How competitor tracking works in AI Visibility. Matching by name + domain, sentiment, matrix view.
Tracking your own brand in LLMs tells you reputation. Tracking competitors tells you market share and where you can take ground. Same prompt set; different aggregations.
For every prompt run, we scan the response text for:
Match counts increment for any of the three. The mention is recorded with the sentence context (so you can read what the LLM actually said).
For every mention, we classify sentiment as positive, neutral or negative using a fine-tuned classifier. Aggregated views show trend over time per competitor. A competitor whose sentiment drifts negative is often about to lose default-recommendation status – a leading indicator.
AI Visibility → Competitors → Matrix. Rows = prompts, columns = your brand + each tracked competitor, cells = mention rate (% of recent runs where the brand was mentioned).
Sort by:
In each prompt's response text, we surface unfamiliar brand-shaped tokens (capitalized phrases that look like product names but aren't in your tracked list). If the same unfamiliar name appears in 3+ prompts in a week, we suggest adding it.
Set up Slack/email alerts on competitor events:
bashcurl https://api.semoptimiser.com/v1/ai/mentions?competitor=ahrefs \ -H "Authorization: Bearer sk_live_..."
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