Category Archives: AI Search & Visibility

Brief the Analysts: You’re Aiming at the Pins Instead of the Arrows

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The free channel every founder walks past on the way to buying more ads.

A textbook strike touches four pins. Four. The ball hits the 1, the 3, the 5 and the 9, and the other six go down because pins hit pins. Founders keep trying to hit all ten with the ball. That is not how the deck works, and it is not how AI-assisted buying works either. The assistant your buyer is talking to does not take your word for anything. It goes looking for someone else to say it first.

  1. Your website is the 5-pin, not the headpin. AirOps found roughly 85% of brand mentions live on third-party pages rather than your own domain, and Otterly’s State of AI Search puts the figure at 95% of all AI citations. One study of 233 ChatGPT software recommendations found the vendor’s own site cited just 11.6% of the time. You are being talked about, not read.
  2. Aim at the arrows. The lane is 60 feet long; the arrows sit about 15 feet out. Nobody decent stares at the pins, because you cannot control something 60 feet away, you can only control what the ball does at 15. Analysts and research sites are the arrows. Hit those and the pins take care of themselves.
  3. The whole invoice is one hour. Gartner vendor briefings run 45 minutes with one or two analysts, routed to a specialist within a business day and typically scheduled two to four weeks out. Forrester allots 30 or 60. Neither requires you to be a paying client, and most firms will take one or two briefings a year from a non-client. An hour. A deck. A calendar hole. That’s it.
  4. Do not throw it harder. Ball speed never fixed a bad line, and volume never fixed a bad pitch. Analysts have sat through hundreds of these. Give them the five-minute version: who you are, what problem you kill, who switched to you and what they left behind. Do not open with a demo, and never quote a rival firm’s market forecast in the deck.
  5. You are not leaving a split, you are not bowling. Quoleady’s 2026 research found 100% of tools that ChatGPT named in B2B answers had Capterra reviews and 99% had G2 reviews. Being absent from the sources isn’t a bad shot, it’s showing up without a ball. Meanwhile only about 30% of brands stay visible in back-to-back responses to the same question, so one appearance is not a position.
  6. Carry compounds, and so does staleness. Pin action is the whole game: an analyst mentions you, the trade press repeats it, the crawlers eat the trade press, and the model repeats it back to your buyer. But roughly 65% of AI crawl activity targets content from the past year, and pages refreshed within two months earn about 28% more citations. Coverage dries out like lane oil. Re-brief.
  7. Read your own lane. One Q2 2026 sample had the big aggregators at only 8.6% of citations; another had G2 as ChatGPT’s fourth most-cited source. Both are probably right for their category and wrong for yours. House shot or Sport pattern, you find out by throwing the ball and watching, not by trusting a stranger’s chart. Including mine.

The score. A 300 is twelve strikes, but it’s really one shot you trusted twelve times. The briefing is that shot: repeatable, free, and boring in the way profitable things usually are. Your competitor booked theirs in March.

Own the Dictionary: Build the Glossary Nobody Else Bothered to Write

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Everybody wants to write the definitive guide. Almost nobody wants to write the definition. That gap is the cheapest authority play left on the internet, and it is sitting there unclaimed like a live straddle nobody noticed.

  1. Definitions are the most retrievable prose there is. Roughly 70% of Google’s featured snippets are paragraph snippets – the definition box – and Semrush pegs the winning ones at 40 to 60 words. Sixty words. You have written longer text messages declining a dinner invitation.
  2. Nobody owns the vocabulary of your niche. There is no rights-holder for “polarized range” or “minimum defense frequency.” The dictionary of your industry is unsurveyed land, and the deed goes to whoever bothers to walk it first.
  3. Forty terms, not four. Ahrefs found a single article holding 4,658 featured snippets across the keyword universe. Forty entries is forty front doors, each catching phrasings you would never have thought to target on purpose.
  4. The long tail is where definitions live. Backlinko found 54% of featured snippets come from searches doing under 50 queries a month. Semrush found 55.5% of ten-word queries trigger a snippet versus 4.3% of one-word queries. Nobody wins “poker.” Anybody can win “what is a donk bet and why is it called that.”
  5. Write the disagreement – that is the entire moat. Any intern can type “a donk bet is a lead into the previous street’s aggressor.” The version that gets quoted for a decade adds that purists restrict it to the flop, that it was coined as an insult, and that solvers have since made it standard – meaning half the internet is using a slur to describe correct play.
  6. Three more you can steal tonight. “GTO” strictly means a Nash equilibrium in a heads-up zero-sum game, and its guarantees quietly evaporate three-handed – yet it gets used daily to mean “whatever the solver said.” Sklansky defined a semi-bluff as a bet that is probably not best but can improve; today people call king-high a semi-bluff. And a “merged” range means value-plus-marginal to one camp and close to the opposite to another. Say so. Cite both. Now you are the referee.
  7. Front-load or forfeit. About 44.2% of AI citations are pulled from the first 30% of a page. Term, one clean sentence, then the nuance. Bury the answer and you are bluffing into a machine that folds instantly and never pays you off.
  8. Mark it up. Schema-tagged pages are cited roughly 2.3x more often in AI Overviews. Definition schema takes fifteen minutes. That is the best price-to-equity ratio on this page.
  9. The door is open right now. Ahrefs’ March 2026 data shows only 38% of AI Overview citations come from top-10 organic results, down from 76% a year earlier. You no longer have to outrank Wikipedia. You have to out-define it – and Wikipedia is not allowed to have an opinion about which definition is better. You are.

