t compensate for structural inefficiencies.
Return on ad spend alone isn’t a sufficient signal for scaling.
Search campaigns primarily capture existing demand. They don’t lend themselves to creating it outside of AI surfaces.
If you increase budget without increasing demand, the system often responds by:
Sustainable growth requires expanding demand, not just competing harder for the same users.
This includes investing in:
AI-powered surfaces also play a role. Campaigns that use automation and broader matching approaches are more likely to capture incremental demand signals, especially when supported by strong visual and text creative.
Not all growth should happen within a single campaign.
If a campaign is already optimized and stable, allocating additional budget to it can introduce risk without creating new opportunities.
Consider alternatives such as:
This approach allows you to scale while protecting what’s already working, and it enables clearer measurement of incremental impact.
If impression share lost due to budget is high and conversion tracking is reliable, increasing budget can unlock incremental volume.
In this scenario, you’re not fully participating in available auctions, which creates room for additional spend to perform. This can mean more budget for high-performing keywords and more advertising hours.
For newer campaigns, additional budget can accelerate the learning phase by providing more data.
If you’re already in a learning period and willing to accept short-term variability, increasing budget early can help the system stabilize and identify performance patterns more quickly.
Budget increases are most effective when paired with demand generation efforts.
This includes:
In this context, increasing budget becomes part of a broader growth strategy rather than a standalone tactic.
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A high-performing campaign with strong return on ad spend is a strong foundation, but it doesn’t guarantee that additional budget will drive additional value.
Before increasing spend:
Deliberate scaling protects existing performance while unlocking new opportunity.
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Google has confirmed that the Google May 2026 core update has finished rolling out. The second core update of 2026 started on May 21, 2026 and took about 12 days to roll out completing on June 2, 2026.
As a reminder, this is Google’s second core update of 2026. It follows the March 2026 core update, the March 2026 spam update, and the February 2026 Discover update.
What Google is saying. Google updated its Search Status Dashboard to state:
Google posted on LinkedIn saying:
What we saw. This core update didn’t take long to land, as it was announced on a Thursday afternoon and was already felt in a big way the following Saturday, May 23rd. It was pretty significant throughout that first week and then we saw more large ranking movements the following Saturday, May 30th. We even saw some even more volatility in the past 24-hours, right before Google marked this core update done.
Here is a chart from Semrush of the volatility over the past 30-days – notice those spikes in volatility:
What to do if you are hit. Google didn’t share new guidance specific to the May 2026 core update. However, Google has previously offered advice on what to consider if a core update negatively impacts your site:
In short: write helpful content for people, not for search engines.
For more details on Google core updates, you can read Google’s documentation.
Previous core updates. Here’s a timeline and our coverage of recent core updates:
Why we care. By now, the May 2026 core update is done and if your site was impacted – in a positive or negative way – you would probably know by now. The main thing is to continue to focus on building a great website and make content that your users want to read and share.
Meanwhile, as Google Search sends less and less traffic to sites, due to the changes it is making to the search results with AI Overviews and AI Mode. So you need to do what you can to get whatever traffic you can from Google and ranking in the first position is ever more important.
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