App Store Optimization is no longer just a metadata game. As assistants like ChatGPT become a front door to software, the ranking that matters is the one you cannot see: whether the assistant routes a user’s intent to your app at the moment of need.
Conversational ASO: the practice of optimizing how AI assistants understand, select, and fulfill an app’s capabilities from natural language requests.
From keywords to intents
Definition and schema
Your primary unit of optimization becomes the intent, not the query. Map top tasks in plain language, then express them as structured capabilities with parameters and outcomes. Think “book a same-day dog walker” rather than “pet services.”
Key insight: If the assistant cannot parse what your app does with precision, it will never route to you, no matter how strong your store keywords are.
From listings to capabilities
APIs beat aesthetics
Assistants prioritize reliable capabilities. Publish clear actions, input validation, rate limits, error semantics, and success states. Provide example prompts, sample payloads, and deterministic fallbacks so the assistant can execute confidently.
Key insight: Capability clarity is the new creative; the best screenshot is a well-specified action with predictable outcomes.
From installs to completions
Measure routing, not just downloads
Add metrics that reflect assistant-mediated demand: intent match rate, routing share by task, deep link landing accuracy, completion rate, and time-to-first-outcome. Treat installs as a byproduct of value, not the goal.
Key insight: What gets measured gets routed; assistants will learn from completion signals faster than from raw install counts.
From marketing to trust signals
Operational credibility
Assistants prefer trusted executors. Maintain verified developer profiles, transparent pricing, permission scopes, security attestations, and user-level controls. Surface guarantees and escalation paths inside your capability docs and deep links.
Key insight: Trust primitives decide tie-breaks when multiple apps can do the same task.
What to do next
Make the assistant your first user
Refactor your backlog around intents. Ship a public capability schema, harden deep links to drop users into the right flow, and align growth with completion metrics. Two quotable truths: “Capabilities route, not keywords.” “Completion rate is the new CTR.”
TL;DR
- Optimize intents, not keywords; publish precise capabilities the assistant can execute.
- APIs and reliability outrank screenshots; specify inputs, outputs, and fallbacks.
- Shift KPIs to routing share and completion rate over installs.
- Trust signals and verification determine tie-breaks among similar apps.
- Design deep links for task handoff so users land in the exact outcome flow.