Kaleigh Moore

In their view, credibility belongs to the individual expert, not the brand.

• Models favor expertise that appears repeatedly across independent sources and is attached to a verifiable name.
• Moore coined the term "Creator AEO" for earning AI citations through human expertise published on third-party platforms.
• They include LinkedIn creators, B2B influencers, customer advocates, and employees in the category.
• They also argue that, because individuals get cited, how a person is described across the internet becomes a practical asset.
• Their advice: narrow a topic until it feels slightly uncomfortable, write a headline that makes a claim rather than states a job title, publish material built to be lifted—lists, headings, named tools, hard numbers—and use the same exact version of your name everywhere while claiming bylines you already hold.
• Guest-post bios, podcast pages, and speaker profiles are an under-managed surface, Moore argues.

Kaleigh Moore reports that LinkedIn is the most cited source for work-related queries in AI tools, that 75% of those citations go to individuals rather than company pages, and that more than half of the cited people have fewer than 10,000 followers.

• To apply the idea, they built a tool with Ahrefs Agent A that finds every site carrying their bio, ranks them by Domain Rating, identifies the right contact at each site, and drafts an update request.
• They send three to five emails a week and report four bio updates on DR 90+ sites.

Kaleigh Moore developed the Creator AEO argument in a special edition of Lia Haberman's newsletter.

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The old approach—writing one post around one keyword phrase—no longer matches how the answer is built.

• A brand has to answer the whole constellation of questions around a purchase.
• Moore argues that language models reward depth and specificity, so marketers should go deep on one narrow slice and answer questions buyers did not know to ask.
• They urge readers to ask themselves whether they truly own a topic or merely show up for it.
• Moore says they have advocated narrowing to a specific niche for about a decade.

Their example is a B2B SaaS founder coach looking for a CRM.

• In the old model, a brand writes one post called "Best CRM for B2B SaaS Founder Coaches" and hopes it ranks.
• In the new one, the brand must cover the setup walkthrough, how it handles HubSpot contacts, the learning curve, whether it integrates with call recording software, what happens as the client list grows, and the cost after the free trial ends.

Kaleigh Moore traces the niche argument to about ten years ago, when they taught freelancers with Paul Jarvis on Creative Class. They now discuss it on the Fan Out podcast, which they co-host with Krista Doyle.

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AI speeds up tedious writing, they say, but creates nothing wholly new because it works only from existing information.

• It cannot interview a real person or fact-check itself; Moore notes that it will invent data.
• Nor can it replace the original perspective that comes from lived experience.
• They rank prompting as the most important skill right now and teach it by comparing the process to onboarding a junior writer: give the model examples, dos and don'ts, brand guidelines, and full content briefs.
• They also make the human side of that process a priority.

Kaleigh Moore wrote that they have never used AI more than they do now, and have also never hired more human professionals.

• They named a website designer and video editors among the people they pay rather than automate.
• They discussed the same argument on the Practical Ecommerce podcast, hosted by Eric Bandholz.

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A survey figure they cite shows 52.8% of marketers saying their SEO team handles AEO, while Reddit, YouTube, and LinkedIn rank close behind as cited sources.

• Those are communities, not search surfaces.
• Moore argues that work with strong social and community dimensions has landed with a team that may lack the context to do it well: you cannot keyword your way into a human conversation, and no one inside most organizations clearly owns AI search visibility end to end.
• They see a career opportunity in that gap: someone who can speak credibly about both citation rates and community norms is becoming a scarce, valuable hire in B2B marketing.

Kaleigh Moore says they repeatedly ask people how their teams handle AEO and AI search visibility, only to find that no one can say who owns the work as a whole. They see an opening for marketers amid job cuts.

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This explains what they are hired to do and shows their view that the problem is as much organizational as technical.

Kaleigh Moore describes a mid-market B2B SaaS company of about 300 employees whose teams tracked ChatGPT, Perplexity, and Google AI Overviews but did not know what to do with the findings. After the session and 90 days of follow-through, they report that the brand's mention rate across its tracked prompt set rose from 11% to 24%, about 30% of the creator budget shifted to creators already appearing in AI answers for the category, and creator briefs were rewritten around the specific buyer questions each piece should answer.