Guides get skimmed and forgotten. A glossary gets bookmarked, linked, argued with, and quoted – by people and by models – for years. Write forty definitions, note who disagrees and why, and stop playing the hand. Become the house.

Answer in Spanish: The Second Court Nobody Is Playing

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Your English authority stops at the net. In U.S. insurance distribution, the other court is empty.

1. Clay is not grass. Rafael Nadal won Roland Garros fourteen times. That bought him zero free points at Wimbledon, where he won twice. Same forehand, different surface, different bounce, different everything. Language models work the same way: each language is a partially separate knowledge space. Ranking #1 in English does not seed you in the Spanish draw. Nobody carries a ranking across the net for free. Surfaces are learned.

2. The 97-to-19 problem. Researchers taught a model new facts in English. Quizzed in English, it recalled them 97% of the time. Quizzed on the identical facts in another language, accuracy fell to 19%. Same model, same facts, one language apart. A second study estimates perfect cross-language sharing could lift accuracy up to 150% – a polite academic way of saying it does not happen today.

3. Untranslated means invisible. If your annuity explainer and licensing FAQ exist only in English, a Spanish query does not rank you low. It does not see you. You are not losing the point; you never entered the tournament. English is 49.7% of identifiable web content, Spanish just 6.0% (W3Techs, June 2026).

4. The crowd is already in the stadium. 44.9 million U.S. residents speak Spanish at home (2024 ACS) – 1 in 7 people age five and up. That group grew 21.3% from 2010 to 2024 while the population grew 11.2%. And 41% say they speak English less than “very well.” They are asking chatbots about deductibles, beneficiaries and IUL right now, in Spanish.

5. The number that should sting. Hispanic life insurance ownership fell from 51% in 2021 to 40% in 2025, the lowest of any group LIMRA tracks. Roughly 20 million Hispanic adults say they are underinsured, and 72% overestimate what term costs. That is not a demand problem – the demand is already there. It is an answer-supply problem, and the answers are sitting in the wrong language.

6. Do not practice against a ball machine. Auto-translating your English pages is hitting against a ball machine and calling it a match. “Rider,” “surrender charge,” “face amount” – rendered literally, they land as nonsense that no Spanish speaker and no model treats as authoritative. Write it natively, in the vocabulary agents actually use in Miami and Houston.

7. Serve first. Carlos Alcaraz did not inherit a grass game. He built one on purpose, then won Wimbledon in 2023 and 2024. The Spanish-language retrieval surface in insurance is wide open and lightly defended. Every month you leave it untranslated is a free point handed to whoever translates first.

Searching Your Own AI Archive Is a Trip Back to 1997

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You worked on it three days ago. The keywords were specific, unusual, and yours. You type them in. The first result is from two months ago. The second has nothing to do with anything. The third one is what you wanted.

Anyone who used the web before Google knows that feeling. AltaVista held the whole index and ranked it badly: term frequency over intent, no notion of authority, no sense of when. You learned to scroll, to guess synonyms, to accept that the machine had your answer and could not put it on top.

Recency Is a Signal, Not a Tiebreaker

The failure repeats across Claude, ChatGPT, Gemini and Grok, because retrieval runs on semantic similarity alone. But a person searching their own history is not asking what is most alike. They are asking what did I just do. Recency, revisits, thread length, whether the session actually produced something: all ranking signals, all mostly unused. It is the absence of PageRank over again. The corpus is excellent; the ordering is naive.

Citizen Kane opens in a warehouse of a dead man’s possessions, catalogued and worthless. The one object that explained him sits there, indistinguishable from the crates around it. That is an index without ranking.

The Irony Is Exquisite

The people who solved this are alive and employed. Twenty-five years of work on freshness decay, click models, query intent and personalization sits at Google, at Microsoft, and in every ranking team they trained. The AI labs rebuilt retrieval from first principles and faithfully reproduced 1998.

The fix is not a bigger model. It is an information retrieval hire.

Search companies helping AI companies with search – that is the hoot. Welles had never directed a feature when he made Kane. He also had Gregg Toland, who had shot fifty of them and knew exactly where to put the camera. Vision needed craft standing next to it.

What Good Looks Like

Time-aware ranking on by default. Filters that survive contact with a real question. A working answer to “the last thing I did on X.” And one line telling you why a result matched, so you can correct the query instead of guessing at it. None of this is research. It is product work that was finished a generation ago and simply never carried across.

Kane ends with reporters combing an archive for a single word, failing, while the answer burns in front of them. Our archives are smaller, better indexed, and still ask us to guess. Rosebud was in the room the whole time.

