Tag: Content Strategy

  • Remembering Bruce Clay: SEO Pioneer’s Final Lessons

    Remembering Bruce Clay: SEO Pioneer’s Final Lessons

    My heart sank when I learned that Bruce Clay had passed away. I knew he had been in the hospital, but my mind went straight to the two long conversations we had last fall: one simply to catch up, and one for what would become a deeply meaningful podcast interview.

    I first reached out to Bruce nearly 25 years ago. I had emailed him cold to ask whether I could republish some of his industry writing about ethics. He said yes. Somehow, the article I cited unintentionally ranked No. 2 on Google for “Bruce Clay” for years. I joked with him about that more than once, and he always seemed both amused and slightly annoyed, probably because I had done it with his own content and his own blessing.

    A few years later, I worked with Bruce and many other search professionals on the board of the Search Engine Marketing Professionals Organization, better known as SEMPO. It was a business nonprofit built to support and legitimize the then-new search industry. We promoted best practices, helped make the business case for search, and later became involved in U.S. Internet policy work in the early 2010s.

    SEMPO brought together board members from around the world, and in a very literal way, it took some of us around the world. That work is where I really got to know Bruce. Later, we would run into each other at conferences, sometimes even on the same panels. We were doing serious work, but we also had a great time doing it. The organization lasted about 15 years, and if I remember correctly, Bruce was one of its founding members around 2000 or 2001.

    One memory of Bruce has stayed with me vividly. A group of us from the SEMPO board were walking back to our hotel on the east side of Midtown Manhattan after dinner. A snowstorm had just begun, one that would leave several feet of snow by the next day. The usual roar of traffic had been softened by the weather and the empty streets. It was eerie, but almost joyously quiet. The city that never sleeps seemed to be taking a nap under a blanket of snow.

    Then something happened that I had never seen before, and have never seen since.

    As snow poured silently into the streets, a massive lightning strike hit just a few blocks away, over Bruce’s shoulder. I do not know whether he saw it directly. It felt like an explosion. We stood there for several minutes trying to understand the contrast: a shattering bolt of lightning between skyscrapers, in the middle of a torrent of snowflakes, with not a drop of rain.

    None of us knew what to call it. I believe Bruce called it “thunder snow,” and the name stuck. In that moment, his naming streak continued.

    Bruce was, and remains, the real deal in search. His legacy was never only about coining a term. He pushed the field forward, taught others generously, and stayed deeply connected to the people he cared about. Like many of the earliest professionals in search, he helped shape practices that still feel foundational today. Through his writing, interviews, books, tools, and hundreds of industry events, he became one of the people the industry looked to for clarity. For many who remember the beginning, and for many who still followed him closely, Bruce was the GOAT.

    I always felt that Bruce approached search intellectually. I do not think he saw it only as a job. It was exciting, unfinished, and new. Very few people get to help invent an entirely new discipline, and Bruce understood what that meant. He also recognized that AI is one of those moments now, and he approached it with the same curiosity, energy, and insight he brought to early search. Many people in the industry may only now be realizing that Bruce pioneered things they do every day. They feel obvious now, but they were not obvious then. Even the basics had to be debated and established.

    He was not only passionate about search. He was passionate and generous toward the people in search. If you cared about the work, you were part of his tribe. That was true for thousands of people in the industry, myself included.

    With Bruce, I could get deep into the weeds of the trade and still talk broadly about where everything was headed. He was an engineer with an MBA, and that combination came through in his leadership, expertise, and authority. He understood the work from top to bottom, and then back to the top again.

    He was also genuinely kind. He had friends around the world. In our last conversations, I sensed that he was content with his life and accomplishments, and that he felt blessed by the path life had given him. He had nothing left to prove.

    In the podcast interview, Bruce was as sharp and insightful as ever. He offered some of the most sensible thinking I have heard about where search is going in the world of LLMs. He was still innovating, just as he had been when search first began taking shape nearly 30 years ago.

    Because search is so closely tied to language, I have been especially interested in how we think about, and what we call, this “new” thing. Bruce’s perspective helped crystallize my own research. Over the last year, I have watched much of the industry move toward the same conclusion he shared in our discussion.

    If you are one of the many thousands of people who talked shop with Bruce over the years, I think you will recognize him in the ideas that follow. You may even relive some of your own conversations with him.

    As I reviewed the podcast transcript, I realized we had recorded hours of conversation beyond search, including cars and all kinds of other subjects. At the end of our first conversation, he said goodbye with great love and care. That was Bruce. Those words land differently with me now, and they always will.

    Rest in peace, Bruce. I miss you already.

    What Bruce taught me in our final industry conversation

    When I asked Bruce to talk about how he got started in the 1990s, he took us back to 1996. He had been working in corporate roles and wanted to become a consultant. His background was in math, programming, mainframes, PCs, networking, and optimization. When the Internet began moving into the mainstream, he saw something that matched both sides of his skill set: marketing and technical work.

    He started studying search engines because that was where the opportunity was. He experimented with what they wanted, adjusted web pages, and watched rankings appear. Then people began calling him and paying him. What he thought might become a one-person consulting business grew quickly into something global, with offices and work across Japan, Australia, Asia, Europe, India, and beyond. Bruce told me he never would have predicted it would take off the way it did.

    I reminded him how small the field was in those days. There were literally only tens of people doing this early on. Bruce was one of the first to build a legitimate service for businesses that needed to rank for their own brand names and for broader generic terms, while other corners of the field were still experimenting with black-hat tactics.

    Bruce pointed out that this was three years before Google. Search was a wild west. There were more than 20 major search engines, and many of them were taking data from one another. At the first SEO conference he remembered attending, all of the leading people in the field sat together at one round table in a bar. He joked that if a natural disaster had happened there, the whole industry might have disappeared.

    We talked about Danny Sullivan, Search Engine Watch, Search Engine Strategies, and the early vocabulary of the industry. Bruce had long been credited with helping coin the term “SEO,” though he was careful to say that no one can know who said something first. What he did know was that only a handful of people were in the room when the term started to take hold.

    At the time, other terms were in play, including “search engine positioning” and “ranking.” Bruce believed “optimization” won because it sounded technical, valuable, and precise. It was like fine-tuning a race engine. People could see themselves building a profession around it. Once the industry attached itself to that word, the term spread quickly around the world.

    That led us into the newer terms now being proposed around AI, including AIO, GEO, and AEO. I have been writing about how many of these terms still depend on the word “optimization.” Bruce’s view was clear: search engine optimization was never limited to organic blue links. It was about optimizing for anything a search engine produces that can drive business and traffic.

    In Bruce’s view, if AI appears inside search and influences discovery, citations, visibility, or traffic, then it belongs under SEO. GEO and AIO were not separate disciplines to him. They were extensions, just like link building or on-page optimization. He warned that many new terms are marketing labels more than practical new fields. If the work required to appear in AI results is still mentions, links, schema, authority, content structure, and rankings, then the work is still SEO.

