What Competitors shows
The Competitors page lets you compare how often your brand and your tracked competitors appear in AI-generated responses. All brands are measured against the same prompt set, date range, and filters — so the comparison is apples-to-apples.How to add competitors
Competitors are registered at the account level and apply across all Intelligence views. To add a competitor:- Go to Settings → Team or contact your account admin
- Add the brand name and any known name variants
- Optionally link the competitor to a root domain for source correlation
Reading the comparison table
Each row in the table is one tracked brand. Columns show:| Column | Description |
|---|---|
| Brand | Brand name and domain |
| Total mentions | Raw mention count across all runs in the period |
| Mention rate | Percentage of prompt responses containing this brand |
| vs. prev. period | Change in mention rate compared to the prior equivalent window |
| ChatGPT | Mention rate within ChatGPT responses only |
| Gemini | Mention rate within Gemini responses only |
| Perplexity | Mention rate within Perplexity responses only |
| Google AI | Mention rate within Google AI Overviews only |
Model-level breakdown
Select any brand row to expand a per-model breakdown. This shows how each AI model independently covers the brand, which is useful when models behave differently — for example, if Google AI cites a brand far more than Perplexity.Trend chart
The trend chart above the table plots mention rates for all tracked brands as overlapping lines. Switch between:- All models combined — aggregate across all AI models
- Per model — one line per brand, filtered to a single AI model
Tips for analysis
- A competitor with a low overall mention rate but a high rate in one specific model may be targeting that platform’s content preferences
- A sudden drop in mention rate often correlates with a prompt set change or a model update — check Prompts for recent edits on the same dates
- Use tags to compare competitors only within a specific campaign or topic cluster