What does "Bounce Rate" mean?
Definition of Bounce Rate in the context of A/B testing (online controlled experiments).
What is Bounce Rate?
In web analytics the classical definition of bounce rate is the proportion of sessions during which a user performed only one action, usually expressed as a percentage bounce rate: Bounce rate(%) = Number of bounces / Number of sessions x 100. It varies from platform to platform depending on the definition of session and action. In custom implementations a particular measurement team can decide to redefine it by manipulating what user actions are tracked and which of them have an effect on the bounce rate which is why it is important to understand its precise definition in the current case before you start using it to draw conclusions.
Notably, the bounce rate is one of the metrics which gets most affected by faulty or inconsiderate tracking implementations, usually resulting in unrealistically low rates.
The bounce rate is rarely a primary KPI though it can often be used as a secondary KPI or as a part of an Overall Evaluation Criterion. Due to its high signal to noise ratio it can be a useful early predictor of the success or failure of an intervention if the intervention has the capacity to affect it (e.g. an A/B test experimenting with the shopping cart page should not influence bounce rate).
Like this glossary entry? For an in-depth and comprehensive reading on A/B testing stats, check out the book "Statistical Methods in Online A/B Testing" by the author of this glossary, Georgi Georgiev.
Statistical Methods in Online A/B Testing
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