How to Succeed with AI Visibility in Ecommerce

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The question many ecommerce companies now have to ask themselves is no longer whether Artificial intelligence affects the customer journey, but how. As more and more people search, compare and make purchase decisions via ChatGPT, Google AI Overview and other Ki-based interfaces, the rules of the game for visibility change fundamentally.

What do you do with your online store and website when customers increasingly meet you through an AI response — and not through a traditional search result?

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What do we really mean by KI in this context?

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When we talk about KI today, it is particularly generative KI, also called Large Language Models (LLM), which is relevant. These are models that analyze and generate text, code, images, and other information based on large amounts of data and linguistic patterns.

The reason why these models have gained such rapid prevalence is the low threshold for use. Compared to more advanced AI systems, LLMs require little technical expertise, while satisfying a basic human need: getting fast, coherent answers to complex questions. That is why they have also become a new gateway to information — and to purchases.

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One Critical Contact Surface: The KI Response

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It is important to distinguish the company's use of KI internally and customer's use of KI remotely. For AI visibility, only one thing is essential:

The customer meets your business through the answer the KI gives.

Whether it's in a chat, in an AI Overview on Google, or in a future purchase flow directly inside a KI platform, it's the KI agent who interprets, prioritizes, and communicates the information about you. You're not just competing for ranking -- you're competing to be understood, cited, and recommended.

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Is KI taking over for search?

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No -- but it changes the nature of the search.

Figures from Statistics Norway show that 54% of Norwegians have used KI in 2025up from 36% the previous year. The Whole 84% use it for private purposes, and studies show that around 24% of all prompts are about information retrieval — a category that is growing fastest and that also includes transactional issues.

At the same time, we see that KI-referred traffic converts significantly better than traditional search traffic. When the user has already received the recommendation, context, and response before they click, the decision is often far along the way made.

This makes KI visibility a strategic channel—not an experiment.

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From SEO to AEO: visibility for KI agents

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Many people are familiar with SEO. AEO (Answer Engine Optimization) is the same principle, but adapted to KI agents instead of classic search engines.

In order for KI to use, trust and cite your content, three basic conditions must be in place:

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1. Entity understanding

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KI doesn't read pages the way humans do. Through natural language processing It tries to identify entities (companies, products, concepts) and the relationships between them. The clearer these relationships are, the easier it is for KI to correctly position you in its internal knowledge structure.

The goal is not just to answer what something is, but to explain How it relates to something else.

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2. Semantic structure

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The HTML structure is the skeleton Ki-en interprets. A logical order in headings, paragraphs, and content gives signals about what is most important, what is explanatory, and what is supporting information.

Good semantics isn't cosmetics -- it's communication with machines.

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3. Scheme markup

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Schema.org serves as a common vocabulary for web pages. By explicitly labeling products, organizations, reviews, and content, you reduce interpretation doubts for the KI agents. It increases the likelihood that your information will be used directly in responses.

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New AI Visibility Rating Signals

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Early studies show that classic SEO signals do not disappear, but that they are weighted differently in the KI context.

For small and medium-sized players, three factors stand out in particular:

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1. Visibility in discussion forums
   Brands featured on platforms such as Reddit and Quora are substantially more likely to be cited by KI models.
2. Questions in titles and content
   Content that explicitly answers specific questions is far more often used by KI — especially for smaller domains.
3. Freshness
   Content updated in the last three months is nearly twice as often cited as older content, regardless of domain size.

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The most important advice

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KI visibility is not about “optimizing for robots” in isolation. It's all about making your information clear, structured and contextual, so that both people and machines understand what you're offering -- and why it's relevant.

The company that wins in KI-driven trade is not necessarily the one that shouts the loudest, but the one that stays properly understood when the customer asks the question.

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