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Konstantin Khalyushev
ENRUESPT

Retention

Day 1 install retention

Of everyone who installed, the share who opened the app again the next day.

This measures whether anyone came back. Subscription retention measures whether a paying subscription survived. They share the word 'retention' and nothing else.

Denominator
installs
Cohort
an install cohort
Time horizon
day 1
Sources
2
Observations
24

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Can these be compared?

Roughly comparable

The same thing is being measured, but at least one condition differs. Read the direction, not the gap.

These observations cannot be combined into one figure, so they are shown separately. Different platforms: cross-platform vs iOS.

Adjust — Insights into what makes a good mobile app retention rate 2024

Published 2024-04-16 · 15 observations

Sample
Adjust's measurement data across its client apps, all verticals combined for the platform figures and broken out by vertical and region elsewhere. The published article does not state a sample size.
How it is aggregated
Stated as median retention rates across verticals for the overall and platform figures. Vertical breakdowns are described in the article as 'average', so the statistic is not consistent throughout.
Measurement period
Not stated in the published article.
Denominator
installs

26%

Median

Evidence Sample, statistic and metric definition all stated by the publisher.

Methodology
Stated as the median across all verticals combined, broken out by platform. Adjust defines a 'day' as a rolling 24-hour period measured from install, not a calendar day. Tools that bucket by calendar date read slightly lower.
As published
“Overall, retention rates across all platforms and verticals drop to 26% on day 1. By day 7, they hit 13%, and by day 14, they sit at 10%. At the end of the 30 days, the rate settles at 7%.”

Adjust — Insights into what makes a good mobile app retention rate 2024Published 2024-04-16What is a good retention rate? · All platforms and verticals

27%

Median

  • iOS

Evidence Sample, statistic and metric definition all stated by the publisher.

Methodology
Adjust defines a 'day' as a rolling 24-hour period measured from install, not a calendar day. Tools that bucket by calendar date read slightly lower.
As published
“iOS shows higher retention rates, with 27% on day 1, 14% on day 7, and 11% on day 14. By day 30, iOS maintains an 8% retention rate.”

Adjust — Insights into what makes a good mobile app retention rate 2024Published 2024-04-16What is a good retention rate? · iOS

24%

Median

  • Android

Evidence Sample, statistic and metric definition all stated by the publisher.

Methodology
Adjust defines a 'day' as a rolling 24-hour period measured from install, not a calendar day. Tools that bucket by calendar date read slightly lower.
As published
“The decline is slightly more pronounced for Android users, with a 24% retention rate on day 1, 11% on day 7, and 8% by day 14. By day 30, the Android retention rate is 6%.”

Adjust — Insights into what makes a good mobile app retention rate 2024Published 2024-04-16What is a good retention rate? · Android

29%

Average

  • Gaming

Evidence The publisher's own labelling is inconsistent for this figure. Treat it as indicative only.

Methodology
The article describes vertical figures as averages while its platform figures are medians, and does not explain the change. Adjust defines a 'day' as a rolling 24-hour period measured from install, not a calendar day. Tools that bucket by calendar date read slightly lower.
Comparability
Statistic is inconsistent with the same article's global figures, so a vertical number and a global number from this source should not be differenced.
As published
“Gaming: day 1 retention rate of 29%.”

Adjust — Insights into what makes a good mobile app retention rate 2024Published 2024-04-16Day 1 retention rates by vertical

29%

Average

  • Social

Evidence The publisher's own labelling is inconsistent for this figure. Treat it as indicative only.

Methodology
The article describes vertical figures as averages while its platform figures are medians, and does not explain the change. Adjust defines a 'day' as a rolling 24-hour period measured from install, not a calendar day. Tools that bucket by calendar date read slightly lower.
Comparability
Statistic is inconsistent with the same article's global figures, so a vertical number and a global number from this source should not be differenced.
As published
“Social: day 1 retention rate of 29%.”

Adjust — Insights into what makes a good mobile app retention rate 2024Published 2024-04-16Day 1 retention rates by vertical

27%

Average

  • Health & Fitness

Evidence The publisher's own labelling is inconsistent for this figure. Treat it as indicative only.

