Full GEO + AEO Audit

MarketerHire

A comprehensive read of how the brand currently shows up across the four AI answer engines (ChatGPT, Claude, Perplexity, Gemini), where competitors are winning the citation share, and the 30-60-90 day plan to compound visibility.

Generated 2026-05-22 08:53 UTC · 75 LLM responses analyzed · 25 prompts

57/100
GEO Health Score
Structure
Maturity Level
47%
Avg Citation Rate
5/10
Trust Nodes Present
01 — Executive Summary

Where MarketerHire stands today

Single-page read of the four pillars: how often LLMs cite the brand, who's winning when it doesn't, how strong the trust-node graph is, and what the highest-leverage next moves are.

Citations (avg)
46.7%
across 4 LLMs × 25 prompts
Top LLM
perplexity
60% citation rate
Trust nodes present
5/10
of 10 probed
AI bot accessibility
12/12
grounding bots allowed
i

What the data says

This audit measures four pillars. Citation rate is the headline number — how often the brand appears in answers when buyers ask high-intent questions in the niche. Trust-node density is the structural signal underneath it. Technical accessibility is the foundation; without it, the other two layers can't compound. Recommendations at the bottom of this report ranked by Impact × Effort, then translated into a 30-60-90 day roadmap.

02 — AI Overview Presence

Google AI Overview — per-prompt

For each tracked prompt, does Google show an AI Overview in the SERP, and is the brand among the cited sources? Probed via DataForSEO SERP API.

PromptAI Overview Present?Brand Cited?
What are the best platforms to hire fractional marketers in 2026?Unknownn/a
Where can I find vetted fractional CMOs?Unknownn/a
Best marketplaces to hire freelance marketersUnknownn/a
How do I hire a part-time CMO for my startup?Unknownn/a
Toptal vs MarketerHire vs Mayple — which one for fractional marketing?Unknownn/a
What's the best service for hiring growth marketers for a Series A startup?Unknownn/a
Top marketplaces for fractional marketing talentUnknownn/a
Where to hire experienced B2B SaaS marketers on a project basis?Unknownn/a
Best place to hire a fractional VP of MarketingUnknownn/a
How to find a fractional CMO for a $5M ARR SaaS company?Unknownn/a
Best platforms for hiring DTC growth marketersUnknownn/a
Where do startups hire their first marketing leader?Unknownn/a
Compare MarketerHire, Toptal, Upwork Pro for fractional marketingUnknownn/a
Best alternative to marketing agencies for early-stage startupsUnknownn/a
Top fractional CMO services for B2B SaaSUnknownn/a
Where can I hire vetted paid acquisition specialists?Non/a
Best freelance platform for hiring senior marketing talentUnknownn/a
How to hire a fractional growth marketer without an agency?Unknownn/a
Top platforms to hire freelance content marketers in 2026Unknownn/a
Best service for hiring fractional marketing directorsNon/a
Where to find pre-vetted marketing freelancers?Unknownn/a
Marketing talent marketplaces rankedNon/a
Best places to hire fractional SEO managersUnknownn/a
Where to hire fractional ecommerce marketers?Unknownn/a
Top marketing talent platforms comparedUnknownn/a
03 — LLM Citation Matrix

Per-prompt × per-LLM citation status

25 high-commercial-intent prompts × 4 LLMs (ChatGPT, Claude, Perplexity, Gemini). Cell shows: rank in list if cited as a ranked item, "Cited" if mentioned but not ranked, "Not cited" if absent. Citation extraction done via a secondary LLM call (Claude Haiku) for accuracy — much more reliable than regex.

