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SB05: How many active users does the Corona-Warn-App have?

CWA Team, on July 29, 2022, last updated March 3, 2022 (German version)
  1. The most important points at a glance: Numbers, data, facts
  2. The CWA serves its purpose and is effective
    1. Purpose 1 – Accessing the test result
    2. Purpose 2 – Warning others
    3. Purpose 3 – Risk assessment
  3. Downloads and use of the Corona-Warn-App
    1. What are active users?
    2. Use of the core functionality
  4. Estimations of the active users
    1. From the number of individuals providing a warning
    2. From the CWA data donation
    3. From a heuristic
  5. Key figures from the CWA backend
  6. Key figures relating to the use from the stores
    1. Google Play Store
    2. Apple App Store
  7. Comparison of the information relating to active users
  8. Conclusion
  9. What comes next

1 The most important points at a glance: Numbers, data, facts

  • The Corona-Warn-App was downloaded 43.2 million times (as of: February 27, 2022).

  • The updated analysis relating to the effectiveness of the CWA highlights its importance in quickly ending chains of infection:

    • Test results are reported back quickly by means of the CWA. Approximately 270 laboratories and more than 20,000 test sites (source: T-Systems International) are currently connected to the CWA and can submit results directly to the backend of the CWA . Based on the data from the CWA data donation it can be shown that test results are submitted into the CWA on average 20 hours after test registration, half of them within 13 hours (median).
    • Individuals are warned quickly by means of the CWA. On average, the warning about contact with a verifiably infected person was received 4.2 days after the exposure (half of them within 4 days. Warned individuals get tested on average 4.4 days after the warning (half of them within 1.7 days)
    • Almost 2.9 million CWA users have already shared a positive test result via the CWA and have thus warned other users. Based on insights from the data donation, it can be estimated that for each individual providing a warning, 19 individuals receive a red warning.
    • The CWA ends chains of infection: Approximately every fifth individual who had received a red warning at the time of the test registration (PCR), tested positive for SARS-CoV-2. - A current analysis of the pandemic occurrence at the beginning of 2022 showed that approximately 17% of all positive Corona test results in Germany were accessed and shared in the CWA and that other users were thus warned promptly and without involving third parties.
  • The number of individuals providing a warning yields an estimation for the number of active users of 27 million (as of: February 27, 2022, CI: 21 million – 33.3 million).

  • The data from the data donation yields an estimation for the number of active users of 31 million (as of: February 27, 2022, CI: 25.8 million – 33.6 million).

  • According to the data from the Google Play Store, the number of active apps/devices is 16.5 million, the number of ‘active users’ (according to the Google definition) is 15.2 million, and the number of (monthly) active users is 13.5 million (as of: February 26, 2022).

  • The number of monthly active users from the Apple App Store can be projected to be 11.6 million (as of: February 27, 2022).

  • This results in a total of 25.1 million (monthly) active users or 28.1 million (monthly) active devices (as of: February 26, 2022) from the App Stores.

  • An analysis of CWA backend data over 46 days (from December 4, 2021, to January 19, 2022) resulted in 24.9 million active users or 27.9 million active devices, respectively (as of January 19, 2022; with 112 devices per 100 users).

  • In a European comparison of the ratio between downloads and active users, the Corona-Warn-App thus holds a leading position.

2 The CWA serves its purpose and is effective

At this point, we want to take the opportunity to compile and to update the aspects presented in the blog ‘About the Effectiveness and Benefits of the Corona-Warn-App’. Additional insights can be gained relating to the effectiveness of the CWA and to its significance for containing the pandemic, in particular in view of the estimations of the number of active users compiled in that post. Some of these key figures are also available on a daily basis via the CWA dashboard.

2.1 Purpose 1 – Accessing the test result

A total of 150,788,351 test results were submitted to the CWA backend system (as of: March 1, 2022), 15,191,927 of which were positive, 133,991,100 negative, and 1,292,683 invalid. Of the positive test results, 4,069,825 were accessed via the CWA and 2,603,206 were shared. In addition, a teleTAN was issued for 262,546 positive tests, and 254,374 of them were shared.