Methodology
The article describes vertical figures as averages while its platform figures are medians, and does not explain the change. Adjust defines a 'day' as a rolling 24-hour period measured from install, not a calendar day. Tools that bucket by calendar date read slightly lower.
Comparability
Statistic is inconsistent with the same article's global figures, so a vertical number and a global number from this source should not be differenced.
As published
“Health & Fitness: day 1 retention rate of 27%.”

Adjust — Insights into what makes a good mobile app retention rate 2024Published 2024-04-16Day 1 retention rates by vertical

22%

Average

  • Fintech

Evidence The publisher's own labelling is inconsistent for this figure. Treat it as indicative only.

Methodology
The article describes vertical figures as averages while its platform figures are medians, and does not explain the change. Adjust defines a 'day' as a rolling 24-hour period measured from install, not a calendar day. Tools that bucket by calendar date read slightly lower.
Comparability
Statistic is inconsistent with the same article's global figures, so a vertical number and a global number from this source should not be differenced.
As published
“Fintech: day 1 retention rate of 22%.”

Adjust — Insights into what makes a good mobile app retention rate 2024Published 2024-04-16Day 1 retention rates by vertical

18%

Average

  • Shopping

Evidence The publisher's own labelling is inconsistent for this figure. Treat it as indicative only.

Methodology
The article describes vertical figures as averages while its platform figures are medians, and does not explain the change. Adjust defines a 'day' as a rolling 24-hour period measured from install, not a calendar day. Tools that bucket by calendar date read slightly lower.
Comparability
Statistic is inconsistent with the same article's global figures, so a vertical number and a global number from this source should not be differenced.
As published
“Shopping: day 1 retention rate of 18%.”

Adjust — Insights into what makes a good mobile app retention rate 2024Published 2024-04-16Day 1 retention rates by vertical

16%

Average

  • Travel

Evidence The publisher's own labelling is inconsistent for this figure. Treat it as indicative only.

Methodology
The article describes vertical figures as averages while its platform figures are medians, and does not explain the change. Adjust defines a 'day' as a rolling 24-hour period measured from install, not a calendar day. Tools that bucket by calendar date read slightly lower.
Comparability
Statistic is inconsistent with the same article's global figures, so a vertical number and a global number from this source should not be differenced.
As published
“Travel: day 1 retention rate of 16%.”

Adjust — Insights into what makes a good mobile app retention rate 2024Published 2024-04-16Day 1 retention rates by vertical

13%

Average

  • Food & Drink

Evidence The publisher's own labelling is inconsistent for this figure. Treat it as indicative only.

Methodology
The article describes vertical figures as averages while its platform figures are medians, and does not explain the change. Adjust defines a 'day' as a rolling 24-hour period measured from install, not a calendar day. Tools that bucket by calendar date read slightly lower.
Comparability
Statistic is inconsistent with the same article's global figures, so a vertical number and a global number from this source should not be differenced.
As published
“Food & Drink: day 1 retention rate of 13%.”

Adjust — Insights into what makes a good mobile app retention rate 2024Published 2024-04-16Day 1 retention rates by vertical

26%

Median

  • APAC

Evidence One of sample, statistic or definition is missing or ambiguous.

Methodology
Adjust defines a 'day' as a rolling 24-hour period measured from install, not a calendar day. Tools that bucket by calendar date read slightly lower.
As published
“Day 1 retention in APAC: 26%.”

Adjust — Insights into what makes a good mobile app retention rate 2024Published 2024-04-16Retention rates by region · Day 1

24%

Median

  • Europe

Evidence One of sample, statistic or definition is missing or ambiguous.

Methodology
Adjust defines a 'day' as a rolling 24-hour period measured from install, not a calendar day. Tools that bucket by calendar date read slightly lower.
As published
“Day 1 retention in Europe: 24%.”

Adjust — Insights into what makes a good mobile app retention rate 2024Published 2024-04-16Retention rates by region · Day 1

26%

Median

  • LATAM

Evidence One of sample, statistic or definition is missing or ambiguous.

