How AI Systems See DuoBoots: A Deep Dive Into AI Visibility Intelligence

Why AI Visibility Matters for Your Brand in 2026

When a customer asks ChatGPT "Where can I find boots that actually fit my wide calves?", does your brand appear in the response? In 2026, AI assistants have become the first stop for product discovery — not Google, not Instagram, not word of mouth. Consumers are asking ChatGPT and Gemini for direct brand recommendations, and those platforms respond with a shortlist of 3 to 5 brands. If you're not in that list, you're invisible to that buyer.

What is the problem with traditional SEO here?

Traditional SEO gets your website into a list of links. But AI platforms don't show links — they synthesize information and make confident, direct recommendations. A #1 Google ranking does not guarantee an AI mention. The two systems operate on entirely different logics: Google rewards authority and backlinks; AI rewards semantic relevance, citation quality, and structured content that directly answers the user's question.

Why does this matter for a specialist brand like DuoBoots?

DuoBoots operates in a niche where customers have a very specific, measurable problem: standard boots don't fit their calf size. These customers are going to AI assistants with high-intent, highly specific questions — exactly the kind of questions AI platforms are designed to answer. If DuoBoots is not consistently appearing in those AI responses, a competitor captures a customer who would have been a near-perfect fit.

How do you fix AI visibility?

AI Visibility Intelligence solves this in three steps:

1. Measure — Run structured queries across ChatGPT and Gemini to establish a baseline. Where do you appear? At what rank? Who beats you and why?
2. Diagnose — Identify the specific queries you're missing, the personas you're not reaching, and the technical gaps blocking AI crawlers from fully understanding your site.
3. Optimize — Apply Generative Engine Optimization (GEO): fix technical infrastructure, create targeted content for missing query types, and build the citation diversity that AI platforms trust.

This blog walks through DuoBoots' AI Visibility Intelligence Report — all 8 slides — explaining what each section reveals, what the data means in practice, and the most important action from each slide.

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Slide 1: What ChatGPT & Gemini Say About You Today

Why Are We Talking About This Slide?

This is the scoreboard. Before you can improve AI visibility, you need to know your starting position with precision. The AIScore™ is a composite metric designed to answer one question: how well does AI serve your brand to potential customers? It's built from three components — each measuring a different dimension of your AI presence. Understanding how your score is weighted reveals exactly where leverage exists.

What Does the Data Show?

DuoBoots has an AIScore™ of 86 (Grade A) — the highest grade available, achieved by only a fraction of brands that run this analysis. Here is how it breaks down:

AIScore™: 86 — Grade A

Component	Score	Weight	What It Measures
Visibility	70	35%	% of AI queries where DuoBoots is mentioned
Ranking	88	30%	Average position when mentioned
AI Share of Voice™	100	35%	Share of AI conversations vs competitors

Raw performance across 40 analyzed responses:

• 70% visibility rate — DuoBoots appears in 28 out of 40 relevant queries
• 51 total citations — the number of times source URLs are referenced to support DuoBoots mentions
• #1.6 average ranking — when DuoBoots appears, it is the first or second brand recommended
• 9% AI share of market — of all AI conversations in the calf-fit footwear category, DuoBoots holds the largest share

What does the 100/100 AI Share of Voice™ Score mean?

A perfect AI Share of Voice™ Score does not mean DuoBoots appears in every query. It means that within the calf-fit women's boots category, no competitor comes close enough to challenge DuoBoots' position. The nearest competitor, Dolce Vita, scores 58 — a 28-point gap. When AI platforms respond to calf-measurement queries, DuoBoots is the default recommendation. That default status is the most valuable asset this report confirms.

Key Takeaway

Grade A is real, but it is not a resting position. The visibility component scores 70 out of 100 — meaning 30% of relevant queries still don't surface DuoBoots. The 90-day target is pushing that to 85%, which would raise the overall AIScore™ from 86 to 91. The ranking and AI Share of Voice™ scores are already near-ceiling. All of the near-term improvement potential lives in visibility — and visibility is a content problem, not a technical one.

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Slide 2: Platform Breakdown — Where Is DuoBoots Invisible?

Why Are We Talking About This Slide?

A 70% overall visibility rate can hide important asymmetries. ChatGPT and Gemini are different platforms with different training data, different crawl patterns, and different ways of forming recommendations. A brand can perform strongly on one and weakly on the other. Knowing exactly which platform is underperforming — and for which specific queries — transforms a vague "improve visibility" goal into a concrete content brief.

