CiteWorks Studio

HOKA AI Market Strategy Report - Hiking Boots, Trail Shoes, and Outdoor Footwear

Mark HuntleyBy Mark HuntleyFounder and CEO
10 minutes read

Key Takeaways

  • HOKA ranked third in the category with 72.78% valid recommendation coverage, behind Merrell at 82.35% and Salomon at 81.13%.
  • Its top-three recommendation rate improved from 37.0% in July to 43.13% in September, even as overall coverage slipped slightly.
  • The main performance gap is rank-one placement: HOKA reached 10.24% versus 41.11% for Salomon and 17.92% for Merrell.
  • Google AI Overviews was HOKA's strongest platform at 83.16% coverage, while Gemini was its weakest at 65.59% and a 7.53% rank-one rate.

Answer Capsule

HOKA holds a strong third-place position in AI-generated recommendations for hiking boots, trail shoes, and outdoor footwear, with 72.78% valid recommendation coverage in September 2026. The brand shows a notable split: its overall coverage declined slightly from July, yet its top-three rate improved from 37.0% to 43.1% over the same period, indicating stronger positioning where it does appear. HOKA's clearest weakness is the gap to the top two brands, with Merrell at 82.35% and Salomon at 81.13% coverage. The clearest opportunity lies in converting its strong presence and positive framing into more first-place recommendations, where its 10.24% rank-one rate trails Salomon's 41.11% by a wide margin.

Who This Report Is For

This report is for HOKA's brand, marketing, and ecommerce leadership teams tracking how AI search systems discover and recommend the brand in the hiking and trail footwear category.

Report Card

Field

Value

Report type

AI Company Market Strategy Report

Target company

HOKA

Category / market studied

Hiking Boots, Trail Shoes, and Outdoor Footwear

Reporting month

September 2026

AI platforms tracked

6 (ChatGPT, Copilot, Gemini, Perplexity, AI Overviews, AI Mode)

Public high-intent clusters

1 (Best Hiking Boots and Trail Shoes)

AI observations analyzed

742

Competitors tracked

9

Executive Summary

HOKA holds a strong third-place position in AI-generated recommendations for hiking boots, trail shoes, and outdoor footwear, with 72.78% valid recommendation coverage in September 2026. The brand appears in 89.22% of qualified AI responses, yet converts that presence into valid recommendations in 72.78% of observations, a conversion gap that signals room for improvement in how AI systems frame the brand.

The benchmark shows HOKA with 565 positive mentions, 96 neutral mentions, and 1 negative mention across 742 qualified observations. This positive framing is consistent with the brand's strong reputation in the category, but it does not automatically translate into top recommendation placement.

HOKA's strongest cluster is the Best Hiking Boots and Trail Shoes consideration set, which accounts for all 742 qualified observations in the current public series. The brand's weakest area is rank-one placement, where it achieves only 10.24%, compared with Salomon's 41.11% and Merrell's 17.92%.

The strongest platform signal for HOKA is Google AI Overviews, where the brand reaches 83.16% valid recommendation coverage and a 95.35% net sentiment score. The clearest platform gap is Gemini, where HOKA's coverage drops to 65.59% and its rank-one rate falls to 7.53%.

The overall pattern suggests HOKA is consistently named and positively framed across AI surfaces, but it is not consistently selected as the first or best option. The brand wins consideration but loses the final recommendation decision to Salomon in particular.

What HOKA Is Winning

Questions This Section Answers

  • Where is HOKA gaining ground in AI-generated recommendations?
  • How did HOKA's top-three placement rate change between July and September 2026?

HOKA's strongest evidence-backed win is its top-three placement rate. The brand's top-three rate rose from 37.0% in July to 43.1% in September 2026, even as its overall coverage eased from 75.2% to 72.8%. This means HOKA is winning a larger share of the consideration set in the answers where it does appear.

HOKA also holds a strong presence position. Its 89.22% raw mention presence rate places it third in the category, behind only Merrell at 97.84% and Salomon at 95.01%. The brand is being named in AI responses at scale.

The brand's sentiment profile is another clear win. HOKA's net sentiment score of 0.852 reflects 565 positive mentions against just 1 negative mention across 742 observations. This positive framing is a foundation the brand can build on.

