Category: News

  • SMX Advanced Expands to San Diego and Boston in 2027

    SMX Advanced Expands to San Diego and Boston in 2027

    You no longer have to treat SMX Advanced as a one-date, one-coast decision. In 2027, you can choose between San Diego in March and Boston in September, which makes geography, timing and the business problem you need to solve more important than fear of missing the only event.

    The useful move now is not simply to pick the closer city. Put both dates on your planning calendar, define what would make attendance worthwhile, and wait for the detailed agenda if your decision depends on specific SEO, PPC, AI-search or measurement coverage.

    The 2027 SMX Advanced schedule at a glance

    Two unlabeled calendar pages on a desk are paired with miniature coastal and red-brick harbor convention venues.

    For the first time in its history, SMX Advanced will run twice in one year. The two confirmed date blocks are:

    LocationDatesCoast
    San DiegoMarch 17-19, 2027West Coast
    BostonSeptember 20-22, 2027East Coast

    The expansion also coincides with the conference’s 20th anniversary. SMX Advanced began in Seattle in 2007 and has been positioned around advanced, actionable search marketing work rather than introductory instruction.

    Both 2027 editions are expected to include expert-led sessions, deeper discussions, detailed question-and-answer time, and structured and informal networking. That establishes a common format, but it does not establish that the agendas, speakers or individual session topics will be identical. Do not make a two-event commitment based on an assumed difference between the programs.

    Choose San Diego or Boston by your real constraint

    There is no universally better location. The right choice depends on which constraint is hardest for you to move: travel, timing, agenda relevance or team coverage. Work through them in that order.

    1. Calculate the full travel burden. Compare likely transit, lodging, time away from work and internal travel rules. A shorter trip can preserve more of the budget for attendance, but the lowest airfare alone does not reveal the total cost.
    2. Match the date to an actual decision. San Diego is the practical option if you need new inputs earlier in 2027. Boston may fit better if your major planning, budgeting or strategy work happens later in the year. Write down the decision the conference must inform before choosing the date.
    3. Decide whether topic specificity is essential. If you need sessions explicitly covering AI visibility, answer-engine optimization, generative-engine optimization, structured data, paid-search automation or a particular measurement problem, wait for named sessions. Those subjects should be selection criteria, not assumptions about the program.
    4. Plan team coverage deliberately. A distributed search team could send different people to the nearer coast, reducing the need for everyone to cross the country. If you are considering both editions, wait until the agendas give you a defensible reason to divide attendance.
    5. Treat networking fit as part of the choice. Both events will provide opportunities to meet peers, potential hires and employers across the search community. Decide which relationships matter to your role, then consider which location and date make those conversations more practical.

    If geography and calendar timing already produce a clear winner, you can select a city before the full agenda appears. If your choice depends on particular technical or strategic coverage, keep both dates provisional and let the program resolve the decision.

    Turn attendance into a working plan

    Three marketing professionals organize blank planning cards and notes around a laptop during a conference preparation meeting.

    SMX Advanced is designed for experienced practitioners who want ideas and tactics they can apply after the event. Your preparation should therefore begin with a live business problem, not a general desire to learn more about search.

    Write the approval case around an output

    A useful internal request should fit on one page. Give the person approving time and budget enough information to judge the return without asking them to interpret the conference for you.

    • Problem: Name the search problem you are responsible for solving, such as declining non-brand discovery, weak AI citation visibility, inefficient paid-search expansion or unreliable reporting.
    • Decision: State what you expect to decide differently after attending.
    • Session criteria: List the themes or practitioner experience the agenda must contain before you commit.
    • Questions: Prepare the hard questions you want to take into the in-depth Q&A sessions.
    • People: Identify the roles you need to meet, such as technical SEO leads, paid-media operators, analysts, potential hires or prospective employers.
    • Deliverable: Commit to a concrete return artifact: a prioritized test plan, an implementation brief, a measurement correction or a documented recommendation not to pursue a tactic.
    • Total cost: Include registration, travel, lodging, local transportation and time away from normal work. Verify approval and cancellation terms before buying travel that cannot be changed.

