Platform
Market Coverage
See which buyer questions, topics, and decision spaces your brand owns, misses, or loses to competitors.
See it inside Findable
A map of the topics, decision spaces and missed opportunities Findable detects in your category.
What it is
Market Coverage maps the full space of buyer questions and decision topics in your category and shows which ones your brand currently shows up for in AI answers. It moves beyond a single visibility score to a topic-level view: which questions you own, which you partially appear in, and which are dominated by competitors.
Why it matters for AI search
AI engines pick a small set of brands per topic. Owning a topic means the model recommends you when buyers ask. Missing a topic means competitors are answering on your behalf. Coverage tells you which decision spaces are still up for grabs and which are already lost — so growth bets are aimed at real gaps, not assumptions.
The shift
"AI owns topics. Brands compete for topic ownership."
How Findable helps
Findable generates hundreds of representative buyer prompts per category, runs them across engines, and clusters answers into topics and decision spaces. Each cluster is scored for coverage, ownership, and competitor share — so you can see at a glance where your story lands and where it doesn't.
From AI answers to decisions
Coverage moves from individual prompts to topic ownership.
- 1Cluster promptsGroup hundreds of buyer prompts into a manageable topic set.
- 2Group topicsRoll clusters into decision spaces by funnel stage.
- 3Measure ownershipScore each topic as owned, contested or missed.
- 4Find gapsSurface the highest-intent missed topics to prioritize.
Key capabilities
Topic ownership
Findable rolls every prompt result into a topic, then scores how much of each topic you own. The view makes it obvious where to defend, where to invest, and where it’s already too late.
Decision space mapping
Not every topic is equally valuable. Findable maps topics to awareness, consideration and decision stages so you can see whether you’re losing eyeballs, evaluation or actual deals.
What this allows teams to do
- •Pick topics from gut feel
- •Treat all topics equally
- •Discover gaps months late
- •Argue about content priorities
- •Pick topics from AI-search demand
- •Score topics by ownership and intent
- •Surface missed topics every week
- •Ground priorities in coverage data
What teams find
Anonymous examples from real Findable workspaces.
One B2B brand discovered 31 buying-stage topics it had no presence in — and built a content plan to close them.
One marketplace shifted 40% of its SEO roadmap after seeing the AI topic ownership map.
One healthcare brand found that competitors owned every comparison topic in its category.
What you can see inside Findable
- Market coverage score
- Prompt and topic opportunities
- Missed buyer questions
- Topics you own
- Competitor-owned topics
- Decision spaces by stage
- Content gaps to close
Methodology
Coverage is computed from clustered prompt results: topics where you appear above a threshold count as owned, partial appearances as contested, and absence as missed. Clusters are refreshed as the prompt set evolves so the map stays current.
Coverage is computed by intersecting the brand's recommendation, citation, and mention footprint with the full prompt universe its category generates across AI systems, competitors, industries, and entities — so absence is measured as carefully as presence.
Examples of market coverage analysis
Illustrative views of how teams measure category and topic coverage across AI engines.
- •A sportswear retailer maps which product categories (running, training, lifestyle) it is consistently surfaced in across AI engines.
- •A fashion brand evaluates whether AI assistants cover its sustainability, fit, and price-tier prompts.
- •A clinic group measures coverage across condition-specific prompts to spot underserved decision spaces.
How AI engines evaluate market coverage
Coverage emerges from how thoroughly AI engines associate a brand with the prompts, topics, and decisions that define its market.
- Topic ownershipHow consistently the brand is named for a defined topic across engines.
- Semantic coverageHow wide a set of related concepts the brand is associated with.
- Prompt diversityWhether the brand surfaces across many distinct buyer questions.
- Recommendation breadthHow many decision spaces include the brand in recommended sets.
- Citation breadthHow many distinct topics cite sources tied to the brand.
- Entity associationsWhich products, themes, and categories the brand is co-mentioned with.
Findable maps each signal so teams see exactly where coverage is strong, thin, or absent.
Related concepts
Foundational terms used across this capability.
Underlying research
Powered by a full market observation corpus.
Related platform areas
- AI VisibilityTrack where your brand appears in AI answers across engines, prompts, competitors, and buyer questions.
- SourcesUnderstand which third-party and owned sources shape AI answers about your brand and competitors.
- CompetitorsSee which brands AI recommends instead of you and why they win visibility across prompts, engines, and sources.
Learn more
Deeper guides on the concepts behind this capability.
Coverage challenges vary by industry.
Teams using this capability
Anonymized examples of how teams in different industries apply this capability.
- RetailA retail team measures coverage across product categories and seasons.
- Consumer brandsA consumer-brand team measures coverage across sustainability, fit, and price prompts.
- Healthcare servicesA healthcare-services team measures coverage across condition-specific decision spaces.
- Executive educationAn executive-education team measures coverage across program types and seniority levels.
Compare AI visibility platforms
Side-by-side comparisons with other AI visibility and SEO tools.
Related industry research
External references on AI search and generative answer engines.
External links open in a new tab.
Related guides
Frequently asked questions
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