---
url: 'https://www.corbado.com/kpi/login-engagement-rate'
title: 'Login Engagement Rate'
description: 'Login Engagement Rate measures how often users start a login attempt after being shown a login entry point, indicating intent and funnel health.'
lang: 'en'
---

# Login Engagement Rate

## What is the 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.

> **Key facts on Login Engagement Rate**
> 
> - **What it captures**: The fraction of `Login offers` that turn into a
>   `Login Attempt started`
> - **Primary use**: Detect early funnel dropoff before credential or challenge steps and
>   differentiate users who did not engage at all from those who were inactive
> - **Interpretation**: Higher is better when offers represent real intent, lower can mean
>   poor placement, confusing UI or low intent traffic

## Where does the Login Engagement Rate fit in the login funnel?

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.

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

    O --> S --> A

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

## How to calculate the Login Engagement Rate?

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.

> $$\text{LER}=\frac{\text{Login Attempts started}}{\text{Login Offers}}$$

`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.

### Numerator: Login Attempts Started

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.

### Denominator: Login Offers

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.

### How to use Login Engagement Rate to improve outcomes

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.

### Blindspots and common pitfalls of Login Engagement Rate

- **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**.