    Sort sessions by usefulness, not novelty

    The agenda will be assembled by the team behind Search Engine Land with a programming committee of SEO and PPC experts. Once session details are available, label each option as Must, Useful or Skip.

    • Must: The session maps directly to your defined problem and could change a pending decision.
    • Useful: The session closes a known capability gap but is not tied to an immediate decision.
    • Skip: The material appears too introductory, repeats knowledge your team already has, or has no clear path into your work.

    This filter matters at an advanced event because an impressive title can still be irrelevant to your operating environment. For every Must session, write the question you need answered and the evidence that would change your current position. That turns Q&A from an open microphone into a targeted research opportunity.

    Give networking a job to do

    Both editions will include structured and informal networking. Do not measure that time by the number of contacts collected. Prepare a one-sentence explanation of the problem you work on, a role-based list of people you want to meet, and a useful question for each type of conversation.

    When you return, convert notes into owned actions on the next working day. Give every worthwhile idea a decision, an owner and a place in the existing workflow. Ideas that remain in conference notes rarely affect search performance.

    Key takeaways

    • SMX Advanced will run twice in 2027: March 17-19 in San Diego and September 20-22 in Boston.
    • This is the first year with two SMX Advanced events and the conference’s 20th-anniversary year.
    • Both editions will feature advanced programming, expert-led sessions, deeper discussion, in-depth Q&A and networking.
    • The common event format does not prove that the two detailed agendas will be identical or different.
    • Choose now if geography and timing decide the issue; wait for program details if named topics or speakers determine the value.
    • Define the business decision, session criteria, questions, target relationships and return deliverable before requesting approval.

    What to watch before you commit

    The SMX Advanced event channel is the place to follow updates for both cities. As new details appear, check them against your written criteria rather than restarting the decision from scratch.

    • Session titles and descriptions that map to your priority problem
    • Speaker roles and evidence of relevant practitioner depth
    • Differences, if any, between the San Diego and Boston agendas
    • Registration pricing, deadlines, transfer rules and cancellation terms
    • Venue details and the full travel burden for your team
    • Sponsorship information if your objective is market presence rather than practitioner attendance

    For now, place both dates on hold and write your Must criteria. When the agenda arrives, you should be able to choose San Diego, Boston, both or neither without letting urgency make the decision for you.

    References


  • How I Justify GEO Investment Without Perfect Attribution

    How I Justify GEO Investment Without Perfect Attribution

    Fractured attribution

    My eight-year-old daughter desperately wanted a Nintendo Switch. Her “evil” parents—my spouse and I—refused to buy one for her.

    She was too young to get a job, so she did what any resourceful child would do: she opened a lemonade stand in front of our house.

    She did more than set out a table and a pitcher, though. She designed what amounted to a high-stakes A/B test.

    Her hypothesis was simple: if she could persuade more people to stop, she could sell more lemonade and reach her Nintendo Switch goal faster.

    Variant A was her two-year-old sister, Julie, stationed out front to attract attention.

    Variant B was our dog, Ginger.

    Lemonade stand visibility A/B test comparing Julie and Ginger

    I know what I would have guessed.

    The dog. Obviously, the dog.

    But Julie won—and it was not even close.

    The only metric that mattered

    The funny part is that my daughter did not really care about the A/B test result. She was not interested in how many people stopped at the stand or which variant produced the best response.

    She cared about one outcome and one outcome only:

    Side-by-side lemonade stand A/B test comparing a smiling young sister with a golden retriever, with Variant A marked the winner.
    At this lemonade stand, the cute-dog advantage loses: Variant A, featuring the seller’s young sister, wins the visibility A/B test over Variant B’s golden retriever.