    That point stayed with me. Bruce said that if someone claims you no longer need SEO and only need AI optimization, you should watch closely, because either they are going to do SEO under a different name or they do not understand what they are doing. He believed ranking in AI was possible, but the method was deeper and more complex than traditional SEO. To him, it was still SEO, just several levels more advanced.

    We also discussed whether AI feels like search did in the late 1990s. Bruce believed it does in important ways. AI depends heavily on search engines because search engines have spent decades fighting spam and building trust signals. AI systems do not yet have that same history, so they rely on what search engines have already learned to filter, evaluate, and rank.

    Bruce also believed AI could still be gamed at the content level. If enough pages repeat a false idea, an AI system may begin to treat it as true. He had already seen examples of people trying to influence AI answers by placing their names into “best SEO” lists across enough sources. To him, this was a sign that AI would need its own version of the spam fight search engines have been having for decades.

    One of the most important parts of our conversation was Bruce’s explanation of Google AI Mode and how it changes the way SEOs should think about structure. He described how a query can produce an overview, followed by sections and subsections that allow users to drill into narrower parts of a topic. When a user clicks into a section, the supporting sites can change to match that specific subtopic.

    That means content cannot simply be built around one broad keyword anymore. Bruce believed pages need to be structured so each section can stand on its own as an expert answer. A page should support a topic, but every H2-level section may need its own clarity, completeness, and internal logic. In his view, this raises the importance of siloing across a site and within a page.

    I framed this as a shift from keyword-led thinking to context-led thinking. Bruce agreed and connected it to entities, fan-outs, references, and cross-links. Keywords helped build the industry, but he believed the future depends on understanding entities in context. If content cannot answer the question clearly, it fails the core purpose of AI-assisted search.

    Bruce described the long-term target as something like the Star Trek computer: no matter what question someone asks, the system provides the answer. We are not there yet, but that is the direction. For websites, he believed the future architecture is question-centered, highly usable, structured into sub-silos, and able to answer and refer within a page while also fanning out to supporting pages.

    That naturally led us to content. Bruce said that for years SEO treated content like a stepchild, but now content is a peer. If SEO teams and content teams do not share the same goal, they will keep writing the way they did 20 years ago and fail in the AI search environment. He was already being hired to train content teams, even though he did not consider himself a “content guy” in the traditional sense.

    He believed the industry still suffers because SEO and content do not cross-pollinate enough. Content marketers may not attend SEO conferences, and SEOs may not spend enough time learning how content teams actually work. That separation matters more now because the structure of a page, the expertise of each section, and the way a topic is divided all affect visibility in AI-driven search experiences.

    Bruce’s advice was direct: stop spreading one keyword across a page and calling that optimization. Instead, build each section as if it were a standalone expert answer. If the sections belong to the same theme, they should support one another, but each needs to carry its own weight. In his words, the hierarchy is no longer only the page. The hierarchy is also the section of the page.

    When I asked Bruce about AI-generated content, he made an important distinction. AI is a tool, not a solution. He did not believe businesses should simply generate content, read it once, and publish it. Detection tools are inconsistent, and search engines may not reliably identify every AI-generated page. But that does not make low-effort AI content a good strategy.

    Bruce believed AI is strongest as a research assistant. His own Pre-Writer product was built around that idea: gather deep research and give a human writer a stronger starting point. The writer still finishes the work, adds style, voice, judgment, compliance, and business understanding. For Bruce, reducing a four- or five-hour writing project to two hours was a win. Replacing the writer entirely was not.

    He was especially clear that writers are artists. AI does not know a business the way its people do, and it does not bring the same finesse or judgment. The future, in Bruce’s view, requires writers, SEOs, and AI workflows to be integrated around shared goals. Without that maturity, teams will keep producing pages that look like they were built for search 10 years ago, and those pages will be ignored.

    We ended by talking about tools. Bruce reminded me that in the beginning, he wrote tools because none existed. He built one of the first page analyzers, including what he once called a keyword density analyzer. He later received a patent related to that kind of technology. His tools were never meant to replace large platforms like Semrush, Ahrefs, or Surfer. They were meant to extend them by analyzing things those platforms did not.

    Bruce pointed people to seotools.com and described the tools as inexpensive power tools, not products designed for the masses. Some users did not understand them at first, but came back later when they saw the value. He was still building, still solving problems, and still thinking about what the industry needed next.

    Near the end, Bruce mentioned a newer tool designed to show traffic loss through Search Console data over time, helping site owners see whether they had fallen off a cliff or declined gradually. It struck me as classic Bruce: while others complained that something should exist, he was building it.

    I thanked him for the conversation, and he answered with warmth: he was glad I had him on, and he loved talking with me. I hear those words differently now. I am grateful we had that final conversation, and I am grateful for everything Bruce gave to search, to this industry, and to the people inside it.

    Listen to the full episode

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    Inspired by this post on Search Engine Land.


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  • Google Ask Maps SEO: Earn Visibility Through Trust

    Google Ask Maps SEO: Earn Visibility Through Trust

    I see Google Ask Maps changing local visibility in a meaningful way. Instead of showing people a long list of nearby businesses and leaving them to sort through everything, Ask Maps narrows the options, interprets the searcher’s intent, and explains why certain businesses look like a strong fit.

    That changes how I think about local SEO. Visibility is no longer only about ranking somewhere near the top of a long results list. It is increasingly about whether Google understands a business well enough to recommend it with confidence.

    I would not treat Ask Maps as a separate optimization channel or a brand-new tactic to chase. I would focus on making the business easier for Google to understand, easier to match to real customer situations, and easier to trust. The foundations of local SEO still matter, but the way those signals work together matters even more.

    Visibility in Ask Maps starts with filtering

    One of the first things I notice about Ask Maps is how small the result set can be. In testing, it often showed around three to eight businesses, depending on the query. That feels very different from traditional Google Maps, where people can scroll through dozens of options and compare them on their own.

    With Ask Maps, much of that comparison happens earlier. Google filters the market first, interprets what the person is really asking for, and then presents a smaller group of businesses with an explanation of why each one fits.

    That means I have to think beyond the question of whether a business ranks. I also have to ask whether Google has enough confidence to include that business in a short recommendation set and explain why it belongs there.