The difference between the positive test results provided in the CWA backend and those accessed via the CWA results from the fact that the consent for submitting the test result to the CWA was checked when commissioning the SARS-CoV-2 testing, but the tested individual either did not install or did not use the CWA, respectively, or did not receive a QR code in order to register the test in the CWA, and to then access the result via the CWA. As a result, the test result remained in the backend. The 27% accessed and 19% shared (positive) test results allow for an estimation of the active users from the number of individuals providing a warning in consideration of the known share rate and are in line with the expected range. At the same time, it can also be seen that the large potential of the Corona-Warn-App is not yet utilized completely. To do so, even more individuals, who download and use the CWA, could be informed about the option of test registration and of accessing the result in the CWA, for example by doctors and test sites.

The chronological sequence (daily and 7-day average) of the above-mentioned key figures (and by comparison also of the SARS-CoV-2 new infections) is illustrated in the following figure (in logarithmic illustration).

Tests provided and accessed via the CWA and their results.

The data from the CWA data donation shows that a PCR test result is submitted on average 20 hours after test registration (half of them within 13 hours).

Time delay between test registration and receipt of the test result (PCR).

The provision of test results (PCR tests and rapid antigen tests (RAT)) thus occurs extensively and quickly.

2.2 Purpose 2 – Warning others

The following figure specifies the chronological sequence of the individuals providing a warning and of those who are warned via the CWA (in logarithmic illustration). While the number of individuals providing a warning is known from the CWA ecosystem, only the CWA data donation can be resorted to as data source for the number of warned individuals. Since March 5, 2021 (beginning of the CWA data donation) 27,307,066 red warnings and 17,571,796 green warnings were already submitted (as of: February 28, 2022).

The brief slump of the number of individuals who received a red warning in the middle of August was caused by a comparable slump of the CWA data donation data due to technical problems (see also blog 4, 4.3).

Since March 5, 2021 (for comparisons with data from the CWA data donation, we must consider the point in time, since when this data has been available), 2,572,787 individuals have warned others via the CWA, from which we can conclude that there were approximately 19 (red) warned individuals per individual providing a warning (as of February 28, 2022). There was an average value of 12 (green) warned individuals per individual providing a warning results for warnings without an increased risk. In the last 30 days, these ratios were 23 or 13, respectively. The chronological sequence of individuals who received a red and green warning per individual providing a warning is indicated in the following figure.

Number of individuals who received a red and green warning per individual providing a warning in chronological sequence.

The occasional high spikes (in June, middle of August, and middle of October) resulted from brief slumps of the CWA data donation (with subsequent supply; see also blog 4, 4.3).

It is important for the effectiveness of the warnings with regard to ending chains of infection that the warned individuals are also warned promptly. On average, the warning was received 4.2 days after the exposure (half within 4 days).

It is just as important that the warned individuals adapt their behaviour after warnings from the Corona-Warn-App, in that they start to quarantine and get tested. 27,307,066 (in the last 30 days 14,713,346) red warnings were registered via the CWA data donation. Valid statements about the percentage of those, who get tested after a red warning, cannot be obtained via the available sources, in particular because individuals often also take a test themselves. As part of the event-related user survey (EDUS) in the spring of 2021, the majority (65.1%) of the respondents of the base survey indicated wanting to get tested for SARS-CoV2 due to a red warning (see ibidem, Table 12). An additional 15.8% made this dependent on medical advice or advice from a public health authority, which generally results in a test recommendation. In the follow-up survey, in which almost 60% of the participants of the base survey participated, 87% indicated having in fact taken a test as a result of the red warning. No data is available relating to the test rate of those participants of the base survey who did not participate in the follow-up survey (see ibidem, Table 16). When looking only at registered tests, the following evaluation is obtained: According to this, a total of 4,341,891 test results (in the last 30 days 2,144,859) that had an increased risk at the time of the test registration (as of: February 28, 2022), were registered during the observed time period (via the CWA data donation). Of the registered PCR tests (which had an increased risk at the time of the test registration), 36.4% were positive (in the last 30 days 53.5%), among the registered rapid antigen tests, the positivity rate was 2.6% (in the last 30 days it was 3.8%). A total of 11.7% (in the last 30 days 14.1%) of the warned individuals thus tested positive. Warned individuals get tested on average 4.4 days after the warning (half of them within 1.7 days).

