Category AI Visibility Report
Track Spikes AI Visibility Report 2026: Top Brands & Buyer Topics in AI Search
Data updated 2026-08-27 · 30-day window · ChatGPT · Google AI Mode · Google AI Overviews
≈6,536
Est. AI queries / month
13
Buyer topics monitored
10
Brands on the AI shelf
Key insights
- Over the last 30 days, GEOly monitored 13 buyer topics in Track Spikes across ChatGPT, Google AI Mode, Google AI Overviews — an estimated 6,536 AI queries per month.
- Nike leads the AI shelf with 55.5% of brand mentions, followed by adidas (14.6%) and New Balance (7%). The top three hold 77.1% combined — a concentrated shelf where challengers need a differentiated topic wedge.
- The highest-demand topic is “indoor track spikes” (top keyword “indoor track shoes spikes”, ~1,600 searches/mo).
- AI answers lean on runrepeat.com most (29.1% of citations) — earning presence on these sources is the shortest path to being recommended.
Brands AI recommends most
Share of brand mentions across AI answers in the last 30 days (Share of Model).
| # | Brand | AI mentions | Share |
|---|---|---|---|
| 1 | Nike | 3,095 | 55.5% |
| 2 | adidas | 815 | 14.6% |
| 3 | New Balance | 392 | 7% |
| 4 | ASICS | 352 | 6.3% |
| 5 | On | 200 | 3.6% |
| 6 | Puma | 180 | 3.2% |
| 7 | Under Armour | 152 | 2.7% |
| 8 | Saucony | 149 | 2.7% |
| 9 | Hoka | 77 | 1.4% |
| 10 | Brooks | 45 | 0.8% |
What shoppers ask AI
Buyer topics monitored in this category, with estimated monthly AI queries and the top Google keyword behind each topic.
| Topic | Est. AI queries / mo | Top keyword | Search volume / mo |
|---|---|---|---|
| indoor track spikes | ≈2,262 | indoor track shoes spikes | 1,600 |
| track spikes for triple jump | ≈2,165 | triple jump track spikes | 2,400 |
| track spikes with needle spikes | ≈2,109 | needle track spikes | 1,600 |
| youth track spikes | — | youth track spikes | 1,900 |
| distance track spikes | — | long distance spikes for track | 3,600 |
| cross country track spikes | — | cross country and track spikes | 8,100 |
| men's track spikes | — | men's track shoes with spikes | 4,400 |
| sprint track spikes | — | track spikes for sprinters | 9,900 |
| track spikes for pole vault | — | pole vaulting track spikes | 2,400 |
| personalized track spikes | — | personalized track spikes | 1,000 |
| track spikes for high jump | — | track spikes for high jump | 4,400 |
| women's track spikes | — | track spikes women's | 5,400 |
| best track spikes | — | track spikes | 74,000 |
Sources AI cites in this category
Root domains AI engines cited most when answering category queries in the last 30 days.
| Domain | Citations | Share |
|---|---|---|
| runrepeat.com | 312 | 29.1% |
| nike.com | 266 | 24.8% |
| reddit.com | 238 | 22.2% |
| outsideonline.com | 89 | 8.3% |
| runningwarehouse.com | 85 | 7.9% |
| fleetfeet.com | 18 | 1.7% |
| sprintingworkouts.com | 15 | 1.4% |
| puma.com | 11 | 1% |
Related category reports
FAQ
Which brands do AI assistants recommend most for track spikes?
Over the last 30 days the top brands by AI mention share are: Nike (55.5%), adidas (14.6%), New Balance (7%), ASICS (6.3%), On (3.6%). Data from GEOly's continuous monitoring across ChatGPT, Google AI Mode, Google AI Overviews.
How many people ask AI about track spikes?
GEOly estimates ~6,536 AI queries per month in this category across 13 buyer topics, led by “indoor track spikes”.
Which sources do AI engines cite for track spikes?
The most-cited domains are: runrepeat.com, nike.com, reddit.com, outsideonline.com, runningwarehouse.com. Building brand presence on these sources is the most direct way to win AI recommendations.
Methodology
GEOly continuously runs category buyer prompts across ChatGPT, Google AI Mode, Google AI Overviews and records which brands are mentioned and which sources are cited. Figures aggregate a 30-day window; AI query volumes are modeled estimates from keyword demand and AI-adoption share. Data: GEOly MCP Server, updated 2026-08-27.
See your brand inside this category
GEOly tracks how ChatGPT, Google AI Mode and Google AI Overviews mention, rank and cite your brand against every competitor above — and what to fix to win the AI shelf.