Maintain, Do Not Publish

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Every content meeting ends the same way. Somebody asks how many posts we’re shipping. Nobody asks how many we’re fixing. American Idol learned what that costs in front of 30 million people.

𝗧𝗵𝗲 𝗧𝗵𝗶𝗿𝘁𝗲𝗲𝗻-𝗪𝗲𝗲𝗸 𝗦𝗵𝗲𝗹𝗳 𝗟𝗶𝗳𝗲

  1. 𝗧𝗵𝗲 𝘄𝗶𝗻𝗱𝗼𝘄 𝗶𝘀 𝘄𝗲𝗲𝗸𝘀, 𝗻𝗼𝘁 𝘆𝗲𝗮𝗿𝘀. Roughly half the content cited in AI answers is under three months old. Ahrefs analyzed 17 million citations: cited pages run 25.7% fresher than the organic results. ChatGPT is most ruthless: 76.4% of its top-cited pages were updated within 30 days. Your 2023 masterpiece isn’t evergreen. It’s a rerun.
  2. 𝗥𝗲𝗳𝗿𝗲𝘀𝗵𝗶𝗻𝗴 𝗽𝗮𝘆𝘀 𝗯𝗲𝘁𝘁𝗲𝗿 𝘁𝗵𝗮𝗻 𝗽𝘂𝗯𝗹𝗶𝘀𝗵𝗶𝗻𝗴. AirOps tracked 4,000-plus cited pages: 35.2% were updated within three months, 53.4% within six. Refreshed pages average 6 citations versus 3.6 for stale ones, a 67% lift on work you already paid for.

𝗦𝗲𝗮𝘀𝗼𝗻 𝟭𝟮 𝗪𝗮𝘀 𝗮 𝗣𝘂𝗯𝗹𝗶𝘀𝗵𝗶𝗻𝗴 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝘆

  1. 𝗠𝗼𝗿𝗲 𝘀𝗲𝗮𝘀𝗼𝗻𝘀 𝗶𝘀 𝗻𝗼𝘁 𝗺𝗼𝗿𝗲 𝗿𝗲𝗹𝗲𝘃𝗮𝗻𝗰𝗲. Idol peaked in 2006-07 at 30 million viewers a night. When numbers slipped, Fox did what content teams do: more, louder. The Season 12 finale drew 14.3 million, off 40% in a year and the first ever to miss 20 million. Average audience fell from 23.1 to 13.2 million in two years. Volume wasn’t the fix. Volume was the symptom.
  2. 𝗧𝗵𝗲 𝗼𝗹𝗱 𝗮𝘀𝘀𝗲𝘁 𝗼𝘂𝘁𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗲𝗱 𝘁𝗵𝗲 𝗻𝗲𝘄 𝗼𝗻𝗲𝘀. Carrie Underwood won Season 4 in 2005, became the best-selling Idol winner ever, and returned 20 years later as a judge. Idol didn’t need a new champion; it needed to update the one it had.
  3. 𝗔 𝗻𝗲𝘄 𝗱𝗮𝘁𝗲 𝗶𝘀 𝗻𝗼𝘁 𝗮 𝗿𝗲𝗳𝗿𝗲𝘀𝗵. Fox cut Idol from 50 hours a season to 37 and rotated the panel. The audience left anyway, bottoming at an 8.03 million finale. A fresh timestamp on a 2023 pricing table is a new stage set, same tired song.

𝗡𝗮𝗺𝗲 𝗮𝗻 𝗢𝘄𝗻𝗲𝗿. 𝗧𝗵𝗲𝗻 𝗢𝗽𝗲𝗻 𝗮 𝗖𝗮𝗹𝗲𝗻𝗱𝗮𝗿.

  1. 𝗦𝗼𝗺𝗲𝗯𝗼𝗱𝘆 𝗵𝗮𝘀 𝘁𝗼 𝗯𝗲 𝗦𝗲𝗮𝗰𝗿𝗲𝘀𝘁. Twelve judges have come and gone, from Cowell to Katy Perry. Ryan Seacrest has hosted since 2002. Maintenance without a named owner is a group project, which is to say nobody’s job.
  2. 𝗧𝗵𝗲 𝗰𝗮𝗱𝗲𝗻𝗰𝗲 𝗶𝘀 𝘁𝗵𝗲 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝘆. Idol opens auditions every August, excited culture or not. Rank your top 20 pages by revenue and refresh five a month; everything gets touched twice a year.
  3. 𝗧𝗵𝗲 𝘂𝗻𝗴𝗹𝗮𝗺𝗼𝗿𝗼𝘂𝘀 𝗲𝗻𝗱𝗶𝗻𝗴 𝗶𝘀 𝘁𝗵𝗲 𝗴𝗼𝗼𝗱 𝗼𝗻𝗲. Idol returned on ABC in 2018 and still runs in 2026, season 24, at 5.9 million viewers a week. Nobody throws a party for updating a pricing page. Do it anyway. The citation goes to whoever showed up this quarter.

Twenty maintained pages beat twenty new ones. You already know which twenty.