AI as a new entry point into the customer journey
In classic customer journey models, the process begins with a search query or a need for information that is served by search engines. In AI chats, this entry point is different. Users formulate complete questions, describe contexts or describe specific problems. The AI responds with a curated answer, often including recommendations or comparative statements. This shifts the focus from the mere findability of individual content to its presence within a generated response. Companies that are not considered at this stage often do not make it onto the shortlist at all.
From information gathering to pre-selection
AI models not only serve as a source of information, but also perform a pre-structuring function. They reduce complexity, prioritise options and establish connections. From the user's point of view, this means efficiency. From the company's point of view, it means that an external actor makes the pre-selection of relevant providers. This pre-selection is not random. AI systems draw on structured, consistent and trustworthy information. Brands whose content does not meet these criteria are mentioned less frequently or not at all, regardless of their actual market position.
Impact on purchasing decisions
The increasing use of AI chats influences purchasing decisions and has a particularly profound impact on the e-commerce sector:
Reduced range of comparison: Users see fewer options because AI condenses answers.
Early opinion formation: Preferences are formed even before visiting a website.
Increased dependence on context: AI classification shapes the perception of a brand.
This shifts a relevant part of the decision-making process to a phase that was previously difficult to control. Companies must accept that visibility today no longer arises exclusively through traditional touchpoints.
Why AI is becoming a recommendation engine
AI models combine information from different sources and present it in a seemingly neutral and summarised form. This creates the impression of an objective recommendation. For users, this type of response often replaces their own research efforts. For companies, it is crucial that only those that are clearly and consistently represented in the underlying information structures are recommended. Lack of clarity, contradictory statements or unstructured content significantly reduce the likelihood of being considered in AI responses.
Consequences for marketing and communication
The new customer journey requires a rethink of content and brand strategy and the optimisation of content for generative systems.
Key requirements include:
Clear, structured information presentation
Unambiguous brand and service descriptions
Consistent statements across all digital channels
Comprehensible, fact-based content
These principles form the basis for Generative Engine Optimization (GEO) – an approach that aims to make content interpretable and usable for AI systems.
comdaily conclusion: AI chats are becoming a central entry point into the customer journey. They influence which brands are perceived, compared and ultimately considered. This presents a clear challenge for companies. Those who do not appear in AI responses lose potential customers very early in the decision-making process. The new customer journey therefore requires an expansion of existing strategies. Visibility is no longer achieved solely through rankings or reach, but through relevance within generative responses. Companies that take this development into account at an early stage will secure a competitive advantage in an increasingly AI-driven market environment.