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They describe twelve years of self-employment, content marketing projects drying up, reaching the final stages of two full-time interviews and losing both, and deciding in February 2026 to go all-in on being a B2B creator on LinkedIn, with a rebuilt newsletter and YouTube channel.

• They say they keep wrestling with the title "B2B creator" because it sounds bizarre for a 37-year-old woman rather than a twenty-something with a large Instagram following.
• They see the work as the next evolution of their content marketing and journalism, now done on camera and distributed through their own channels.
• They are equally direct about the economics, including thinner margins after heavy spending on video production.

Five months in, they reported $72,422 in revenue, 2,068 new email subscribers, 1.2M Twitter impressions, 720,200 LinkedIn impressions, 8 brand deals for ongoing content creation, and one paid speaking offer.

• At six months, they said their margin was the thinnest in six years after spending more than $37,000 on video production and related professional services.
• In a separate post, they noted they had deliberately booked no new client work for ten weeks while making the shift.

Kaleigh Moore presents their creator work as a continuation of an earlier career: PR at a Feeding America food bank; an Etsy jewellery business that passed $100K with no paid ads; social media retainers for a PBS station and Illinois state tourism; freelance SaaS writing for teams at Shopify, Stripe, SAP, IBM, and AT&T; an SEO content agency that peaked above $550K in a year; and journalism for Forbes, Vogue Business, and Time Inc.

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Start here for their central argument before reading their tactical posts.

Moore defines "Creator AEO" as earning AI citations through human expertise published on surfaces a brand does not own.

• They contrast it with the onsite blog work most companies already do, which they say caps out at the small share of citations a company's own domain can earn.
• Corroboration is the mechanism: models favour expertise that appears repeatedly across independent sources attached to a verifiable person.
• Individual experts, not the brand, are the unit of credibility.
• Moore wrote a deeper version for Lia Haberman's newsletter.

For brands planning a campaign

Build a brief around this: commission a named expert to publish substantive, consistent material on their own LinkedIn, YouTube, or newsletter—not another piece on the brand blog. Ask partner creators to answer specific buyer questions so the same expert appears across several independent places.

This is the item that shows their consulting method end to end.

Moore describes a session they ran for a mid-market B2B SaaS company of roughly 300 employees, whose social, influencer, SEO, and content leads were not aligned on AI visibility.

• The session covered how answer engines choose sources; a citation gap analysis against three competitors, by engine and by which creators drove mentions; a shared KPI (the team chose Google AI Overviews); and a written cross-departmental plan naming internal owners and revising creator briefs around specific buyer questions.
• At 90 days, the brand's mention rate across the tracked prompt set rose from 11% to 24%, and the influencer team moved about 30% of its creator budget toward creators already appearing in AI answers for the category.

For brands planning a campaign

A paid engagement could include a working session across marketing teams, competitor citation benchmarking, agreed KPIs, and creator briefs rewritten around specific buyer questions. Buyers can use Moore's 90-day results as a realistic benchmark when setting expectations.

This is the clearest plain-language explanation of the change in search they are reacting to.

Moore explains query fan-out: a tool like ChatGPT, Perplexity, or an AI Overview takes one question, expands it into five to twenty sub-questions, then stitches the best answer to each into one response.

• Their worked example is a business coach searching for a CRM.
• The old approach was one blog post targeting one phrase; the new approach means owning the whole constellation of setup, migration, learning-curve, integration, growth, and pricing questions.
• Moore ties this back to teaching freelancers to niche down with Paul Jarvis on Creative Class, and notes they co-host the Fan Out podcast on AI search with Krista Doyle.

For brands planning a campaign

Shift a content plan from keyword coverage to topic ownership. Brief creators to answer the sub-questions buyers actually ask, not to repeat one headline phrase.

This is an unusually candid account of their move into creator work, with their own results.

Moore describes deciding in February 2026 to pivot into B2B creator work after twelve years of self-employment, losing out on two full-time content roles, and committing to daily LinkedIn posts plus a rebuilt newsletter.