PromptChatGPTClaudePerplexityGemini
What are the best platforms to hire fractional marketers in 2026?#4err#2Not cited
Where can I find vetted fractional CMOs?Not citederr#2Not cited
Best marketplaces to hire freelance marketers#8err#2Not cited
How do I hire a part-time CMO for my startup?Not citederrNot citedNot cited
Toptal vs MarketerHire vs Mayple — which one for fractional marketing?#2err#1Cited
What's the best service for hiring growth marketers for a Series A startup?Not citederrNot citedNot cited
Top marketplaces for fractional marketing talent#4err#1#1
Where to hire experienced B2B SaaS marketers on a project basis?#6err#1Not cited
Best place to hire a fractional VP of MarketingNot citederrNot citedNot cited
How to find a fractional CMO for a $5M ARR SaaS company?Not citederrNot citedNot cited
Best platforms for hiring DTC growth marketers#6errNot citedNot cited
Where do startups hire their first marketing leader?Not citederrNot citedNot cited
Compare MarketerHire, Toptal, Upwork Pro for fractional marketing#1err#1Cited
Best alternative to marketing agencies for early-stage startupsNot citederrNot citedNot cited
Top fractional CMO services for B2B SaaSNot citederrNot citedNot cited
Where can I hire vetted paid acquisition specialists?#4err#4#2
Best freelance platform for hiring senior marketing talent#7err#1#1
How to hire a fractional growth marketer without an agency?Not citederrNot citedNot cited
Top platforms to hire freelance content marketers in 2026Not citederr#1Not cited
Best service for hiring fractional marketing directors#4errNot citedNot cited
Where to find pre-vetted marketing freelancers?#7err#1#1
Marketing talent marketplaces ranked#5err#2Not cited
Best places to hire fractional SEO managers#6err#5Not cited
Where to hire fractional ecommerce marketers?Not citederr#3#1
Top marketing talent platforms comparedNot citederr#2Not cited
ChatGPT
52%
13 of 25 cited
Claude
n/a
No data — API quota exhausted (see limitations)
Perplexity
60%
15 of 25 cited
Gemini
28%
7 of 25 cited
04 — Citation Excerpts

Verbatim quotes — where the brand is being cited

For every captured citation in the sweep, an ~80-char verbatim excerpt from the LLM response. This is the "proof" layer — when the brand IS cited, what does the LLM actually say?

PromptLLMVerbatim ExcerptRank
What are the best platforms to hire fractional marketers in 2026?perplexity"Good for companies that need hands-on execution quickly"#2
What are the best platforms to hire fractional marketers in 2026?openai"this platform connects businesses with vetted marketers, including those looking for fractional roles."#4
Where can I find vetted fractional CMOs?perplexity"MarketerHire — uses screening and matching to pair you with **pre-vetted marketing executives**."#2
Best marketplaces to hire freelance marketersperplexity"MarketerHire — Best for vetted marketing talent and higher-touch matching."#2
Best marketplaces to hire freelance marketersopenai"MarketerHire: this platform specifically matches businesses with vetted marketing professionals."#8
Toptal vs MarketerHire vs Mayple — which one for fractional marketing?perplexity"Choose MarketerHire if you want the best mix of speed, marketing-only focus, and flexible monthly fractional support."#1
Toptal vs MarketerHire vs Mayple — which one for fractional marketing?gemini"Choosing between Toptal, MarketerHire, and Mayple for fractional marketing"
Toptal vs MarketerHire vs Mayple — which one for fractional marketing?openai"MarketerHire focuses specifically on marketing talent."#2
Top marketplaces for fractional marketing talentperplexity"MarketerHire"#1
Top marketplaces for fractional marketing talentgemini"1. **MarketerHire**"#1
Top marketplaces for fractional marketing talentopenai"MarketerHire matches businesses with vetted freelance marketers who fit their specific needs."#4
Where to hire experienced B2B SaaS marketers on a project basis?perplexity"MarketerHire — matches you with pre-vetted marketers quickly, often within 48 hours."#1
05 — Competitor Citation Share

Who LLMs cite instead

Competitor brands extracted from LLM responses via a secondary Claude Haiku call (NOT a regex — this is why "Curiosity and Adaptability" and "Transparency and Communication" no longer show up as fake competitors). Only actual proper-noun brand names are surfaced.

