How I got my brand cited by ChatGPT in 30 days
June 16, 2026 · SeenByLLM Team · #case-study, #chatgpt, #optimization
A step-by-step case study on improving AI visibility from zero mentions to consistent citations across ChatGPT, Perplexity, and Gemini in one month.
This is the playbook we used to take a brand from zero AI mentions to consistent citations across multiple assistants in 30 days. The brand sells premium skincare products on Shopify. Before we started, not a single AI assistant mentioned their products.
The starting point (Day 0)
We ran a baseline audit across 8 AI assistants using 15 buyer prompts relevant to their product category:
| Assistant | Brand mentioned | Products named | Details correct |
|---|---|---|---|
| ChatGPT | 0/15 | 0 | - |
| Gemini | 0/15 | 0 | - |
| Perplexity | 0/15 | 0 | - |
| Claude | 0/15 | 0 | - |
| Copilot | 0/15 | 0 | - |
| DeepSeek | 0/15 | 0 | - |
| Total | 0/90 | 0 | 0% |
Zero. The AI assistants did not know this brand existed.
Week 1: Fix the data foundation
What we did
- Audited every product page. Found that 60% of products lacked text-based specifications — specs were only in images or PDFs.
- Added structured data. Implemented
Productschema on every product page with name, price, description, availability, and review ratings. - Created FAQ sections. Added 5-8 FAQ entries per product page in conversational language matching how real shoppers ask questions.
- Fixed inconsistencies. Product names varied between the site, Amazon listing, and social media. Standardized everything.
Effort: ~20 hours (product manager + developer)
Results at Day 7
| Assistant | Brand mentioned | Products named |
|---|---|---|
| ChatGPT | 0/15 | 0 |
| Gemini | 1/15 | 0 |
| Perplexity | 0/15 | 0 |
| Others | 0/45 | 0 |
One mention on Gemini. Barely anything. But the data foundation was in place.
Week 2: Build third-party presence
What we did
- Submitted to review sites. Sent products to 5 beauty review bloggers and submitted to 3 review aggregators.
- Posted on Reddit and forums. Answered category questions on r/SkincareScience and 2 niche forums — genuinely helpful answers, not spam.
- Published a comparison guide. Wrote "Premium vs Budget Moisturizers: What Actually Works" on the brand blog.
- Updated Google Business Profile. Added products, categories, and descriptions.
Effort: ~15 hours (content writer + outreach)
Results at Day 14
| Assistant | Brand mentioned | Products named | Details correct |
|---|---|---|---|
| ChatGPT | 2/15 | 1 | 50% |
| Gemini | 3/15 | 2 | 67% |
| Perplexity | 4/15 | 3 | 75% |
| Claude | 1/15 | 0 | - |
| Others | 1/45 | 0 | - |
| Total | 11/90 | 6 | ~60% |
Progress. Perplexity was picking up the review citations. ChatGPT and Gemini starting to notice. But accuracy was still low.
Week 3: Fix accuracy and expand reach
What we did
- Corrected stale data. Found 3 review sites listing wrong prices. Contacted them with updates.
- Expanded FAQ content. Added category-level FAQ pages ("Best moisturizers for sensitive skin") with detailed, data-backed answers.
- Created competitor comparison pages. "Brand X vs [Competitor Y]" pages that framed the positioning correctly.
- Published on Medium and LinkedIn. Two thought leadership articles on skincare formulation, citing the brand's products.
Effort: ~10 hours (content + outreach)
Results at Day 21
| Assistant | Brand mentioned | Products named | Details correct |
|---|---|---|---|
| ChatGPT | 5/15 | 4 | 75% |
| Gemini | 6/15 | 5 | 80% |
| Perplexity | 8/15 | 7 | 85% |
| Claude | 3/15 | 2 | 67% |
| Copilot | 2/15 | 1 | 50% |
| Others | 2/30 | 1 | 50% |
| Total | 26/90 | 20 | ~75% |
Significant jump. Perplexity was citing them in over half the prompts. Accuracy improving as correct data propagated.
Week 4: Consolidate and monitor
What we did
- Monitored for regressions. Checked daily for any accuracy drops or new competitive threats.
- Optimized top-performing products. For the 3 products getting the most AI mentions, doubled down on FAQ content and third-party reviews.
- Addressed competitive framing. One competitor was consistently described as "premium" while our brand was "mid-range." Updated positioning language across all owned channels.
Effort: ~8 hours (ongoing monitoring)
Results at Day 30
| Assistant | Brand mentioned | Products named | Details correct |
|---|---|---|---|
| ChatGPT | 8/15 | 7 | 86% |
| Gemini | 9/15 | 8 | 88% |
| Perplexity | 11/15 | 10 | 90% |
| Claude | 5/15 | 4 | 75% |
| Copilot | 4/15 | 3 | 67% |
| DeepSeek | 3/15 | 2 | 67% |
| Total | 40/90 | 34 | ~82% |
From zero to being mentioned in 44% of relevant AI prompts, with 82% accuracy, in 30 days.
What worked (and what did not)
High impact
- Adding Product schema markup (foundation)
- Third-party reviews on authoritative sites (credibility)
- FAQ content in natural language (answerability)
- Consistent data across all platforms (trust)
Medium impact
- Blog comparison content
- Reddit and forum participation
- Google Business Profile updates
Low impact
- Social media posts (AI assistants do not weight these heavily)
- Press releases (unless picked up by authoritative outlets)
- Generic "about us" content
Key takeaway
The brands that show up in AI answers are the ones with clean data, third-party credibility, and FAQ content that matches how real people ask questions. None of this requires a big budget or a specialized team. It requires consistent execution over 30 days.
Want to track your own 30-day AI visibility journey? Start a free SeenByLLM trial and get your baseline today.
Also read: What is AI Visibility? and How to Optimize for ChatGPT and Perplexity.