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Data Science & Analytics vocabulary · Metrics and KPIs

Retention

Meaning in data science & analytics, with examples

/rɪˈtenʃən/nounCore term

In data science & analytics, retention means: The ability to keep customers or users coming back over time; also the percentage of them who are still active after a set period, such as 30 days.

In Turkish: elde tutma, retention, tutundurma

How it is used

The mirror image of churn. You measure, improve or drive retention; analysts show it with retention curves and cohort tables, as in 'day-7 retention'. In HR, 'employee retention' means keeping staff.

Example sentences

  1. Day-30 retention for the January cohort was 22%.

  2. The new onboarding flow improved retention in the first two weeks.

Common collocations

  • retention rate
  • improve retention
  • retention curve
  • day-7 retention
  • user retention
  • churnThe loss of customers or users who stop using a product or cancel a subscription during a given period; also the rate at which this happens.
  • cohortA group of users who share a starting point or experience in the same period, such as everyone who signed up in January, and who are followed over time.
  • daily active usersThe number of unique users who use a product at least once on a given day; one of the standard measures of how engaged an audience is.
  • KPIShort for key performance indicator: one of a small number of metrics that a company or team has chosen to measure progress towards its main goals.

This word in other fields

The same English word can have a different meaning in another field:

More terms: Metrics and KPIs

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