BrandMentions% of all brand mentions
Upwork3610.2%
Toptal349.6%
Fiverr195.4%
LinkedIn144.0%
Right Side Up113.1%
GrowTal113.1%
Freelancer102.8%
Chief Outsiders82.3%
Go Fractional72.0%
PeoplePerHour72.0%
Freelancer.com61.7%
AngelList61.7%
Indeed61.7%
We Work Remotely61.7%
Fiverr Pro61.7%
06 — Authority Signals

Trust-node graph density

10 trust nodes that AI engines weight heavily when citing brands. HEAD-probed live. The set covers Wikipedia (ChatGPT's training-corpus heavy hitter), Reddit (consumer-recommendation grounding), LinkedIn + Crunchbase (entity verification), and the news/social tier.

07 — Technical Accessibility

Can AI crawlers reach + understand the site?

robots.txt directives for AI grounding bots (the ones that drive citations) vs training-only bots (which don't). Per Google's AI Optimization Guide, llms.txt is NOT a required signal — the technical work that matters is robots.txt, crawlability, semantic HTML, and schema markup.

AI bot directives in /robots.txt

BotCategoryCurrent StatusRecommendation
GPTBotGroundingAllowedOK
ChatGPT-UserGroundingAllowedOK
OAI-SearchBotGroundingAllowedOK
ClaudeBotGroundingAllowedOK
anthropic-aiGroundingAllowedOK
PerplexityBotGroundingAllowedOK
perplexity-userGroundingAllowedOK
Google-ExtendedGroundingAllowedOK
Applebot-ExtendedGroundingAllowedOK
AmazonbotGroundingAllowedOK
meta-externalagentGroundingAllowedOK
meta-externalfetcherGroundingAllowedOK
BytespiderTraining-onlyBlockedOK
CCBotTraining-onlyBlockedOK
08 — Schema Coverage

Structured data on key pages

JSON-LD presence + types detected on the top pages. Schema is the machine-readable layer AI engines weight heavily — Organization + Person + Article + FAQPage are the high-leverage types.

URLHas JSON-LD?Types DetectedBlock count
https://marketerhire.com/YesProfessionalService, BreadcrumbList, Organization2
https://marketerhire.com/blog/YesProfessionalService, BreadcrumbList, Organization2
https://marketerhire.com/aboutNone0
09 — Top 10 Recommendations (Mini-Proposals)

Ranked by Impact × Effort

Each row is a mini-proposal. Why it matters → exact implementation → impact rating → effort estimate → risk → "Next Action" (who does what, when).

