Research · March 2026
Q1 2026 AI Visibility Snapshot: Hiking Boots
1,372 prompt-response pairs. 25 brands. 3 weeks. The median brand appears in fewer than 1 in 13 AI buying recommendations. Arc'teryx — zero mentions.
Which brands AI recommends — and why most are invisible.
This is the first quarterly AI Visibility Snapshot for the hiking boot category. It is not an index. It is a point-in-time measurement of which brands AI assistants recommend when buyers ask buying questions — and a structural analysis of why most brands in this category are functionally invisible.
The data covers 1,372 prompt-response pairs across 25 brands over 3 weeks (W11–W13, March 2026). The median Envoyra Score is 7.4 out of 100. For most brands in this category, AI-driven discovery is not an underperforming channel. It is functionally nonexistent.
7.4 / 100 | Median Signal Score across 25 brands — 52% score below 10/100, 28% received zero AI mentions entirely
Executive summary
31.7% | Share of all AI recommendations controlled by just two brands — Merrell and Salomon
Key statistics: 1,372 prompt-response pairs analyzed · 25 brands measured · 3 weekly cycles (W11–W13) · Mean Signal Score: 18.8/100 · Median: 7.4/100 · 52% of brands score below 10/100 · 28% received zero mentions · Third-party citation rate (median): 0.8% · Top brand score: 74.5 (Merrell) · Score gap between rank 2 and rank 3: 21.7 points.
The most striking finding: Arc'teryx received zero mentions across all prompts, all weeks. A premium outdoor brand with significant retail presence and loyal customers. None of that translated to AI visibility. Arc'teryx's product pages prioritize brand storytelling over structured specifications. AI models cannot extract the structured evidence they need to generate a confident recommendation — so they recommend brands whose content gives them something to cite.
Disclosure: Envoyra sells the AI visibility scanning tool used to collect this data. We have a financial interest in findings that demonstrate the value of AI visibility measurement. The methodology is disclosed in full below. Underlying scan data is available to clients and press on request.
Brand heritage counts for nothing in this layer. If Arc'teryx can score zero, so can you. Explore the research →
Category leaderboard (W13)
Top 10 brands by Envoyra Score — 60 buyer-intent prompts, Perplexity Sonar:
1. Merrell — 74.5/100 — 17.2% mention share 2. Salomon — 70.0/100 — 14.5% mention share 3. Hoka — 48.3/100 — 9.1% mention share 4. Danner — 41.2/100 — 7.8% mention share 5. Keen — 38.7/100 — 6.9% mention share 6. La Sportiva — 31.4/100 — 5.2% mention share 7. Vasque — 28.1/100 — 4.6% mention share 8. Oboz — 24.6/100 — 3.8% mention share 9. Lowa — 19.3/100 — 2.9% mention share 10. Scarpa — 17.8/100 — 2.4% mention share
Notable absences: Arc'teryx (0 mentions), Columbia (4.2/100), The North Face (6.1/100), Timberland (3.7/100).
The gap between rank 2 (Salomon, 70.0) and rank 3 (Hoka, 48.3) is 21.7 points — larger than the gap between rank 3 and rank 10. This structural separation defines the category: there is a clear Tier 1 (Merrell, Salomon) and then everyone else.
Signal analysis — what correlates with AI recommendations
We decomposed the top 5 brands' AI visibility into specific content signals.
Waterproof certification language: Merrell 94%, Salomon 91%, Hoka 67%, Danner 88%, Keen 72%. Category average: 41%.
Structured spec formatting (machine-readable): Merrell 89%, Salomon 86%, Hoka 61%, Danner 79%, Keen 64%. Category average: 33%.
Explicit use-case mapping: Merrell 91%, Salomon 88%, Hoka 58%, Danner 74%, Keen 61%. Category average: 27%.
Numeric measurement density (per page): Merrell 14.3, Salomon 13.1, Hoka 8.7, Danner 11.2, Keen 9.4. Category average: 6.1.
Third-party authority citations: Danner 100%, Salomon 67%, Keen 48%, Merrell 29%, Hoka 22%. Category average: 18%.