    Did she make enough money to buy the Nintendo Switch?

    I believe marketers are facing a similar problem right now.

    Generative engine optimization (GEO) is the practice of increasing a brand’s visibility in AI-generated answers across platforms such as ChatGPT, Gemini, Perplexity, and AI Overviews.

    I can track AI visibility, citation share, impressions, rankings, and nearly every other signal available. Meanwhile, leadership is asking a much simpler question:

    Is any of this helping the business grow?

    I answer that question with a simple test I call the Dollar Rule: if I cannot put a dollar sign in front of a metric, I treat it as a channel metric rather than a business metric.

    That distinction captures the central measurement challenge in GEO.

    Most of the numbers we track are valuable operational signals. They show us what is happening within the channel, but leadership wants to understand the resulting business impact.

    GEO emerged at precisely the moment attribution was becoming less reliable.

    Traditional SEO measurement relied on a straightforward journey: someone searched, clicked, visited a website, and converted. We could trace that path and connect it to an outcome.

    Dollar Rule Framework infographic showing Align, Verify, and Translate steps for connecting imperfect GEO data to measurable financial impact.
    The Dollar Rule turns imperfect GEO attribution into a business case: align metrics with outcomes, verify directional signals, then translate performance into financial language leaders value.

    AI search disrupted that model.

    I now see buyers forming opinions and making decisions before they ever reach a company’s website. That makes AI’s influence much harder to capture with conventional attribution.

    AI search broke attribution

    I see buyers discovering brands through AI-generated answers, citations, publishers, forums, reviews, videos, and many other sources. Those touchpoints can shape a decision long before a click occurs, and much of that influence never appears cleanly in analytics.

    That is why I see so many teams struggle to justify GEO investments. The visibility is real, and the influence is real, but the attribution is frequently incomplete.

    I do not believe waiting for perfect attribution is a sound strategy. Increasingly, it is simply a convenient reason to avoid acting.

    When I want leadership to support GEO, I need to connect its influence to business outcomes—even when I cannot connect every interaction to a conversion.

    How I make the financial case for GEO

    The biggest mistake I see marketers make is trying to prove attribution before proving value.

    Before I worry about attribution, I ask whether I am measuring something the business actually considers important. That is where the Dollar Rule becomes useful.

    I have found that justifying a GEO investment usually comes down to three actions:

    • I align my metrics with business outcomes.
    • I verify that those metrics reliably point me in the right direction.
    • I translate the evidence into language a CFO understands.
    The Dollar Rule framework for connecting GEO metrics to financial impact

    My Dollar Rule is deliberately simple:

    Split target infographic contrasting high precision but low accuracy, with clustered misses, against high accuracy but low precision around the bullseye.
    Precision can form a tight cluster in the wrong place; accuracy keeps evidence centered on the outcome that matters. For GEO measurement, a useful estimate can beat an exact but irrelevant metric.

    If a number does not translate into dollars, I treat it as a channel metric, not a business metric.

    I focus on revenue opportunity, revenue at risk, payback period, and customer acquisition cost. Those metrics live on a P&L, and they are the numbers leadership teams use to evaluate investments.

    In my experience, CFOs do not allocate budget because an attribution model looks impressive. They allocate budget based on credible expectations of financial return, risk, and growth.

    That principle changes how I measure and present GEO.

    I measure influence, not just attribution

    AI search did more than change discovery. It changed what I can realistically measure.

    Traditional organic attribution assumes a clean sequence: search, click, visit, convert.

    AI platforms increasingly answer questions before a click, influence buyers across multiple touchpoints, and withhold the referral data marketers once relied on.

    That leaves me in an unusual position: a GEO campaign may be influencing pipeline even while the analytics platform struggles to prove it.

    One estimate illustrates the gap. Loamly estimates that roughly 70% of AI-influenced traffic appears as Direct traffic in GA4, making a substantial share of AI’s contribution difficult to trace through traditional attribution models.