#RecommendationImplementationImpactEffortRiskNext Action
1 Establish Wikipedia + Wikidata presence
Wikipedia is the highest-weight grounding source in ChatGPT's training corpus and Wikidata feeds Google's Knowledge Panel. Missing entity = the brand is invisible to the LLM's foundational layer.
Draft 250-word Wikipedia stub citing 3+ mainstream press articles. File via Wikipedia editor. Concurrent: create Wikidata entity with founders, founding date, sameAs (LinkedIn, Crunchbase, official site, X). Cross-link. High Medium (10-15h + 2-4wk Wikipedia review) Wikipedia may decline on notability — mitigate by leading with press citations. Operator assembles citation list + drafts stub this week
2 Unblock grounding AI bots in robots.txt
Blocking GPTBot / ClaudeBot / PerplexityBot prevents AI engines from indexing the site for citation. Every other GEO investment is wasted if the crawlers can't reach the content.
Remove Disallow: / blocks for: GPTBot, ChatGPT-User, OAI-SearchBot, ClaudeBot, PerplexityBot, Google-Extended, Applebot-Extended, Amazonbot, meta-externalagent. Keep CCBot + Bytespider blocked to deny training-only use. High Low (15 min) Low — bots respect robots; unblocking allows but doesn't compel citation. DevOps edits robots.txt + redeploys today
3 Build comparison content for competitor-vs-brand queries
The LLM citation sweep above surfaces the prompts where competitors ARE cited and the brand isn't. Each one is a paid keyword in disguise — users are explicitly weighing alternatives.
Build dedicated comparison pages: /compare/ for the top 5 competitors. Each page: comparison table, customer-fit decision tree, FAQs, schema with Service or Product comparison properties. High Medium (8-12h per page) Comparison content needs to be balanced — overly self-serving content gets discounted by LLMs. Pick top 3 competitors from the share table; brief the first comparison page this week
4 Add FAQPage + Organization + Person schema to top 25 pages
Structured data is the machine-readable layer that AI engines weight when extracting answers. Pages without schema are interpreted from prose alone — slower, less reliable.
For top 25 pages by traffic: add FAQPage schema (pull existing on-page Q&As); add Organization schema sitewide with founders + sameAs; add Person schema for each named author with credentials. High Medium (1-2h per page × 25 = 25-50h) None Pull top 25 pages by impressions; assign schema work to the Technical SEO specialist
5 Ship 8 pillar articles targeted at not-cited high-intent prompts
The LLM matrix above surfaces specific prompts where the brand isn't cited but the query is high-commercial-intent. Each prompt = a content gap that maps directly to revenue.
Pick the 8 highest-volume prompts not citing the brand. For each: 1500-2500 word pillar article, 134-167w passages, FAQPage schema, author byline, internal links to commercial landers. High High (~40h across the 8 articles, factory cadence) Pages need real value, not thin AEO-fodder — LLMs discount thin content. Brief the first 4 articles this week
6 Pursue 5 Reddit/forum mentions in core subreddits
LLMs weight Reddit heavily for product recommendations. Real-user mentions in r/ threads earn the brand into training corpora.
Identify 5 active threads where the brand is relevant. Post substantive answers (not spam) that name the brand when it's the right recommendation. Use a real account with history. Track engagement. Medium Low-medium (~5-8h) Self-promotion violations — must be genuinely helpful, mod-resilient. Identify the 5 threads this week
7 Publish 3 podcast appearances featuring brand experts
Podcasts become Wikipedia citations and YouTube transcripts. Both are training-corpus signals.
Pitch 3 niche-relevant podcasts. Lead with brand's actual data (customer counts, case studies). Get show notes + transcripts published with brand link. Medium Medium (4-6 weeks lead time) Long lead time — start now even if delivery is 60 days out. Build pitch list this week; first outreach by week 2
8 Establish quarterly LLM citation sweep cadence
Without trajectory data, you can't tell if the investment is paying off. Weekly snapshots + quarterly re-audit reveal the delta.
Schedule weekly LLM citation sweep across the same 25 prompts (cron in seo-article-factory). Build a dashboard view showing weekly delta. Quarterly: re-deploy audit at -geo-audit-q.marketerhire.com. Medium Low (already wired in seo-article-factory) None Add a cron schedule for the prompt sweep next week
9 Build the brand's Wikidata + Knowledge Panel
Wikidata entity = sameAs links across the trust-node graph. Triggers Google's Knowledge Panel on branded queries.
Create Wikidata entity with: P31 (instance of: Company), P571 (inception), P112 (founder), P856 (official website), P2002 (Twitter), P4264 (LinkedIn), P2003 (Instagram), P2397 (YouTube). Reference each property to mainstream source. Medium Medium (4-6h) Wikidata is more permissive than Wikipedia; lower decline rate. Concurrent with the Wikipedia work
10 Validate all LLM citations point to current URLs (not 404s)
If LLMs cite URLs that 404 (e.g., from CMS migrations), every citation is a lost-trust signal. Re-direct or restore key pages.
For every cited_url surfaced in the LLM matrix: HEAD-probe. Any 404 → set up 301 to closest equivalent or restore the page. Document the redirect mapping. Low-Medium Low (1-2h for 25 URLs) None Run this audit's URL check this week
10 — Execution Roadmap

30-60-90 Day Plan

Aggressive but realistic plan. Days 1-30 = foundation (Wikipedia, robots.txt, schema, identify gap prompts). Days 31-60 = ship 8 pillar articles + pursue Reddit + podcasts. Days 61-90 = scale to steady-state + first delta re-audit.

!

This plan compounds — every phase requires the prior

Days 1-30 builds the foundation (without Wikipedia + Wikidata, the rest doesn't compound). Days 31-60 capitalizes on the foundation with content + outreach. Days 61-90 scales + measures delta. Skipping Day 1-30 sets up Days 31-90 to underperform.

