What it is
Topics are strategic groupings of related search terms in AI Visibility.
They allow you to organize prompts into meaningful categories so you can:
Measure visibility by theme
Compare performance across product areas
Analyze competitors within a specific category
Improve prompt suggestions in Find Terms
Topics act as the structural backbone of your AI visibility reporting.
Why it matters
Without topics, search terms exist in isolation.
That makes it difficult to:
Identify strengths and weaknesses by category
Benchmark competitors within a segment
Report clearly to stakeholders
Expand coverage logically
Topics allow you to move from prompt-level data to strategic insight.
Because AI search is intent-driven, grouping prompts by topic gives you visibility into where your brand performs well, and where competitors dominate.
Creating a topic
To create a topic:
Go to Topics
Click + Add Topic
Enter:
Topic name
Description
Optional keywords
Save
Topic name
The topic name should clearly represent a strategic category.
Examples:
CRM software
Digital PR monitoring
Insurance compliance tools
AI whiteboard platforms
Avoid vague names like “Marketing” or “General.”
Specific topics produce clearer insights.
Topic description
The description helps define:
What the topic covers
Target use cases
Industry focus
Business context
This description improves:
Reporting clarity
Internal documentation
Find Terms suggestion relevance
Topic keywords (optional)
Optional, add keywords relevant to this topic. These are not prompts that will be tracked. The keywords guide the Find Terms suggestion engine.
They:
Provide semantic direction
Improve prompt generation quality
Reduce irrelevant suggestions
Adding strong topic keywords leads to better AI-generated prompt ideas.
How topics influence Find Terms
Find Terms generates prompt suggestions based on:
Your brand
Topic name
Topic description
Topic keywords
Well-structured topics produce more relevant suggestions.
Weak or vague topics produce generic prompts.
If Find Terms results seem broad or misaligned, refine the topic definition first.
Assigning search terms to topics
You can assign a topic when:
Adding a new term
Bulk adding terms
Uploading via CSV
Editing an existing term
Every search term should belong to a topic.
This ensures:
Clean dashboard segmentation
Topic-level trend analysis
Engine comparison within categories
Scalable reporting
Editing and maintaining topics
You can:
Edit topic name
Update description
Adjust keywords
Reassign search terms
If strategy evolves, topics should evolve with it.
For example:
Split “CRM software” into “SMB CRM” and “Enterprise CRM”
Separate informational from commercial categories
Create region-specific topic groupings
Topics should reflect how you think about the business, not just how prompts were added.
Topic-level reporting
Topics power:
Topic-level visibility trends
Competitive comparisons within a category
Engine performance by segment
Filtered dashboard views
This allows you to answer questions like:
Where is our brand strongest in AI-generated recommendations?
Which category shows the most competitive pressure?
Are we gaining visibility in high-value segments?
Topic reporting turns raw AI responses into strategic direction.
Topics vs tags
Topics and Tags serve different purposes.
Topics
Strategic category structure
Permanent grouping
Used for dashboard aggregation
Tags
Flexible filtering
Cross-topic segmentation
Reporting customization
Example:
Field | What they define | Example |
Topic | "what" |
|
Tag | "context" |
|
Both together create scalable organization.
Best practices
Create topics before adding large numbers of search terms
Use clear, specific names
Add descriptions for strategic clarity
Include keywords to improve Find Terms suggestions
Avoid creating too many overlapping topics
Review topic-level trends monthly