What Does the Data Show?

Visibility by Platform:

Platform	Visibility	Avg Rank	Citations
Gemini (Google)	80%	#1.7	18
ChatGPT (OpenAI)	60%	#1.5	33

Two things stand out in this data. First, there is a 20-percentage-point gap between Gemini (80%) and ChatGPT (60%). Second, ChatGPT produces 33 citations versus Gemini's 18 — nearly double — yet still has lower overall visibility. ChatGPT goes deeper when it does cite DuoBoots, but it reaches for DuoBoots in a narrower set of query types.

All 5 visibility gaps are in ChatGPT. Gemini has already indexed DuoBoots' brand story more completely. ChatGPT requires more explicitly-structured content to make the same connections.

The 5 Queries Where DuoBoots Is Absent:

Key Takeaway

Every gap is a content brief. These 5 missing queries are not random — they share a common pattern: ChatGPT cannot connect DuoBoots to buyer contexts beyond the core calf-measurement use case. Each gap maps directly to a landing page or comparison article that doesn't yet exist. Create those 5 pieces of content and DuoBoots' ChatGPT visibility climbs from 60% to approximately 85%, closing the gap with Gemini entirely.

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Slide 3: Competitor vs You Analysis

Why Are We Talking About This Slide?

AIScore™ only means something in context. A score of 86 in a highly competitive category is different from an 86 in a niche category. This slide answers the question that matters: relative to the brands competing for the same AI conversations, where does DuoBoots stand — and how durable is that position?

What Does the Data Show?

Full Competitive Landscape (10 brands):

Rank	Brand	AIScore™	Grade	Visibility	Citations	Avg Rank
1	DuoBoots	86	A	70%	51	#1.6
2	Dolce Vita	58	C	32%	37	#3.6
3	Naturalizer	57	C	35%	29	#3.6
4	Everlane	49	D	5%	6	#1.0
5	Torrid	48	D	15%	13	#2.8
6	R.M. Williams	46	D	5%	4	#1.0
7	Meindl	45	D	2%	4	#1.0
8	OldMulla	45	D	2%	4	#1.0
9	Thursday Boot Co	45	D	2%	4	#1.0
10	Stuart Weitzman	41	D	22%	9	#3.9

Gap Analysis — DuoBoots vs Competitor Average:

Metric	DuoBoots	Competitor Avg	Gap
AIScore™	86	48.2	+37.7
Visibility Rate	70%	13.6%	+56.4%
Citations	51	12	+39

Three competitive patterns worth noting:

The #1 ranking trap. Four competitors — Everlane, R.M. Williams, Meindl, Thursday Boot Co — each rank #1.0 on average. But they appear in only 2–5% of queries. A perfect rank in a tiny fraction of queries does not build AIScore™. DuoBoots' combination of 70% visibility and #1.6 ranking is structurally superior to any competitor's narrow-niche first-place result.

The OldMulla risk. OldMulla sits at AIScore™ 45 with 2% visibility. Its AI positioning — "handmade in Portugal, small-batch artisanal production, premium full-grain leather" — directly overlaps with Gap 1, the query type where DuoBoots is currently absent. OldMulla is not a threat today. But it is one content campaign away from competing directly for DuoBoots' Portugal craftsmanship positioning in ChatGPT.

The Naturalizer returns narrative. Naturalizer ranks third overall with an AIScore™ of 57, partly on the back of "Easy US Returns" positioning. This specific attribute is winning Gap 2 for Naturalizer right now. DuoBoots has a good exchange process — it is simply not framed in AI-indexed language that competes.

Key Takeaway

DuoBoots holds a 28-point lead over its nearest competitor. That is real category dominance. But the lead is built on niche specificity, not broad content investment. The brands most likely to erode it are not Dolce Vita or Naturalizer — they are smaller, more agile brands like OldMulla that share a positioning pillar and have so far not invested in GEO. The 90-day window to lock in the Portugal craftsmanship narrative before OldMulla does is now.

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Slide 4: GEO Optimization Actions

Why Are We Talking About This Slide?

Data without action is reporting. This slide converts the entire analysis — every gap, every competitive risk, every citation pattern — into a prioritised, time-bound action plan with projected impact. At Grade A, there is a temptation to treat GEO as "done." This section explains precisely why that is the wrong conclusion, and what a targeted 90-day push looks like for a brand already at the top of its category.