    ```json
{
  "alt": "Flowchart illustrating Ask Maps process from eligibility to recommendation for businesses.",
  "caption": "Discover how Ask Maps efficiently determines business recommendations, ensuring clarity and trust in every listing.",
  "description": "This infographic explains the Ask Maps process from selecting eligible businesses to making confident recommendations. It shows three stages: all businesses, eligible businesses, and recommended businesses, detailing how Google evaluates category, location, credibility, and reviews. This visual provides a step-by-step guide to how trust and clarity improve business rankings and recommendations, branded by Streetlight Local."
}
```

    I think of this as a two-step problem. First, Google decides which businesses are eligible for the query. Then, it decides which eligible businesses it can confidently recommend.

    Ask Maps needs enough detail to explain the business

    Ask Maps does more than list businesses. It interprets and describes them. Even for simple searches, I often see businesses framed around qualities such as responsiveness, experience, specialization, professionalism, or the kinds of situations they seem best suited for.

    That creates a different optimization challenge. It is not enough for Google to know that a business exists or that it offers a basic service. Google needs enough information to answer a more practical question: when should this business be recommended?

    To support that, I want Google to understand the types of jobs the business handles, the situations it commonly deals with, the concerns customers usually have, and how the business approaches those situations.

    If that information is vague, scattered, or inconsistent, Ask Maps has less to work with. When Google cannot clearly explain why a business fits a specific situation, I would expect that business to be less likely to appear as a recommendation.

    ```json
{
  "alt": "Comparison between Traditional Google Maps and Google Ask Maps with highlighted features and filtering process.",
  "caption": "Discover the efficiency of Google Ask Maps, a tool that pre-filters search results, providing users with top-rated options and reasons for selection.",
  "description": "This image illustrates the difference between Traditional Google Maps and Google Ask Maps interfaces. Traditional Maps display a long list of business options, requiring user filtering. In contrast, Ask Maps pre-filters results to show a curated list of top businesses with rationales. The image features two smartphones displaying both app interfaces and icons highlighting user experience differences. It emphasizes Ask Maps' efficiency in offering tailored recommendations, saving users time and effort."
}
```

    Google Business Profile becomes the identity layer

    For me, the Google Business Profile sits at the foundation of this whole process. In earlier-stage queries, Ask Maps appears to rely heavily on profile data, including business descriptions, services, reviews, ratings, hours, and operational details.

    Many businesses still treat their profile like a basic listing to fill out and keep current. That is necessary, but I do not think it is enough for an environment where Google is trying to describe and recommend businesses. The profile needs to communicate a clear, specific identity.

    A generic profile might say that a business offers plumbing, HVAC, electrical work, or another broad service. A stronger profile clarifies the kinds of problems it handles, the situations it is built for, and the details that make it useful to specific customers.

    For example, I would use the profile to reinforce details such as emergency availability, response times, specific repair or installation types, experience with older homes, complex systems, or common customer problems the business solves.

    That level of specificity gives Google more direct evidence. Instead of forcing the system to infer what the business is known for, I want the profile to make that identity clear.

    ```json
{
  "alt": "The CapmatchOne logo with a gradient circle and bold text.",
  "caption": "Discover innovation with the CapmatchOne logo, featuring sleek typography and a modern gradient circle.",
  "description": "The CapmatchOne logo features bold, modern typography coupled with a gradient circle, symbolizing connection and innovation. The sleek design conveys a sense of progress and creativity. This image can be used for branding or promotional purposes, appealing to audiences interested in innovative solutions and forward-thinking designs."
}
```

    Reviews shape positioning, not just credibility

    Reviews have always mattered in local search, but I see them playing a more structured role in Ask Maps. Review language can show up in the way Google describes a business, especially around themes like responsiveness, honesty, communication, professionalism, and quality of work.

    That tells me reviews are doing more than supporting credibility. They are helping define how the business is positioned.

    I would still pay attention to rating, volume, and recency. But I would also look closely at what customers actually say. The language inside reviews can give Google useful context about what the business does, how it works, and what customers value about the experience.

    A vague review such as “great service” signals satisfaction, but it does not explain much. A detailed review that mentions a same-day response, a drain backup, clear communication about options, and a repair-focused solution gives Google several stronger signals about the business.

    Over time, those patterns accumulate. In that sense, I view reviews as one of the main ways Google learns what a local business is known for.

    ```json
{
  "alt": "Infographic contrasting weak versus strong business descriptions for Google explanations.",
  "caption": "Optimize your business presence on Google by crafting clear, specific descriptions and reviews. Strong positioning makes your business easier to recommend.",
  "description": "This infographic compares weak and strong business profiles for Google explanations. Weak businesses show vague services, generic reviews, and unclear positioning, leading to a 'hard to explain' result. In contrast, strong businesses provide specific services, detailed reviews, and clear positioning, resulting in an 'easy to recommend' status. Keywords include business clarity, Google explanation, and online presence optimization."
}
```

    Website content matters more when decisions get harder

    I also see website content becoming more important as queries become more complex. For basic service searches, the Google Business Profile and reviews may carry a lot of the weight. But when the search involves higher cost, uncertainty, or trust, Google appears to look for deeper supporting evidence.

    That is where the website can help. Many service pages explain what a business offers and why it is qualified. That still matters, but it does not always match how people search when they are trying to make a difficult decision.

    In more situational searches, people are not just looking for a service. They are trying to understand a problem, compare options, reduce risk, and decide what to do next.

    That is why I would build content around the customer’s situation, not just around the service name. Stronger pages explain what leads to the problem, how to recognize it, what options are available, how to think through the decision, and what outcomes to expect.

    For example, a furnace repair page can go beyond a basic list of services. It can cover common symptoms, when repair makes sense, when replacement might be worth considering, and how a homeowner can evaluate the decision. That kind of content lines up more closely with the prompts Ask Maps is trying to interpret.

