Brand Case Study · No. 001
Running Footwear · United States · April 2026

Nike Running in Our April 2026 Scan: AI Visibility 23%.

Across the US running queries we tested in April 2026, four AI models surfaced Hoka, On Running, and Brooks more often than Nike. Here is what our scan saw — and our read of why.

About this analysis
Scan period
April 2026
Geography
United States
Models tested
GPT-4o, Claude Sonnet, Gemini 2.5, Llama 3.3
Source
RadarFox AI brand-visibility scan
How to read the numbers. AI Visibility Index, Share of Voice, attribute scores, and citation influence are RadarFox proprietary metrics derived from the prompts and models we tested for this brand in this period. They describe how AI assistants surfaced Nike across our prompt set; they are not an independent or industry-standard benchmark.
What this is not. These results describe how AI assistants surfaced Nike in our scan. They are not a measure of overall market share, sales, consumer preference, or product quality.
RadarFox CMO Dashboard · Nike Running · US · April 2026 Scan
23%
AI Visibility Index RadarFox metric
In our April 2026 scan, Nike surfaced at a 23% AI Visibility Index for US running queries. Highest-surfaced peer in the same scan: Hoka at 68%.
#4 of 5 brands surfaced in our scan · Running Footwear · US
AI Share of Voice · In our scan RadarFox metric
Hoka68%
On Running52%
Brooks39%
Nike23%
New Balance18%
Attribute Performance · In our scan RadarFox metric
Brand recognition
9.2
Running expertise
4.1
Serious runner trust
2.2
Innovation
6.8
Comfort / cushion
2.9
Sustainability
3.1
Performance value
3.5
Marathon / elite
5.5
Top Citation Sources · What our scan saw the models cite RadarFox metric
SourceTypeInfluenceCited inPrimary narrative
runnersworld.comSpecialist MediaStrong61%Nike as lifestyle brand, not serious runner pick
reddit.com/r/runningCommunityStrong58%Community consensus: Hoka/On > Nike for daily training
hokaoneone.comCompetitorStrong52%Hoka frames itself as the serious runner's choice
nike.comBrand OwnedWeak8%Lifestyle and culture-first messaging, not performance
nytimes.com/sportsPressModerate34%Labour controversies and cultural capital, not product
trustpilot.comReviewsModerate27%Mixed — premium price, limited specialist positioning

Nike's brand recognition is not in question. In our scan, every model we tested identified Nike as a major sports brand — its 9.2 brand-recognition score is the highest in the set.

This piece is about a narrower question: when shoppers ask AI assistants for a running shoe recommendation, how often do those assistants surface Nike — and what do they say? Across the US running queries we tested in April 2026, Nike surfaced less often than Hoka, On Running, and Brooks.

Below is what our scan found, the sources our scan saw the models cite, and our read of what those patterns suggest a CMO might do about it.

For this scan we asked four AI models — GPT-4o, Claude Sonnet, Gemini 2.5, and Llama 3.3 — a set of US running discovery prompts: category questions, specific use cases (marathon training, daily comfort, trail), attribute comparisons, and direct head-to-heads. Nike was never named in the prompt; we let the models reach for brands on their own.

$ query: "best running shoes for marathon training 2026" — GPT-4o (1 of the 4 models in our scan)
Hoka Clifton 9 — described as a long-distance comfort benchmark
On Cloudmonster — described in terms of energy return for serious runners
Brooks Ghost 16 — framed around consistency for coached runners
Nike Vaporfly — surfaced in 1 of the 4 models we tested, in an elite racing context
$ query: "best everyday running shoes" — Claude Sonnet (1 of the 4 models in our scan)
Nike not surfaced in the top 4 of this response

What our scan saw on running queries

In our April 2026 scan, when prompts framed the user as a "runner" — preparing for a marathon, looking for daily training shoes, asking about cushion or stack height — the models we tested more often surfaced specialist brands first. When prompts framed the user around lifestyle or design ("cool sneakers", "stylish trainers"), Nike surfaced more often. The two halves of the scan looked quite different.

