Login Engagement Rate

Login Engagement Rate measures the share of login opportunities where a user actually starts a login attempt. It tells us whether people who are presented with a sign in entry point choose to engage, which is an early signal of intent, usability and whether login is being shown at the right time.

We start measuring when we show a login entry point that the user can act on and we end measuring when the user initiates any login method. Measurement boundary sentence, we count an offer only after it is rendered and interactive and we count a start only when the user action triggers the first authentication step.

flowchart LR
    O((Offer Login))
    S((Start Login))
    A((Authenticated))

    O --> S --> A

    O -. "LOGIN ENGAGEMENT RATE" .-> S

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We calculate Login Engagement Rate per login offer instance. Each offer is counted once, even if the user taps multiple times, and each started attempt is tied back to the offer that preceded it.

Login Attempts started is how many offers resulted in a start event. Login Offers is how many times we presented a login entry point that could be used.

Typical ranges vary by product and when login is shown, but many teams treat the following as a starting benchmark.

Counts when a user takes an explicit action that initiates login, for example tapping Sign in, continuing to a method or triggering the first challenge request. Do not count passive page views, auto redirects that do not require a user action or retries that happen after a start unless you can reliably link them to the same offer.

Counts when the login entry point is visible and usable, for example a login screen render, a modal shown or a protected page that presents a sign in prompt. Do not count background preloads, hidden UI states, or repeated renders caused by layout thrash.

We use Login Engagement Rate to increase the number of users who begin authentication when it is appropriate, without inflating low intent prompts.

We can improve the following business outcomes:

• Higher successful sign ins that reach the intended authenticated state, diagnose low engagement at key entry points, change copy and placement, validate by confirming engagement rises for the same entry point mix.
• Lower user dropoff during authentication, diagnose hesitation before users even start, change the first screen clarity and method defaults, validate with session replays and a sustained lift over a full traffic cycle.
• Lower support contacts caused by authentication issues, diagnose confusion about when login is required, change error messaging and requirement cues, validate with fewer contacts tagged as login confusion and stable engagement.
• Better operational cost through fewer retries, diagnose users repeatedly reloading without starting, change performance and render stability, validate by reduced duplicate offers per session and higher engagement.

• Intent and selection bias: Showing login to low intent visitors can push Login Engagement Rate down even if the login flow is excellent.
• Missing telemetry or inconsistent logging: If Login Offers fires but Login Attempts Started is dropped on some clients, Login Engagement Rate will look artificially low.
• Mix shifts across segments: A shift toward new users, a new entry point, or a specific platform can change Login Engagement Rate without any true product regression.
• Offer inflation: Re rendering the login UI multiple times per visit inflates Login Offers and depresses Login Engagement Rate.

Report Login Engagement Rate by entry point, platform, app version, traffic source, and user state. Always pair the rate with counts of Login Offers so small sample segments do not drive decisions.