    I do not take that measurement gap to mean measurement is impossible. I take it as a reason to broaden the evidence I examine.

    Quote graphic stating that a rough estimate of revenue impact beats a precise click count, illustrated by a scale weighing clicks against revenue impact.
    When attribution is incomplete, business value tips the scale: a credible estimate of revenue impact can guide GEO investment better than a perfectly precise tally of clicks.

    Instead of asking only, “How many clicks did we receive from AI search?” I ask:

    • Is our branded search growing?
    • Are prospects arriving already familiar with our positioning?
    • Are we being cited in AI answers for questions that drive revenue?

    I would not treat any one of these signals as definitive. When I combine them, however, they can create enough confidence to support a responsible investment decision.

    That is the essential difference between GEO measurement and traditional SEO measurement. I am not simply measuring a click path; I am measuring market influence.

    I believe the marketers who adapt fastest will stop treating attribution as a traffic-sorting exercise. We will combine quantitative signals with qualitative evidence because the goal is not absolute certainty. The goal is confidence that our GEO investment is moving the business in the right direction.

    Why I may be measuring the wrong thing

    I do not think SEO or GEO metrics are inherently wrong. The problem is that they can be highly precise without being relevant to the business outcome I am trying to influence. They tell me exactly what happened inside a channel, but not whether the business is moving in the right direction.

    SEO tools are packed with precise numbers. The challenge is that many of those numbers have only a weak connection to business outcomes.

    Precise = exact

    Accurate = connected to business outcomes

    I have found that leadership would rather receive a roughly correct estimate of revenue impact than a perfectly precise count of clicks.

    I studied engineering in school, where we spent a great deal of time discussing precision: how exact and repeatable a measurement is, right down to the decimal point.

    Infographic showing fuzzy math: 10% mention rate × 1,200 sales calls × $500K contract value × 20% win rate equals $12M in pipeline at risk.
    The fuzzy math equation turns a qualitative sales signal into a figure leaders understand: a 10% competitor-content mention rate translates to $12 million in annualized pipeline at risk.

    In marketing, I see that kind of precision in organic clicks, rankings, impressions, and click-through rates. Tools such as Google Search Console can give me extremely exact figures for those channel activities.

    Precision compared with accuracy in GEO and SEO measurement

    The problem is that a precise channel number is not necessarily accurate in the business sense. I consider a measurement accurate when it tells me whether I am getting closer to an outcome that matters.

    Even when those measurements are not perfectly precise, I find them more useful if they point toward the bullseye: the business outcomes leadership cares about.

    Knowing that a page received 40 organic clicks is precise. It tells me almost nothing about whether we are winning or losing in the market—just as a visitor count did not tell my daughter whether she was close to buying her Nintendo Switch.

    Revenue impact compared with a precise click count

    That is how I apply the Dollar Rule in practice. When attribution is incomplete, I translate the evidence I do have into a directional estimate of business impact.

    Why I put revenue ahead of attribution

    For me, a rough number tied to revenue beats an exact number tied only to channel activity.

    When reliable attribution is unavailable, I build the case from signals I can actually access and then work through the math.

    I do not use fuzzy math to replace SEO metrics or attribution. I use it alongside them when traffic-based attribution cannot capture the influence taking place.

    One of our healthcare clients gave us a useful example.

    Prospects were arriving at sales calls already convinced of claims that were not true.

    Vertical ladder infographic titled “Translating SEO Metrics for Your Leadership,” moving from impressions and citations to business outcomes and $122K in revenue.
    Climb from channel data to executive value: translate SEO impressions and citations into pipeline and lower CAC, then show leadership what matters—$122K in revenue and a three-month payback.

    We traced the source to a competitor’s comparison page. That page was shaping buyer perceptions long before our client had an opportunity to present its side of the story.

    We recommended publishing content that would counter the narrative, but the leadership team did not believe there was enough evidence to justify a response. We needed to make a stronger business case.

