AngryturtleWhat Is Prompt Coverage?
Prompt coverage is the percentage of a business's defined query set that produces an AI citation in at least one engine. If a dermatology clinic has mapped 25 queries a prospective patient might ask an AI assistant, and the clinic gets cited somewhere — ChatGPT, Perplexity, Gemini, or an AI Overview — for 15 of them, its prompt coverage is 60%.
It's a close cousin of share of AI voice, but the two measure different things and it's worth being precise about which one a report is actually showing.
Prompt coverage vs. share of AI voice
Share of AI voice tracks the percentage of every query-by-engine combination that produces a citation. Prompt coverage tracks the percentage of unique queries that produce a citation in at least one engine, regardless of how many engines it shows up in.
A business could sit at 100% prompt coverage — cited somewhere for every query in its set — while its SAV is only 25%, because it's only showing up in one of four engines each time. The reverse is also possible: 50% prompt coverage with 40% SAV, meaning the queries where the business does appear, it tends to appear across more than one engine.
Neither number is "better." They answer different questions. Prompt coverage answers "are we visible for this topic at all." SAV answers "how dominant is our visibility once we are."
Why prompt coverage is the better early milestone
For a business just starting AEO work, prompt coverage is the more useful thing to report and track. "We're cited somewhere for 12 of our 25 core queries" is a concrete, understandable milestone. "We have 15% SAV" means less to a business owner who hasn't yet built any AI visibility at all — it sounds low in an absolute sense even when it represents real early progress.
As a business's AEO maturity increases, the more demanding SAV metric becomes the more useful one, because it starts to distinguish businesses appearing in one engine from businesses appearing consistently across all of them for the same queries.
Building prompt coverage
Coverage tends to expand in a rough order, though the boundaries blur in practice. Recommendation-style queries — "best dermatologist near me," "top-rated clinic in the area" — are usually the first to get covered, and they depend heavily on review count clearing whatever bar the engine is implicitly using. Service-specific queries come next, and they depend on a complete GBP services section along with FAQ content that names the specific service being asked about. Informational queries — "how does this treatment work," "what does it cost" — follow from there, driven mostly by FAQ pages carrying FAQPage schema or QAPage schema depending on the page's structure.
Each layer needs different inputs, so a business that's strong on reviews but weak on FAQ content will see recommendation-query coverage rise while informational-query coverage lags, and vice versa.
India context
For most Indian local businesses starting from close to zero, a realistic 12-month target is 60–70% prompt coverage across a defined 20-prompt set. Full SAV optimisation — chasing citations across every engine for every one of those queries — is usually worth attempting only once that broad coverage floor is already in place. Trying to optimise for SAV before basic coverage exists tends to spread effort too thin across queries the business isn't showing up for at all yet.
A worked example
A multi-location diagnostics chain in Hyderabad mapped 30 prompts across recommendation, service, and informational categories. Six months into structured AEO work, it had citations somewhere for 19 of the 30 — 63% prompt coverage — concentrated most heavily in recommendation and service queries, with informational coverage still catching up. That gap told the team exactly where to focus the next quarter's FAQ content build-out, rather than spreading effort evenly across all 30 queries.
Related terms: Share of AI voice → · Prompt-space → · Answer engine optimization → · FAQPage schema → · QAPage schema → · Review velocity →
AEO Services → | Share of AI Voice Tracking → | Get Cited by ChatGPT →
Related glossary terms
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