Methodology
Adjust defines a 'day' as a rolling 24-hour period measured from install, not a calendar day. Tools that bucket by calendar date read slightly lower.
As published
“Day 1 retention in LATAM: 26%.”

Adjust — Insights into what makes a good mobile app retention rate 2024Published 2024-04-16Retention rates by region · Day 1

23%

Median

  • North America

Evidence One of sample, statistic or definition is missing or ambiguous.

Methodology
Adjust defines a 'day' as a rolling 24-hour period measured from install, not a calendar day. Tools that bucket by calendar date read slightly lower.
As published
“Day 1 retention in North America: 23%.”

Adjust — Insights into what makes a good mobile app retention rate 2024Published 2024-04-16Retention rates by region · Day 1

24%

Median

  • MENA

Evidence One of sample, statistic or definition is missing or ambiguous.

Methodology
Adjust defines a 'day' as a rolling 24-hour period measured from install, not a calendar day. Tools that bucket by calendar date read slightly lower.
As published
“Day 1 retention in MENA: 24%.”

Adjust — Insights into what makes a good mobile app retention rate 2024Published 2024-04-16Retention rates by region · Day 1

Adjust — Mobile app retention benchmarks for 2023 2023

Published 2023-01-01 · 9 observations

Sample
Adjust measurement data covering calendar year 2022, reported globally and by region and vertical. No sample size stated.
How it is aggregated
Explicitly stated as median global retention rates, with 2021 medians given for comparison.
Measurement period
Calendar year 2022.
Denominator
installs

25%

Median

  • Calendar year 2022

Evidence Sample, statistic and metric definition all stated by the publisher.

Methodology
Explicitly stated as median global retention rates for calendar year 2022. Adjust defines a 'day' as a rolling 24-hour period measured from install, not a calendar day. Tools that bucket by calendar date read slightly lower.
As published
“Day 1, Day 14, and Day 30 all saw a percentage drop of 1%, revealing median 2022 global retention rates to be 25%, 9%, and 6%, respectively.”

Adjust — Mobile app retention benchmarks for 2023 2023Published 2023-01-012022 global retention rates

29%

Median

  • Gaming
  • Calendar year 2022

Evidence Sample, statistic and metric definition all stated by the publisher.

Methodology
Explicitly stated as median global retention rates for calendar year 2022. Adjust defines a 'day' as a rolling 24-hour period measured from install, not a calendar day. Tools that bucket by calendar date read slightly lower.
As published
“gaming app Day 1 retention rates were the highest of all verticals in 2022 at 29%, followed by hyper casual at 26%, health & fitness at 24%, with both lifestyle and social apps at 23%. Trailing, e-commerce apps in 2022 saw a Day 1 retention rate of 19%, travel at 15%, and food & drink apps at 12%.”

Adjust — Mobile app retention benchmarks for 2023 2023Published 2023-01-012022 Day 1 retention by vertical

26%

Median

  • Hyper casual
  • Calendar year 2022

Evidence Sample, statistic and metric definition all stated by the publisher.

Methodology
Explicitly stated as median global retention rates for calendar year 2022. Adjust defines a 'day' as a rolling 24-hour period measured from install, not a calendar day. Tools that bucket by calendar date read slightly lower.
As published
“gaming app Day 1 retention rates were the highest of all verticals in 2022 at 29%, followed by hyper casual at 26%, health & fitness at 24%, with both lifestyle and social apps at 23%. Trailing, e-commerce apps in 2022 saw a Day 1 retention rate of 19%, travel at 15%, and food & drink apps at 12%.”

Adjust — Mobile app retention benchmarks for 2023 2023Published 2023-01-012022 Day 1 retention by vertical

24%

Median

  • Health & Fitness
  • Calendar year 2022

Evidence Sample, statistic and metric definition all stated by the publisher.