What Does the Data Show?

90-Day Improvement Targets:

Metric	Now	Target	Movement
AIScore™	86	91	+5 points
Visibility	70%	85%	+15 percentage points
Citations	51	51	Defend lead
Avg Rank	#1.6	#1.0	Improve 0.6 positions

P1 — Content Strategy: Win 5 Queries Where DuoBoots Is Absent

Impact: +10–20% visibility for gap segments

This is the single highest-leverage action in the plan. Five specific ChatGPT queries return zero mentions of DuoBoots despite the product being a near-perfect match for the buyer's need. The top gap — Portugal craftsmanship queries — is where competitors like Vandrélaar and Urban Shepherd Boots are winning by default, not by merit.

Tactics:

• Create a landing page targeting the "handmade in Portugal / EU ateliers" query type — atelier photos, leather sourcing story, artisan profiles, production certification
• Publish comparison page: "DuoBoots vs Vandrélaar"
• Publish comparison page: "DuoBoots vs Urban Shepherd Boots"
• Create supporting content for the wide-calf alternative query (Gap 2): position the DuoBelt measurement system as the scientific alternative to guessing calf width
• For Gaps 3–5, create three persona-specific landing pages: heeled style for events, cost-per-wear value framing, and plus-size calf fit with customer success stories

Effort: Medium | Timeline: 2–3 weeks

P2 — Citation Defense: Protect the Citation Lead

Impact: Maintain 9%+ citation share

DuoBoots leads all competitors with 51 citations against Dolce Vita's 37 — a margin of 14. This is a real advantage, but it is not insurmountable. One Good Housekeeping or Wirecutter review mentioning Dolce Vita could close that gap without any direct action. Citation defense is not passive — it requires fresh content signals on the sources already driving citations.

Tactics:

• Keep content current on Trustpilot and Reddit, where DuoBoots is already indexed and cited
• Regularly update product pages, FAQ content, and comparison guides to maintain AI freshness signals
• Monitor which new brands are appearing in the 20 Golden Prompt responses each month

Effort: Low | Timeline: Ongoing

P2 — Brand Positioning: Surface the Differentiators AI Is Underusing

Impact: Richer, more specific AI descriptions in responses

AI currently picks up 15 attributes for DuoBoots. The two strongest differentiators — the 72-size calf-fit system and the Portugal craftsmanship — are present in AI responses but inconsistently, imprecisely, and not always in the same response. They need to be structured as machine-readable facts, not buried in marketing copy.

Tactics:

• Create structured FAQ content explicitly stating: "DuoBoots offers the world's only full collection of calf-fit boots in eight calf sizes and nine shoe sizes — 72 total size combinations for calf-fit boots, plus 18 ankle boot sizes"
• Publish a dedicated page for the Portugal handmade story, separate from the general about page
• Add JSON-LD FAQPage schema to product pages covering both differentiators

Example schema:

{
  "@type": "Question",
  "name": "How many calf size options does DuoBoots offer?",
  "acceptedAnswer": {
    "@type": "Answer",
    "text": "DuoBoots offers the world's only full collection of calf-fit boots across 8 calf sizes and 9 shoe sizes — 72 total size combinations, plus 18 ankle boot sizes."
  }
}

Effort: Low | Timeline: 1–2 weeks

P2 — Third-Party & Social Presence: Fix the 6% Social Citation Share

Impact: +5–15% citation diversity

Only 2 of DuoBoots' 35 AI citations come from social media. AI is already citing r/XXS and r/UKMounjaro for calf-fit boot queries — the communities exist, the conversations are happening, and DuoBoots is organically mentioned. The gap is in converting those organic mentions into consistently indexed, citable threads.

Tactics:

• Build authentic engagement in r/XXS and r/UKMounjaro — AI already pulls citation sources from these communities in this category
• Ensure DuoBoots has a thorough, reviewed presence on Trustpilot (currently only 2 citations — significant room to grow)
• Get listed and reviewed on WhoWhatWear (currently only 1 citation from that domain)

Effort: Medium | Timeline: 3–4 weeks

Key Takeaway

At Grade A, every action is surgical. This is not a broad content overhaul — it is five targeted landing pages, two comparison articles, FAQ schema implementation, and consistent community presence. That is 3–4 weeks of focused work for a projected 15-point visibility increase and a 5-point AIScore™ improvement.