    ```json
{
  "alt": "Diagram illustrating the elements of a Google Business Profile, such as services, areas served, photos, and business description.",
  "caption": "Explore how your Google Business Profile shapes public understanding, highlighting services, service areas, and more for improved visibility.",
  "description": "This image presents a detailed diagram of a Google Business Profile, emphasizing how it defines business perception. Central to the diagram is the profile, surrounded by elements like Services, Service Areas, Business Description, Photos, and Attributes. Each component is essential for building a comprehensive profile that helps businesses stand out on Google Maps. The image underscores the importance of specificity and completeness in business profiles for improved match and recommendation accuracy."
}
```

    I also see a strong fit for jobs-to-be-done pages. Instead of organizing every page around a service category, I would create pages around the situation the customer is trying to solve and the decision they are working through.

    Trust signals matter more as risk increases

    As searches move from simple service needs into decision-making, trust becomes more important. When people mention cost, honesty, uncertainty, or fear of making the wrong choice, Ask Maps tends to highlight qualities such as transparency, fairness, careful workmanship, and clear communication.

    That makes sense to me because it reflects how people actually think in those moments. When someone faces an expensive repair or an unexpected issue, they are not only asking who can do the work. They are asking who they can trust to handle it correctly.

    I would support that trust with evidence across the business’s online presence. Reviews can show that customers felt respected and informed. Website content can explain the process. Examples of completed work can show experience. Clear “what to expect” sections can reduce uncertainty.

    The higher the perceived risk, the more supporting evidence matters. I want Google to see a consistent pattern that the business explains options clearly, avoids unnecessary pressure, handles similar situations, and leaves customers confident in the outcome.

    Infographic showing how detailed Google reviews help Ask Maps frame a local business as responsive, honest and repair-focused.
    Detailed customer reviews do more than boost ratings. They give Google Ask Maps the context it needs to understand, position and confidently recommend a local business.

    External signals should reinforce the same story

    For more complex or trust-heavy queries, Ask Maps may look beyond the Google Business Profile, reviews, and website. Third-party platforms, directories, and other public sources can help reinforce how Google understands a business.

    I do not take that to mean every external mention is equally important. I take it to mean consistency matters. If a business is described one way on its website, another way in reviews, and differently across directories or social platforms, the overall picture becomes harder to interpret.

    When those signals align, they strengthen each other. Business descriptions, services, customer experiences, types of work handled, and overall positioning should tell the same story wherever they appear.

    From a practical standpoint, I would not try to appear on every possible platform. I would make sure the important sources are accurate, credible, and consistent.

    I would optimize for evidence, not just keywords

    Infographic comparing basic and complex HVAC local searches, showing Google relies more on website content as decisions get harder.
    As local search decisions become more specific and higher risk, Google needs deeper signals from business profiles, reviews, and website content to recommend the right provider.

    Taken together, these patterns push me to think differently about optimization. Traditional local SEO often starts with keywords and rankings. Those still matter, but they do not fully explain what Ask Maps is doing.

    I find it more useful to think in terms of evidence. For a business to be recommended, Google needs enough information to understand what it does, what types of jobs it handles, what situations it fits, how customers experience it, and whether it can be trusted in higher-stakes decisions.

    Each source contributes something different. The Google Business Profile establishes the baseline identity. Reviews add real-world context. Website content provides depth and explanation. External sources help confirm the same picture.

    Individually, none of those elements tells the whole story. Together, they create a clearer and more consistent understanding of the business. That is where the shift from ranking to recommendation becomes most obvious: keywords can support relevance, but evidence supports recommendation.

    My practical framework for Ask Maps visibility

    When I evaluate a business for Ask Maps visibility, I would look at five areas: identity, relevance, trust, context, and consistency.

    Infographic comparing keywords and evidence for Google Ask Maps visibility, showing keywords help local SEO rankings while evidence earns recommendations.
    Google Ask Maps rewards more than keyword relevance. This visual shows why reviews, service details, trust signals, and real proof help local businesses get recommended.

    Identity asks whether Google can clearly understand what the business does and where it operates. Relevance asks whether the business can be matched to specific services and situations. Trust asks whether there is enough proof that customers feel confident choosing it.

    Context asks whether the content reflects the decisions customers are actually trying to make. Consistency asks whether different sources reinforce the same understanding of the business.

    I do not see this as a checklist to complete once. I see it as a practical way to evaluate how clearly and consistently a business is represented across the sources Ask Maps appears to use.

    What I would avoid

    With any new search feature, it is easy to overcorrect. I would avoid treating Ask Maps as an isolated channel that needs thin content, unnatural profile language, generic service-page duplication, or review language that feels forced.

    Those tactics may create more content, but they do not necessarily create more useful evidence. The better approach is to align more closely with how customers actually search, evaluate options, and make decisions.

    Infographic outlining five pillars for Google Ask Maps visibility: identity, relevance, trust, context, and consistency for local SEO recommendations.
    A practical local SEO framework shows how businesses can earn visibility in Google Ask Maps by clarifying identity, proving relevance, building trust, adding context, and staying consistent online.

    When the business presence reflects real customer needs clearly and consistently, it naturally creates the kinds of signals Ask Maps seems to rely on.

    What I still do not know about Ask Maps

    I would treat all of this as directional, not definitive. Ask Maps is still being tested and refined, and the system is not fully documented.

    The result structure can vary by query and test environment. The feature’s usability is also still changing. In many cases, users may still need to click into a Google Business Profile to call, book, or engage, rather than acting directly from the Ask Maps response.

    Measurement is another open issue. Right now, I do not see a clean way to isolate Ask Maps visibility or performance inside standard reporting tools. That makes it difficult to attribute calls, traffic, or conversions directly to this experience.

    I also would not assume the same signal weighting applies to every query. Google Business Profile data, reviews, website content, and external sources may all matter, but their relative importance likely changes based on the search intent and the complexity of the decision.

    The real shift is from ranking to recommendation

    I see Ask Maps as a version of local search where retrieval, evaluation, and decision support are moving closer together. Instead of making users search, compare, research, and decide across several steps, Google is trying to guide more of that process inside one experience.

    That changes the meaning of visibility. In Ask Maps, it is not enough for a business to simply appear. The business needs to be understood well enough for Google to explain why it fits the situation and trusted enough to be recommended.

    For businesses and SEOs, I would not respond by chasing a narrow trick. I would build a clearer, more complete, and more consistent representation of the business across the sources that shape Google’s understanding.

    The businesses most likely to benefit are the ones that are easiest to interpret, easiest to trust, and easiest to match to real-world customer needs.


    Inspired by this post on Search Engine Land.


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  • 6 Claude Content Audit Workflows I Reuse for Better SEO

    6 Claude Content Audit Workflows I Reuse for Better SEO

    Claude content audit

    I see existing content as a goldmine, but only when I have a practical way to improve it. The hard part is usually finding the time, and that is where Claude has made a large, messy job feel much more manageable for me.

    I do not start by building a giant content audit system. I start with one article, run one focused audit, refine the output, and then turn the prompt into a reusable Claude skill. Over time, those one-off audits become a working library I can improve every time I use it.

    I use Claude to uncover topical gaps, flag outdated information, check brand voice, and evaluate whether a page is easy for AI systems to retrieve and cite. The real value comes from iteration: each time I improve a skill, the next audit becomes faster and more useful.

    Here are six content audit workflows I would build in Claude. The first four work at the page level, so I can start with a single article before moving into larger library-wide analysis.

    Page-level audits

    When I am not ready to build a full workflow, I start with page-level audits. These audits only require one article, which means I do not need a content inventory, a data export, or a complicated setup. After each session, I ask Claude to turn the process into a reusable skill for future page-level reviews.

    1. Brand voice consistency