The specified numbers correspond well to the insights from the event-related user survey (EDUS) from the spring of 2021. There, approximately 13,000 of approximately 26,000 participants (all of whom had received a red warning) submitted information relating to their test results. Among them, a total of 5.9% tested positive. The positivity rate using the PCR tests was 13%, using the rapid antigen tests, it was 0.3% (ibidem, Tables 15 and 17).

The warnings by means of the CWA thus also take place extensively, adequately, and in a timely manner.

2.3 Purpose 3 – Risk assessment

Approximately every fifth individual, who had received a red warning at the time of the test registration (PCR), tested positive for SARS-CoV-2. Among those without risk assessment, the percentage was significantly lower to some extent (see figure and blog 4, 6.5).

Positivity rate after risk notification in chronological sequence (PCR).

The high positivity rate from the test number collection by the RKI and for individuals without increased risk since November of 2021 can be explained by the high infection rates in this phase of the pandemic and also suggests a high utilization of the laboratories. A PCR test is only performed when there is reasonable suspicion. Due to the fact that many individuals are infected, this suspicion is often confirmed in fact.

In the case of rapid antigen tests, this ratio is even more convincing.

Positivity rate after risk notification. The number of new infections in chronological sequence (RAT).

The warnings from the CWA are thus precise and reliable, in spite of the known shortcomings of the BLE technology. The CWA warns the right individuals.

The significance of the CWA can also be illustrated in the current pandemic occurrence. The number of nationwide new infections in the last 7 days was 1,007,987 (as of: February 28, 2022). During the same time period, 1,388,486 positive Corona test results were submitted into the backend of the CWA, and 330,228 were accessed there by CWA users (23.8%). Of those, around two-thirds (70.7%) were shared, in turn. A total of almost 16.8% of the positive tests in Germany within the CWA were thus used and shared in order to warn others (in the last 7 days, 233,377 individuals). Assuming that for each person providing a warning, 23 CWA users receive a red warning (this value was higher during the last 30 days than observed over the entire time period), this results currently in approximately 5,367,700 individuals who received a red warning, of which approximately 15% get tested, and register their result via the CWA. In addition, it can be assumed that another 72% get tested (largely also officially, see above), but cannot register their test result in the CWA. Of this total of approximately 3,887,000, approximately 14.1% and thus up to 548,500 additional CWA users test positive. Due to the quick warning and the prompt behaviour adaptations of potentially infected CWA users, chains of infection are ended early by means of the CWA.

An exact estimate of the ended chains of infection or of the prevented cases, respectively, is only possible as part of a simulation or modelling. The actual situation has to be compared to a virtual (hypothetical) one thereby, in which there is for example no CWA test. This is planned for a future blog post.

In summary, the current evaluation shows that the CWA plays an important role in the containment of the pandemic. Due to the direct reporting of test results into the CWA and the brief time window between the exposure and warning, infections can be uncovered promptly and without involving third parties and can thus be ended as quickly as possible. As an aside, it is important to note that the early detection of an infection is also advantageous for the affected individual himself/herself, in particular when this individual has an increased risk for a severe progression of the disease and benefits from an early systematic therapy.

3 Downloads and use of the Corona-Warn-App

We were able to show in the above analysis and in the past blog posts that the Corona-Warn-App (CWA) ends chains of infection successfully and quickly. The benefit of the CWA for the general public is thereby larger, the more people use the app. It is thus important to take a closer look at the popularity, dissemination, and use of the CWA in Germany. Different key figures (metrics) can be used for this.

A central indicator for the dissemination of an app is the number of its downloads or of the percentage of the general public, respectively, that downloaded the app. The Corona-Warn-App was downloaded 43.2 million times (as of: February 27, 2022). This corresponds to 52.1% of the general public or to 72% of the individuals over the age of 15, who have a smartphone, respectively.

