RH Consulting Blog
Share of Model: The New Battleground After AEO
By Rick Hancock · February 14, 2026
SEO
Find & Index
AEO
Understand & Cite
Share of Model
Choose & Recommend
SEO gets you indexed. AEO gets you cited. Share of Model gets you chosen.
AI search is collapsing discovery into a short answer — often a single recommendation. If you're not in that answer, you're not just "lower ranked." You're invisible.
Answer Engine Optimization (AEO) gets you eligible to appear in AI responses. Share of Model measures whether you're actually being chosen.
Share of Model — a concept pioneered by practitioners like Jack Smyth at Jellyfish and popularized by Tom Roach (Marketing Week) — describes how often AI systems select your brand over alternatives.
At RH Consulting, we've built a proprietary Share of Model Snapshot™ methodology to audit, score, and improve AI visibility across ChatGPT, Gemini, Claude, Perplexity, and more. If you want the broader framework (AEO + LinkedIn + Share of Model) in one place, grab the brochure here.
Key Takeaways
- Share of Model = how often and how favorably AI systems recommend your brand vs. competitors across real buyer prompts.
- AI search is winner-take-most: if the model doesn't pick you, you're invisible — not just lower-ranked.
- Three drivers determine selection: content & distribution, retrieval & structure, and trust & authority.
- Measurement = cross-model prompt testing + GA4 AI-referrer tracking + Search Console query monitoring.
- Start now: define your top 10 buyer prompts, test them across ChatGPT/Gemini/Claude/Perplexity, and fix the gaps.
What Share of Model means (in plain English)
Share of Model is how often and how favorably your brand appears in AI-generated answers compared to competitors — across the prompts your buyers actually use.
It answers:
- • Do AI models mention us at all?
- • Are we in the top slot or buried as an afterthought?
- • Is the context positive, neutral, or wrong?
- • Are competitors consistently getting picked instead?
Winner-take-most behavior is already here. AI rarely returns ten blue links. It returns a verdict.
SEO isn't dead — but the KPI changed
Traditional SEO optimizes for:
- Rankings
- Clicks
- Traffic
AI search optimizes outcomes:
- A direct answer
- A shortlist
- A recommendation
Gartner projected that brands could see a 25% decline in organic search traffic by 2026 as AI-generated summaries satisfy queries before users ever click through (Gartner, Feb 2024). An Ahrefs study of AI Overviews found they can reduce click-through rates by as much as 60% for featured queries (Ahrefs, Dec 2025).
The game shifts from "how high do I rank?" to:
"When AI is forced to pick 2–3 options… does it pick us?"
The AI Visibility Stack
Think of visibility as a 3-layer stack:
1. SEO
Can engines find and index you?
2. AEO
Can models understand, trust, and cite you?
3. Share of Model
When AI chooses, how often does it choose you?
AEO is necessary. Share of Model is what determines who wins.
Why LinkedIn is now a visibility engine (not just social)
AI systems learn authority from distributed signals: profiles, mentions, content, engagement, and proof assets across trusted domains. LinkedIn is uniquely powerful because:
- • It's a high-authority professional graph
- • Content spreads through real human networks
- • It's continuously refreshed (activity, roles, proof, positioning)
- • It influences how people describe you publicly — which influences how models summarize you
If you want the full integrated playbook, the RH Consulting – LinkedIn, AEO & Share of Model Brochure lays it out end-to-end.
How we measure Share of Model (and improve it)
Share of Model is measurable. We treat it like a growth KPI.
Step 1: Define "AI buyer questions"
- "best [service] for [industry]"
- "top [vendor type] in [region]"
- "alternatives to [competitor]"
- "who can help with [outcome]"
Step 2: Cross-model testing
We test across the major models (not just one) because each engine has different retrieval, weights, and bias.
Step 3: Scoring + rank weighting
- Mention frequency
- Rank position (1st vs 3rd is a massive delta)
- Sentiment and framing
- Consistency across models
Step 4: Fix misclassification and missing signals
- Models misunderstand your category
- Models don't trust your claims
- Models can't find proof, structured facts, or entity clarity
- Competitors dominate distribution channels you're absent from
Step 5: Publish + reinforce
- Structured site content (FAQs, services, proof)
- Entity clarity (who you are, what you do, where you operate)
- Distributed authority (LinkedIn, partner mentions, case studies, citations)
Going deeper: analytics, tools, and real-world results
Track AI referral traffic in GA4
Create a custom channel group in GA4 that captures traffic from AI referrers — including chat.openai.com, perplexity.ai, claude.ai, and copilot.microsoft.com. Label the group "AI Chat Referrals" and monitor volume, engagement, and conversions over time. This gives you a direct signal of how often AI-driven users are arriving — and whether optimization efforts are moving the needle.
Search Console: AI-adjacent query monitoring
In Google Search Console, segment your queries into branded vs. non-branded buckets and watch for AI-adjacent patterns — queries that mirror how someone would prompt ChatGPT or Gemini (e.g., "best AI consulting firm for mid-market SaaS"). Track impressions and clicks over time. Rising impressions with flat clicks often signals that AI Overviews are answering the query before the user reaches your listing.
Simplified visibility score formula
A starting-point formula for internal benchmarking:
Visibility Score = Mention Frequency × Sentiment Weight + Position Bonus
Our Share of Model Snapshot™ uses a more advanced, proprietary version that normalises across models, weights by buyer-intent relevance, and adjusts for citation context.
Recommended tools
- Otterly.ai — monitors AI citations and brand mentions across ChatGPT and Perplexity.
- Peec AI — tracks inclusion and ranking in AI-generated answers over time.
- Brandlight — identifies how AI models frame and describe your brand relative to competitors.
Mini case examples
B2B SaaS firm (mid-market) — went from zero AI mentions to top-3 recommendation across 8 of 10 buyer prompts within 90 days. Key fix: structured FAQ content + entity clarity on their services page.
Multi-location services company — AI models consistently recommended a smaller competitor. After improving distributed authority (LinkedIn thought leadership + partner citations), they overtook the competitor in 6 of 10 prompts within 60 days.
Professional services firm — models misclassified them as a different category entirely. After targeted schema markup and content restructuring, correct categorization achieved across all four major models in under 45 days.
The deliverable: Share of Model Snapshot™ (Mini-Audit)
If you want to stop guessing and see where you stand today, start here.
Share of Model Snapshot™ includes:
- Top 10 buyer prompts tested across major AI models
- A visibility score + simple "leaderboard" view
- Brand sentiment + positioning notes
- 3–5 highest-leverage fixes to increase selection frequency
Ideal for: B2B services, SaaS, multi-location businesses, and professional firms.
Bottom line
AEO is the entry ticket.
Share of Model is the scoreboard.
If your competitors are being recommended and you aren't, you don't have a traffic problem — you have an AI selection problem.
Sources
- 1.Gartner, "Gartner Predicts Search Engine Volume Will Drop 25% by 2026," February 2024 — gartner.com
- 2.Ahrefs, "AI Overviews: How They Impact Organic CTR," December 2025 — ahrefs.com
- 3.BrightEdge, "BrightEdge Research on AEO and AI Search" — brightedge.com
Get your Share of Model Snapshot™
We test your top 10 buyer prompts across ChatGPT, Gemini, Claude, and Perplexity — then deliver your visibility score, competitive leaderboard, and your 3–5 highest-leverage fixes.
Book a Share of Model Snapshot™Or download the brochure for the full AEO + LinkedIn + Share of Model playbook.