Reebok SEO & GEO Audit: Does Google AI Cite Reebok?

What is Reebok.com trying to do — and why audit it ninth?

This is part 9 of GeoParrot’s sports-brand series, running the same evidence-first method we used on Lululemon, Skechers and New Balance. Reebok is a useful ninth name because it has changed hands twice in recent years — sold by Adidas to Authentic Brands Group (ABG) in 2021 — and its storefront infrastructure shows it: reebok.com now runs on Shopify (confirmed via its public /.well-known/ucp endpoint, which names the backing shop as abg-reebok-store.myshopify.com), a platform none of the previous eight brands in this series used. That migration brought Shopify’s own emerging “agentic commerce” infrastructure along with it — which turns out to be a genuinely different category of llms.txt than anything we’ve seen so far.

The product we tracked: Classic Leather Shoes

AI citation snapshot: 10 real queries, Google AI Mode

We sent 10 verbatim queries to Google AI Mode (udm=50) and checked both direct a[href] links and citation chip aria-labels for the Reebok brand family (reebok.com, reebok.co.kr, reebok.eu, reebok.com.au). Method note, reported honestly: direct link capture worked well this run (most queries returned 2-20 raw URLs), so counts lean on actual hrefs rather than chip labels alone — the same convention used for New Balance and Lululemon.

Result: Reebok’s domain family cited in 7/10 queries (Nike 5/10, Adidas 4/10, Puma 5/10, Under Armour 8/10, New Balance 6/10, ASICS 7/10, Skechers 4/10, Lululemon 8/10) — tied for second-highest in the series. The two head-to-head brand-comparison queries split: Reebok won when compared against Adidas (both domains cited), but lost when compared against New Balance (only New Balance’s domain family appeared) — continuing the series-wide pattern that comparison queries are the least predictable for any single brand’s own domain to win. The named-product review query succeeded this time, breaking the five-brand losing streak we’d tracked on “[brand] [product] review” queries through New Balance.

G-score audit: the 8-pillar hygiene checklist, and a client-side schema gap

We scored six representative Reebok URLs with the same 8-pillar static-HTML checklist (JSON-LD present, FAQ content, visible date, author byline, concrete data points, table/list structure, 3+ subheadings, a 30–500 character early answer) used in our Week 17 quality-score experiment and on all eight prior brands. What we found this time is new to the series: on reebok.com, a plain HTTP fetch of the homepage and Contact Us page returns zero application/ld+json blocks, but the identical URL re-fetched through a full browser session (JavaScript executed, 5-second settle) carries a complete Organization + Product schema. We confirmed this isn’t a fluke by running both fetch methods side by side on the same four US pages in the same pass.

Method note, reported honestly: repeated plain-HTTP requests to reebok.com’s category and product pages returned HTTP 429 (Too Many Requests) partway through this audit — Shopify-side rate limiting, not a hard block, and notably the exact behavior Reebok’s own agents.md tells AI agents to expect (“Back off on 429 responses and respect Retry-After when provided”). We didn’t attempt to defeat it; those two rows use the browser-rendered score only, consistent with how we handled Akamai blocks on Adidas, New Balance and Lululemon earlier in this series.

Blending the primary fetch method used per page (plain where it succeeded, browser-rendered where 429 forced a fallback), the six-page average is 0.5417 (Nike: 0.4375, Puma: 0.354, Under Armour: 0.5208, New Balance: 0.5833, Adidas: 0.6458, ASICS: 0.4583) — middle of the series range. But the headline isn’t the average, it’s the gap: reebok.com’s own Product schema exists and is reasonably complete, yet it’s invisible to anything that fetches the page without running JavaScript — which describes most AI crawlers (GPTBot, ClaudeBot, PerplexityBot and CCBot do not execute JavaScript by default).

US support, and the Korea storefront: a different company, a different platform

Reebok’s US Contact Us page runs standard hCaptcha-protected support form. The Korea storefront, reebok.co.kr, is a visibly different site end to end — different design system, different e-commerce platform (GODOMALL, not Shopify), and as the product page itself discloses, a different operating company.

Technical check: robots.txt, llms.txt, agents.md, sitemap, locale

What works / What to verify

Target query check — reported honestly, not inflated

We have not re-measured “reebok seo” or “reebok geo audit” query volume this session. Per the pattern already confirmed across nine earlier subjects in this series on October 20, 2026 (Keyword Planner, US) — the large majority showed no measurable search volume at all for “[brand] SEO/GEO audit” phrasing — we’re not claiming this title drives ranking-based traffic. The distribution case for this series rests on internal links, our own index, and readers already following the GEO Lab arc, not on search demand for “[brand] SEO audit” as a query.

Frequently asked questions

Does Reebok’s llms.txt actually help AI engines cite Reebok more?

We have no evidence either way from this snapshot. Reebok’s domain family was cited in 7/10 queries — near the top of the series range — but the llms.txt we read is a Shopify commerce-agent integration guide, not AI-citation guidance, so there’s no mechanism by which its content would influence what Google AI Mode chooses to cite. Google Search doesn’t read llms.txt at all; see our explainer.

Why is Product schema missing from a plain fetch of reebok.com but present after a browser renders the page?

We can only report what we observed, not the underlying engineering decision: the Organization and Product JSON-LD blocks appear in the DOM only after JavaScript executes, meaning Shopify (or this specific store’s theme) builds and injects them client-side rather than including them in the initial server-rendered HTML. A crawler that doesn’t execute JavaScript — which describes most AI crawlers by default — would see a page with no structured data at all on this URL.

Why does reebok.co.kr’s robots.txt block ClaudeBot and GPTBot specifically?

We can’t confirm intent, only what’s disclosed: the file itself is commented ‘Default Bot Policy List provided by GODOMALL,’ the Korean e-commerce platform reebok.co.kr runs on, which suggests this may be a platform-wide template rather than a decision LF Corporation made specifically about Reebok’s Korea storefront. It’s still the first robots.txt in this series to name AI crawlers for an outright block rather than a crawl-delay or a welcome.

Does a G-score around 0.54 mean Reebok is more likely to be cited by AI engines?

Not reliably — this audit is itself a data point against that idea, consistent with all eight prior brands. Our Week 17 experiment found hygiene/structure score was not a dependable predictor of AI citation, and here ASICS scored a lower 0.4583 average yet matched Reebok’s 7/10 citation rate, while Skechers scored a comparable hygiene profile yet landed at just 4/10. Our 10-query snapshot measures the domain family, not individual URL citation, so we can’t confirm which specific page — if any — drove Reebok’s 7 successful citations.

This is part 9 of a daily series. Every day, GeoParrot runs this same evidence-first method — real screenshots, a 10-query AI citation snapshot, an 8-pillar G-score audit, and an honest target-query check — against one more major sports and athletic-wear brand. Next: Converse.