    I use a brand voice consistency audit when a content library has drifted over time. Voice can shift because of new writers, changing services, product updates, or evolving positioning. This audit helps me spot where a page no longer sounds aligned with the brand.

    If I do not have detailed brand guidelines with strong examples, I let Claude extract the voice guide from high-quality content. That usually works better than relying on vague phrases like “conversational but authoritative” or “educational, not too formal.”

    I pick three to five articles that represent the brand at its best. If possible, I download them as markdown files and ask Claude to describe how the voice works in concrete terms.

    • How the articles usually open, such as whether they begin with a direct claim, a counterintuitive statement, or a specific scenario.
    • How sentences and paragraphs are built, including average length, range, rhythm, and how paragraphs tend to close.
    • Three to five personality dimensions framed as “We say X, but not Y,” with do and don’t examples.
    • Words and phrases the brand tends to use, and words or phrases it should avoid.
    • Specific constructions, phrases, and conventions the brand never uses.

    Instead of accepting a vague voice description, I want Claude to return concrete observations. For example, it might say that articles open with a direct claim rather than a scene-setting paragraph, sentences average 15 to 20 words and rarely exceed 30, and transitions are functional, such as “here’s why that matters,” rather than formulaic, such as “furthermore.”

    I also want example pairs, such as: “We’d say ‘the data shows three things,’ not ‘there are multiple factors to consider.’” The goal is not to create a voice guide for writers. The goal is to create one an LLM can understand and apply consistently.

    Once I like the output, I ask Claude to save it as a skill and evaluate an article against it. If Claude flags issues I disagree with, I update the skill until the feedback becomes useful and repeatable.

    I can then use that skill to find voice inconsistencies in older content, check new drafts for alignment, and even generate more on-brand first drafts. I still edit the output, but the starting point is much stronger.

    Dig deeper: How to train Claude to sound like your brand

    2. Coverage comparison

    When I need to improve content performance, I use a coverage comparison to find topical gaps. This helps me understand what competing pages cover that my article misses.

    I use the Claude in Chrome extension to have Claude review the top three to five ranking pages for my target keyword. Then I ask Claude to compare those pages against my content and highlight the most important gaps.

    • What competitors are doing well.
    • What my article already does well.
    • Where I can improve the piece without bloating it.

    If I want the output in a table, I ask Claude to format it that way. If I want a downloadable DOCX for review or handoff, I ask for that instead.

    When Claude recommends additions I would never publish, I make a note of those exclusions before packaging the workflow into a skill. That way, the skill gets closer to my editorial standards each time I refine it.

    3. Freshness audit

    Old content adds up quickly, and it is hard to prioritize refreshes while I am also producing new material. A freshness audit skill helps me identify what needs attention without rereading every older article from scratch.

    I give Claude an older article and ask it to flag anything time-sensitive: statistics tied to a specific year, named tools or platforms, references to “current” or “recent” trends, and claims that depend on a market, regulatory, or product context that may have changed. I am not asking Claude to rewrite the article yet. I am asking it to build an issue list I can act on.

    If my company has launched new products, removed old services, changed positioning, or updated terminology, I include that context in the input. That helps Claude flag what should be added, removed, or revised.

    Dig deeper: How to turn Claude Code into your SEO command center

    4. AEO and AI retrievability

    I use an AEO and AI retrievability audit to understand whether a page is likely to be surfaced in AI-generated answers. Tools such as ChatGPT, Perplexity, and Google AI Overviews tend to favor content that answers questions directly. If an article buries the answer under too much preamble, or structures key information in a way that is hard to extract, it becomes less useful for those systems.

    I give Claude the article and the target query, then ask it to evaluate several retrieval signals.

    • Whether the article answers the main question directly and early.
    • Whether key statements are specific enough for an LLM to quote or cite.
    • Where an FAQ-style section would improve clarity.
    • Whether the page includes authority signals, such as primary research, first-person experience, outbound citations, or specific examples.

    Once I save this as a skill, it becomes an extra editor focused specifically on AI visibility and answer retrieval.


    Library-level audits

    Once I am ready to move beyond individual pages, I use library-level audits. These require performance data, a content inventory, a connector, or a manual export.

    5. Performance triage

    When I think about a traditional content audit, performance triage is usually what comes to mind. It helps me analyze a content library and identify the pages that deserve attention first.

    Before I begin, I make sure Claude has access to the right data through a connector such as BigQuery or the Semrush API. If that is not available, I export the data I normally use for large-scale audits, such as traffic, clicks, engagement metrics, conversions, rankings, and related performance signals.

    I ask Claude to prioritize pages that have suffered meaningful performance drops in the past six to 12 months, pages with high impressions but consistently low click-through rates, and pages that have been live long enough to rank but never gained traction.

    I also define what a meaningful performance drop looks like for the site I am analyzing, because traffic patterns vary by industry, audience, and page type. Then I ask Claude for a prioritized list of what is worth investigating and why. From there, I use the page-level audits above to diagnose the problem.

    If I have run this analysis before, I give Claude the previous output. That helps the skill learn the kind of prioritization and reasoning I expect.

    Dig deeper: How to build a Claude Code-powered second brain for agency work

    6. Topical gap analysis

    I treat entities as a major part of AEO and semantic search. A topical gap analysis helps me see whether my content library has enough coverage to build authority around the entities tied to my brand.

    The core question I ask is simple: what is my content library not covering that it should?

    To start, I create a list of target entities. For example, at my agency, I want to be known for SEO and AEO. If I have a clear list of services or products, I can use that instead of a formal entity list.

    Using Cowork or Code, I ask Claude to analyze my sitemap and compare it to those target entities. If I have a Screaming Frog export with URLs, page titles, and meta descriptions, I use that as input for a more accurate analysis.

    Then I ask Claude to identify topic clusters that are missing or underrepresented based on the target entities, services, or products. If I want prioritization, I can use the Semrush MCP so Claude can check search volume for potential keywords.

    Not every gap is worth filling. I filter the results against audience needs, business relevance, and editorial standards. Then I feed those decisions back into Claude so the skill produces better recommendations next time. The final list can go directly into my content creation workflow or be handed off to a content team.

    I do not try to audit everything at once

    I have seen content audits stall because the scope feels too large, not because the team lacks data. My preferred approach is to pick one audit and one article, run the workflow, save the skill, and use it again on the next piece.

    For me, iteration is part of the value. I enjoy taking one Claude skill, improving it, and then chaining it with other skills to uncover more content opportunities. Starting small is what makes the system easier to keep using.


    Inspired by this post on Search Engine Land.


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  • Navigate AI-Driven Searches with Engaging Reading Strategies

    Navigate AI-Driven Searches with Engaging Reading Strategies

    I’ve realized that AI Overviews are fundamentally changing how users interact with search results. Gone are the days of simple, task-oriented searches. Today, AI Overviews encourage users to dive into comprehensive reading sessions right on the search engine results pages (SERPs).

    Let’s talk about some critical insights. AI Overviews merge multiple search intents into a single reading session, disrupting the traditional understanding of search behavior. Winning what I call the ‘second impression’ is crucial for different types of web pages.

    Recently, I teamed up with Eric Van Buskirk from Clickstream Solutions to analyze vast amounts of anonymized clickstream data. We discovered that time-on-SERP is no longer solely dependent on search intent when AI Overviews are in play.

    Historically, search intent—navigational, informational, etc.—predicted user behavior. But with AI Overviews, now users spend similar amounts of time regardless of their initial intent.

    ```json
{
  "alt": "Graph comparing active seconds on Google SERPs by user intent with and without AI overviews, showing increased engagement with AI.",
  "caption": "AI Overviews Enhance Engagement: A comparative graph shows user activity on Google SERPs is prolonged with AI overviews across various intents.",
  "description": "This image displays a graph depicting the active seconds users spend on Google SERPs, categorized by user intents: informational, local, navigational, transactional, and video. The left side shows activity without AI overviews, while the right illustrates increased engagement with AI overviews. The data highlights a significant extension in user activity across all intents when AI overviews are applied. Source: Clickstream Solutions, Surfer SEO."
}
```