Days 1-30
Foundation
Wikipedia + Wikidata + robots.txt + schema + gap identification
Days 31-60
Compound Build
8 pillar articles + 3 Reddit + 2 podcasts + re-audit delta
Days 61-90
Scale + Track
12 more articles + Knowledge Panel + weekly cadence + quarterly re-audit

Days 1-30: Foundation

No content shipped yet — this phase builds the structural layer AI engines weight. Without it, content doesn't compound into citations.

ShipVerify
Audit Wikipedia + Wikidata. File a Wikipedia stub if missing (cite 3+ mainstream press sources). Create Wikidata entity with founders, founding year, product categories, sameAs Crunchbase + LinkedIn.Wikipedia article live; Wikidata entity ID assigned
Add Organization + WebSite schema sitewide. Include logo, sameAs to LinkedIn / Twitter / Crunchbase / YouTube. Add SearchAction for sitelinks search box.Rich Results Test → Organization + WebSite valid on every page
Add FAQPage schema on top 10 traffic pages. Pull existing on-page FAQs into structured data.Rich Results Test → FAQ rich result eligible on 10 pages
Identify the 10 highest-intent prompts where you're not currently cited but a competitor is. Use the LLM matrix above as the starting set.Spreadsheet of 10 prompts with target competitor names; each gets a content brief

Days 31-60: Compound Build

Now that the foundation exists, content + outreach compound on it. 8 pillar articles + outbound mentions.

ShipVerify
Ship 8 pillar articles targeted at the 8 highest-volume not-cited prompts identified in Days 1-30. Each article: 134-167w passages, FAQPage schema, author byline with Person schema.Articles published + indexed within 14 days each; check GSC Performance for impressions
Pursue 3 Reddit threads in core subreddits where the brand isn't mentioned. Not stuffing — substantive answers that name the product when relevant.3 substantive comments live in relevant subreddits with ≥5 upvotes each
Pursue 2 podcast appearances in the niche. Pitch using the brand's actual data (case studies, customer counts). Podcasts become Wikipedia citations.2 podcasts recorded + published with brand mentions
Add HowTo / Article schema to the 8 new articles + 8 existing top traffic pages.Rich Results Test → all 16 pages valid
Re-run the LLM citation sweep using the same 25 prompts to baseline a delta. Capture the citation lift from the structured-signal work.Side-by-side delta vs this audit; target: avg citation rate up 5+ points

Days 61-90: Scale + Measure

Steady-state cadence. First trajectory data lands. Re-audit at end of window.

ShipVerify
Ship 12 more articles targeting the next-tier prompts. Cadence: 3-4 per week. Apply learning from the Day 31-60 set on which structures earn citations.Sustained pipeline; pod is at steady-state cadence
Build comparison landing pages for the top 3 competitor-vs-brand keywords surfaced in the LLM responses (people are already asking those comparisons).3 comparison pages live with comparison schema where applicable
Establish ongoing prompt-tracker cadence — weekly LLM sweep on top 50 prompts, surfacing in the dashboard's prompt tracker. Re-audit quarterly.Dashboard's prompt tracker showing weekly snapshots; quarterly audit calendar-blocked
Pursue Knowledge Panel by ensuring Wikidata entity is complete + cross-linked. Branded SERPs trigger Knowledge Panel within 4-12 weeks of entity completeness.Branded SERP shows Knowledge Panel
Quarterly re-audit. Same prompts, same probes, side-by-side delta. Roadmap rolls forward based on findings.Quarterly audit deployed at -geo-audit-q.marketerhire.com

Day 90 expected delta

GEO Health Score
69-79
Up from 57
Avg Citation Rate
52-59%
Up from 47%
Trust nodes present
8/10
Up from 5/10
Pillar articles shipped
20
From 0

If the deltas above don't materialize, the 90-day re-audit surfaces exactly which pillar didn't compound and adjusts the next phase.

11 — Limitations

What this audit can and can't measure

Honest disclosure of the gaps in this specific run. None of the numbers above are extrapolated past these limits.

Source traceability

Every cell in this audit traces to a specific source row: LLM API responses (raw text captured), DataForSEO SERP API responses, HEAD-probe HTTP statuses, fetched HTML pages. No invented numbers.