The attribute pattern in our scan tracks with that split. Nike scored 9.2 on brand recognition (the highest in the set we tested), 4.1 on running expertise, 2.2 on serious-runner trust, and 2.9 on comfort and cushioning. These numbers are RadarFox metrics from this scan; they describe the language the four models reached for, not Nike's actual products.

What our scan saw the models cite

When the models we tested talked about Nike in a running context, they leaned on a small set of sources. Three patterns showed up across our prompt set:

A pattern RadarFox has observed across other scans

In other scans we have run for legacy category leaders, owned media tends to score lower on AI citation influence than third-party publications and community sites. Where the gap is widest, the brand surfaces less in discovery prompts than its share of category mentions might suggest. Nike's pattern in our April 2026 running scan is consistent with that broader observation; we are not generalising it to other categories or scans.

How the brands above Nike showed up

In the same scan, Hoka surfaced at 68% AI Visibility, On Running at 52%, Brooks at 39%. The citations the models pulled around Hoka clustered on specialist running media and coached-community sources; the citations around On clustered on energy-return and engineering language across similar sources. We don't have evidence here of what those brands spent or how they got there — only of what the four models we tested reached for in April 2026.


Six moves a CMO might consider

The actions below are derived from what our April 2026 scan surfaced — specific sources, attribute scores, and gaps. They are options for a CMO to consider, not predictions about Nike's market outcomes. They are sequenced by where we think a measurable AI-visibility shift is most likely.

RadarFox Strategic Playbook · Derived from Scan Data
Six moves. Sequenced by impact.
01
Build a sustained presence in specialist running media
In our scan, specialist running publications (Runner's World and similar) appeared in roughly 61% of running prompts where a source surfaced. A consistent performance-data presence in those publications would increase the chance Nike running shoes are surfaced when AI reaches for those citations.
High Impact
02
Restructure nike.com/running for AI legibility
In our scan, the nike.com pages cited around running queries leaned on lifestyle and culture content. AI assistants extract structured facts — weight, stack height, drop, use case. Landing pages that lead with those facts, plainly, would give models more of what they tend to cite.
High Impact
03
Engage running communities on their terms
In our scan, the r/running subreddit appeared in roughly 58% of running prompts and the framing the models pulled from there was largely sceptical of Nike for daily training. Authentic engagement — shoe trials, coach partnerships, honest performance data sharing — typically takes 6–12 months to shift the kind of community language AI reflects.
Medium Effort
04
Anchor a clear cushioning narrative in third-party content
In our scan, cushioning showed up as a dominant attribute in running prompts. Nike scored 2.9 on cushion in our prompts. A focused third-party content effort around cushioning specifically (ZoomX positioning, comparative testing, runner reviews) is the kind of input we would expect to move that score on a future scan.
Medium Effort
05
Distinguish the running line from the lifestyle line in citation-heavy sources
In our scan, sources the models cited for general Nike queries (including Wikipedia) framed Nike heavily as a lifestyle/streetwear brand. Foregrounding running heritage and current performance work in those sources is a way to give the models a different default to reach for in running prompts.
Quick Win
06
Track head-to-head framing scan-over-scan
In our scan, the Nike-vs-Hoka prompts tended to surface culture-vs-performance language. A periodic re-scan is the simplest way to see whether actions on the moves above are shifting that framing in the prompts and models you care about most.
Quick Win

The broader lesson

Nike is not a cautionary tale; this is one scan, in one geography, in one period. What our April 2026 running scan does illustrate is a pattern we see in other RadarFox scans of large category leaders: AI assistants tend to talk about a brand the way the third-party sources they cite have been talking about it.

The practical brief that follows from that, for any CMO, is not "be more visible" — it's "make sure the sources AI assistants reach for are saying the right thing about you, for the queries you actually want to win."

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Disclaimer
This is an independent, methodology-limited analysis of AI model outputs and publicly available sources. It is not affiliated with Nike, Hoka, On Running, Brooks, or New Balance, and should not be read as a claim about Nike's overall market performance, consumer preference, or product quality. AI Visibility Index, Share of Voice, attribute scores, and citation influence are RadarFox proprietary metrics derived from the prompts and models we tested in April 2026 for US running discovery queries.