HOKA's strongest platform performance comes through Google AI Overviews, where it achieves 83.16% valid recommendation coverage, its highest of any tracked surface. The brand also posts a 95.35% net sentiment score on that platform, indicating very strong framing quality where AI Overviews surfaces the brand.

Where HOKA Has the Clearest AI Visibility Gaps

Questions This Section Answers

  • Why does HOKA's rank-one placement trail Salomon and Merrell?
  • On which platforms does HOKA's recommendation coverage drop most sharply?
  • What does HOKA's average recommended rank reveal about its position?

HOKA's clearest gap is rank-one placement. The brand achieves a 10.24% rank-one rate in September 2026, compared with Salomon's 41.11% and Merrell's 17.92%. When AI systems are asked to name the single best hiking boot or trail shoe, they select HOKA far less often than they select Salomon.

The gap to the top two brands is substantial. Merrell leads at 82.35% valid recommendation coverage, with Salomon close behind at 81.13%. HOKA trails at 72.78%, a difference of roughly 9 to 10 percentage points. This is not a marginal gap; it represents a meaningful share of recommendation-stage visibility that HOKA is not capturing.

HOKA's average recommended rank of 2.96 confirms the pattern. When the brand is recommended, it tends to appear around the third position, while Salomon's average recommended rank of 1.77 places it much closer to the top of the answer.

The Gemini platform shows a specific weakness. HOKA's valid recommendation coverage drops to 65.59% on Gemini, below its performance on ChatGPT at 77.78%, Copilot at 76.09%, Perplexity at 67.01%, and Google AI Overviews at 83.16%. Its rank-one rate on Gemini falls to 7.53%, and its rank-one rate on Perplexity drops to 2.06%.

The public benchmark does not yet contain qualified observations for pricing and value or multi-brand comparison prompts, so HOKA's visibility in those high-intent contexts remains unmeasured.

Biggest Opportunity

Questions This Section Answers

  • What is HOKA's clearest opportunity for converting visibility into recommendation share?
  • How does Salomon's presence-to-rank-one conversion compare with HOKA's?

HOKA's clearest opportunity is converting its strong presence and positive framing into more first-place recommendations. The brand is named in 89.22% of AI responses and receives positive framing in 76.15% of observations, yet it is selected as the single best option in only 10.24% of responses. Salomon demonstrates what is possible: a 95.01% presence rate converts into a 41.11% rank-one rate.

The path forward involves understanding which prompts and surfaces drive Salomon's rank-one advantage and where HOKA is being named as a strong option without being selected as the best option. The brand's improving top-three rate, up from 37.0% in July to 43.1% in September, suggests momentum that could be extended into rank-one placement with targeted work on the answer layer and citation architecture.

Competitive Landscape

Questions This Section Answers

  • Where does HOKA stand relative to Salomon and Merrell on recommendation placement?
  • Which metrics separate HOKA's position from the mid-tier brands?

Salomon and Merrell hold the strongest recommendation-stage positions in the category, with Salomon leading on rank-one placement and Merrell leading on overall coverage. HOKA sits in a clear third position, ahead of the mid-tier brands but behind the top two by a meaningful margin.

Brand

Top-3 rate

Rank-1 rate

Avg recommended rank

Sentiment

Salomon

61.86%

41.11%

1.77

0.8865

Merrell

58.49%

17.92%

2.36

0.876

HOKA

43.13%

10.24%

2.96

0.852

La Sportiva

12.40%

2.29%

4.23

0.8523

Altra

12.26%

1.62%

4.31

0.8402

KEEN

12.26%

2.43%

4.33

0.7894

Danner

3.64%

0.13%

5.15

0.736

Oboz

3.10%

0.67%

5.38

0.8306

Columbia Sportswear

2.70%

0.40%

5.24

0.6011

Vasque

0.27%

0.00%

5.50

0.5625

Average recommended rank covers rank-eligible recommendations only.

The table shows HOKA holding a clear third position on top-three rate, rank-one rate, and average recommended rank. The brand's sentiment score of 0.852 is competitive with the top two brands, indicating that framing quality is not the differentiator. The gap is in recommendation placement, where Salomon's 41.11% rank-one rate is roughly four times HOKA's 10.24%.