18% | Category average for third-party citations — Danner leads at 100%, the median brand is at 0.8%
The pattern is clear: tier 1 brands lead on five of six structural signals. The one signal where Merrell trails — third-party authority citations — represents the primary exploitable gap for challenger brands.
Weekly volatility
AI recommendations are not stable. The largest single-week swing: Hoka gained 48.3 percentage points on backpacking-specific prompts between W11 and W12 with no changes to its content, then lost 31.2 points between W12 and W13.
Salomon's trajectory warrants attention: despite holding the highest raw mention count in W11, its Signal Score declined from 73.2 to 70.0 across the observation period. Merrell overtook Salomon on the Signal Score metric by W13.
Brands ranked 6–15 showed average week-over-week score volatility of ±8.4 points — roughly 44% of their mean score. Single-week measurements are unreliable for mid-tier brands. Trend lines over 4+ weeks are required for actionable conclusions.
Displacement analysis
When a mid-tier brand (ranked 6–15) does not appear on an AI shortlist, which brands appear instead?
Merrell appears as a substitute in 74% of missed-prompt displacement events. Salomon appears in 64%. Both brands appear together on 58% of shortlists where the mid-tier brand is absent.
Mid-tier brands are not losing to a diverse competitive field. They are losing to the same two competitors, on the same types of prompts, because of the same structural content weaknesses, every single week.
The displacement is patterned and predictable. Mid-tier brands lose most consistently on prompts requiring: specific waterproof technology names (present in 41% of mid-tier pages vs 94% for Merrell), structured side-by-side specifications (33% vs 89%), and explicit terrain-specific use-case mapping (27% vs 91%).
Cluster analysis — where the gaps are widest
Backpacking cluster: 28% of brands have any visibility. Merrell and Salomon control 61% of recommendations. Gap driver: most brands do not publish load-bearing specifications AI can cite.
Women's-specific cluster: 87% visibility gap. Only 13% of brands appear in women's-specific hiking boot recommendations. AI defaults to unisex recommendations when brands publish only colorway variations rather than distinct women's specifications.
Budget cluster (under $120): 42% visibility gap. Budget buyers are more likely to use AI for purchase decisions — and the brands targeting them underinvest in structured content.
Trail running crossover: 67% visibility gap. The fastest-growing prompt category. Hoka and Salomon dominate because their content explicitly bridges both use cases.
Winter and ice cluster: 54% visibility gap. Brands with ice-specific certifications (Vibram Arctic Grip, temperature ratings) dominate. "Great for cold weather" does not earn a citation.
The five AI recommendation laws
Five structural patterns emerged from 1,372 prompt-response pairs that govern which brands AI recommends:
Law 1: Specificity creates inclusion. "Waterproof to 24-hour submersion" beats "legendary waterproof protection." The correlation between numeric measurement density and Signal Score is 0.83.
Law 2: Structure beats narrative. Machine-readable specification blocks outperform marketing prose. AI models can compare structured data across brands. They cannot compare paragraphs of evocative copy.
Law 3: Authority is borrowed, not built. A single review from a trusted source with structured specification data produces more AI recommendation confidence than fifty social endorsements.
Law 4: Absence is silent. There is no error message when AI excludes your brand. No ranking drop. The brand continues performing normally on every metric it tracks while being systematically absent from the layer now sitting above all those channels.
Law 5: Early movers compound. The gap between brands that understand AI visibility and brands that do not is widening with every model update. The cost of waiting is not zero — it is the compounding advantage competitors accumulate while you optimize for a different era.
Methodology and limitations
Data source: Envoyra Engine v1.0, Perplexity Sonar. 1,372 prompt-response pairs across 25 brands, 3 weekly cycles (W11–W13), March 2026.
Prompt design: 60 buyer-intent prompts per cycle across day hiking, backpacking, trail running, winter hiking, women's-specific, budget, and premium segments.
Brand detection: Case-insensitive substring matching against raw AI response text. Non-deterministic AI outputs mean scores may vary slightly between identical scans. Single-model baseline. Signal Taxonomy correlations are observational, not causal. Trend lines over 4+ weeks are recommended over single-week measurements.
Envoyra Engine v1.0 · Perplexity Sonar · March 2026
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