3.1 What are active users?

To evaluate the benefit of the Corona-Warn-App, it is important to know how many users actively use the core functionality. We call this the active use in the narrower sense. This key figure can be determined by means of corresponding monitoring of backend activities. While some countries decided on such monitoring, this did not happen in Germany with reference to the decentralised approach of the CWA. We will provide two estimations for this later (from the number of individuals providing a warning as well as from the data from the data donation).

During the first months after the introduction of the CWA, the number of first-time downloads was a good approximation, but has to be viewed as an increasingly bad approximation over time because the CWA can be deleted from a smartphone or because an old smartphone is replaced by a new one, on which the CWA is installed again under a new account. We will provide an estimation of the active users from a heuristic further below, which clarifies this increasing deviation between downloads and active users or active apps/devices, respectively.

In addition, the Corona-Warn-App has been expanded by many additional features over time (see Table 1). It is likewise not determined whether users maybe only use the contact diary (starting with Release 1.10), the range of information (starting with Release 1.11), the check-in function for events (starting with Release 2.0) or the certificate management (starting with Release 2.3) in the CWA.

In the case of the active use in the broader sense it is not differentiated, which features are used. Someone is thus counted as an active user, as long as any feature is used (e.g. exclusive use of the certificate verification), regardless of whether the core functions are used.

The key features identified by the Apple App Store and Google Play Store are defined differently and are measured differently, often relate only approximately to the same facts and can thus not be totalled or compared directly. In addition, special care must be taken: The term ‘active users’ is defined completely different (homonym) there than in this blog and represents something which we could call potential users. In addition to the differentiation between users and devices, the concept of a user in terms of an account also exists, which additionally complicates matters. Where they refer to the use, these key figures can also describe at least only the active use in the broader sense. We will thus separately describe the numbers of the stores as well.

Table 1: Releases of the CWA and the essential features thereof.
Release Functions implemented in the CWA
1.0 Core functionalities (proximity tracing via Bluetooth LE, sharing of positive Corona test results, warning other users), counting active days
1.1 Text adaptations, improving the accessibility, translation: Turkish
1.2 Permitting screenshots, translation: Bulgarian, Polish, Romanian
1.3 Additional information relating to the risk status, text improvement in the case of indicated low risk of infection, correcting the legal texts
1.5 Supporting the European Corona-App-Gateway, voluntary symptom assessment, improving the text comprehensibility
1.6 More detailed explanation when changing the risk status
1.7 Risk review can be performed several times each day, reminder function for sharing positive test results via CWA
1.9 Converting to G/A-ENF Version 2, improving the risk assessment, improving the process of scanning the test results until sharing the diagnostic keys
1.10 Contact diary
1.11 Key figures relating to the infection
1.12 Expanding the contact diary (encounter history), supporting the iPhones 5s, 6 and 6 Plus
1.13 Voluntary data donation (Privacy-Preserving-Analytics (PPA))
1.14 Expanding the contact diary (pop-up menu, among others), expanding the voluntary data donation (new data points)
1.15 Cross-country risk submission (Switzerland), changing the risk map
2.0 Event registration (check-in)
2.1 Integrating rapid antigen tests
2.2 Rapid antigen test profile and error reports
2.3 Integrating the digital proof of vaccination
2.4 Test certificates for rapid antigen tests and PCR tests, digital EU test certificate, expanding contact diary (automated entry of test results), expanding the voluntary data donation (new data points)
2.5 Certificates of recovery, certificate for family members, key figures relating to the vaccination progress in Germany
2.6 Expanding the key figures (local 7-day incidence for up to five counties or districts, respectively), EU certificate verification, processing the rapid antigen test profiles
2.7 Automatically verifying the signature of vaccination certificates, certificates of recovery, and test certificates for authenticity as well as displaying its technical expiration date
2.8 Standardised spelling of the personal names in certificates, adapting the EU certificate verification
2.9 Representative warning and proof of booster shots
2.10 Rules and information relating to booster shots, certificate as PDF document
2.11 Universal QR code scanner, import function of QR codes from images or PDF documents (Android)
2.12 Direct central access to QR code scanners, expanding the displayed key figures (7-day incidence of hospitalisations, people with COVID-19 in intensive care units), import function of QR codes from images or PDF documents (iOS)
2.13 Recycle bin function for certificates, expanding the displayed key figures (local 7-day incidence of hospitalisations), improving the algorithm for the certificate mapping
2.14 Recycle bin function for PCR tests and rapid antigen tests
2.15 Revising the suggestions in the case of status display ‘increased risk’ (red tile), validation service of vaccination certificates, certificates of recovery, and test certificates
2.16 Updating the proof of status for certificate
2.17 Statistics relating to booster shots, recycle bin indicates deletion date, link to the social media channels of the CWA, revising the information on how to proceed in the case of positive PCR and rapid antigen test result, information about the change of the risk status (Android)
2.18 Updating and differentiating the proofs of status, revising the representation and information of the proofs of status, revising the certificate management, determining the status of the booster shots