    SEO tools estimated that the competitor’s page received roughly 40 organic visits per month. Whether that estimate was right or wrong was beside the point: it did not measure the page’s influence on active buyers.

    So we looked for evidence that was closer to the business outcome.

    We spoke with our client’s salespeople. They told us that roughly 10% of qualified B2B discovery calls included unprompted mentions of specific claims from the competitor’s page.

    That was not a clean number suitable for an exact attribution model, but we could not dismiss it. The influence was real, and it was showing up during live sales conversations.

    We used that evidence to build a directional calculation:

    10% mention rate on discovery calls

    × 1,200 qualified B2B sales calls per year

    × $500,000 average contract value

    Quote graphic stating a competitor wins 64% of AI citations, appears in 10% of discovery calls, and influences $12 million in pipeline.
    A competitor’s comparison page earns 64% of citations on decision-stage AI questions and surfaces in 10% of discovery calls—putting an estimated $12 million in pipeline under its narrative.

    × 20% average win rate

    = $12 million in annualized revenue being influenced by the competitor’s narrative

    I did not present this as a forecast or a formal attribution model. It was a directional estimate of how much revenue the competitor’s messaging could influence.

    That reframing changed the conversation. We stopped debating 40 clicks per month and started discussing $12 million in influenced revenue.

    Fuzzy math equation estimating revenue influenced by a competitor narrative

    That is the number we brought to leadership—not impressions or citation share, but $12 million in revenue being influenced by a page our client had declined to counter. That is a number a CFO immediately understands.

    I lead with value metrics

    If we enter a GEO campaign review and lead with rising citation share or growing impressions, our CMO may lose interest and our CFO may wonder what those numbers mean financially. In the worst case, we can lose budget because leadership cannot see the return.

    Translating SEO and GEO channel metrics for leadership

    Here is how we framed the situation for our client’s leadership team:

    Executive talking points connecting market influence to revenue

    I have learned that leadership funds marketing campaigns based on business impact. Translating a problem into dollars changes the nature of the discussion.

    The decision-makers did not need certainty. They needed a credible financial story supported by leading indicators, observable momentum, and enough evidence to inspire confidence.

    I focus on what the business values

    That is what my eight-year-old intuitively understood at her lemonade stand. Her goal was never to count visitors. Her goal was to buy the Nintendo Switch.

    Angled smartphone displaying a ChatGPT screen with an Advertisement card, illuminated by blue and magenta neon light against a dark background.
    A neon-lit smartphone imagines advertising inside ChatGPT, highlighting how AI platforms are reshaping brand discovery, GEO strategy, and the measurement of marketing influence.

    GEO has created anxiety because it disrupted attribution models we relied on for years. But I remind myself that attribution was never the ultimate objective.

    The real objective is business growth.

    If I can connect GEO activity to revenue opportunity, revenue at risk, pipeline influence, or customer acquisition, I do not need perfect certainty to justify the investment.

    I need credible evidence that our GEO campaigns are moving the business in the right direction.

    Precise metrics tell me what happened. Relevant metrics tell me whether we are winning.

    Before I deliver my next GEO report, I can examine every metric on the page and ask one question:

    If this metric doubled tomorrow, would the business care?

    Then I ask the follow-up:

    Can I translate this metric into revenue opportunity, revenue at risk, pipeline influence, or customer acquisition cost?

    If I cannot, I am probably reporting channel impact rather than business impact—and that is unlikely to justify the next GEO investment.


    Inspired by this post on Search Engine Land.


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  • Google Merchant Center Drops “Next” in Simple Rebrand

    Google Merchant Center Drops “Next” in Simple Rebrand

    I’m adjusting how I refer to Google’s shopping platform now that Google has dropped “Next” from Merchant Center Next. Going forward, the product is simply called Google Merchant Center.

