From Zero AI Visibility to the Top Five in One Quarter
How Boë Beauté reached 22.2% AI visibility and began shaping the customer journey without hiring a specialist
From Zero AI Visibility to the Top Five in One Quarter
How Boë Beauté reached 22.2% AI visibility and began shaping the customer journey without hiring a specialist
The challenge: customers were moving to AI, but Boë Beauté was absent from the journey
The way consumers discover products is changing faster than most brands can measure.
The traditional user journey began with a Google search and an analysis of 20 blue links. The AI-native journey is fundamentally different. Consumers now ask ChatGPT everyday questions about their needs and receive a synthesised answer telling them:
What their problem is
Which type of solution they need
Which products match their situation
Which brands they should trust
What they should ultimately choose
In this journey, being indexed is not enough. A brand must first be understood, then trusted and ultimately recommended by AI before the consumer ever reaches its website.
For Boë Beauté, a Danish biotech skincare brand specialising in self-tanning products for sensitive skin, that journey initially took place entirely without them.
Across thousands of prompt executions covering relevant markets, languages and consumer needs, Boë Beauté was found zero times.
Not occasionally. Not at a low rank. Zero times.
Meanwhile, larger competitors were accumulating visibility, authority and influence across the category. They had years of external coverage, extensive content libraries and significantly larger marketing operations.
Boë Beauté had to build the signals required to compete with a fraction of those resources.
The real problem: you cannot improve what you cannot see
Brands can see declining organic traffic. They can see competitors gaining ground. What they usually cannot see is the AI journey increasingly taking place before a consumer reaches their website.
They do not know how AI interprets their brand, which competitors it recommends, which sources influence its answers or why their company is excluded.
The first challenge was therefore not content production. It was visibility into the decision environment.
3RD enabled Boë Beauté to see how the brand and its wider category were represented across AI-generated customer journeys. More importantly, the platform reconstructed why the market performed as it did:
How AI understood Boë Beauté and its competitors
Which brands were trusted and recommended
Which sources shaped the category narrative
Where Boë Beauté disappeared from the customer journey
Which commercial opportunities were being lost
What measurable improvement would look like
Unlike tools that simply monitor whether a brand is mentioned, 3RD created the data foundation for deciding where Boë Beauté needed to compete, why specific interventions mattered and how they should be executed.
The objective was not simply to create more content. It was to determine which interventions could produce the greatest measurable commercial improvement with the resources available.
The starting point
Boë Beauté entered the project with:
0.0% visibility across a wide range of relevant consumer questions, markets and languages
Zero recognition of Boë Beauté as a distinct entity
No effective external signals supporting AI recommendations within its line of business
Existing third-party mentions that were not being selected as sources in relevant industry answers
No internal GEO or SEO specialist to lead the work
The brand did not lack a good product or satisfied customers. It lacked a measurable position within the AI-native customer journey.
The strategy: start where the commercial signals are strongest
Based on platform data, commercial potential, Boë Beauté’s ideal customer profile and the emerging AI-native journey, 3RD advised a US-first challenger strategy.
The project was designed around a simple strategic principle: do not spread limited resources evenly across every market and opportunity. Concentrate them where commercial demand, brand differentiation and AI adoption create the strongest possibility of winning.
The US market offered an attractive combination:
High commercial potential within self-tanning and sensitive skincare
Strong alignment with Boë Beauté’s customer profile
An AI-native discovery journey increasingly led by ChatGPT
An opportunity to establish authority before expanding more broadly
Google AI Overviews remained an important indicator of how search was changing. However, the primary ambition was larger: to build Boë Beauté’s position across the full-funnel, AI-native customer journey of 2026.
3RD combined platform intelligence with end-to-end advisory to answer four questions:
Which improvements were relevant?
Which should be prioritised first?
Why would they matter?
How should Boë Beauté execute them?
The result was not another dashboard of opportunities. It was a curated, data-informed execution layer built around the company’s brand, commercial objectives and available resources.
The execution: building authority in the right sequence
1. Creating a foundation AI could understand
Before Boë Beauté could become a trusted recommendation, AI systems needed to recognise it consistently as a distinct company and brand.
The initial work focused on strengthening its entity foundation through structured, verifiable company and category information. This included establishing and enriching its Wikidata presence and improving consistency across the wider digital footprint.
The objective was not visibility for visibility’s sake. It was to reduce ambiguity about who Boë Beauté was, what it offered and which consumer needs it could credibly address.
2. Making the brand’s knowledge accessible
The platform identified content that was not being discovered, interpreted or cited as intended.
Technical work focused on readability, structured data, information architecture and crawl accessibility. These were not generic website improvements. Each task was connected to an observed failure in how AI systems accessed or understood the site.