3.2 Use of the core functionality

In order to determine the difference between active users in the narrower and broader sense, we can take a look at the data from the CWA data donation. In addition to the information relating to red and green warnings, there is also information relating to ‘white tiles’. This is the information, with which an evaluation of the risk is not possible. There can be various reasons for this: missing network connections, not enough days of recording encounters or also an intentional deactivation of the exposure logging. The core functionality cannot be used in each of these cases.

Fraction of users, for whom the risk determination is not possible (CWA data donation).

We can see that there are approximately 3.4% of users, who do not use the core functionality of the CWA. The difference between users in the narrower and broader sense is thus very small. It could be higher among those who do not participate in the CWA data donation. However, no data is available for this.

4 Estimations of the active users

Based on the mentioned limitations, the number of active users cannot be determined precisely, but can only be estimated with the help of different methods and sources. We specify three different estimations, based on the data relating to the number of individuals providing a warning, the CWA data donation and a heuristic approximation.

4.1 From the number of individuals providing a warning

A first option for estimating the active users (in the narrower sense) follows from a comparison of the number of individuals providing a warning (individuals who tested positive, who share their keys via the CWA) with the number of new infections in Germany submitted to the RKI. The following figure shows the virtually parallel course of these key figures.

Individuals providing a warning adapted to new infections.

A constant ratio of the percentage of the individuals providing a warning among the newly infected individuals was assumed hereby. However, this ratio has in fact developed over time. The difference at the end can be explained by the missing delay in reporting among the individuals providing a warning (and the data provision via the CWA ecosystem) compared to the established reporting system. In the case of the new infections, we should furthermore disregard the younger age groups because they are not assumed to be users of the CWA due to the age limitation (use authorization from the age of 16). The mentioned percentage— and thus the estimation — likewise depends on the share rate, that is, which percentage of those who register a test via the Corona-Warn-App, receive their test result and then also share it with others. These rates are illustrated in the following figure.

Share rate and ratio of individuals providing a warning to new infections (in consideration of the age limit).

If we now assume that the ratio of individuals providing a warning to new infections behaves exactly the same way as the ratio of the active users (in the narrower sense) to the (relevant) general public in consideration of the share rate (whereby we estimate 83 million for the general public or 60 million for the potential individuals who download, respectively (that is, individuals from the age of 15, who have a smartphone)):

Mathematische Formel

We can determine the number of active users. The following figures show the chronological sequence of this estimation.

Estimation of the active users from the number of individuals providing a warning.

For the last 30 days (when not considering the last 5 days, due to the delay in reporting in the case of new infections: January 25, 2022 – February 23, 2022), we thus obtain 27 million (CI: 21 million – 33.3 million).

4.2 From the CWA data donation

At present, more than 16 million users donate their data daily (as of: February 28, 2022). From the percentage of individuals donating data estimated (and updated) in the previous blog post, together with the number of the CWA data donations, we can estimate the daily number of active users (in the narrower sense):

Mathematische Formel

It is important to take into account thereby that the data donations come from devices, whereas the test results come from users. For the last 30 days, we obtain on average 31 million active users of the Corona-Warn-App (CI: 25.8 million – 33.6).

