A 30-Day AI Discoverability Plan for Mobile Apps

You do not need to expose an entire application catalog or invent a new protocol to test AI-assisted discovery. In 30 days, a small cross-functional team can publish a bounded, measurable slice: representative entities, truthful machine-readable records, crawlable pages, and verified routes into the app.

The aim is a maintainable app map: explicit capabilities, relevant experiences, publisher preferences and tested destinations. Onboarding can begin with one useful experience; the rest of the month connects that map to the team's normal release and review workflow.

Week 1: Map the information surface

Choose a major experience that creates real user value: finding a workout, exploring tours, booking a table or browsing listings. Map its capability, user intent and destination first. Add named items when their attributes help selection; twenty records are an optional enrichment exercise, not an onboarding requirement. Include applicable edge cases such as unavailable, regional, renamed, localized and multi-platform experiences.

For each record, identify:

• authoritative source system;
• stable native ID;
• selection fields a user needs;
• source modification time;
• public/private boundary;
• intended iOS, Android, web, and store destinations.

Audit current exposure. Can a logged-out browser see the facts? Are pages canonical? Do links lead to the selected item? Does the app have valid Apple and Android domain associations?

Do not start keyword production yet. Google’s people-first guidance favors content that helps the intended audience and warns against extensive automation used mainly to attract search traffic.

Week 2: Build the smallest feed

Create a manifest and one record per entity. Require a stable ID, type, name, and destination. Add a short summary, typed attributes, availability, language, and timestamps where they improve selection.

Use JSON Schema or another portable contract and retain namespaced extensions for vertical detail. Decide whether the feed is a complete snapshot or incremental stream. Define deletion behavior before the first deletion occurs.

Generate the output from the source system. Validate unknown fields, duplicate identities, unsafe URLs, units, timestamps, and null versus omitted values. Keep publisher claims separate from index-derived trust, freshness, and destination health.

Week 3: Publish and route safely

Create human-readable pages that display the same core information as the structured records. Add canonical links, internal navigation, and a segmented sitemap. Use accurate JSON-LD where a public vocabulary fits; Google says structured data should match visible page content and is not a special shortcut into AI features.

Verify entity-level destinations. Apple’s Universal Links and Android App Links provide secure app/web associations, but test specific paths on installed and uninstalled devices. Define fallbacks that preserve the selected item whenever possible.

Review robots and CDN controls for public pages, account routes, APIs, previews, and search/training crawler policy. Do not treat robots as security.

Week 4: Review the representation and maintain it

Create a fixed set of queries covering brand, category, constraints, comparisons, and negative cases. Ask an independent person or retrieval system to find the entities using only public surfaces. Record:

• whether the app and exact entity were found;
• cited sources;
• freshness and authority clues;
• selected destination;
• route success;
• time and manual intervention.

Establish server-log and analytics baselines. Separate crawler requests, index visibility, assistant citations, referral sessions, app opens, and qualified in-app actions.

Decide what happens on day 31

Assign an owner for app-map freshness. Keep reviewed configuration in the app repository, stage changes with each relevant release, inspect the diff and activate deliberately. Preserve stable IDs and check the publisher-site connection after website changes.

Add richer metadata where an answer needs more context, not simply because more records are available. Keep complete content and live workflows in the app. Review any unexpected routing or stale offers, correct the source and publish a new revision.

Use the Blue Jetty publisher quickstart to put the shared-index path into production: start with a small representative catalog, validate it, submit it, and keep its timestamps and destinations current.

The result is a repeatable publisher workflow: map the app, authorize the packet, make it discoverable, and keep its representation aligned with the experience users will actually reach.