The trail was measurable:
Pages that were not being found began appearing.
Content that was not being cited became a selected source.
Distinct sentences from Boë Beauté’s content began appearing in citations and answers.
This allowed the team to evaluate individual interventions through observable changes rather than assumptions.
3. Winning questions with a credible right to win
Boë Beauté did not attempt to compete across the entire skincare market immediately.
Content and authority-building were concentrated on questions where the brand already had genuine differentiation, particularly the intersection of self-tanning and sensitive skin.
This created a stronger connection between:
The consumer’s expressed need
Boë Beauté’s product differentiation
The language used on owned channels
The external sources validating those claims
The recommendations generated by AI
Highly competitive comparison content was deprioritised until the brand had developed sufficient authority to compete credibly.
4. Turning external validation into category influence
Boë Beauté already appeared in some third-party content. But those mentions were not being selected as evidence when AI answered relevant category questions.
3RD identified the sources, topics and content structures that could influence the answers Boë Beauté needed to win. Outreach and content creation could therefore be focused on sources with a specific role in the AI customer journey.
The purpose was not simply to accumulate links or mentions. It was to create authoritative material that AI systems could use as evidence when deciding what consumers should believe and buy.
Specialist-level direction, executed without a specialist team
Boë Beauté did not hire a GEO specialist or establish a dedicated search department.
One single in-house marketeer with no previous specialist background in GEO or SEO executed the work for a limited number of hours each week alongside other responsibilities.
3RD provided:
Market and customer-journey intelligence
Category and competitor diagnosis
Commercial prioritisation
Task-level recommendations
Execution guidance
Continuous measurement of outcomes
This turned a technically complex discipline into a manageable operating model.
Boë Beauté did not need to become an expert in AI discovery. The company needed to understand which actions mattered and execute them consistently.
The result: from zero appearances to 22.2% visibility
Within one quarter, Boë Beauté moved from complete absence across thousands of prompt executions to a current weekly AI visibility level of 22.2%.
The brand also entered the top five among seven tracked competitors, moving ahead of established names such as Malin+Goetz and beginning to close the gap to CeraVe and La Roche-Posay.
These were not isolated brand mentions. Boë Beauté began appearing across relevant consumer questions at stronger average positions and with consistently positive representation.
Across 77 measured AI-generated mentions, sentiment was classified as 100% positive.
The progression was visible at each stage:
Pages that had not been discovered began appearing.
Boë Beauté’s content moved from uncited to cited.
Distinct brand language began informing generated answers.
Recommendations appeared across more consumer questions.
The brand’s average position improved.
Visibility developed into trust and recommendation.
The significance is not simply that AI began mentioning Boë Beauté. It is that the brand began earning a role in the answers influencing consumer decisions.
From appearing in answers to shaping them
More than 9,000 tracked source citations now connect Boë Beauté’s information and external authority to the AI answers shaping its category.
The number is not valuable merely because it is large. Its value lies in what the sources represent.
They indicate that Boë Beauté is no longer relying solely on its own website to make claims about the category. A growing ecosystem of owned and independent information is giving AI systems material from which to understand the market, validate recommendations and construct answers.
Boë Beauté is therefore moving beyond simply appearing as a product option. The brand is helping shape the information environment that determines:
How consumer needs are defined
Which product attributes matter
What trustworthy solutions look like
Which brands are considered credible
Which products are ultimately recommended
That is the strategic difference between being visible in an existing customer journey and helping form the journey itself.
Why this matters for challenger brands
Boë Beauté did not outspend its competitors. It made better-informed decisions about where to concentrate its limited resources.
The case demonstrates that challenger brands can gain ground in AI discovery when four elements work together:
A clear view of how AI represents the market
Commercial prioritisation based on real customer journeys
A curated sequence of technical, content and authority-building work
Continuous measurement connecting specific interventions to observable outcomes
The result is not a claim that one task alone caused a tenfold increase. It is a documented chain of evidence showing how targeted interventions changed discovery, citation, understanding, trust and recommendation over time.
The new competitive reality
When consumers use AI to understand their needs, compare solutions and select products, the commercial decision begins before they visit a brand’s website.
The brands included in that conversation gain visibility, authority and demand. Those excluded from it risk losing traffic and market position without being able to see where the journey moved.
Boë Beauté began with zero appearances across thousands of relevant AI interactions.
One quarter later, the brand had reached 22.2% visibility, entered the category’s top five and begun influencing the sources AI uses to guide consumers.
The opportunity for other challenger brands is still open.
But as AI systems accumulate stronger signals about which companies and sources they can trust, the advantage will increasingly belong to the brands that begin shaping those answers now.