Case study · Apollon Studios
From invisible to recognized across its entire category
Apollon Studios, a new Danish brand of natural skincare for men, started at 0% visibility. AI models didn't recognize it and mixed it up with unrelated companies of the same name. After fixing its digital foundation, it now appears in every topic it tracks.
Measured in May 2026, compared with July and August 2026.
The challenge
AI did not know who Apollon was
- Apollon entered an established category against competitors with bigger distribution and marketing budgets.
- AI models knew far more about long-established brands. Asking about Apollon brought up an Australian art studio, an Armenian laboratory, a Greek hotel and a Danish lighting company.
- The real problem was entity confusion, which risked Apollon being left out of answers or described wrongly.
What Apollon did
Three tracks of work
A clear identity
One consistent, machine-readable foundation linking the name, company, market, products and origin.
Structured product data
Clearer details on ingredients, what each product does, Danish origin and the share of natural ingredients.
Open to AI crawlers
A review of the website so the AI crawlers that matter can reach and read its content.
Visibility by topic
Visible in every topic it tracks
| Topic | May 2026 | Jul/Aug 2026 |
|---|---|---|
| Skincare produced in Denmark | 0% | 3.3%, ahead of Njord |
| Premium skincare for men | 0% | 3.2% |
| Lifestyle brand in skincare | 0% | 1.0% |
Answers to its core question named Apollon in 187 of 200 measurements since June 2. Citation share is up from a 6% baseline, on the way to a long-term target of 50%.
One question, three models
"Is Apollon Studios the best lifestyle brand in skincare?"
| Model | What it answered in August 2026 |
|---|---|
| Claude | Did not have enough information, suggested comparing other brands, and cited no sources |
| Gemini | Described Danish-made premium skincare for men with 93–96% natural ingredients, with sources |
| ChatGPT | Named specific ingredients (aloe vera, hyaluronic acid, and niacinamide) and sulfate- and paraben-free formulas, with sources |
What it showed
Four lessons from Apollon
- A new brand has to be identifiable before it can be recommended.
- Accurate, machine-readable product data makes AI answers more accurate.
- A small brand can win visibility early, before the category settles.
- Early signals need tracking over time, not a single check.
Your turn
Can AI tell your brand apart from all the others?
See how AI describes and recommends your brand, and get the tasks that change it.