Key competitors
Cross platform competitor set. Each row carries name, URL, the AI models that named the brand, and a strength score for consensus.
Executive summary
Three short paragraphs explaining the feature and value.
Key competitors discovers the brands actually competing for AI search visibility, not the brands a marketing team assumes are competitors. The discovery agent fans out across multiple AI models in parallel with the brand's keyword and region context. Each model returns the brands it names as alternatives for the queries that matter for the buyer.
Results aggregate into a single ranked competitor list. Each row carries name, canonical URL, the AI models that named the brand, and a strength score reflecting how many models agreed. A brand named consistently across every AI model gets a high strength score. A brand named once by one model gets a low one.
Users review, edit, and curate the resulting set. Add a competitor missing from the auto detected list. Mark one as not actually a competitor and the system stops weighting them in scoring. The curated list is the basis for every comparative score, leaderboard, and the BT10C top ten consistency tracker across visibility scans downstream.
Key highlights
Five capability points teams should know about quickly.
- Discovery agent fans across multiple AI models
- Per row strength score for cross platform consensus
- Add, remove, and curate the competitor list inline
- Feeds the BT10C top ten consistency tracker
- Basis for every comparative score downstream
Top FAQs
Five common questions answered for fast practical clarity.
How are competitors discovered?
The discovery agent reads the brand's keywords, ICPs, and region, then queries multiple AI models in parallel with prompts shaped like buyer research questions. Each model returns the brands it considers alternatives. Responses aggregate into a single ranked list with a strength score showing how many models named each brand independently of each other.
What does the strength score mean?
Strength is a normalised score from zero to one hundred. It measures cross platform consensus: how many of the AI models named this brand at least once. A score of one hundred means every model named the brand as a competitor across multiple queries. A score of ten means only one model named them once.
Can I edit the list manually?
Yes. Click add to drop in a competitor the auto discovery missed and the system fills in URL and metadata. Click remove on any row to drop a brand the user decides is not actually competing. Click flag to mark a row for later review without removing it. All edits persist across new discovery runs automatically.
How often does competitor discovery re run?
On demand from the Key competitors page or automatically when the Brand keywords set changes by more than ten percent. Markets shift; AI model training data shifts; the relevant competitor set today may not be the one from six months ago. Discovery runs are recorded with timestamps so users can compare versions easily and clearly.
Why does this matter for visibility scoring?
Every visibility scan tracks where the brand ranks versus its competitors. Without an accurate competitor set, the brand could win on visibility against irrelevant brands while losing to the brands that actually matter to its buyers. Key competitors is the truth source for who counts; everything downstream uses this curated list always.