You have a better product, but AI recommends the competition. Why?

No. The examples will be set in the context of window joinery and construction systems, but the topic broadly concerns manufacturers of solutions whose selection is based on comparing parameters, technologies, applications, and product advantages. The webinar will therefore also be valuable for manufacturers of gates, blinds, profiles, automation, assembly systems, and other solutions used in construction. The key question is common: can AI properly understand the advantages of your product and use them when the customer compares available solutions?

ChatGPT is just one of the places where customers can ask about products, technologies, and manufacturers today. During the webinar, we will talk more broadly about large language models and AI-generated responses. This is important because the answer to a similar question may vary depending on the model, the way the question is asked, the type of investment, the parameters expected by the customer, or the stage of the purchasing process. Therefore, a single test conducted in one tool does not yet provide a reliable picture of the situation.

Yes. The webinar will not be a general presentation on artificial intelligence. The starting point will be situations where AI compares manufacturers and solutions and uses criteria such as technical parameters, safety, certifications, durability, design, automation, quality of execution, or method of installation. We will show not only which brands appear in the response but, more importantly, what arguments AI attributes to individual manufacturers and whether they actually correspond to what companies build their advantage on.

Yes. In this industry, the purchasing decision often does not belong to one person. Different information may be sought by the investor, architect, contractor, business partner, or person responsible for purchasing. AI may appear at various stages of such a process as a source of information, a tool for comparing solutions, or the first 'advisor' suggesting brands worth further investigation. Therefore, it is important not only whether AI knows the manufacturer but also what it associates it with and when it considers its solution appropriate.

In the case of well-known brands, the problem can be particularly interesting. Simply knowing the name does not mean that AI correctly understands the advantages of the product. The model may mention a well-known brand but simultaneously reduce it to very general features, overlook important technologies, or attribute stronger arguments to the competition. From a business perspective, therefore, not only the presence of the brand matters but also the justification for its choice.

This is one of the main topics of the webinar. The advantage existing in the product does not automatically become an advantage in AI responses. If information about technology, parameters, certifications, or applications is poorly described, scattered, ambiguous, or insufficiently present in the sources used by the models, AI may not utilize them when formulating recommendations. During the webinar, we will show how to recognize such discrepancies and how to think about them as a business problem, not just a technological one.

The goal is not to prepare a ready-made audit of a specific company but to show a way of thinking that allows you to identify areas requiring further work. This may include descriptions of systems, product sheets, technical parameters, information about applications, certifications, guides, commercial communication, materials for partners, or how to present advantages on the manufacturer's website. The webinar aims to help answer the question: 'which information is truly important for our advantage and can AI read it?'

No. The topic is technology, but the perspective remains business-oriented. Those who will benefit the most are individuals responsible for marketing, communication, product, sales, and brand management. We will primarily discuss what AI tells a potential customer, how it presents manufacturers' advantages, and what consequences this may have for the selection process. No programming knowledge or technical understanding of how language models work will be required.

The webinar is led by Michał Grzebyk, Chief Operating Officer and co-founder of Brand Semantics, involved in marketing since 2009. He combines experience in marketing, semantics, SEO, communication, and strategic planning with practical use of language models in business. He is a strategist and trainer, and during the webinar, he will focus not on the technology itself but on its implications for marketing, product, and sales. An additional argument is Brand Semantics' experience working for the sector. Among the company's clients and partners, Hörmann Polska is mentioned.

During the substantive part, we will focus on previously prepared examples to show the entire analysis process step by step. However, a separate Q&A session is planned after the presentation. If you have a question regarding your own brand, a specific product category, or a situation you observe in AI responses, you can raise it then. We cannot guarantee a full analysis of each company submitted during the meeting, but we will try to answer as many questions as possible.

Registration gives you access to the online webinar and a Q&A session with the host. After the event, you will also receive a recording, so you can return to the presented examples and conclusions during discussions with your own team. The entire session will take about 45 minutes: 35 minutes of substantive content and about 10 minutes allocated for participant questions. The webinar will take place online on the ClickMeeting platform.

Yes. The recording will be sent after the event, so registration makes sense even if the timing conflicts with a meeting, trip, or obligations at work. Live participation primarily offers the additional opportunity to ask your own question to the host.

The webinar is primarily educational in nature. Its main goal is to show how AI interprets manufacturers' advantages and how to distinguish a random model response from information that may be significant for marketing and sales. We will also show how to analyse this area more systematically. If after the webinar you want to check your brand's situation more broadly or discuss collaboration with Brand Semantics, there will, of course, be an opportunity, but this is not a condition for participation.

After 45 minutes, you should primarily look at the question 'is our brand visible in AI?' differently. Instead of limiting yourself to checking whether the company name appeared in ChatGPT, you will know that you need to analyse the context, argumentation, attributed advantages, the position of the competition, and the stage of the purchasing process. This will make it easier for you to assess whether it is worth changing content, product data, or the way advantages are communicated, rather than starting actions just because 'something needs to be done about AI.'