    Google made the change official in a Merchant Center announcement, saying, “The platform you use today will simply be referred to as Google Merchant Center.” For anyone managing product feeds, shopping campaigns, or merchant accounts, this is mainly a naming update rather than a product change.

    I remember when Google Merchant Center Next was introduced in 2023 as the newer version of the old Google Merchant Center. Over the past few years, more merchants, site owners, and advertisers moved into that updated experience.

    At this point, it appears that Merchant Center Next has effectively become the standard experience. So Google is removing the “Next” branding and returning to the simpler name: Google Merchant Center.

    Futuristic data archive with glowing server-like filing cabinets, stacked documents, and network lights symbolizing AI marketing data infrastructure.
    Rows of illuminated data cabinets and paper files stretch into the distance, capturing the pressure on marketers to turn fragmented customer data into a smarter performance engine.

    Google said users will start seeing the “Next” branding removed from Help Center articles, email communications, and the Merchant Center interface.

    Google also clarified that no action is required and that the name change does not affect existing accounts. In other words, I do not need to update settings, migrate anything, or make account-level changes because of this rebrand.

    Why does this matter? When I talk about Google’s merchant tools now, I can leave off “Next” and just call the platform Google Merchant Center. Honestly, that is what many of us were already calling it anyway.


    Inspired by this post on Search Engine Land.


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  • Traffic Think Tank Joins Search Engine Land Community

    Traffic Think Tank Joins Search Engine Land Community

    [Boston, MA, July 6, 2026] — I am sharing that Traffic Think Tank has officially joined the Search Engine Land family, creating more opportunities for search marketers like us to connect, collaborate, and keep learning through one of the industry’s most established professional communities.

    I want members to know that Traffic Think Tank will continue operating as a private Slack community. It will remain a trusted place where we can exchange ideas, validate strategies, solve real marketing challenges, and stay current on search engine optimization, paid media, artificial intelligence, and related marketing topics.

    As part of this relationship, I see Search Engine Land supporting the community’s continued growth by increasing visibility across its editorial and marketing channels while preserving the collaborative environment members already value.

    “For years, Search Engine Land has represented the marketing community through its contributor network in a way few other sites have,” said Kyle Morley, Head of Sales and Marketing at Third Door Media, parent to Search Engine Land. “Launching a community like Traffic Think Tank feels like a natural extension of our identity, and I’m thrilled we now have more opportunity to connect with marketers in our space.”

    I am also noting that David Broderick has been appointed Lead Community Manager and will oversee the day-to-day community experience. He will be supported by Liz Dougherty, who will take an active role in encouraging member engagement and helping guide the community’s continued growth.

    Beyond ongoing peer-to-peer discussions, I expect members to benefit from expanded community programming and discussions, increased visibility through Search Engine Land and Third Door Media channels, exclusive discounts on Search Marketing Expo events and training, and new opportunities to connect with search marketers across the industry.

    For me, Traffic Think Tank fits naturally with Search Engine Land’s mission of helping marketers stay informed and succeed in a rapidly evolving search landscape. Together, the publication and community give us access to trusted journalism, practical education, live events, and an active peer network for ongoing professional development.

    Futuristic SEO and AI search illustration showing old tools breaking apart as blue data streams lead to a glowing search platform and digital icons.
    Old search marketing tools give way to a faster, connected future, with data streams, AI icons, and a glowing search hub symbolizing SEO innovation and community growth.

    If you are a search marketer interested in joining the community, I recommend learning more at https://searchengineland.com/trafficthinktank.

    About Search Engine Land

    I view Search Engine Land as a leading publication for news, insights, and education covering search engine optimization, paid media, artificial intelligence, and digital marketing. Through editorial coverage, events, training, and professional resources, Search Engine Land helps marketers stay ahead of industry change.

    About Traffic Think Tank

    I see Traffic Think Tank as a private community for search marketers that connects professionals through expert discussions, peer collaboration, and practical knowledge sharing. Members use the community to exchange ideas, solve challenges, validate strategies, and stay current on what’s working across search engine optimization, paid media, and artificial intelligence.


