SOV by AI Model
Understand how your visibility differs across AI models.
Why break down by model?
Not every AI model treats your brand the same way. Different models have different training data, are updated at different times, and use different methods to incorporate information from the web. As a result, your Share of Voice on one model can be significantly higher or lower than on another.
The SOV by AI Model view breaks down your Share of Voice per model, allowing you to analyze and optimize with precision.
The AI models at a glance
ucited.ai tracks the most important AI models that users rely on for research and recommendations:
ChatGPT (OpenAI)
The most widely used AI model globally. ChatGPT can access real-time web data and frequently cites sources. High visibility on ChatGPT is particularly valuable given its massive user base.
Gemini (Google)
Google's AI model is deeply integrated into the Google ecosystem and powers features like AI Overviews in Google Search. Visibility on Gemini often correlates with strong web presence and structured data.
Perplexity
Perplexity is purpose-built as an AI search engine and almost always provides source citations. Brands that are visible here benefit from direct links back to their content.
Copilot (Microsoft)
Microsoft's AI assistant is integrated into Bing, Windows, and Microsoft 365. Copilot accesses current web data and provides source citations, making it an important channel for brand visibility.
Configuring models
Under Configuration → LLMs you can choose which models are tracked. This selection applies to all clients in your company. Not all models need to be active — focus on the ones that are relevant to your target audience.
Reading the table
The SOV by Model table shows a separate row for each active AI model. For each model, you can see:
- Your SOV share — The percentage of your brand's mentions on this model
- Competitor shares — How the selected competitors are distributed
- Total mentions — The absolute number of mentions per model
Watch for large gaps
If your SOV on one model is significantly lower than on others, that is a strong signal for targeted optimization. Different models favor different content formats and source types.
How to use this metric
1. Recognize model strengths
Identify the model where you have the highest SOV. Analyze which of your content performs particularly well there — these insights can often be transferred to other models.
2. Address weaknesses strategically
Which model has your lowest SOV? Check which competitors lead there, and use the Mentions view to understand their mention patterns.
3. Optimize per platform
Each model has its own characteristics: Perplexity favors well-structured, citable content. Gemini benefits from strong Google presence. ChatGPT draws on current web content. Tailor your content strategy accordingly.
4. Track changes over time
Model updates can change your visibility overnight. Monitor SOV by Model regularly to detect these shifts early and respond proactively.
Related pages
Complement your model analysis with these pages: