The App Store Snippet Cookbook: 12 JSON‑LD Feature Cards That Turn Store Copy into AI‑Citable Answer Cards

AI agents and modern search engines increasingly prefer content that’s machine-structured and extractable. A short, well-marked JSON‑LD block that maps a single question or feature claim to a concise answer makes it far easier for a model or an answer engine to verify and cite your copy as an authoritative source.

That doesn’t mean replacing human‑readable copy — it means adding transparent metadata that mirrors the exact sentence you want machines to quote. Google’s documentation and Schema.org types (FAQPage, Question/Answer, HowTo, SoftwareApplication) remain the standards for communicating structure to indexers and agents — and they work best when the JSON‑LD corresponds exactly to visible page content.

Treat each feature card like a single-purpose sentence: short, factual, and complete on its own. AI extractors favor self-contained answers — a one-sentence answer with the key metric or behavior is more likely to be surfaced than a paragraph that requires context.

Match the visible copy exactly in your JSON‑LD. For example, if your store blurb says “Offline maps that update automatically,” your structured data should reproduce that exact string as the answer text. That guarantees the agent can verify the claim against page content.

Below are twelve card types you’ll paste into any product page or agreement page. Each card maps one feature claim to an answer. Use the type that best matches intent: "Question/Answer" for claim citation, "HowTo" for step processes, and "SoftwareApplication" for product facts (version, platform, price). Keep the JSON‑LD in the page head or directly before the visible blurb.

Important guardrails: every Question and Answer used in FAQPage must appear on the page as visible content; don’t hide answers behind scripts or gating. Also, don’t expect structured data alone to guarantee placement — it increases the chance of being cited when the page already ranks or is relevant to the query.

Below are three minimal, copy-first JSON‑LD templates you can adapt. For each template, replace the example strings and URLs with your app copy and canonical page URL. Keep answers short and literal.

Template usage notes: use FAQPage when your blurb reads like a question+answer pair; use SoftwareApplication properties for platform/version facts; use HowTo for multi-step features that you want a bot to reproduce in an answer box.

Small, measurable experiments give you a roadmap to know which phrasing becomes citable. Run A/B tests that swap a one-sentence answer for a slightly different word order. Track which variant attracts more external citations (backlinks quoting the sentence) and which appears verbatim in search answer boxes or AI outputs.

Operational tests: use server logs and a ranked query sampling to find queries returning your page; put small, visible changes in the answer text (e.g., include the keyword you want cited) and re-run line-level validations to confirm the JSON‑LD still exactly matches visible content.