    Inspired by this post on Search Engine Land.


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  • Google Review Glitch: Missing Reviews Under Investigation

    Google Review Glitch: Missing Reviews Under Investigation

    I’m tracking a growing Google Business Profile issue after several days of complaints from businesses that say reviews have disappeared from their local listings. Google has now confirmed that it is investigating the reports, and in some cases, review submissions on affected profiles appear to be paused.

    What Google said. Google told us that when its systems detect suspicious review activity, it may take several actions, including removing reviews and temporarily pausing reviews on a profile to prevent further abuse. Google also said it is investigating the issue and will restore any reviews that were incorrectly removed.

    What I’m seeing. As I documented on the Search Engine Roundtable, there are dozens of complaints in the Google Business Profile Forums from business owners and local SEOs who say their reviews have mysteriously vanished. In some cases, businesses are also unable to receive new reviews on their local listings.

    From what I can tell, Google’s review spam detection systems may be identifying certain patterns and aggressively removing or blocking reviews on suspected Google Business Profiles. What remains unclear is whether this is tied to spammers abusing some profiles, a recent algorithmic adjustment, or Google’s systems becoming overly sensitive.

    More details. Amy Toman, a volunteer Google Product Expert for Google Business Profiles, shared on LinkedIn that businesses or clients affected by this issue can post in the forum if they want to, but Google is already aware of the problem and working on it. She also noted that no timeline for a resolution has been provided yet.

    She said she is seeing a new pattern where, after fake or spam reviews are reported, some Google listings receive a review block and all reviews are hidden. In at least one case, she said the rating was reduced to 0.

    Why I care. If I noticed a sudden drop in reviews or stopped receiving new reviews this week, I would consider this issue a likely explanation. For local businesses, reviews can directly affect trust, visibility, and customer decisions, so even a temporary review disruption can be frustrating.

    Google is investigating, and I’m watching to see whether missing reviews are restored and whether affected Google Business Profiles can begin receiving new reviews again.


    Inspired by this post on Search Engine Land.


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  • 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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  • Fabrice Canel Leaves Microsoft Bing After Iconic Run

    Fabrice Canel Leaves Microsoft Bing After Iconic Run

    After nearly 30 years at Microsoft, I am seeing one of Bing’s most influential search leaders close a remarkable chapter. Fabrice Canel announced that he is retiring from Microsoft, writing on LinkedIn, “I am retiring from Microsoft, effective today July 1st.” He also reflected, “Today marks nearly 30 years with Microsoft. Thirty years…”

    When I think about Fabrice Canel’s impact, I think first about the foundation of Microsoft Bing Search. He was responsible for indexing at Bing, including crawling, URL discovery, content selection, and content processing. Those areas are core to how search engines understand the web, and Fabrice helped shape them at massive scale.

    He was also the person behind the IndexNow initiative, and he played a major role in creating and powering Bing Webmaster Tools. For anyone working in SEO, publishing, or technical search, those contributions matter because they helped make discovery, indexing, and webmaster communication faster and more practical.

    I have watched Fabrice contribute far beyond product work. He has spoken at countless industry events, including SMX, and has written extensively about how search works, how sites can perform better in Bing, and how search is evolving with generative AI. He helped run one of the world’s most important search engines, while also giving the SEO community tools, education, and direct insight.

    In his retirement message, Fabrice addressed fellow Microsoftees, engineers, attorneys, marketers, webmasters, publishers, SEO champions, product leaders, journalists, people across search and AI, and even friends at Google. His note was warm, personal, and full of gratitude for the people who shaped his Microsoft journey.

    He described his three decades at Microsoft as a wonderful adventure, from solving real business problems with IndexNow to helping webmasters and publishers thrive in the constantly changing world of SEO and AI. He thanked colleagues, partners, publishers, and the people he trained and mentored, saying they are ready to carry the mission forward.