• They report trying B2B influencer matching platforms for small deals, hiring out video editing, relaunching a dormant YouTube channel, and moving their newsletter to beehiiv.
• Moore's stated five-month numbers are $72,422 in revenue, 2,068 new email subscribers, 1.2M Twitter impressions, 720,200 LinkedIn impressions, 8 brand deals for ongoing content creation, and one paid speaking offer, with over 12,500 subscribers across beehiiv and LinkedIn.
• They also note hiring human specialists for editing and web design rather than doing everything themselves.

For brands planning a campaign

Moore's posts show audience growth and inbound brand demand within a short window, and a creator willing to publish performance data. Their transparency about results makes terms and outcomes easier to discuss for a pilot sponsorship.

This is the fastest way to see the range they draw on.

In a post written with Lia Haberman, Moore traces their path: PR at a Feeding America food bank after college; an Etsy jewellery business run for five years that passed $100K with no paid ads and gave them their first influencer-marketing experience; social media retainers for a local PBS station and Illinois state tourism; freelance SaaS writing through referrals for teams at Shopify, Stripe, SAP, IBM, and AT&T; a small SEO content agency that peaked at over $550K in a year; journalism for Forbes, Vogue Business, and Time Inc.; consulting with international agencies on legacy and luxury brands; and a Harvard graduate programme after AI cut writing demand. They describe advising and auditing brands on building AI visibility as the combination of all of it.

For brands planning a campaign

For a report-led campaign, name these skills: Moore reads research with a journalist's eye and can interview subject-matter experts—a different deliverable from a standard sponsored post.

This is a rare itemised list of the work itself.

Moore openly wrestles with the title, noting they are a 37-year-old woman who works with B2B companies on sponsored and co-authored content on LinkedIn, Twitter, and their newsletter.

• They list the work: diving into companies' new reports and tying findings back to what they know about LLMs and AI visibility; demonstrating tools and use cases from their own stack; and explaining on video how to start AEO work.
• Moore frames this as the next evolution of content marketing and journalism, now done on camera and distributed through their own channels, with their own subject-matter reputation at stake.

For brands planning a campaign

These three formats—report analysis, tool demonstration, and how-to video—map cleanly onto a SaaS brief. Ask for the report analysis when the goal is citation-worthy commentary, and the tool demo when the goal is product education.

The recap opens with Moore saying they spent more than $37,000 on video production and related professional services in 2026.

• August marks six months of doing B2B creator work as their actual job rather than a side project.
• They promise an honest recap, including the fact that their margin is the thinnest in six years.

For brands planning a campaign

Signals that video is a real production line, not a phone-recorded add-on—a relevant distinction when a brief needs polished video. Ask for the full post before citing details beyond the opening of this recap.

Moore reports that LinkedIn is the most cited source for work-related queries in AI tools, that 75% of those citations go to individual people rather than company pages, and that more than half of the cited people have fewer than 10,000 followers.

• They trace the common problem to scattered, vaguely described expertise that no model can attach to one identifiable human.
• Their four-step fix: narrow a topic until it is uncomfortable; rewrite the LinkedIn headline to make a claim rather than state a job title; publish content built to be lifted, such as lists, clear headings, named tools, and hard numbers; and use one exact version of your name everywhere while claiming existing bylines.

For brands planning a campaign

Directly supports a creator roster decision: individual experts on LinkedIn, including smaller accounts, are the ones being cited. The four steps also double as a brief template for creators a brand works with.

Moore describes updating their historical bios across the web so that language models build an accurate entity graph around their current focus on AEO for B2B SaaS.

• They built a tool with Ahrefs Agent A that pulls every site where their bio appears, ranks them by Domain Rating, identifies the right contact at each site, and drafts an outreach email requesting an update.
• Moore sends three to five emails a week and reports four bio updates on DR 90+ sites, with a compounding effect on how models verify their expertise.
• The post is labelled as a partner post.

For brands planning a campaign

A concrete, cheap AEO tactic a client team can copy: audit distributed bios on guest posts, podcast pages, and speaker profiles, then work the list. The post also shows Moore building and demonstrating a working tool inside sponsored content.

Her published case study covers a mid-market B2B SaaS company (about 300 employees) whose social, influencer, SEO, and content leads were unsure how to respond to buyers researching in ChatGPT, Perplexity, and Google AI Overviews.

