voiceoptimizationSEO

Optimize Your Content for Siri, Gemini, and Other App-Level AIs

ddigital wonder

2026-01-30

9 min read

Make your content discoverable by Siri, Gemini, and on-device AI with a practical checklist: metadata, timestamps, JSON-LD, and app signals.

Hook: Your audience is now inside apps — is your content speaking their language?

Creators and publishers in 2026 face a new reality: discovery no longer happens only in search engines or social feeds. It increasingly happens inside app-level and on-device AI — Siri (now powered by Gemini in late 2025), Google Assistant, system agents, and embedded AI in apps that pull context from a user's photos, calendar, and reading history. If your headlines, metadata, and episode timestamps are optimized only for traditional search, you are invisible to a rapidly growing channel of high-intent traffic.

What this guide delivers

This article gives you a practical, prioritized creator checklist to optimize content for voice AI optimization and on-device AI discovery. You’ll walk away with concrete metadata templates, episodic timestamp standards, JSON-LD examples, app-level signals to add, measurement tactics, and a 90-day rollout plan. Apply these steps to podcasts, video series, longform articles, and landing pages to improve app-level AI indexing and overall searchability.

The new rules for 2026 (context you must know)

Major platforms moved fast in late 2025 — Apple announced it’s using Google’s Gemini for next-gen Siri, and Gemini models now pull contextual signals from users’ apps (photos, videos, YouTube history), increasing the value of contextual, time-based metadata.
On-device and app-level AI prioritize concise, structured signals and privacy-preserving contextual cues over long-form SEO keyword stuffing.
Entity-based SEO has matured: AI agents rely on named entities, relationships, and structured metadata to answer queries and propose content inside apps.
Creators must provide both human-facing UX (transcripts, chapters) and machine-facing signals (JSON-LD, app link metadata, NSUserActivity) to be surfaced by AI assistants.

Fast-action checklist (start here — priority order)

Add rich, standardized metadata to every asset
- Web pages: Title tag (60 char), meta description (140–155 char), Open Graph (og:title, og:description, og:image), canonical link.
- Media: Provide a machine-readable transcript (full text) and a concise summary (one-sentence, 140 char) in the meta or via JSON-LD.
- Podcast & Video: Publish episode-level JSON-LD (PodcastEpisode, VideoObject) with duration, guests, topics, and category tags.
Publish episodic timestamps (chapters) and align them to entities
- Add human-readable chapters (YouTube-style timestamps in description or WebVTT for video), and mirror them in JSON-LD under hasPart or in a chapters array for audio.
- Label each chapter with the primary entities (names, topics, product names) so assistants can surface short answers for specific time slices.
Expose contextual signals for app-level AI
- Implement deep links / universal links and App Links (Android) so apps and on-device AIs can open exact content.
- For iOS: support NSUserActivity, App Intents, and Siri Suggestions with relevant user activity types and donate shortcuts for important flows.
- Include structured tag fields for audience intent (e.g., "how-to", "buying-guide", "episode-clip") that are easy for an app agent to read.
Ship structured JSON-LD everywhere
- Use Article, PodcastEpisode, VideoObject, Person, and Organization where appropriate.
- Include named entities, speaker lists, guest social handles, and related links to build entity graphs that agents can traverse.
Optimize content structure for short answers and follow-ups
- Provide TL;DRs for sections, 1–2 sentence summaries, and FAQ blocks with direct Q/A pairs that voice assistants can read aloud.
- Use clear H2/H3 headings that match likely voice queries (e.g., "How long is episode 12?", "Key takeaways from interview with X").
Make media machine-readable (transcripts, VTT, WebVTT)
- Publish full transcripts alongside media and break them into timestamped sections (00:00 format). This is one of the highest-impact steps for voice AI optimization. Also publish matching WebVTT and SRT files for players.
Signal freshness and update history
- Include datePublished and dateModified in JSON-LD and visible update notes on the page. App agents prioritize fresh, recently updated content for actionable queries.
Test with devices and measure
- Regularly test queries on iOS Siri, Google Assistant, in-app assistants, and device emulators. Log what results are returned and refine metadata where needed.

Why each item matters (quick explainer)

Metadata is the first thing on-device AIs read. In 2026, agents prioritize short, labeled metadata fields over raw page content. That means concise summaries, explicit categories, and entity links win.

Episodic timestamps let agents answer slice-specific queries ("play the part about product pricing at 12:32"). Gemini-powered Siri and similar agents now surface clips directly from transcripts when chapters are present.

Contextual signals (app links, NSUserActivity) enable AIs to create personalized suggestions based on a user's app usage, while privacy-preserving APIs let apps share safe context without exposing personal data.

Practical templates you can copy (meta & JSON-LD)

Meta tags (HTML head)

<title>How to Build a Creator Media Kit — Episode 12 | Your Brand</title>
<meta name="description" content="Episode 12: Quick guide to building a creator media kit — guests: Jane Doe. 18-min, chapters included." />
<link rel="canonical" href="https://example.com/episode-12" />
<meta property="og:type" content="article" />
<meta property="og:title" content="How to Build a Creator Media Kit — Episode 12" />
<meta property="og:description" content="Episode 12: Quick guide to building a creator media kit — guests: Jane Doe. 18-min, chapters included." />

JSON-LD for a podcast episode (simplified)

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "PodcastEpisode",
  "name": "How to Build a Creator Media Kit",
  "episodeNumber": 12,
  "partOfSeries": {"@type": "PodcastSeries","name":"Creator Growth"},
  "datePublished": "2026-01-05",
  "description": "18-min interview with Jane Doe on building a media kit. Chapters included.",
  "duration": "PT18M",
  "author": {"@type":"Person","name":"Host Name"},
  "transcript": "https://example.com/episode-12/transcript",
  "hasPart": [
    {"@type":"WebPageElement","name":"Intro","startOffset":0},
    {"@type":"WebPageElement","name":"Media Kit Checklist","startOffset":120}
  ]
}
</script>

Note: include public transcript URL and mirror chapter start times in the transcript. Use seconds for startOffset so app agents can map to media players.