Methodology
Explicitly stated as median global retention rates for calendar year 2022. Adjust defines a 'day' as a rolling 24-hour period measured from install, not a calendar day. Tools that bucket by calendar date read slightly lower.
As published
“gaming app Day 1 retention rates were the highest of all verticals in 2022 at 29%, followed by hyper casual at 26%, health & fitness at 24%, with both lifestyle and social apps at 23%. Trailing, e-commerce apps in 2022 saw a Day 1 retention rate of 19%, travel at 15%, and food & drink apps at 12%.”

Adjust — Mobile app retention benchmarks for 2023 2023Published 2023-01-012022 Day 1 retention by vertical

23%

Median

  • Social
  • Calendar year 2022

Evidence Sample, statistic and metric definition all stated by the publisher.

Methodology
Explicitly stated as median global retention rates for calendar year 2022. Adjust defines a 'day' as a rolling 24-hour period measured from install, not a calendar day. Tools that bucket by calendar date read slightly lower.
As published
“gaming app Day 1 retention rates were the highest of all verticals in 2022 at 29%, followed by hyper casual at 26%, health & fitness at 24%, with both lifestyle and social apps at 23%. Trailing, e-commerce apps in 2022 saw a Day 1 retention rate of 19%, travel at 15%, and food & drink apps at 12%.”

Adjust — Mobile app retention benchmarks for 2023 2023Published 2023-01-012022 Day 1 retention by vertical

23%

Median

  • Lifestyle
  • Calendar year 2022

Evidence Sample, statistic and metric definition all stated by the publisher.

Methodology
Explicitly stated as median global retention rates for calendar year 2022. Adjust defines a 'day' as a rolling 24-hour period measured from install, not a calendar day. Tools that bucket by calendar date read slightly lower.
As published
“gaming app Day 1 retention rates were the highest of all verticals in 2022 at 29%, followed by hyper casual at 26%, health & fitness at 24%, with both lifestyle and social apps at 23%. Trailing, e-commerce apps in 2022 saw a Day 1 retention rate of 19%, travel at 15%, and food & drink apps at 12%.”

Adjust — Mobile app retention benchmarks for 2023 2023Published 2023-01-012022 Day 1 retention by vertical

19%

Median

  • Ecommerce
  • Calendar year 2022

Evidence Sample, statistic and metric definition all stated by the publisher.

Methodology
Explicitly stated as median global retention rates for calendar year 2022. Adjust defines a 'day' as a rolling 24-hour period measured from install, not a calendar day. Tools that bucket by calendar date read slightly lower.
As published
“gaming app Day 1 retention rates were the highest of all verticals in 2022 at 29%, followed by hyper casual at 26%, health & fitness at 24%, with both lifestyle and social apps at 23%. Trailing, e-commerce apps in 2022 saw a Day 1 retention rate of 19%, travel at 15%, and food & drink apps at 12%.”

Adjust — Mobile app retention benchmarks for 2023 2023Published 2023-01-012022 Day 1 retention by vertical

15%

Median

  • Travel
  • Calendar year 2022

Evidence Sample, statistic and metric definition all stated by the publisher.

Methodology
Explicitly stated as median global retention rates for calendar year 2022. Adjust defines a 'day' as a rolling 24-hour period measured from install, not a calendar day. Tools that bucket by calendar date read slightly lower.
As published
“gaming app Day 1 retention rates were the highest of all verticals in 2022 at 29%, followed by hyper casual at 26%, health & fitness at 24%, with both lifestyle and social apps at 23%. Trailing, e-commerce apps in 2022 saw a Day 1 retention rate of 19%, travel at 15%, and food & drink apps at 12%.”

Adjust — Mobile app retention benchmarks for 2023 2023Published 2023-01-012022 Day 1 retention by vertical

12%

Median

  • Food & Drink
  • Calendar year 2022

Evidence Sample, statistic and metric definition all stated by the publisher.

Methodology
Explicitly stated as median global retention rates for calendar year 2022. Adjust defines a 'day' as a rolling 24-hour period measured from install, not a calendar day. Tools that bucket by calendar date read slightly lower.
As published
“gaming app Day 1 retention rates were the highest of all verticals in 2022 at 29%, followed by hyper casual at 26%, health & fitness at 24%, with both lifestyle and social apps at 23%. Trailing, e-commerce apps in 2022 saw a Day 1 retention rate of 19%, travel at 15%, and food & drink apps at 12%.”

