CASE STUDY · SNEAKERS · 3-MONTH PILOT · MAY 2026
40 press mentions.
1 AI citation.
A Mumbai-based performance sneaker brand. DA 42. Featured in Mint and Economic Times. A blog ranking for 200 keywords. Rs 25–40 Cr revenue. When customers asked any AI engine about Indian sneakers — this brand appeared in exactly 1 of 20 buyer prompts. A competitor with weaker SEO owned the other 12.
Status on Day 1
- Domain Authority
- DA 42
- Press mentions
- 40+ (Mint, ET)
- Keywords ranked
- 200+
- Revenue
- Rs 25–40 Cr
- AI citations — Day 1
- 1 / 20 prompts
- Competitor AI presence
- 12 / 20 prompts
“We had DA 42. Backlinks from Mint and Economic Times. A blog ranking for 200 keywords. Big Head tested 20 buyer prompts across four AI engines. We appeared in one. One. That number changes how you think about marketing.”
↳ Signed the 3-month retainer immediately. Month 2 target: displace the top 3 competitor-owned prompts.
The 3-month arc
From 1 citation to near-total category coverage.
Month 1 · Foundation
9 of 20
prompts returning the brand — up from 1
- 20 buyer prompts benchmarked × 4 engines
- 3 competitors scored at prompt level
- Schema corrected, sitemap submitted
- Perplexity: 5 new citations in first 30 days
Month 2 · Displacement
15 of 20
prompts returning the brand — 9 competitor prompts reclaimed
- ChatGPT citations arrive as sitemap processes
- Reddit & sneaker community seeding begins
- Brand Memory feeds ShopOS performance squad
- 9 of 12 competitor prompts displaced
Month 3 · Authority
19 of 20
prompts returning the brand — 1 gap left for Month 4
- 3 niche sneaker authority citations earned
- Perplexity: brand T1 on 10 of 20 prompts
- Prompt gap narrowed: 87 → 52
- GEO intelligence feeds PDP + email copy
Google rewards backlinks from high-DA publications. AI engines do not. They reward structured, specific, on-domain content that directly answers buyer questions. A Mint backlink doesn't tell an AI engine which sneaker is best for Indian roads in summer — a 900-word GEO article does. That's the gap this brand closed, and closing it early means the competitor now faces the same mountain they once owned.
From 1 citation to near-total coverage. 90 days.
19 / 20
Active AI citations
Brand named with URL. Was 1 on Day 1.
72
Articles published
28 + 22 + 18 articles + 4 comparison guides. All on the owned domain.
12 / 12
Competitor prompts reclaimed
All 12 competitor-owned prompts from Day 1 now include this brand at T1 or T2.
87 → 52
Prompt gaps remaining
Down from 87 on Day 1. Each one is a future citation.
Citations by engine · cumulative · out of 20 prompts
Perplexity · fastest
Indexes new content within 48–72 hrs. Responded fastest every month. Dominant by Month 3.
0 → 16 / 20
Claude
GEO article structure aligns directly with how Claude formats cited answers.
1 → 13 / 20
Gemini
Absent Day 1. Structured-data corrections in Month 1 activated Google's crawler advantage.
0 → 11 / 20
ChatGPT
Sitemap submitted in Month 1 compounded in Months 2–3 — the slowest engine, the strongest finisher.
0 → 9 / 20
Selected prompt shifts · Day 1 vs Month 3
T1 — brand named first, own URL cited · T2 — brand named / earned media · ABSENT — brand does not appear
| Buyer prompt | Day 1 | Month 3 |
|---|---|---|
| Best Indian performance sneakers for everyday wear | Brand absent. Competitor T1. | Brand T1. Competitor T2. Fully reversed. |
| Running shoes under Rs 5000 India 2026 | Brand absent. Competitor T1. | Brand T1. Competitor no longer appears. |
| Lightweight sneakers for Indian summer humidity | Brand absent. Competitor T1. | Brand T1 on 3 of 4 engines. Competitor displaced. |
| Indian sneakers vs global brands — durability | Neither brand present. Open gap. | Brand named + URL cited T1. Owned from scratch. |
| Best sneakers for flat feet India 2026 | Neither brand present. Open gap. | Brand T1 on Perplexity + Claude. New territory. |
| Canvas vs mesh upper for Indian conditions | Brand absent. Competitor T1. | Brand T2. Competitor still T1. → Month 4 target. |
How E-E-A-T signals directly raise AI visibility
Experience
Technical depth AI can verify against real data
AI engines cross-reference product claims against catalogue data, review aggregators, and e-commerce crawls. Content specifying sole composition, outsole terrain ratings, and humidity performance scores higher on retrieval relevance than generic “best sneakers” copy. This brand's product specs are a competitive data moat no generic content site can replicate.
Expertise
Depth that earns Reddit + Wikipedia presence
Genuinely expert content gets referenced outside owned channels — sneaker subreddits, Wikipedia's Indian footwear pages, running community forums. These third-party citations are exactly what Perplexity and Claude pull when answering product queries. Each Reddit thread and Wikipedia entry in Month 2–3 added a new retrieval pathway no competitor had built.
Authoritativeness
Domain signals that gate AI retrieval entirely
AI engines evaluate the source. A domain with press backlinks (Mint, ET), consistent publishing, structured data, and Wikipedia citations signals high authority. This brand had the press authority but lacked the on-domain GEO content to activate it — Months 1–3 built the missing layer, and the press backlinks started working.
Trustworthiness
Factual accuracy AI penalises when violated
AI engines validate cited claims against price aggregators, reviews, and e-commerce crawls. Content contradicting the live store is downgraded. 72 articles, zero contradictions — the clean trust signal held throughout, which is why Month 2–3 gains didn't reverse as new articles went live.
How we measured this
- What we tested
- 20 buyer prompts from real search-volume data for performance and lifestyle sneakers in India (e.g. “best Indian running shoes for flat feet,” “sneakers that last on Indian roads”), tested on ChatGPT, Claude, Perplexity, and Gemini (standard public versions). 20 prompts × 4 engines = 80 tests per measurement, run at Day 1, 30, 60, and 90.
- What counts as a citation
- Brand named in the answer text, with or without a URL. URL-only appearances are tracked separately as partial. The 19/20 Month 3 figure counts only named brand citations.
- Content published
- 72 on-domain pieces (28 + 22 + 18 articles + 4 comparison guides) plus 50+ Reddit touchpoints and 3 Wikipedia entries across 3 months. Wikipedia and Reddit are cited directly by Perplexity and Claude in a significant share of product category answers.
- Engine vs prompt totals
- Engine-level totals (Perplexity 16, Claude 13, Gemini 11, ChatGPT 9 = 49) exceed the 19-prompt headline because one prompt can be cited by multiple engines — about 2.45 engines per cited prompt.
In AI search, early is the only moat that compounds.
The Indian sneaker category is being indexed by AI engines right now. The brands building citation signals today will be treated as the default authorities in 12–18 months. For the next 6–12 months, the market is still catchable. After that, it won't be.
Start your GEO pilotAudit across all 4 AI engines. Results in 48 hours. Brand details anonymised at client request.