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What passkey analytics is and why teams need it
Passkey analytics helps product, identity, and security teams understand what’s really happening in passkey authentication: where users drop off, which platforms struggle, how adoption evolves over time, and what drives successful passkey login. Standard product analytics often shows only coarse events (page views, “login clicked”), while identity logs focus on backend outcomes. Passkeys introduce new failure modes and UX paths (biometric prompts, credential managers, cross-device flows) that require more specialized visibility.
A practical passkey analytics setup focuses on three outcomes: activation (users create passkeys), usage (users actually log in with passkeys), and reliability (errors, cancellations, platform issues).
Authentication funnel analysis for passkeys
The foundation is an authentication funnel that visualizes real user paths through signup, login, and passkey creation flows. Think of it like process mining for authentication: you can see which screens users hit, which route they take (passkey vs fallback), and where they abandon.
A useful funnel view typically includes KPIs such as rollout progress (who is eligible), creation success (append rate), passkey login success, and fallback frequency. The biggest value is not the chart itself, but how quickly you can answer questions like: “Are users reaching the passkey prompt?”, “Do they complete creation?”, and “Where do they detour into passwords or OTP?”
Common funnel use cases include:
- Implementation validation: confirm the “happy path” works before scaling rollout.
- Passkeys vs legacy comparison: quantify differences in success rate and drop-off between passkey users and fallback users.
- Cross-device flow analysis: identify whether QR and Bluetooth-based cross-device authentication is confusing, error-prone, or being skipped.
You also want segmentation (web vs native, iOS vs Android vs Windows) and trend views so you can spot sudden changes after OS updates or product releases.
Device analytics: who adopts passkeys (and where issues hide)
Device analytics answers “who is using passkeys” with context. A common pattern is to segment users by login frequency (occasional users vs power users) and then compare passkey behavior across those groups. This helps teams avoid misleading averages: strong passkey adoption in power users can coexist with weak adoption in first-time or low-frequency users.
Device analytics should also break down platform and environment:
- OS and OS version distribution
- Browser distribution (for web)
- Passkey readiness (device capability)
- Device authentication configuration (biometrics vs PIN/passcode)
This is often the fastest way to pinpoint platform-specific friction and to ground stakeholder discussions in real data.
Activation analytics: improving passkey creation rates
Activation analytics focuses on passkey creation, usually measured as append rate (how many users create a passkey when shown the creation screen). A key insight is that users don’t always create a passkey on the first prompt. Tracking creation performance across multiple exposures helps teams optimize timing and placement without guessing.
Activation analytics becomes especially valuable when you break results down by OS and version, because passkey creation behavior can vary significantly across environments.
Login analytics: passkey usage rate and speed
Once passkeys exist, you want to measure passkey usage rate (how often users choose passkeys for login) and compare performance against fallback methods. A good analytics view also shows how logins are initiated: passkey autofill (Conditional UI), one-tap entry points, native credential selectors, or traditional “type identifier then authenticate.” If users keep defaulting to text-field login even after creating passkeys, that’s usually a UX discoverability problem, not a passkey problem.
Passkey insights: credential managers, sync, and cross-device capability
Passkeys live in different credential managers (iCloud Keychain, Google Password Manager, Windows Hello, third-party password managers). Passkey insights should show:
- authenticator distribution (what users rely on)
- sync status (whether passkeys carry over to new devices)
- transport capability (local vs cross-device “hybrid” flows)
- time-series changes (to catch shifts after OS updates)
This is where many teams discover hidden constraints, like segments that end up device-bound and therefore struggle during device changes.
Why generic analytics tools fall short
Tools like GA4 or Mixpanel can track basic events, but they typically lack passkey-specific visibility (credential manager mix, sync state, cross-device flows) and often introduce delays or limits that make troubleshooting harder. Many teams end up combining generic product analytics (journey context) with dedicated passkey observability (auth detail).
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