How to add episodic timestamps the right way

Write a chapter title that includes the entity and intent: "00:00 — Intro: Why creators need a media kit"
Include the timestamps in the top of the description and inside the transcript as anchors.
Publish a WebVTT file for video with exactly matching timestamps; for audio, use a timestamped transcript file (SRT or plain text with timestamps).
Mirror timestamps in JSON-LD (see example above) and in an on-page data-chapters attribute for players.

App-level signals and iOS / Android specifics

On iOS, agents like Siri use donations via NSUserActivity and App Intents to build suggestions. Donate the most important flows — episode playback, landing page funnels, and purchase pages. On Android, support App Links and Digital Asset Links so assistants can deep link reliably.

Donate NSUserActivity for key content views. Include title, keywords, and webpageURL.
Create App Shortcuts for frequent tasks ("Play latest episode", "Open pricing for Creator Kit").
Make sure universal links open to the correct player state (timestamp) using a query param (e.g., ?t=732 for seconds).

Measuring success: What to track

Traditional metrics matter, but now add these voice- and app-focused KPIs:

Impressions/clicks from in-app traffic (use UTM + deep link parameter to segment).
Playback starts from deep link with start time (log the referring parameter in analytics).
Assistant-driven actions: track how often an App Intent or donated shortcut is triggered.
Voice search query performance in Search Console (look for conversational queries) and GA4 events labeled "voice_query" if you capture them via site scripts or server-side logs.

Testing & QA checklist

Run queries on-device (Siri on iPhone, Assistant on Android) using real conversational prompts.
Use a staging app to test NSUserActivity donations and confirm Siri Suggestions display appropriate actions.
Validate JSON-LD in Google’s Rich Results test and your own schema validator; test deep links on multiple devices.
Check transcripts and timestamps align by playing the clip at the chapter start time — audio should match the labeled section.

Implementation roadmap: 90-day plan for creators

Week 1–2: Audit & quick wins

Audit top 20 content pieces for missing metadata, transcripts, and deep links.
Add meta descriptions, TL;DRs, and short summaries to those pages.

Week 3–6: Chapters, transcripts, JSON-LD

Publish transcripts and timestamped chapters for top content. Implement JSON-LD for episodes and videos.
Implement deep link parameters for timestamps.

Week 7–12: App signals & measurement

Donate NSUserActivity for iOS flows and set up App Links for Android. Wire analytics to capture agent-driven events.
Run cross-device tests and iterate based on actual assistant results.

Common pitfalls to avoid

Relying only on long-form content without machine-readable summaries and chapters — agents prefer short, labeled answers.
Not providing transcripts — this alone reduces the chance an AI will extract clipable segments.
Broken or inconsistent deep links — ensure the same timestamp format is respected across web, app, and JSON-LD.
Ignoring privacy: never attempt to surface or donate personal data fields. Use privacy-safe signals and follow platform guidelines.

"In 2026, discoverability means being structurally predictable for AI." — Practical takeaway: inform the agent with clear, concise, and machine-readable signals.

Future signals to watch (late 2026 and beyond)

More apps will expose privacy-preserving context APIs for AI agents — start building content that maps to user intents (e.g., "learn", "compare", "purchase").
AI agents will use multimodal snippets (image + 10s audio + 1-sentence summary) in suggestions. Keep media assets tightly coupled to metadata.
Expect standardized "AI App Schema" initiatives across platforms; early adopters who already have strong JSON-LD and chaptering will benefit first.

Short checklist you can paste into your CMS

Title (<=60): filled
Meta description (140–155): filled
One-sentence summary (140 char): added to top of page
Transcript: uploaded & timestamped
Chapters: listed in description & WebVTT/SRT
JSON-LD for content type: added + validated
Deep link with timestamp param: tested
NSUserActivity/App Intent donation (iOS): implemented
Measurement events for voice/assistant: wired

Case study snapshot (example)

Creator X (audio-first publisher) implemented chapters, transcripts, and episode JSON-LD for their top 30 episodes in Q4 2025. Within six weeks of rolling out, they observed a 28% increase in podcast playback starts coming from mobile assistant-driven deep links and a 22% lift in time-on-site for pages opened from assistant suggestions. The key change was enabling timestamped deep links and donating NSUserActivity for "Play episode" — agents could now present the clip directly in suggestions.

Final tactical takeaways

Priority 1: Publish transcripts and timestamped chapters — highest ROI for voice AI optimization.
Priority 2: Add concise machine-readable summaries and JSON-LD to every asset.
Priority 3: Implement deep links and donate app-level signals (NSUserActivity / App Intents) so app agents can open exact content.
Measure agent-driven events and iterate monthly.

Call to action

Ready to get surfaced by Siri, Gemini-powered assistants, and other on-device AIs? Download our 1-page implementation checklist or book a quick audit with our team at digital-wonder.com to map your top 50 assets to the app-level AI signals that matter in 2026. Let’s make your content not just findable — but playable, answerable, and recommendable inside the apps your audience uses every day.

digital wonder

Contributor

Senior editor and content strategist. Writing about technology, design, and the future of digital media. Follow along for deep dives into the industry's moving parts.