More and more people ask ChatGPT, Gemini or Claude before choosing a supplier. Some brands show up in those answers and others don’t, and the reason has more to do with data than with luck.
The use of conversational AI tools
The shift in behavior is already visible in the numbers. ChatGPT has more than 900 million weekly users, and Google’s AI Mode has passed one billion monthly users. When an AI summary appears above the results, people click less, and 35% of consumers already discover products through AI, compared with 13.6% who still start with a traditional search engine. For companies that measure marketing by traffic, this shows up as a decline that often has little to do with how well the team is performing.
How does the language model work?
A language model builds its answer from two sources. The first is what it learned during training, a huge volume of text from which it picks up which names are associated with which topics, and how often. The second, in systems connected to the internet, is a real-time search in which the model retrieves a handful of pages it considers relevant and reliable and builds the answer from them. In both cases, a brand that appears many times, across different sources and in contexts consistent with its category, is more likely to be mentioned. Articles in well-known media outlets meet exactly those conditions.
Findability strategy
The available data points the same way. Brand mentions correlate with AI visibility about three times more than backlinks do. Distributing content across several publications increases citations by up to 325% compared with publishing only on a company’s own site, and including statistics raises the likelihood of being cited by 41%. ChatGPT also names brands 3.2 times more often than it links to them. All of these findings follow the same logic. The more independent sources connect a brand to a topic, the stronger the signal the model receives.
What should your company do?
For a company, the work falls into two areas. One is producing its own data, such as studies, surveys or industry indicators, because that is the kind of content media outlets publish and models cite most easily. The other is getting that content into outlets with authority in each market, instead of leaving it on the corporate blog. At LatAm Intersect, a leading communications agency LATAM, we combine data and AI analysis with direct relationships with the key media in each country, a model that positions us as a top PR agency in Latin America. On top of that comes a technical layer on the company’s website, with FAQs, schema markup and open access for AI crawlers, which helps content get found and understood.