• The session explained how answer engines choose sources, compared the brand’s AI citations with those of three competitors by engine, helped the teams agree on shared KPIs and choose one engine to focus on, then assigned named owners for creator selection, brief changes, and community engagement.
• She reports that the brand’s mention rate across its tracked prompt set rose from 11% to 24% in one quarter, about 30% of creator budget shifted to creators already cited in the category, and creator briefs were rewritten around specific buyer questions.

A four-part working session: teach current retrieval and citation patterns, quantify the citation gap against competitors, agree on joint KPIs, then assign cross-departmental ownership with a 90-day re-evaluation.

For brands planning a campaign

Brands can hire Kaleigh Moore for a cross-team workshop, not just a single deliverable. They can expect a session that brings social, SEO, content, and influencer teams together to leave with named owners, shared metrics, and creator briefs tied to buyer questions.

Examples: Source 1

She calls this off-site work “creator AEO”: earning AI citations through human expertise published on third-party surfaces.

• The umbrella includes LinkedIn creators, B2B influencers, customer advocates, and employees.
• The mechanism is corroboration: models surface expertise that appears repeatedly across independent sources and is tied to a verifiable name.
• She wrote a special edition of Lia Haberman’s newsletter on the topic.

For brands planning a campaign

Useful framing for brands deciding whether creator spend belongs in an AI visibility program. Moore’s pitch is consistency and repetition across independent surfaces: plan multiple creators and placements around one narrow topic rather than one-off posts.

Examples: Source 1

Her conclusion: brands no longer compete for one keyword but for the whole cluster of questions around a purchase, and models reward depth on a narrow slice of a market.

• She uses a CRM example for B2B SaaS founder coaches, listing the setup, integration, learning-curve, and pricing questions a buyer asks.
• She challenges readers to consider whether they own a topic or merely show up for it.
• She links the argument to niche advice she gave freelancers years earlier with Paul Jarvis on Creative Class, and mentions her Fan Out podcast with Krista Doyle.

Teaching through a worked buyer example and a direct weekly challenge, not abstract SEO theory.

For brands planning a campaign

Brands considering her for content work can expect topic-depth recommendations and question-cluster briefs, not single-keyword articles. She’s a fit when a brand has a narrow category position it can defend.

Examples: Source 1

She outlines four steps for getting named by AI tools: narrow a topic until it is slightly uncomfortable, rewrite a LinkedIn headline to make a claim rather than state a job title, publish content designed to be lifted (lists, headings, named tools, hard numbers), and use one exact version of your name everywhere while claiming existing bylines.

• In a separate post, she describes the unglamorous process she used herself: a tool built with Ahrefs Agent A that pulls every site carrying her bio, ranks them by Domain Rating, finds the right contact, and drafts an outreach email, which she sends three to five times a week.
• She reports four bio updates on DR 90+ sites and says the changes shift how models verify her expertise.

Hands-on self-experiment: she builds the tool, runs the outreach herself, and publishes the intermediate results.

For brands planning a campaign

Relevant to brands running an executive visibility or spokesperson program.

• Moore can advise on bios, bylines, and speaker pages, and has done the clean-up work on her own name.
• Treat the reported results as her account; the posts don’t describe the Ahrefs tool output.

Examples: Source 1 · Source 2

Her argument: a task with significant social and community dimensions has landed on a team without the context to handle it well; nobody clearly owns AI search visibility end to end; and people who can speak to both citation rates and community norms are becoming scarce and valuable hires. She returns to the ownership question in discussions with people working on AEO.

This post analyzes a survey figure and an organizational gap; it isn’t a description of a service she sells, though it supports her consulting positioning.

For brands planning a campaign

Brands can hire her to address internal alignment, not just outsource content. This topic also signals an audience of in-house marketers weighing job moves, which matters when choosing who will see a sponsored placement.

Examples: Source 1

She says she has tested AEO tools from AirOps, Scrunch, Profound, and Ahrefs, and describes three recurring kinds of paid creator work: examining a company’s new report through a journalist’s lens and tying findings to LLMs and AI visibility; demonstrating tools and use cases she actually uses; and explaining on video how to start AEO execution with tools she has tested. Her published brand collaborations include AirOps, Scrunch, Ahrefs, beehiiv, viktor.com, and Cluing.