    Fabrice also shared that, after many conversations with family and friends, he decided to take advantage of Microsoft’s Voluntary Retirement Program. His message ended with the same sense of warmth and storybook style that many in the industry have come to associate with him: gratitude for Microsoft, confidence in the Bing team’s future, and a final wish that everyone stay curious, keep innovating, and make content easier to find.

    Why do I care so much about this? Because Fabrice has been a true friend to the search industry. His work will live on through the products, systems, and initiatives he helped create, and his willingness to share knowledge has made a lasting difference for SEOs, publishers, developers, and search professionals.

    I know Fabrice has trained a team to continue the work, and I believe Bing remains in good hands. Still, I would be lying if I said I am not sad to see him retire. It has been an honor to work with him and learn from him over the years, and his legacy at Microsoft Bing will be felt for a long time.


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  • Google Clarifies Age Estimation Ads Policy for Advertisers

    Google Clarifies Age Estimation Ads Policy for Advertisers

    I’m watching Google update its advertising policy to make clearer how certain ads are limited while the company estimates a user’s age. The change gives advertisers more transparency as Google expands its age assurance technology worldwide.

    What I’m seeing: Google has renamed its Default Ads Treatment policy to “Categories restricted while Google is estimating a user’s age.” To me, that wording matters because it makes the policy sound less like a permanent restriction and more like a temporary safeguard while Google’s systems work out whether a user is old enough to see certain types of ads.

    What’s changing: I see three main updates here: the policy has a clearer name, the language now emphasizes that these protections are interim measures during the age estimation process, and enforcement remains unchanged.

    What’s different: Google has also narrowed the list of ad categories restricted while a user’s age is being estimated. Previously, the restricted categories included adult content and pornography, alcohol, gambling, and shocking content.

    Under the updated policy, I now see only three restricted categories: adult content and pornography, alcohol, and gambling. Shocking content no longer appears on that restricted list.

    Why I care: This update does not introduce new advertising restrictions, but it does make the policy easier to understand. For advertisers in affected verticals, the key takeaway is that these limits are tied to Google’s age estimation process, not a broader or permanent policy shift.

    The bottom line: I do not see any operational change for advertisers, but Google’s updated policy makes it much clearer that restrictions on adult, alcohol, and gambling ads are temporary safeguards while a user’s age is being estimated.


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  • Google Ads All Campaigns Redesign Makes Navigation Easier

    Google Ads All Campaigns Redesign Makes Navigation Easier

    I’m seeing Google Ads roll out a redesigned All Campaigns selector, and the goal is clear: make it easier to move through large, complicated account structures without wasting time hunting for the right campaign.

    What’s happening is that Google is refreshing the All Campaigns selector across Google Ads with a cleaner layout and better navigation tools. For advertisers who manage bigger accounts, this should make day-to-day campaign work feel more organized.

    The selector has also been moved to a new location in the interface, which means I’d expect some advertisers to need a short adjustment period before the new placement feels familiar.

    The biggest improvement I notice is the new expandable hierarchy view. Campaigns now appear in a structure that makes campaign groups and nested setups easier to browse, especially when an account has grown beyond a simple list of campaigns.

    Google has also added search inside the selector, which should help advertisers quickly find specific campaigns or campaign groups instead of manually scanning through long account lists.

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    Why I care: this update could save meaningful time for anyone managing large Google Ads accounts. When campaigns are split across multiple groups or complex organisational structures, faster navigation can make daily optimization work less frustrating.

    The bottom line is that Google’s redesigned All Campaigns selector is meant to streamline campaign management with a clearer hierarchy and built-in search, helping advertisers navigate complex accounts more efficiently.

    The update was first spotted by performance marketer Vivek Gupta on LinkedIn. Since the rollout is gradual, I would not expect it to be available in every Google Ads account immediately.


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