AI Topic Map FAQs

When Conductor identifies an optimization opportunity, we are not referring to distinct pages that your should optimize. Instead, we are describing a semantic area in a topic where your site could be performing better. For a given optimization opportunity, Conductor identifies one or more pages that are potentially relevant to that semantic area. Choosing the specific page to optimize is left to your expertise and familiarity with your site.

You might see pages that don't seem related. This happens because the system detects deeper semantic connections—perhaps both pages discuss similar decision-making processes, target similar user intents, or share underlying themes that aren't immediately obvious.

This can help you identify and consider relationships you might not have considered, which can inform how you structure navigation, internal linking, or content strategies.

If you see a content gap suggestion for something you know exists on your site, the pages covering that topic likely appeared in a different cluster. This isn't a mistake—it's valuable intelligence. This might indicate content that might be mis-categorized on your site, orphaned from related topics, or could benefit from being reorganized to better serve user journeys.

Conductor's AI engine creates descriptive labels based on what it identifies as common themes across your clustered content. Because it doesn't know your brand voice or internal terminology, these labels describe functional relationships rather than your marketing language.

This can reveal how external audiences might naturally categorize your content, which can inform SEO strategy and help identify gaps between your internal language and user expectations.

If you have international content, you'll see higher page counts because each language/region version is counted separately. A product page in English, French, and Spanish shows as three pages. This can help you understand the true scope of your international content footprint and opportunities for better coordination across regions.

Occasionally, you might see keyword suggestions that seem completely unrelated to a topic cluster. This happens due to the mathematical complexity of visualizing over 500 dimensional relationships in two-dimensional space—sometimes the boundaries get distorted.

When this happens, it usually indicates you have strong content in related topic areas that the system recognizes as semantically adjacent, even if they appear visually separate.