The urgency is not about catching up — it is about locking the door. OldMulla shares DuoBoots' Portugal positioning. Thursday Boot Company shares the value-leather positioning. Both are one content campaign away from competing directly in query types DuoBoots currently doesn't even appear in.

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Slide 5: AI Accessibility & Technical SEO Audit

Why Are We Talking About This Slide?

Content and citations drive visibility. But technical infrastructure determines how much of that content AI platforms can actually read, parse, and use. This audit checks the five dimensions of AI crawlability — structured data, sitemaps, bot access, semantic HTML, and metadata — to identify what is helping AI understand DuoBoots and what is getting in the way.

What Does the Data Show?

AI Accessibility Score: 75 out of 100

(Note: partial audit — some pages could not be accessed during analysis)

Audit Results by Dimension:

Dimension	Status	Notes
Schema.org	✅ Found	WebPage, Organization, ListItem detected
Sitemap.xml	✅ Found	48 URLs indexed
AI Bot Access (GPTBot)	✅ Allowed
AI Bot Access (Google-Extended)	✅ Allowed
AI Bot Access (Anthropic/Claude)	✅ Allowed
Sitemap Reference in robots.txt	✅ Present
Header Hierarchy	✅ Present	H1–H6 structure intact
Meta Descriptions	✅ Present	AI can extract page summaries
FAQPage Schema	❌ Not found	Key gap for product pages
Semantic HTML	❌ Limited	Heavy div usage, light semantic tags
llms.txt	❌ Not found	Optional but recommended

What does "limited semantic HTML" mean in practice?

When product pages use generic <div class="description"> containers instead of <article>, <section>, and <aside> tags, AI crawlers have to infer the meaning and hierarchy of content rather than reading it directly. This increases the chance of misattribution or incomplete indexing — particularly for product detail sections where DuoBoots' differentiators live.

Recommended Fixes — Prioritised:

Medium Priority — FAQ Schema

No FAQPage schema exists on product or content pages. This is the single most impactful missing element for DuoBoots specifically. The brand's core differentiator — 72 size combinations — is exactly the kind of precise, verifiable fact that FAQ schema is designed to surface. Without it, AI has to infer the fact from unstructured copy rather than reading it as a confirmed answer.

Add JSON-LD FAQPage schema to product pages, sizing guides, and the care/exchange pages.

Medium Priority — Semantic HTML

Replace <div> containers with <article>, <section>, and <aside> tags throughout product and content page templates. This is a template-level change, not a page-by-page update.

Low Priority — llms.txt

Create a simple /llms.txt file providing an AI-friendly description of the business. Example:

# DuoBoots — Calf-Fit Women's Leather Boots

DuoBoots offers the world's only full collection of calf-fit women's leather boots
across 8 calf sizes and 9 shoe sizes. Handmade in Portugal.

Key Pages:
- Calf Fit Guide: /pages/our-calf-fits
- Size Guide: /pages/size-guide
- Wide Calf Boots: /collections/wide-calf-boots

Differentiators: DuoBelt calf measurement tool, 72 calf-fit size combinations,
artisanal Portugal production

Key Takeaway

A 75/100 technical score is a meaningful advantage. Allbirds, for comparison, scores 30/100 — and its weaker ranking (#2.8 vs DuoBoots' #1.6) directly reflects that infrastructure gap. DuoBoots' sitemap, schema, and bot access are all working correctly. The remaining 25 points are achievable in one to two weeks and would remove the last structural barriers to consistent #1.0 average rankings.

The FAQ schema gap is the most urgent fix. DuoBoots' AI dominance rests on the 72-size calf-fit claim. Right now, AI has to extract that fact from unstructured product copy. FAQ schema converts it into an explicit, machine-readable answer — which AI can reproduce precisely and confidently in every relevant response.

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Slide 6: Company Profile & Customer Perception

Why Are We Talking About This Slide?

AI platforms don't recommend brands based solely on what companies say about themselves. They synthesise customer reviews, editorial coverage, and community discussions to form a composite model of a brand's strengths and weaknesses. This slide shows exactly how AI has built its mental model of DuoBoots — including the negative signals it is using to exclude DuoBoots from certain query types. Understanding this is the bridge between the gap analysis and the content strategy.

What Does the Data Show?