    These insights are crucial. Consider Google’s change in approach: it’s less about presenting links and more about providing exact answers. This requires us to think differently about how we engage users.

    For operators like me, understanding the significance of the ‘second impression’ helps us adapt our strategy for product, category, and blog pages.

    In product detail pages (PDPs), it’s important to manage schemas and compare competitors’ offerings. On category detail pages (CDPs), having visible filters and vast product arrays can make all the difference.

    ```json
{
  "alt": "Visual guide outlining three playbooks for PDP, CDP, and Blog content focusing on trust and relevance signals.",
  "caption": "Discover strategic playbooks for product detail, category detail pages, and blogs to boost trust and relevance. Enhance online visibility with targeted schema and content strategies.",
  "description": "This image presents a structured guide titled 'THE_SECOND_IMPRESSION_HAS_3_PLAYBOOKS', focusing on enhancing online trust and relevance through three types of content: Product Detail Pages (PDP), Category Detail Pages (CDP), and Blogs. It details strategies like using product schemas, comparison review counts, and exposing filter facets for better Google sitelinks. The guide emphasizes the importance of visible publication dates and article schemas. Ideal for SEO and content strategists aiming to enhance SERP visibility. Source: Growth Memo."
}
```

    As for blog content, I’m focusing on credibility signals like publication dates and author names within schema markup to gain trust and validation clicks.

    Instead of predicting user behavior as before, the new focus is on optimizing my content’s visibility and trustworthiness in an AI-influenced SERP landscape. This shift doesn’t change our core content strategy but adds new layers of intricacy to how we optimize for SERP.


    Inspired by this post on Search Engine Land.


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  • Condé Nast Shifts Focus as Google Search Traffic Fades

    Condé Nast Shifts Focus as Google Search Traffic Fades

    Google zero

    Over the years, as Google continually tweaked its algorithms and transformed its search results pages, I’ve seen Condé Nast adjust its strategies considerably. Now, we’re designing our business around the notion that search traffic barely impacts us anymore.

    In a recent conversation featured on TBPN—the tech media network that’s been likened to “technology’s daily show”—CEO Roger Lynch shared that we’ve stopped regarding Google search as a dependable traffic source.

    Here’s what Lynch explained. While Google traffic isn’t expected to vanish completely, we’re intentionally planning as if it’s on the decline:

    “Last year, I instructed our teams: plan as if there is no search—consider search as non-existent.”

    “We’re not saying it will be gone entirely… but we anticipate it will comprise only single digits of our overall traffic—very minimal.”

    The background. Throughout the past few years, Lynch has observed a recurring trend: Google’s adjustments consistently exceeded our expectations in reducing our visibility.

    “For each of the last three years, we predicted some search traffic declines in our budgets, but it fell even more than anticipated,” he noted.

    Why has our search traffic dwindled? Lynch attributes this decline not only to algorithm changes but also to AI Overviews and Google’s increasingly commercial-centric results.

    “Seven or eight years ago, search results had a few ads, followed by ’10 blue links.’”

    Currently, users first encounter AI Overviews, then a slew of commerce links, pushing organic results further down the page.

    “It’s worked out well for Google,” Lynch commented.

    A shifting landscape. The alterations made by Google have disrupted the model that other digital entities, like BuzzFeed, used to convert social media and search traffic into revenue.

    “That era has ended,” he declared.

    Lynch mentioned that brands in the intermediary stages are having the most trouble adapting to changes in AI and search frameworks.

    “In today’s world, having a specified niche with a dedicated audience is crucial. Relying solely on advertising to support significant journalism investments is a challenging position,” he stated.

    Shifting priorities at Condé Nast. We are now emphasizing brands that excel in these areas:

    Dedicated direct audiences.

    Potential for subscriptions.

    Undeniable expertise in a given niche or category.

    Lynch also hinted at a potential advantage for premium publishers against AI-generated content:

    “Our audience expects and desires human-generated content. Creating AI-generated content doesn’t play to our strengths. Identifying and building on your competitive advantages is vital.”

    Why this matters. Lynch emphasized that the practice of turning search and social media traffic into lucrative businesses is outdated. Publishers lacking a strong brand or dedicated readership might face challenges, as platforms can revise their methods at any moment.

    The full interview. You can watch Lynch’s discussion, where he elaborates why human journalism remains crucial in the AI era, starting at 30:28 here.


    Inspired by this post on Search Engine Land.


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  • Why Quality Content Often Fails to Rank on Google

    Why Quality Content Often Fails to Rank on Google

    I find it intriguing how, despite creating stellar content, it often doesn’t make it to the top of Google’s search results. What holds it back isn’t necessarily quality—there are usually other roadblocks in play. Let me break down how to identify what’s hindering your content’s rankings.

    The common advice has always been to create helpful, high-quality content to rank well. However, this piece of advice doesn’t cover the full story of Google’s search algorithm mechanics.

    Even if your content is well-researched and aligned with search intent, technical barriers and competition may still impede its visibility. Identifying these barriers is crucial before deciding to rewrite any piece of content.

    Before blaming your content’s positioning, it’s essential to assess its quality. I often observe pages that don’t stand out, sometimes being autogenerated with minimal editorial input. Google’s guidelines on helpful content underscore the significance of experience and trust.

    Ask yourself: Does your content deliver unique insights, adhere to Google’s preferred format, and offer value beyond the current top results? A ‘yes’ suggests positioning issues; otherwise, focus on enhancing your content’s quality first.

    ```json
{
  "alt": "The CapmatchOne logo with a gradient circle and bold text.",
  "caption": "Discover innovation with the CapmatchOne logo, featuring sleek typography and a modern gradient circle.",
  "description": "The CapmatchOne logo features bold, modern typography coupled with a gradient circle, symbolizing connection and innovation. The sleek design conveys a sense of progress and creativity. This image can be used for branding or promotional purposes, appealing to audiences interested in innovative solutions and forward-thinking designs."
}
```

    In the competitive 2026 search landscape, various factors such as AI summaries and an increased ad presence are reshaping search results pages, making it harder for organic content to achieve visibility.

    Understanding what your content is truly competing against is key. If these external factors push your content down the page, adjustments are necessary to remain competitive.

    When questioning why good content isn’t ranking, I employ a diagnostic framework that prioritizes technical issues. Ensuring that your page is indexed and free from technological hurdles is the first and simplest step to address.

    Matching search intent with your content’s format is also critical. If your content is misaligned, improving it won’t suffice unless you address the fundamental disconnect.