Adjust — Mobile app retention benchmarks for 2023 2023Published 2023-01-012022 Day 1 retention by vertical

Pairwise comparability

The verdict below is produced by a fixed set of rules, not a model. It looks at the metric definition, the denominator, the cohort, the statistic, the segment, the dataset and the publication dates, and reports every reason it found.

Adjust 2024 26%Adjust 2023 25%

Roughly comparable

The same thing is being measured, but at least one condition differs. Read the direction, not the gap.

  • Different sub-segments: not broken out vs calendar year 2022.
  • Different aggregation methods. Adjust 2024: medians across verticals, averages for the vertical cuts. Adjust 2023: medians across verticals.

Adjust 2024 26%Adjust 2023 29%

Roughly comparable

The same thing is being measured, but at least one condition differs. Read the direction, not the gap.

  • Different category scope: not broken out vs Gaming. An all-categories figure is not a substitute for the category you are in.
  • Different sub-segments: not broken out vs calendar year 2022.
  • Different aggregation methods. Adjust 2024: medians across verticals, averages for the vertical cuts. Adjust 2023: medians across verticals.

Adjust 2024 26%Adjust 2023 26%

Roughly comparable

The same thing is being measured, but at least one condition differs. Read the direction, not the gap.

  • Different category scope: not broken out vs Hyper casual. An all-categories figure is not a substitute for the category you are in.
  • Different sub-segments: not broken out vs calendar year 2022.
  • Different aggregation methods. Adjust 2024: medians across verticals, averages for the vertical cuts. Adjust 2023: medians across verticals.

Adjust 2024 26%Adjust 2023 24%

Roughly comparable

The same thing is being measured, but at least one condition differs. Read the direction, not the gap.

  • Different category scope: not broken out vs Health & Fitness. An all-categories figure is not a substitute for the category you are in.
  • Different sub-segments: not broken out vs calendar year 2022.
  • Different aggregation methods. Adjust 2024: medians across verticals, averages for the vertical cuts. Adjust 2023: medians across verticals.

Adjust 2024 26%Adjust 2023 23%

Roughly comparable

The same thing is being measured, but at least one condition differs. Read the direction, not the gap.

  • Different category scope: not broken out vs Social. An all-categories figure is not a substitute for the category you are in.
  • Different sub-segments: not broken out vs calendar year 2022.
  • Different aggregation methods. Adjust 2024: medians across verticals, averages for the vertical cuts. Adjust 2023: medians across verticals.

Adjust 2024 26%Adjust 2023 23%

Roughly comparable

The same thing is being measured, but at least one condition differs. Read the direction, not the gap.

  • Different category scope: not broken out vs Lifestyle. An all-categories figure is not a substitute for the category you are in.
  • Different sub-segments: not broken out vs calendar year 2022.
  • Different aggregation methods. Adjust 2024: medians across verticals, averages for the vertical cuts. Adjust 2023: medians across verticals.

Adjust 2024 26%Adjust 2023 19%

Roughly comparable

The same thing is being measured, but at least one condition differs. Read the direction, not the gap.

  • Different category scope: not broken out vs Ecommerce. An all-categories figure is not a substitute for the category you are in.
  • Different sub-segments: not broken out vs calendar year 2022.
  • Different aggregation methods. Adjust 2024: medians across verticals, averages for the vertical cuts. Adjust 2023: medians across verticals.

Adjust 2024 26%Adjust 2023 15%

Roughly comparable

The same thing is being measured, but at least one condition differs. Read the direction, not the gap.

  • Different category scope: not broken out vs Travel. An all-categories figure is not a substitute for the category you are in.
  • Different sub-segments: not broken out vs calendar year 2022.
  • Different aggregation methods. Adjust 2024: medians across verticals, averages for the vertical cuts. Adjust 2023: medians across verticals.

Related metrics

RetentionCompare your productMethodology and sourcesAll benchmarks