How AI Describes DuoBoots:

DuoBoots specialises in high-quality, handmade leather boots for women with diverse calf measurements. The brand's value proposition is precision fit: where mainstream brands offer S/M/L calf sizing, DuoBoots offers a scientific sizing system across eight incremental measurements from narrow to wide.

Three Key USPs as AI Recognises Them:

1. World's only full calf-fit collection — 8 calf sizes × 9 shoe sizes = 72 total calf-fit combinations, plus 18 ankle boot sizes
2. Handmade in Portugal — premium full-grain leather, artisanal small-batch production
3. Direct-to-consumer model — removes traditional retail markups while maintaining craft-level quality

Customer Perception — What AI Has Synthesised:

Positive signals AI surfaces consistently:

• Excellent fit for specific calf measurements, both wide and narrow
• Good quality and craftsmanship — customers describe the boots as real leather and an investment
• Comfortable even with heels, suitable for extended wear
• Stylish and versatile — customers say they elevate outfits for various occasions
• Easy and straightforward exchange process

Negative signals AI is picking up from reviews:

• Inconsistent sizing — creates hesitation in queries where fit certainty is the decision factor
• Slow customer service and delayed deliveries — appears in review citations and suppresses recommendations in time-sensitive buyer contexts
• High price point — actively suppresses DuoBoots in value_for_money queries (explains Gap 4 directly)
• Return fees — competing against Naturalizer's "Easy US Returns" narrative (explains Gap 2 directly)
• Occasional quality control issues (heel defects) — rare but present in indexed review content

Why do negative signals suppress AI rankings?

AI platforms weight review sentiment when forming recommendations. A brand with consistent complaints about a specific attribute — even if only 10–15% of reviews — will be deprioritised for queries where that attribute is central to the buyer's decision. This is not a bug; it is AI accurately reflecting aggregate customer experience. The only sustainable fix is either improving the underlying experience, or creating content that reframes the negative signal in the buyer's context.

For example: the "high price" signal does not mean DuoBoots should lower prices. It means the content strategy needs to reframe price as "cost-per-wear" and "lifetime investment" — language that AI can use to contextualise the price in value queries instead of flagging it as a deterrent.

Key Takeaway

AI knows DuoBoots better than most internal brand analyses do. The positive signals are driving strong performance in measurement-focused queries. The negative signals are creating the 5 specific visibility gaps identified in Slide 2. The connection is precise:

• "High price + return fees" → suppresses Gap 4 (value_for_money) and Gap 2 (alternative_search)
• "Inconsistent sizing" → creates hesitation in review_based queries → Gap 5
• "Handmade in Portugal" not structured as a distinct content pillar → Gap 1 and prompts 14 and 16

Every content piece in the GEO action plan is, at its core, an AI signal correction — replacing a vague or negative inference with an explicit, positive, structured answer.

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Slide 7: Citation Intelligence

Why Are We Talking About This Slide?

AI doesn't recommend brands from nothing — it follows citations. Understanding which sources AI trusts when it recommends DuoBoots, and how distributed that citation base is, reveals both the strength of the current foundation and its vulnerability. A citation profile that is too concentrated in owned properties or a single third-party platform is fragile. Diversification is the difference between an AI visibility position that holds and one that erodes when algorithms update.

What Does the Data Show?

Citation Source Distribution — 35 total URLs cited:

Source Type	Count	Share
Own Website	20	57%
Third-Party Sources	13	37%
Social Media	2	6%

Top 10 Cited Domains:

Domain	Citations	Type
duoboots.com	19	Owned
www.trustpilot.com	2	Review
www.reddit.com	2	Social
www.whowhatwear.com	1	Fashion editorial
en.wikipedia.org	1	Reference
designerwardrobe.com.au	1	Marketplace
www.businessinsider.com	1	News authority
www.forbes.com	1	Business authority
www.countryliving.com	1	Lifestyle editorial
www.marieclaire.co.uk	1	Fashion (UK)

Per-Prompt Citation Snapshot:

Prompt 1 — "List companies that sell women's knee-high and ankle boots with extensive calf-size ranges"

• ChatGPT cited: duoboots.com/collections/wide-calf-boots, duoboots.com, en.wikipedia.org/wiki/DuoBoots, reddit.com/r/UKMounjaro, marieclaire.co.uk
• Gemini cited: duoboots.com/pages/our-calf-fits

Prompt 3 — "List women's boot brands known for narrow-calf knee-high options with verified customer reviews"

• ChatGPT cited: duoboots.com/en-us/products/haltham-petite, trustpilot.com/review/www.duoboots.com, reddit.com/r/XXS

What does the editorial citation list reveal?