    ```json
{
  "alt": "Google search results page for contact center software, showing sponsored listings for Genesys and Zoho.",
  "caption": "Exploring contact center software options? This Google search results page highlights sponsored listings from Genesys and Zoho, offering AI-powered solutions.",
  "description": "This image shows a Google search results page for 'contact center software'. Two prominent sponsored listings from Genesys and Zoho are displayed. Genesys offers AI-driven solutions for seamless, personalized contact center experiences, while Zoho promotes call analytics and multi-channel interaction management. The page provides further insights into contact center solutions with links and detailed descriptions. Keywords: contact center software, Genesys, Zoho, AI-powered, solutions."
}
```

    If a large trust signal gap exists between your domain and your competitors’, repositioning is often necessary to focus on less competitive keywords where you can compete effectively.

    The type of website you manage affects which barriers are most significant. For example, SaaS platforms typically face challenges concerning authority more than technical issues, while ecommerce sites contend with technical constraints.

    Understanding and applying this diagnostic sequence helps identify and address potential bottlenecks, ultimately allowing your content to rank better by focusing on what truly matters.

    In 2026, as the ease of generating good content continues to grow due to AI, positioning becomes crucial. Differentiated, experience-driven content is what stands out and captures attention.

    Your strategic question isn’t just about creating good content. It’s about understanding the landscape: What else is required for your content to achieve outstanding results in the search arena?


    Inspired by this post on Search Engine Land.


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  • Maximize AI Visibility: Influence, Signals, and Citations

    Maximize AI Visibility: Influence, Signals, and Citations

    I’ve seen how crucial it is to understand that AI visibility starts long before users hit that search bar and ends with citations.

    These insights are vital in shaping what gets seen, summarized, and cited by AI systems.

    Currently, the focus has shifted towards improving the AI ROI story, and I’m right in the thick of it, learning what strategies truly work.

    This year, attending SMX Advanced will be more enlightening than ever, bringing unique perspectives and strategies.

    Let’s dive into why influence matters everywhere, and how it impacts AI citations.

    Rand Fishkin’s study, ‘Influence Happens Everywhere,’ reveals that, although Google commands the majority of search traffic, it’s the influence happening outside of search that truly dictates what people look for online.

    For many, wandering through social media or news sites builds their understanding and interest long before the actual search occurs.

    Despite the exciting growth of AI tools, achieving a stable presence online requires understanding how fragmented channels contribute to this influence.

    When crafting content, it’s essential to dominate the influence phase so thoroughly that an AI assistant doesn’t just suggest your brand—it demands it.

    That’s the strategic thrust behind the discussions at SMX Advanced in Boston and why I align my content calendar accordingly.

    My colleagues at Search Engine Land are among those shaping these discussions. Insights from thought leaders like Dave Davies and Carolyn Shelby are invaluable.

    They emphasize the importance of structured visibility signals and entity recognition, helping AI systems select the right brands to highlight.

    In my own analysis, the various AI models like ChatGPT, Perplexity, and others have unique methodologies for selecting sources, reinforcing the idea that an engaged, multi-platform strategy is critical.

    So, what does full-stack content truly mean today? It’s more than crafting blog posts; it’s about commanding entire topics with authority and depth, enhanced by AI tools like Jasper’s Enterprise Suite.

    ```json
{
  "alt": "The CapmatchOne logo with a gradient circle and bold text.",
  "caption": "Discover innovation with the CapmatchOne logo, featuring sleek typography and a modern gradient circle.",
  "description": "The CapmatchOne logo features bold, modern typography coupled with a gradient circle, symbolizing connection and innovation. The sleek design conveys a sense of progress and creativity. This image can be used for branding or promotional purposes, appealing to audiences interested in innovative solutions and forward-thinking designs."
}
```

    The ability to integrate real-time data, identify competitive content gaps, and create diverse multimedia content packages mean we’re shifting from simply generating content to dominating entire narratives.

    But AI tools can only serve the overarching strategy if our content offers the original insights that help us stand out in AI retrieval systems.

    This year, Purna Virji’s insights at SMX Advanced will challenge us to think critically about the real ROI in AI investment.

    I’m particularly interested in seeing how Google Vids is democratizing video content by eliminating the high entry barriers of previous video production methods.

    Now, video content can be produced and localized for a multitude of markets rapidly, a paradigm shift in how we engage audiences across the globe.

    The standards AI is setting for content — whether text, video, or multimedia — require a strategic framework that aligns with evolving platforms like GEO and AEO.

    For those in the trenches like me, adjusting focus towards an integration of structured data and earned media becomes imperative.

    The real challenge isn’t in the buzzwords but effectively navigating the volatile landscape of AI-driven citations.

    I recognize the adjustments needed in approach, especially when considering the stark differences in referral and conversion rates from traditional search versus AI platforms.

    So, practical actions for the rest of 2026? Audit your AI presence thoroughly, stop gating original research, secure your place in vibrant communities, and refine your focus towards citatability rather than simple visibility.

    Ultimately, the brands ready to adapt will continue to thrive in this AI-enhanced environment.

    Indeed, the bots are crawling, and it’s time I ensured my brand is worth citing.


    Inspired by this post on Search Engine Land.


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  • Discover Why ‘Ugly’ Ads Could Boost Your Marketing Success

    Discover Why ‘Ugly’ Ads Could Boost Your Marketing Success

    For years, I’ve been told to stick to a set of guidelines: always use top-notch creatives, maintain a polished brand, follow scripts, and adhere to platform-recommended formats.

    Lately, while navigating ad accounts or simply scrolling through feeds, I’ve noticed something intriguing. The ads that grab my attention often defy these rules. They’re less polished, scrappier, and sometimes referred to as ‘ugly ads.’ What’s fascinating is that they’re outperforming the traditional, polished ones.

    More brands are deliberately breaking so-called best practices to stand out. It’s important to remember that these practices represent an average of what worked for others in the past. By the time a strategy becomes a platform-recommended rule, it might have already lost its edge.

    This is why defying best practices can lead to success — but only if you understand the reasons behind them.

    Why Breaking Best Practices Enhances Ad Performance

    Before diving into what to change, it’s crucial to understand the rationale behind existing rules. Platforms like Meta and TikTok have dual objectives:

    • They aim for you to spend money on ads.
    • They want to keep users engaged on their platforms.

    The best practices they promote are designed to ensure a seamless experience, encouraging ads to resemble others. The issue is that familiarity eventually breeds invisibility. When I adhere too closely to the rules, my ads risk blending into the background noise, overlooked by users.

    ```json
{
  "alt": "Person holding a dumbbell at the gym, with text saying 'Your AirPods died at the gym' and emoji expressions.",
  "caption": "When your motivation gets heavy! A classic gym moment – your AirPods gave up, but you didn’t. Feel the silence and lift on!",
  "description": "Image shows a close-up of a person’s hand gripping a black dumbbell at the gym. The text overlay humorously reads 'POV: Your AirPods died at the gym' with laughing emojis, depicting the common scenario of exercising without music due to AirPods losing charge. This relatable gym scene captures the blend of determination and humor. Keywords: gym, dumbbell, AirPods, workout, humor."
}
```

    Highly-produced ads often scream ‘this is an ad,’ prompting users to skip them before my message hits home. In contrast, when my ad resembles something a friend might share, users’ defenses remain down longer, potentially transforming a scroll into a conversion.

    This is why many top-performing ads today don’t appear traditionally polished or on-brand. They break patterns instead. Consider:

    • Grainy phone footage.
    • Notes app screenshots.
    • Green-screened reactions or commentary videos.
    • Other lo-fi formats that outperform studio-quality creatives.
    A screenshot of a TikTok video ad featuring POV overlay text, a hand grabbing a dumbbell, and AirPods
    Source: TikTok Ads Manager

    To implement this, I started intentionally reducing my production value and experimented with formats like point-of-view (POV) shots tailored to various personas.

    Dig deeper: TikTok ad creative has a shorter shelf life. Here’s how to keep up

    Founder-Led Ads: Reviving the Human Touch

    Many brands have adopted guidelines that make them seem faceless and untouchable. They refrain from showing a messy office, an unpolished founder, or anything that challenges their corporate script. However, others are discarding that playbook, embracing founder-led ads that deviate from the polished executive version.

    ```json
{
  "alt": "The CapmatchOne logo with a gradient circle and bold text.",
  "caption": "Discover innovation with the CapmatchOne logo, featuring sleek typography and a modern gradient circle.",
  "description": "The CapmatchOne logo features bold, modern typography coupled with a gradient circle, symbolizing connection and innovation. The sleek design conveys a sense of progress and creativity. This image can be used for branding or promotional purposes, appealing to audiences interested in innovative solutions and forward-thinking designs."
}
```

    There’s a catch.

