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Wolfgang Digital is an equal opportunity employer committed to fostering an inclusive workplace
Millies is an Irish-owned beauty and skincare retailer competing against global multinationals for the attention of Irish beauty shoppers online. By combining AI Search optimisation with data-led citation analysis, Wolfgang helped Millies increase AI Search visibility by 34% and AI-attributed revenue by 119%, closing the gap with global beauty retailers dominating AI recommendations.
Winning on Google, sitting out the AI answer
The problem was a strange one. Millies had strong organic visibility on Google, built with us over a previous SEO campaign that grew organic revenue by 138%. That visibility was not carrying over to AI search.
Ask ChatGPT the same questions an Irish beauty shopper would type into Google, and Millies was not in the answer. The brands that came back instead were Boots and Lookfantastic, the same giants we had spent so long battling on Google’s SERP.
To see the scale of the problem, we tracked Millies in Scrunch AI, the tool we use at Wolfgang to measure our client’s AI search visibility. We upload a list of prompts to the tool - the real questions shoppers ask - and it shows how often each brand gets named in the answers that come back.
When tracking went live in mid January 2026, Lookfantastic was named in 26% of those answers and Boots in 25%. Millies sat on 13%, roughly half the multinationals' rate.
Ranking on Google and being recommended by AI are two different games, and Millies was winning one while sitting out the other.
The pressures behind it:
1. Give the machine the full story
AI rewards specificity. It recommends brands it understands, so we set out to give it as much context on Millies as possible: who they are, what they sell, and the USPs that separate them from the multinationals. If a machine was going to recommend Millies, it needed a reason to.
2. Make the context visible on site
Context is no good buried where nothing can be read. We made Millies’ differentiators clear and prominent on the site, in a form both shoppers and AI models could pick up.
3. Reverse-engineer the citations
Using Scrunch AI, we could see which Millies URLs the model had considered and chosen not to cite. We benchmarked those against the competitor URLs that were getting cited, worked out what the winning pages had that ours did not, and closed the gap.
4. Target the prompts that sell
Not every beauty question is a buying question. We concentrated effort on product recommendation and comparison prompts, where a mention converts, rather than chasing editorial advice queries owned by publishers.
Scrunch AI is the engine behind our AI Search work, and it is what made this measurable rather than guesswork.
It starts with the prompt set, the real questions Irish beauty shoppers ask an assistant, built from Millies' own search data rather than guessed at.
From there, it tracks visibility across the platforms that matter, but the real unlock was seeing the URLs the model considered and rejected.
That told us exactly where Millies was losing the citation, so every change we made was aimed at a gap we could actually see.
We increased Millies’ AI Search visibility by 34% and more than doubled AI-attributed revenue, helping the Irish beauty retailer close the gap with global giants like Boots and Lookfantastic.
AI Search Visibility
Monthly AI-Attributed Revenue
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