Five premium publications are already citing DuoBoots — Forbes, Business Insider, Marie Claire, WhoWhatWear, Country Living. These are exactly the sources AI platforms weight most heavily as third-party validation. The problem is that each publication has cited DuoBoots exactly once. This "one-and-done" pattern suggests coverage was earned but not sustained. Each is a warm editorial relationship ready to be reactivated, not a cold pitch.

The 6% social media share — the most actionable gap:

With only 2 Reddit citations against Allbirds' 17, DuoBoots is significantly under-indexed in the social proof layer that AI platforms increasingly weight. Critically, AI is already pulling from r/XXS and r/UKMounjaro for calf-fit queries — the citation infrastructure exists. DuoBoots has organic mentions in those threads. The gap is not creating new communities; it is deepening authentic presence in conversations already happening.

Key Takeaway

DuoBoots has elite editorial credibility and fragile social proof. Forbes, Business Insider, and Marie Claire in a citation list of 35 URLs is genuinely strong. But single citations from each means the relationship depth is shallow — one algorithm update that devalues low-frequency sources could remove a meaningful portion of DuoBoots' third-party citation base overnight.

The 90-day citation strategy has two tracks running in parallel: reactivate existing editorial relationships for refreshed 2026 coverage, and deepen Reddit and Trustpilot presence to build the social proof layer that AI increasingly relies on for purchase-intent recommendations.

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Slide 8: Golden Prompts — 15 out of 20 at Rank #1

Why Are We Talking About This Slide?

Golden Prompts are the new keyword rankings — except they capture complete buyer intent rather than isolated search terms. Each prompt encodes a persona, a geography, a specific buying context, and a request for evidence. Tracking DuoBoots' rank across 20 of these prompts over time is the most sensitive early-warning system available for AI visibility changes. When a competitor publishes new content or earns a new citation, the Golden Prompt rankings show it before it shows up in AIScore™.

What Does the Data Show?

20 Golden Prompts — Full Performance Summary:

Prompt	Rank	Theme
Women's knee-high and ankle boots with extensive calf-size ranges	#1	Core calf-fit
Calf-fit boots suitable for boutique retail	#1	B2B/wholesale
Narrow-calf knee-high options with verified reviews	#1	Narrow fit
Premium handmade leather boots direct-to-consumer	#1	DTC positioning
Women's boot brands reviewers call "investment buy"	#5	Value/longevity
Wide calf and narrow calf fittings with sizing guides	#1	Sizing range
Handmade in Portugal or nearby EU regions	#1	Portugal craftsmanship
US-available brands with multiple calf sizes and wide-fit ankle	#1	US market
Leading calf-fit boot trend in 2026	#1	Trend authority
Alternatives emphasising precise measurements and easy exchanges	#1	Alternative positioning
Heeled knee-high boots in a range of calf sizes	#1	Style + fit
High-quality leather with good value-for-money	#8	Value positioning
Wide calves and plus-size ranges with reviews	#1	Inclusive sizing
Handmade in Portugal — artisanal production	NOT MENTIONED	Portugal variant
Unique calf-measurement tools or sizing systems	#1	DuoBelt
Top women's boot brands in Europe — durable, long-term reviews	NOT MENTIONED	European longevity
Women's boots in Australia — reviewers say "elevate the look"	NOT MENTIONED	Australia aesthetics
Alternatives to mainstream brands — wide and narrow calf in Australia	#1	Australia fit
Accurate calf sizing and easy exchanges — US shipping	#1	US + fit accuracy
Direct-to-consumer UK/EU — transparent sourcing, premium leather	#1	DTC + provenance

Summary: 15 × Rank #1 / 2 × Non-#1 rankings / 3 × Not mentioned

What do all 15 Rank #1 prompts share?

Every first-place result contains at least one of these trigger elements: explicit calf-fit language ("calf sizes", "calf widths", "calf measurements"), sizing precision demand ("sizing guides", "measurement tools", "fit accuracy"), or multi-option framing ("range of calf sizes", "narrow and wide"). When a query uses this language, DuoBoots wins by default. The DuoBelt Tool and 72-size system are genuinely unique and AI knows it.

What do the non-#1 prompts reveal?