    Breaking the rules works only when it’s genuine. I’ve learned that faking authenticity is easy to spot and can backfire. This was evident in a viral series of videos where McDonald’s CEO appeared to present a new burger, but his execution was criticized for being stiff and unconvincing.

    As shown in a Dineline video, his performance appeared staged. Contrarily, Burger King’s president presented their burger with no hesitation, offering a genuine and relatable moment.

    The distinction was evident: One was a product pitch, and the other felt authentic.

    If my leadership doesn’t genuinely believe in the product, neither will my customers. Rule-breaking should allow us to be real, rather than simply appear unpolished.

    ```json
{
  "alt": "A man in a light sweater speaks in a video with McDonald's fries and drink in front of him.",
  "caption": "A promotional video featuring a man discussing while enjoying McDonald's fries and a drink, set against a vibrant yellow background.",
  "description": "The image shows a man seated in an office setting, wearing a light sweater, speaking in a promotional video. In front of him is a McDonald's meal, including a box of fries and a cup with a plastic straw. The background is bright yellow, adding vibrancy to the scene. This promotional video appears designed to emphasize McDonald's offerings in a casual yet professional manner. Keywords: McDonald's, promotional video, fast food, marketing."
}
```
    A screenshot of a YouTube video of theMcDonald’s CEO with their new burger
    Source: Dineline on YouTube

    The Comment Hook Hijack

    You’ve probably encountered video hook best practices like ‘show the product in the first two seconds and state the value prop clearly.’ Sound familiar?

    Imagine my ad starting with a screenshot of a negative comment, like one for a skincare product stating, ‘This probably smells like old socks, and does it even work?’ My ad would then show the founder confidently disproving this in an unscripted manner, applying the product.

    Though this breaks the positive-association rule, it leverages viewers’ curiosity about digital conflicts. By the time they realize it’s an ad, they might already be engaged.

    A screenshot of a TikTok video ad with a comment bubble that a person is addressing
    Source: TikTok Creative Center

    The Rebel’s Safety Net

    I learned not to abandon all polished assets just yet.

    Rule-breaking is strategic, and often misunderstood when the ’80/20 rule’ is ignored.

    ```json
{
  "alt": "Man in a black hoodie answers a question about the game Survivor.io",
  "caption": "Exploring the unbeatable myth of Survivor.io, this video provides insights and tips.",
  "description": "A man in a black hoodie, marked with a logo, responds to a comment asking if Survivor.io is unbeatable. The background shows a two-toned wall with wood paneling. The video aims to address a common inquiry among players, sharing personal experiences and strategies related to the game. Keywords: Survivor.io, unbeatable, gaming tips, strategy."
}
```

    Switching completely to shaky phone footage isn’t wise. Keeping 80% of the budget in traditional ads while using 20% for testing unconventional ones can be effective.

    Next testing campaign, I plan to try:

    • The silent test: Running a silent ad with bold captions to stand out in a noisy feed.
    • The UI ghost: Using static images resembling platform notifications to pause scrolling.
    • The algorithmic trust fall: Disabling auto-optimizations in a campaign to test creative performance without constraints.

    Don’t Follow the Rules; Understand Them

    Best practices are a guide, not a strategy. To move beyond them, I do it systematically.

    I start by questioning the rule’s existence, evaluating its current relevance, and testing its opposite in a structured manner. Comparing traditional and lo-fi approaches helps me understand user engagement better.

    In an environment where brands play it safe, those who understand and strategically break the rules will capture attention and conversions. My goal is to learn faster than the competition, skipping guesswork.


    Inspired by this post on Search Engine Land.


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  • Unlock Unique Insights: Harness First-Party Data for Content Success

    Unlock Unique Insights: Harness First-Party Data for Content Success

    Have you ever wondered how to set your content apart in a competitive landscape? As a content marketer, I often face the challenge of using the same tools and data sources as everyone else, like Semrush, making it hard to create truly unique content.

    We are all casting our nets in the same pond, using identical resources to gather content ideas. The result? Overly similar content across the board. But there’s a smarter way.

    I realized that the wealth of data about my audience and customers is a goldmine, just waiting to be mined. These insights are invisible to my competitors, as they remain untouched and underutilized within my marketing team.

    I discovered how third-party tools often lead to an echo chamber of commoditized content. While essential, these tools don’t always align with what my specific audience is truly looking for, leading to a flood of generic content.

    Recognizing this challenge encouraged me to tap into my own data, creating content that appeals directly to people already interested in my services.

    First-party data is the information I need. It includes internal insights that only I have access to, such as site search queries, sales call transcripts, CRM data, support tickets, and email interactions.

    Let’s dive deeper into why this approach is effective. First-party data is proprietary. No matter how advanced a competitor’s tools might be, they can’t access my internal data, and this gives me a unique edge.

    This data reflects real buyer language, which helps me avoid assumptions based on my internal knowledge bias. I can tailor my content to match the language my audience uses.

    ```json
{
  "alt": "The CapmatchOne logo with a gradient circle and bold text.",
  "caption": "Discover innovation with the CapmatchOne logo, featuring sleek typography and a modern gradient circle.",
  "description": "The CapmatchOne logo features bold, modern typography coupled with a gradient circle, symbolizing connection and innovation. The sleek design conveys a sense of progress and creativity. This image can be used for branding or promotional purposes, appealing to audiences interested in innovative solutions and forward-thinking designs."
}
```

    By mapping this data to my entire marketing funnel, I fill gaps at every stage, driving not just traffic, but conversions and loyalty.

    How do I turn these insights into content ideas? I start with internal site searches. Examining how visitors use my site can reveal content gaps and opportunities for new offerings.

    Next, I analyze sales call transcripts and CRM data to uncover recurring themes and objections, crafting content that addresses potential buyers’ concerns directly.

    My support tickets provide another source of inspiration. By identifying common customer complaints, I create resources that help both my customers and support team.

    Lastly, I pay close attention to email replies and engagement metrics. Tracking which types of communication yield the greatest response helps me understand content preferences.

    Embracing first-party data helps my brand stand out. While competitors can mimic my content style, they can’t replicate these unique insights. Every week, I make it a point to explore a new data set and extract fresh content ideas.


    Inspired by this post on Search Engine Land.


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  • Enhance Your Strategy with Profound Knowledge Base

    Enhance Your Strategy with Profound Knowledge Base

    When I upload documents to the Knowledge Base, I provide Profound Agents with a comprehensive, single source of truth about my company’s unique information. This ensures that every marketing action performed on my behalf is informed with the right context about my brand.


    Inspired by this post on Try Profound Blog.


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