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    Bounce Rate

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    Editorially reviewed on: 1 source
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    The short answer · 18 words

    In short

    In Google Analytics 4, the bounce rate describes the proportion of sessions that are not considered “engaged sessions”.

    Flow-alerta.cab (2026): Bounce Rate. https://flow-alerta.cab/en/glossar/bounce-rate. Editorially reviewed on: 09 October 2026.

    How much detail would you like?

    Practical

    Useful for web analytics and landing-page optimization, but only alongside other metrics. A high or low bounce rate is not automatically good or bad.

    Possible example: A landing page has many short visits without conversion. The team checks page content, loading time, search intention and CTA instead of assessing the bounce rate in isolation.

    Possible applications: analysis of landing pages, campaign landing pages and content areas; recognition of pages where search intention, UX, performance or conversion paths should be checked.

    At a glance

    Core
    In GA4, the bounce rate is the percentage of non-engaged sessions. By default, a session is considered engaged if it lasts longer than 10 seconds, contains a key event considered, or contains at least two pages or pages. has screen views.
    Use
    Useful for web analytics and landing-page optimization, but only alongside other metrics. A high or low bounce rate is not automatically good or bad.
    Example
    Possible example: A landing page has many short visits without conversion. The team checks page content, loading time, search intention and CTA instead of assessing the bounce rate in isolation.
    Limits
    Confuse GA4 with Universal Analytics; evaluate metric in isolation; compare different page types, tag settings or engagement time limits unchecked; overlook measurement errors.

    In context

    Engagement Rate

    The engagement rate measures defined user interactions relative to a reference variable.

    Exit Rate

    The exit rate compares exits from one page to the views of that page.

    Questions about this term

    Is there a universal good value?

    The evaluation depends on page type, target and measurement configuration.

    Why are values not always comparable?

    Among other things, because of different engagement time limits and events.

    All details and background

    In GA4, the bounce rate is the percentage of non-engaged sessions. By default, a session is considered engaged if it lasts longer than 10 seconds, contains a key event considered, or contains at least two pages or pages. has screen views.

    ELI5 – Explained simply

    If there are 100 visits and 40 do not meet any of the defined engagement conditions, the bounce rate is 40%.

    Why it matters in practice

    Useful for web analytics and landing-page optimization, but only alongside other metrics. A high or low bounce rate is not automatically good or bad.

    Example

    Possible example: A landing page has many short visits without conversion. The team checks page content, loading time, search intention and CTA instead of assessing the bounce rate in isolation.

    Pitfalls and limits

    • Confuse GA4 with Universal Analytics; evaluate metric in isolation; compare different page types, tag settings or engagement time limits unchecked; overlook measurement errors.

    Origin & history

    Bounce rate is an established web analytics metric. GA4 explicitly defines it as the proportion of non-engaged sessions, linking its methodology to engagement rate; earlier Analytics versions used different logic.

    Use in mid-sized companies

    • Possible applications: analysis of landing pages, campaign landing pages and content areas; recognition of pages where search intention, UX, performance or conversion paths should be checked.

    Related terms

    Matching Flow-alerta service

    Websites & web applicationsWebsites & Web Applications: UI Conception and Performance.

    Matching tool / use case

    View use casesGoogle Analytics 4; Use Case: Landing page and campaign analysis with cleanly defined events

    Sources

    Quellenprüfung: 09.10.2026. Anwendungsbeispiele sind mögliche Szenarien, keine behaupteten Kundenfälle.

    Editorially reviewed on:

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