Tool demos and use cases grounded in products she already uses, plus on-camera walkthroughs.

For brands planning a campaign

The strongest fit is a tool or platform she can use and demonstrate.

• Expect a workflow demonstration and frank commentary on the tedious parts, not a feature list.
• Her report close-reads are a separate format worth buying for a research launch.

Examples: Source 1 · Source 2 · Source 3 · Source 4

The channel now features weekly tutorials and newsletter-visualization videos.

• They report 22 weeks of the newsletter, over 12,500 subscribers across beehiiv and LinkedIn, and shares in GTM Slack channels that led to podcast guest spots, press queries, and 15+ AI citations.
• They also report spending more than $37,000 on video production and related professional services in 2026, and hiring out video editing after deciding it was not their strength.

Newsletter-first publishing, with video built from the same material; she pays for production help rather than editing herself.

For brands planning a campaign

Her newsletter and video offer repeated sponsorship exposure; LinkedIn posts are the entry point. Brands should ask for newsletter and video placements, not just a post, and budget for the production quality she already funds herself.

Examples: Source 1 · Source 2 · Source 3 · Source 4

They call prompting the skill that matters most and compare it to onboarding a junior writer with examples, dos and don'ts, brand guidelines, and full briefs. They also note that 2026 was the year they used AI most and hired the most human professionals, including a website designer and video editors.

Prompting taught by analogy to onboarding a writer; examples come from client work rather than generated text.

For brands planning a campaign

A brand briefing them on AI-assisted content should expect a human-interview step and an anti-fabrication stance. This angle suits a sponsored piece for writers and content leads deciding how to adopt AI.

Examples: Source 1 · Source 2

They explain S Corp elections and self-employment tax math, give the March 16 deadline, describe moving their LLC to an S Corp structure, and report saving nearly $2,800 a year by dropping a separate bookkeeping service and getting their first tax refund after years of April balances. They say they spent more than a decade paying more tax than they needed to before making the switch.

These posts carry a Collective partner hashtag and their referral code (KALEIGHMOORE), and the topic sits outside their AI search and creator work. Treat them as disclosed partner content for their freelancer audience, not as evidence of tax expertise.

For brands planning a campaign

Their audience includes freelancers and solopreneurs, making finance, tax, and back-office services a fit for sponsorship. The strongest format is a personal before-and-after story with concrete numbers, not general advice.

Examples: Source 1 · Source 2 · Source 3

They describe 12 years of self-employment, a February 2026 decision to pivot into B2B creator work as content marketing projects dried up, failed full-time interviews, and a rebuilt newsletter, website, and YouTube channel.

• At five months in, they reported $72,422 in revenue, 2,068 new email subscribers, 1.2M Twitter impressions, 720,200 LinkedIn impressions, 8 brand deals, and a paid speaking offer; at six months, they said margins were the thinnest in six years after more than $37,000 in video production spending.
• Their account of past roles covers PR at a Feeding America foodbank, an Etsy jewelry business doing over $100K with no paid ads, social media management for a PBS station and Illinois state tourism, freelance SaaS writing for Shopify, Stripe, SAP, IBM, and AT&T, an SEO content agency whose best year exceeded $550K, and journalism for Forbes, Vogue Business, and Time Inc.

First-person recap posts with specific figures and the unflattering parts left in, rather than a polished success story.

For brands planning a campaign

Brands get concrete public numbers to assess their trajectory and workload, and the pivot story offers a strong campaign narrative. They are newly focused on creator work; ask them to substantiate the self-reported figures.

Examples: Source 1 · Source 2 · Source 3 · Source 4

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They report a rise in the brand’s mention rate across its tracked prompts from 11% to 24% in one quarter; the client is not named.

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Both teach by walking through a concrete example rather than stating a principle — Moore uses a software buyer's fan-out questions, while Vijay uses a CRM keyword that a company optimizes for while the model researches something adjacent. Both also push back on treating keyword rankings as a proxy for AI visibility.

Vijay's posts read as diagnostic sequences a practitioner can run: first check whether the model searches the web for your category at all, then count the hidden fan-out searches, then study which domains get cited.

