How to discover the prompts that make your brand visible: Omnia's Topic Explorer
Sep 12, 2025
By Daniel Espejo, Founder & CEO at Omnia. 12th of September 2025
En este artículo:
Why it is essential to know which prompts users employ (and which ones you should be present in).
The difficulty of identifying relevant prompts without a tool.
How AI patterns work to decide which brands appear.
What Topic Explorer is and why it is different from any other solution.
Practical example of use: from prompts to actual positioning.
Conclusion: how to get ahead and gain visibility in the era of generative AI.
1. The importance of knowing the prompts that matter
Digital marketing is experiencing a major shift. For years, the goal was clear: get your website to show up at the top of Google search results. Today, it's a whole different game. Generative AI engines like ChatGPT, Gemini, and Perplexity don't show traditional links anymore, but direct answers to user prompts.
This means that your brand no longer competes only on Google's results page. It competes within AI-generated responses, where only a few brands are mentioned. The key question marketing teams must ask themselves is no longer ‘which keyword should I target?’, but rather: ‘what prompts do users formulate and how do I get my brand to appear in those responses?’
Understanding relevant prompts is vital. They are the new gateway for a potential customer to discover your product, compare options, or make purchasing decisions. But there is a problem: identifying those prompts is not easy.
2. The challenge: thousands of prompts, changing every day
Unlike traditional keywords, the prompts that trigger responses in AI are neither standardised nor static. Thousands of new variations emerge every day: long, complex, contextual questions influenced by trends, news or even local language.
For instance, a user could ask ChatGPT:
‘I'm looking for project management software that is easy to use for small teams but also has AI integration to automate tasks. What options do you recommend?’
‘Which cosmetic brands have official sustainability certifications and are also recommended in specialist forums?’
‘If I want to buy a laptop for 4K video editing for less than €1,500, which brands are the most reliable according to experts and users?’
2.1 Types of intention
Decision: comparisons and shortlist (‘between X and Y for use Z...’).
Discovery: initial options (‘what do the experts recommend for...?’).
Problem/Troubleshooting: specific barriers (‘for very sensitive skin...’, ‘for travelling with children...’).
Adoption/Implementation: integration requirements, compliance, SLAs.
All these variations represent opportunities for visibility... or risks of invisibility if your brand does not appear in them.
The complexity lies in the fact that these prompts are constantly changing. There is no fixed list of ‘the 10 questions in the sector’. The dynamics are much more volatile and require a system capable of monitoring and prioritising on a daily basis.
This is where Omnia's proposal comes into play.
3. Understanding the patterns followed by AI to provide visibility
To understand how to gain visibility on AI engines, you first need to understand how they work. LLMs do not select brands at random: they follow specific patterns that define what appears in their responses. Among these patterns, the following stand out:
Trusted sources: established media outlets, specialised forums, academic publications, YouTube channels with authority in the industry, etc.
Frequency of mentions: brands that are mentioned most often in different contexts are more likely to appear in relevant prompts.
Thematic context: it is not enough to be mentioned; what matters is the context in which you are mentioned (are you the recommended option, or are you simply listed alongside competitors?).
From prompt to response (mind map): User prompt → AI engine → Sources consulted (media, forums, videos, wikis) → Co-occurrence of entities → Synthesis → Response (with or without citations) → Brand mentions.
The challenge for marketing teams is double: not only must they understand what the key prompts are, but also what patterns make a brand visible in them. That's where tools like Omnia's Topic Explorer make a difference.
4. Topic Explorer: simple, powerful and unique
Omnia's Topic Explorer was created to solve precisely this challenge: discovering which prompts matter, how to prioritise them, and how to use them to gain visibility.
How does it work?
Inputs
Brand name/domain
Market/language
Outputs
Automatic list of prompts related to your product/sector.
Monthly volume per prompt.
Difficulty estimated by competitive density and influential sources.
Step by step
Generate an automatic list of prompts for your brand.
Prioritise using a Volume × Difficulty matrix (quick wins vs big bets).
Follow 10–20 strategic prompts (by intent/funnel stage).
Analyse competitors and sources for each prompt.
Activate content, PR, partnerships and presence in aligned forums/KOLs.
Measure SoV in AI and 30/60/90-day trend per prompt.
Why is it different?
Most tools on the market are still based on classic keyword research logic. Topic Explorer, on the other hand, focuses on the actual logic of LLMs. Furthermore:
It is extremely simple: anyone, even without technical SEO experience, can use and understand it.
It is designed for daily action: you can see which prompts are relevant each day and adapt your strategy in real time.
It gives you a clear view of visibility patterns: you understand not only where you appear, but why and in front of whom.
5. Simple practical example of use
Let's imagine a cosmetics brand that wants to position itself in the field of sustainability. The marketing team suspects that users are asking about ‘vegan cosmetics’ or ‘sustainable makeup,’ but they don't know exactly which questions are gaining the most traction.This is especially true because the questions users ask these engines are not as open-ended and generic as when you ask Google. When a user asks about a product, the prompts are more specific. Example: “I want a natural product to remove spots from my face, I have very sensitive skin”.
With Omnia's Topic Explorer, this brand could:
Discover real prompts: the tool shows that ‘best vegan makeup for sensitive skin’ has a high monthly volume and medium difficulty.
Prioritise opportunities: another prompt, ‘recommend me 2 sustainable cosmetic products for sensitive skin’, appears with low volume but low difficulty, ideal for quick positioning.
Monitor progress: the brand begins to follow both prompts to analyse its daily visibility, understand which competitors appear and in what context.
Act strategically: with this data, adjust your content strategy, work on external mentions, and get LLMs to start including you in their responses.
The result is clear: the brand moves from intuition (‘perhaps they are looking for us because of sustainable make-up’) to certainty (‘we know that users are asking this, with this volume, and that we now appear in those answers’).
6. Conclusion: from intuition to data
Traditional SEO taught us to optimise keywords. The era of generative AI forces us to optimise prompts. The difference is huge: it is no longer about competing for positions on a Google page, but about entering the conversation of LLMs, at the moment when users ask their questions.
The challenge is enormous: thousands of prompts, constantly changing, with new and unclear visibility patterns. But it is also a great opportunity: brands that know how to detect them, prioritise them and position themselves in them will have a competitive advantage that is difficult to match.
Omnia's Topic Explorer turns that complexity into a simple, accessible, and actionable process. It allows you to:
Discover which prompts matter in your industry.
Monitor them daily to understand patterns and competition.
Strategically choose where to invest your visibility efforts.
Visibility in AI is not a matter of luck. It's a matter of data, decisions and focus.