A graphic design studio in AI chatbots: the Click Made case, May 2026

Below, we describe the first measurement clickmade.pl, a one-person graphic design and web studio based in Bielsko-Biała, and a plan for the first 90 days. This is the start of a series: subsequent measurements will show what has changed and why. The studio is run by Karolina Wcisło, co-founder of Aelo, so we measure this brand in the same way as our clients’ brands, whilst also knowing exactly what was implemented and when.

What is Click Made, and why are we measuring this particular brand?

Because it’s a typical small service company with a good website, which customers are increasingly searching for via AI chatbots. Click Made designs WordPress websites, brand identities, e-books, presentations and print materials. It works remotely with clients from all over Poland, and locally in Bielsko-Biała. The website features an extensive blog, a portfolio and service descriptions – in other words, everything that, according to traditional SEO, should be sufficient.

That is exactly why it is a good case to measure. If a website like this does not translate into presence in AI answers, the problem lies somewhere other than the amount of content. How we measure brand presence in answers is described in the guide Brand visibility in AI and on the page Methodology.

What did the first measurement show?

A score of zero across every dimension. Brand visibility in the responses was 0%, and citation rate also 0%. In this measurement we checked three models: Claude, ChatGPT and Gemini. None of them mentioned Click Made when answering the questions customers ask when looking for a graphic designer or a website developer. There was not a single mention of the brand, nor a single citation of the clickmade.pl website as a source.

The result was the same for every type of question: local ones, questions about specific services and questions about print materials. There was no topic in which the brand did better, and none in which it did worse. That is an important clue. If the problem concerned one service, improving one subpage would be enough. Since everything was at zero, the cause was shared by the whole brand.

We ask questions without mentioning any brand names, just as a customer who hasn’t yet decided which one to choose would do. We describe this principle in the entry neutral scan, and the questions on which the measurement is based, in the entry keywords.

Why does the AI recognise the brand but not mention it?

Because recognition and recommendation are two different thresholds. When we asked about Click Made by name, all four AI engines knew what the studio was. Only one recommended it. In buying questions, without the brand name, no model mentioned it. A model can know about a company and still decide there are not enough reasons to recommend it to a stranger. We describe this mechanism in the article Knows the brand, but doesn’t recommend it and in the entry recognition and recommendation.

The report also highlighted the main barrier. What the models saw about the brand were mainly business directories, its Google profile and customer reviews. Independent rankings, media comparisons and industry publications were missing, in other words the sources that confirm quality from the outside. A company that only its own website and a few directories talk about is still an uncertain choice for a model.

Who did AI mention instead of Click Made?

Other graphic design and web studios from various cities, and websites where customers look for contractors through listings. The most frequently mentioned business appeared in 18% of the questions examined, the next ones in 15% and 12%. Nobody had a lead that shut others out. AI answers in this category were scattered, which means a new brand has a real chance of getting into them.

The report pointed out one more thing: the models were keen to cite websites with organised lists of contractors and offers. A page like that is easy to turn into an answer such as “here are five companies that do this”. A single studio website, even a good one, needs confirmation from elsewhere. More on this in the article Why does AI recommend the competition?. We measure each brand’s share of answers with the metric share of voice.

What has Aelo planned for the first 90 days?

Work in three areas: off-page sources, on-page organisation, and content that addresses customers’ concerns. The plan was drawn up in the module Tasks as a list of specific tasks, each describing what to expect from it.

On the website: structured data describing the local business, the person and the services, plus a Q&A section. Off-site: a Google Business Profile, portfolio profiles and directory listings that the models were already citing in this category. In the content: answers to the most common concerns of small studios’ clients, i.e. who will look after the website after launch and what to do if the contractor stops replying. In our glossary we call such concerns pain points.

The report also suggested a niche in which the brand can win: a one-person studio working remotely, with technical support after launch. Neither large agencies nor listing websites occupy this position. How to describe such an advantage so that a model understands it is explained in the entries brand positioning and USP.

What do we expect, and what are we not promising?

The first changes within 60–90 days, but with no guarantee. The report pointed out that the lack of an established brand image in the models is also an opportunity: the first signals can quickly move the result off zero. At the same time, models update their knowledge at different speeds, and some of them only use web search for certain questions. Why this is so is described in the article Why do changes take time?.

We will run the next measurement after a month. How often to measure so that the result means something is described in the article How often should visibility be measured?.

What does the first measurement tell us?

• A good website isn’t enough. Click Made had a blog, a portfolio and descriptions of its services, yet the result was still zero.
• Recognition is not a recommendation. A model that knows the brand does not have to mention it in its answer.
• A flat zero across all questions is good diagnostic news: there is one cause, shared by the whole brand.
• Scattered competition means a place in the answers can be won.

How can you find out where your brand stands?

Just as we did for Click Made: with a set of questions without the brand name, put to several models. In Aelo, the measurement is done by the module Visibility in AI, the work plan is drawn up in Tasks, and what Aelo knows about the brand you can check in Brand Knowledge. We describe the manual method in the article How to find out what AI is saying about your business.

Small businesses will find more on the page Aelo for small businesses, personal brands on the page Aelo for personal brands, and agencies that measure their clients, on the page Aelo for agencies. You can take your first measurement on the Free account, without a card.

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Sources

• Aelo, visibility reports
• Aelo, a methodology for measuring visibility in AI: https://aeloapp.io/wiedza/metodologia/