For AI models, the menu and categories of a website or online store are more than just navigation tools. They serve as a map that indicates which topics and product groups are most important to you and how different pieces of content are connected. If the structure is chaotic, too deep, or based on internal jargon, the models will have a harder time accurately describing your offerings and will be less likely to choose your site as a source of answers.
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Step 1-Build categories from the customer’s perspective, not the company’s organizational structure
The most common mistake when designing categories is to mirror the company’s organizational structure rather than the customer’s way of thinking. From an AI perspective-just as from a user’s perspective-categories that align with how people naturally search for services or products are better. If customers search by use case, the categories should reflect that rather than referring to internal department names.
A good starting point is to analyze how customers describe what they’re looking for: in search queries, emails, conversations with customer service, or reviews. These phrases should be incorporated into the names of categories and subcategories. This will make it easier for LLM models to associate your menu with users’ actual intentions, rather than just internal terminology.
Step 2 – Maintain a Flat Structure Instead of a Multi-Level Maze
From an AI perspective, structures that are as flat as possible work very well. Key categories and the most important informational or product pages should be no more than a few clicks away from the homepage. Excessively deep nesting makes it difficult for both users and the model to understand which areas are truly central to your business.
In practice, it’s better to have a few clearly defined top-level categories that lead to well-organized subpages than multiple layers of menus where it’s easy to get lost. For LLM models, these category “hubs” serve as strong reference points from which they can draw definitions, explanations, and context for further responses.
Step 3 – Give categories names that clearly explain what they contain
Clarity is key when it comes to category names. Names that are too creative, metaphorical, or internal make it difficult for both customers and AI to quickly understand what’s in a given section. A catchy slogan in a headline is one thing, but a menu label should clearly state exactly what the user will find there.
A good approach is to combine general categories with more specific details on the page itself. For example, a menu category could be called “online training,” and on the page itself, you can elaborate on who it’s for, what topics it covers, and in what format. This gives LLM models a clear signal about what a given section is about, while also providing them with more details from the content within the category.
Step 4 – Organize the main menu around your most important areas
The main menu should immediately show the pillars of your business. An overly complex navigation bar, where each section has its own link, is difficult for users to grasp and confuses the AI. It’s better to have a few strong items than a dozen or so weaker ones.
Most often, the main menu should include the home page, your offerings, or categories of services or products, a section with educational materials (blog, guides, knowledge base), company information, and contact details. In e-commerce, it’s also worth including the most important categories, a link to the shopping cart, and the user account. This layout clearly communicates what’s most important, which both the user and the model will appreciate.
Step 5 – Use categories as sources of context, not just product lists
In online stores, many category pages are merely product listings. From an AI perspective, this is a missed opportunity. A category can serve as a mini-guide and a hub of context for a given group of products. Simply add a description at the top or bottom of the page explaining how products in this category differ, who each type is intended for, and what to look for when making a selection.
This gives LLM models a source of information for their advisory responses. Instead of searching for advice on third-party sites, they can use your category description as a reliable source. For your store, this is an opportunity to appear in search results not only when a specific product name is searched but also for questions like “which type of product should I choose?”
Step 6 – Ensure Consistent Terminology Throughout the Menu and Category Structure
Consistent naming is crucial from an AI perspective. If one category is called “Services for Companies,” another “Business Solutions,” and yet another “B2B Offerings,” models may have difficulty unambiguously associating them with the same business segment. Similarly in e-commerce: mixing terms like “men’s,” “men,” and “gentlemen” in category names introduces unnecessary noise.
That’s why it’s a good idea to establish a single glossary of names for categories, subcategories, and content types, and then apply it consistently. This not only makes it easier for users to navigate the site but also for models, who-thanks to consistent terminology-can more easily create accurate and coherent descriptions of your offerings.
Step 7 – Use breadcrumbs and internal linking as “thought paths”
Breadcrumbs and well-thought-out internal linking play an important role in providing context for AI. They show which category a given subpage belongs to, how it’s embedded within the structure, and what other sections are related to it. This helps models understand the relationships between content and products.
In an online store, well-designed breadcrumbs might look like this, for example: Home – Main Category – Subcategory – Product. On corporate websites, a similar effect can be achieved by linking from guides to service pages, from FAQs to key subpages, and from case studies to offers. The clearer the paths, the easier it is for AI to navigate the structure.
Step 8 – Don’t overload menus and categories with extra links
It’s natural to be tempted to include as many items as possible in the menu so that everything is right at your fingertips. Unfortunately, an overly complex menu is difficult to navigate, both for users and for AI models. Too many links of equal importance dilute the signal about which areas are most important.
A better practice is to limit the main menu to the most essential sections and place less important content in the footer menu, submenus, or within the blog structure. For AI, this clear division serves as a guide to which parts of the site are central to your business and which are of secondary importance.
Step 9 – Consider the mobile menu and internal search
More and more users are accessing websites and online stores on mobile devices. From an AI perspective, it’s important that the structure of the mobile navigation doesn’t differ significantly from the desktop version. A menu that’s too different can cause confusion if content is grouped differently or is harder to access.
An internal search bar is a good complement to categories and menus. When properly configured-with autocomplete suggestions and results based on real customer queries-it can also provide valuable insights into how people describe your products and services. This information can then be used to further refine categories and menus in line with AI.
Step 10 – Regularly review categories and menus in light of user behavior and AI
The structure of categories and menus isn’t a one-time decision. It’s worth reviewing it regularly, looking at both analytics data and how the AI describes your site. If you notice that users frequently use the search bar instead of the menu, this may indicate that the categories aren’t speaking the customer’s language. If AI models describe your offerings differently than your category names do, you may need to align more closely with the vocabulary used in search queries.
A periodic review of the structure helps you identify dead categories, duplicate sections, overly general names, and areas where logical connections between content are missing. This allows you to keep your menu and categories as a clear framework that helps both users and language models better understand what you offer.