Prompt Evidence

Questions This Section Answers

  • Which prompt and platform combinations show HOKA's strongest and weakest recommendation coverage?
  • How does HOKA's rank-one rate on Perplexity compare with Salomon's on the same platform?

Google AI Overviews / Best Hiking Boots and Trail Shoes Prompt: "What are the best hiking boots for women?" Result: HOKA appears in the response with strong positive framing, achieving its highest platform coverage at 83.16% on this surface.

Perplexity / Best Hiking Boots and Trail Shoes Prompt: "What is the best hiking boot for men?" Result: HOKA is named but rarely selected first, with a rank-one rate of just 2.06% on Perplexity compared with Salomon's 52.58% on the same platform.

Gemini / Best Hiking Boots and Trail Shoes Prompt: "What are the top 10 hiking shoes?" Result: HOKA appears in the answer set but with weaker recommendation conversion, achieving 65.59% valid recommendation coverage on Gemini, its lowest among the six tracked platforms.

What CiteWorks Studio Would Do Next

Phase 1: AI Market Discovery Audit Map the specific prompts and surfaces where HOKA is named but not selected first, with particular focus on the rank-one gap versus Salomon.

Phase 2: Recommendation Readiness Plan Identify the product attributes, use cases, and comparison frames where HOKA wins consideration, then build the answer layer around those strengths.

Phase 3: Owned Answer Layer Buildout Develop owned content that positions HOKA as the first-choice recommendation for specific hiking and trail scenarios, targeting the prompt families where rank-one placement is weakest.

Phase 4: Citation / Authority Layer Development Strengthen the public evidence layer that AI systems draw on when forming recommendations, with emphasis on the sources that support first-place positioning.

Phase 5: Monthly AI Visibility and Recommendation Tracking Track HOKA's coverage, top-three rate, and rank-one rate monthly to measure whether the gap to Salomon and Merrell narrows over time.

Why This Matters

AI-generated recommendations are becoming the buyer shortlist for hiking boots, trail shoes, and outdoor footwear. When shoppers ask AI systems for the best option, the brands named first and most often shape the consideration set before the buyer ever reaches a brand website or retail page.

HOKA's position shows that presence alone is not enough. The brand is named in nearly 9 out of 10 AI responses and framed positively, yet it is selected as the best option in only about 1 out of 10. The next move is targeted correction of the prompt, page, and citation layers to convert strong visibility into stronger recommendation placement, particularly at the rank-one position where Salomon currently holds a commanding lead.

Core Metrics

Metric

Value

Mentions

662

Valid recommendations

540

Top 3 recommendation count

320

Rank #1 recommendation count

76

Average recommended rank

2.96

Positive mentions

565

Neutral mentions

96

Negative mentions

1

Raw mention presence rate

89.22%

Valid recommendation coverage

72.78%

Top 3 recommendation rate

43.13%

Rank #1 recommendation rate

10.24%

Net sentiment score

0.852

Strongest cluster by recommendation behavior

Best Hiking Boots and Trail Shoes

Strongest platform by recommendation behavior

Google AI Overviews

Sentiment Score

Sentiment Score = (positive mentions × 1 + neutral mentions × 0 + negative mentions × -1) / total mentions

For HOKA, this calculation is (565 × 1 + 96 × 0 + 1 × -1) / 662, producing a net sentiment score of 0.852.

This score matters because unclassified mention counts are misleading. A brand can appear in hundreds of AI responses, but those mentions carry very different weight depending on whether they are positive recommendations, neutral references, cautionary mentions, or competitor-displaced mentions. Share of voice is a diagnostic metric, not a business KPI. A positive recommendation, neutral reference, cautionary mention, and competitor-displaced mention are not equal. Counting all mentions as wins is bad measurement. Classified sentiment is required before interpreting AI visibility, because it separates brands that are being recommended from brands that are merely being named.