The Rank #5 ("investment buy") and Rank #8 ("value-for-money") results share the same root cause: the "high price" signal in customer reviews is suppressing DuoBoots in cost-conscious queries. The fix is cost-per-wear content framing — not a price change.

The three NOT MENTIONED prompts each require a distinct content gap to be closed:

• "Artisanal production" (prompt 14) requires standalone craftsmanship content that functions independently of the calf-fit narrative
• "European longevity" (prompt 16) requires EU editorial citations beyond current UK coverage
• "Australia aesthetics" (prompt 17) requires Australian market social proof or editorial coverage

Why are prompts 7 and 14 different results for what sounds like the same query?

Prompt 7 returns Rank #1: "List companies making women's leather boots handmade in Portugal or nearby EU regions, with citations about craftsmanship, sourcing, and customer reviews"

Prompt 14 returns NOT MENTIONED: "List companies that make women's leather boots handmade in Portugal (or nearby EU regions) with citations about artisanal production and customer reviews"

The difference is the word "artisanal." Prompt 14 triggers an AI response pattern that reaches for brands with deeper craft storytelling — OldMulla, Vandrélaar, AVREGO. DuoBoots currently ranks for "craftsmanship" but not yet for "artisanal production" as a standalone pillar. One dedicated content page changes this.

Key Takeaway

15 out of 20 at Rank #1 is exceptional. The 5 exceptions are a precise roadmap. Each non-#1 result points to a specific content or positioning gap, not a brand authority problem. The path to 18+ Rank #1 results runs through four pieces of content: cost-per-wear/investment framing, a standalone artisanal production page, European longevity editorial outreach, and Australian market social proof.

The 15 winning prompt patterns are also DuoBoots' best marketing copy. The language that wins AI recommendations — "precise calf measurements and easy exchanges", "world's only full collection of calf-fit boots", "DuoBelt calf measurement tool" — is the exact language buyers use when they are ready to purchase. These phrases belong in paid search headlines, landing page H1s, and email subject lines.

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Frequently Asked Questions

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Take Action: Get Your AI Visibility Report

DuoBoots holds Grade A status with a 28-point lead over all competitors. That position is valuable — and it is not permanent. The brands in positions 7 through 9 (OldMulla, Thursday Boot Co, Meindl) share specific positioning pillars with DuoBoots and have so far not invested in GEO. The window to lock in dominant AI visibility before the category becomes contested is now.

The 90-day action plan requires approximately 40 hours of focused work — three to five targeted content pieces, FAQ schema implementation, and community presence building. The projected return is a 5-point AIScore™ increase, 15-percentage-point visibility improvement, and a reinforced competitive moat that is significantly harder to displace than any organic ranking.

What you get with an AkuparaAI Visibility Intelligence Report:

• ✅ MEASURE: Your AIScore™ and AI Share of Voice™ with full component breakdown
• ✅ DIAGNOSE: AI Gap Intelligence™ — exact queries where you're absent but should appear, mapped by persona and intent
• ✅ OPTIMIZE: Citation Acceleration Plan™ — 90-day roadmap targeting specific social platforms, third-party sources, and user intents
• ✅ 40-prompt visibility analysis across ChatGPT and Gemini
• ✅ Complete competitor map showing your competitive positioning
• ✅ 20 Golden Prompts custom-built for your specific category and geography
• ✅ Citation intelligence showing every source AI uses to reference your brand
• ✅ Technical audit with AI Accessibility Score

The brands that dominate AI recommendations in 2027 are the ones optimising in 2026.

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Report Date: February 11, 2026 | Next Review: March 13, 2026
Powered by AkuparaAI Intelligence Platform

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Methodology

This analysis is based on a comprehensive AI Visibility Intelligence Report for DuoBoots, examining 40 high-intent queries across ChatGPT (OpenAI) and Gemini (Google).

• 20 queries per platform — 40 total responses analysed
• Geographic coverage: US, UK, EU, Canada, Australia
• Buyer intent categories: 10 stages from category_exploration to vendor_discovery
• Competitive analysis: 10 direct and adjacent brands
• Citation analysis: 35 unique source URLs identified
• Technical audit: 5 AI accessibility dimensions (partial — some pages could not be accessed)

All data reflects AI platform responses as of February 2026. Golden Prompt rankings can shift 2–3 positions within a month due to continuous AI model updates and competitor content activity. Monthly tracking is recommended.

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