• Moore's version of the work leans off-site — creators and individual experts as the unit of citation — and includes the organizational question of which team owns it.
• They also write first-person business recaps, which Vijay does not.

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Both use small, specific cases (a founder chasing an unwinnable category term; a brand tracking its mention rate) instead of general theory.

Cohen stays closest to measurement and keyword selection for founders: cited traffic, branded and direct search lift, self-reported attribution, and comparison or niche terms that are actually winnable. Moore more often describes their consulting engagements and the creator-side mechanics of citation building, and writes about their own business economics in a way Cohen's posts do not.

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Both treat research and first-hand program experience as the basis for what they recommend, and both have argued publicly that finding the right voices fails when the reasons for choosing them are vague.

Odden works at program level as an agency leader, publishing survey research with Ascend2 and mapping different kinds of influencers — brandividuals, practitioners, customers — to awareness, consideration, and decision stages.

• His frame is the campaign and the org chart; Moore's is the individual creator and the citation.
• Odden also has a long conference-teaching record, including sixteen consecutive years presenting at Content Marketing World, while Moore's public teaching happens mostly through LinkedIn posts, a newsletter, and video.

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Their two posts answer those questions.

• They walk through running real buyer questions in ChatGPT to see whether the model searches the web for the category, since answers drawn from training data alone will not change no matter how a page is rewritten.
• They explain query fan-outs, citing an average of 7.6 searches behind one prompt, and advise mapping the sources ChatGPT actually returns rather than checking whether the brand appears.
• They also cite an analysis of 22,881 AI citations, in which 34.5 percent went to domains with DA below 40, to argue that specificity and usefulness can beat raw authority.
• For a brand that needs a framework and worked examples before committing budget, this is the more directly usable material, and it is free to apply.

The two posts teach a method but show no named client engagement, measured visibility lift, or sponsored and co-authored work distributed under the author's own name.

• A brand seeking a practitioner to publish off-site content on their own accounts, brief its creator roster, or report a before-and-after mention rate would need to source that work elsewhere.
• Both posts point to a breakdown, so the published detail stops at the framework level.

Examples: Source 1 · Source 2

Their posts give concrete selection logic: stop chasing a head term when a site has roughly 25 backlinks and the top result has more than a million, and target narrower buyer-intent phrases instead.

• Examples include ranking for a vertical-specific CRM term at difficulty 22 within three weeks and a Shopify-specific automation phrase that became 21 percent of demo requests.
• They also explain how to tell whether AI search work is paying off: track citation clicks through utm_source in analytics; treat direct and branded traffic as lagging signals because most people never click a citation; connect self-reported attribution fields on demo and sign-up forms to the CRM; and conduct periodic manual spot checks without treating them as the primary metric.
• If the need is to fix what the brand optimizes for and how it proves movement, this is the closer match.

This is advice about the brand's own site, analytics, and keyword choices.

• Neither post shows third-party creators or named experts being enlisted as the citation surface.
• The posts offer no named client outcomes beyond illustrative examples.
• Ask about audience, availability, and commercial terms.

Examples: Source 1 · Source 2

Their posts describe surveys of thousands of B2B marketers since 2020, a fifth research report in progress, and work with Ascend2 covering nearly 800 B2B marketers.

• Their argument: original research combined with influencer and experiential content creates differentiation now that every content marketer has AI, while influencer partnerships, industry media, AI search, and social proof build brand validation across awareness, engagement, decision, and post-sale.
• They name the common failure directly: one-size-fits-all influencer research maps a famous brandividual to a decision-stage brief, then disappoints.
• Practitioners and subject-matter experts suit consideration; customers telling challenge-and-solution stories suit decision-making.
• That mapping of influencer type, audience, and activation is the offer here, with an audience already used to the topic, including a long-running conference speaking slot.

The described work is agency-scale program design with a roster, research, and events, not one named expert publishing from their own accounts.

• The corroboration effect of a single repeated byline is spread across a team and would need its own plan.
• The posts describe research, frameworks, and sessions, but no AI-citation engagement or results for a specific client.
• A buyer seeking a proven before-and-after mention-rate case should ask for one.

Examples: Source 1 · Source 2