Sentiment by Platform

Platform

Mentions

Positive

Neutral

Negative

Sentiment Score

Readout

ChatGPT

78

67

11

0

0.859

Strongest public recommendation signal

Copilot

82

71

10

1

0.8537

Present, but not recommendation-led

Gemini

86

66

20

0

0.7674

Present as context, not recommendation

Perplexity

81

70

11

0

0.8642

Positive, but sample too small

AI Overviews

172

164

8

0

0.9535

Strongest public recommendation signal

AI Mode

163

127

36

0

0.7791

Present, but not recommendation-led

Methodology

  1. This report is based on the LLM Authority Index AI Market Discovery Index for hiking boots, trail shoes, and outdoor footwear, interpreted by CiteWorks Studio as a company-level market strategy readout for HOKA.
  2. The reporting window is September 2026, with July 2026 as the baseline comparison month and August 2026 referenced for intermediate movement.
  3. Six AI/search surface families were tracked: ChatGPT, Copilot, Gemini, Perplexity, AI Overviews, and AI Mode.
  4. The benchmark produced 742 qualified observations in September 2026 from an initial collection of 800 prompt-surface observations across 529 unique questions.
  5. The competitor universe includes 10 tracked brands: Altra, Columbia Sportswear, Danner, HOKA, KEEN, La Sportiva, Merrell, Oboz, Salomon, and Vasque.
  6. All qualified observations fell into the Brand Recommendation buyer-intent class, reflecting shoppers seeking direct brand suggestions. No qualified observations were recorded for pricing and value or multi-brand comparison prompts in this period.
  7. Stage 0 extraction captured prompt-level observations including the query, AI surface, answer, brand outcome, recommendation placement, sentiment, and citations where exposed.
  8. A mention is defined as any appearance of a tracked brand in an AI response, regardless of whether the brand is recommended.
  9. A valid recommendation is defined as a clear, actionable recommendation naming the brand, distinct from a neutral reference or cautionary mention.
  10. The public benchmark does not yet contain qualified observations for pricing and value or multi-brand comparison prompts, so HOKA's visibility in those high-intent contexts remains unmeasured.
  11. Columbia Sportswear's August 2026 data reflects a naming inconsistency in that month's records and should not be read as a real month-over-month swing.
  12. Limitations: This public benchmark does not measure market share, attributable sales, every possible AI response, organic-search ranking, social mention volume, or private or sponsored channels. A movement in a metric alone does not establish causality.

See How AI Is Recommending Your Brand

The public benchmark shows where HOKA is winning and losing in AI-generated recommendations. A company-level AI visibility audit goes deeper, mapping the specific prompts, surfaces, competitors, and evidence sources that drive HOKA's recommendation outcomes across ChatGPT, Copilot, Gemini, Perplexity, AI Overviews, and AI Mode.

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Understanding AI search visibility.

AI search experiences create answers by pulling information from many places online and summarizing it into a single response.

What Is AI Citation Intelligence?
AI citation intelligence is the process of measuring where AI platforms source their information and how frequently a brand is mentioned or referenced in AI-generated responses. Because LLMs synthesize across multiple sources, the sites and brands that appear repeatedly tend to influence how a topic or company is framed. This practice focuses on identifying which sources shape AI outputs and tracking brand visibility across different AI systems.
What Is Citation Architecture?
Citation architecture describes the set of sources that consistently inform how AI systems talk about a brand, product, or topic. LLMs draw from websites, articles, forums, and public discussion, and the sources they rely on most often become the backbone of their answers. Building strong citation architecture means ensuring that accurate, credible, high authority sources are the ones most likely to shape the way AI tools summarize and recommend a brand.
What Is Generative Engine Optimization?
Generative engine optimization (GEO) is the practice of improving the chances that AI systems use and cite your brand or content when generating answers. While traditional SEO is centered on ranking pages in search results, GEO focuses on how LLMs retrieve, interpret, and combine information when responding to a question. The objective is to strengthen the content and sources AI systems rely on, so your brand is treated as a trusted reference in AI responses.
What Is AI Share of Voice?
AI share of voice tracks how often a brand appears in AI-generated answers compared with competitors in the same category. It reflects visibility across AI platforms such as ChatGPT, Gemini, Claude, and Perplexity. Monitoring AI share of voice helps organizations see whether AI systems consistently include and recommend their brand for key queries or whether competitor brands are showing up more often.

About The Author

Mark Huntley

Mark Huntley

Founder and CEO

Mark Huntley, J.D. is founder of CiteWorks Studio, a strategic advisory focused on visibility, authority, and recommendation presence in AI-shaped search environments. His work centers on embedding-level GEO, vector optimization, and cosine gap engineering — helping brands align their digital presence with the retrieval systems that increasingly shape discovery, interpretation, and choice.

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