The following figure shows the corresponding daily values.

Estimation of the number of active users resulting from the percentage of the individuals donating data.

4.3 From a heuristic

This also corresponds well with the following heuristic: With currently 43.2 million downloads (as of: February 27, 2022) and with the percentage of approximately 12% of users, who have more than one device (see also the event-related survey (EDUS)), approximately 38.6 million primary devices resulted initially. With the empirical value of approximately 2.6 years, after which a smartphone is replaced with a new one on average, a percentage of approximately 39.5% of the active devices, on which the CWA was downloaded again due to a smartphone change, results after 1.7 years (or 622 days, respectively). As a whole, this yields a rough estimation of currently approximately 23.3 million active users and 26.1 million active apps/devices. It was (conservatively) assumed hereby that each new installation is made under a new account. If this occurs only among two-thirds of the users, this yields an estimation of approximately 28.5 million active users and 32 million active apps/devices. On the one hand, we can thus estimate the active users or active apps/devices, respectively, on the other hand, we also obtain a simple and natural explanation for the increasing difference between the number of downloads and active users or devices, respectively.

By European comparison, Germany is very well positioned with the user-to-download ratio calculated therefrom, thus the ratio of active users to download number (here explained only by natural ‘disappearance’), of between 53.9% and 65.9% (23.3 million or 28.5 million active users (AU), respectively, with 43.2 million downloads (DL)). The comparative values of other European countries range from 52% (3.1 million DL; 1.6 million AU or 2.5 million DL; 1.3 million AU, respectively) to 44% (3.2 million DL; 1.4 million AU), 43% (5.5 million DL; 2.4 million AU) and 36% (1.5 million DL; 0.5 million AU) to 34% (2 million DL; 0.7 million AU). Due to the fact that the specified numbers originate partially from non-published sources, we have forgone the designation of the respective countries. In addition, not all of the information is as current as the German values.

In the following figure, we compare the download numbers and the estimations of the heuristic with the data from the SwissCovidApp. The steadily increasing difference between the number of the downloads and the number of the active apps/devices or users, respectively, can be seen well here.

Comparison of download numbers and active users or active apps, respectively, for Corona-Warn-App, and SwissCovidApp.

5 Key figures from the CWA backend

A further option for estimating the active apps/devices (in the narrower sense) are the files of the daily keys downloaded by the users of the CWA and provided via the CWA backend. Even though the CWA accesses the shared daily keys, which are generated several times each day, the downloading of the daily packages takes place at most once per day. In the following, we analyse the data provided by T-Systems International (TSI) on January 26, 2022, which covers 46 days (from December 4, 2021, to January 19, 2022) and which is broken down by operating system. From this, we obtain 27.9 million active devices or 24.9 million active users (on January 19, 2022).

Active devices in the narrower sense) via downloads of daily key files (TSI).

The data also allows taking a look at the time delay when accessing the daily key files. We also see here (see use of the core functionality) that only a small percentage of the active devices performs the risk determination later than right away on the day it is provided.

Active devices (in the narrower sense) after days since last accessing the daily key files (TSI).

6 Key figures relating to the use from the stores

An analysis of the data from Google Play Store and Apple App Store can provide further insights here.

6.1 Google Play Store

We initially provide an overview of the key figures of the Google Play Store.

Some key figures are calculated on the basis of the data of users, who have agreed to share a summary with the developers. The key figures, which are offered in the play console, are adapted so that they reflect the data from all users.

Various key figures can be accessed in the Google Play Store for installation. In particular the number of the active devices, of the active users, and of the monthly active users (MAU)) are of interest for us.

Table 2: Key figures relating to installations (Google).
Key figure Definition
Users A single Google Play user. A user can have several devices.
Active users The number of users, among whom the app is installed on at least one device, which was used in the last 30 days.
Acquired users The number of users who installed the app when it was not yet installed on any of their devices. This also includes users who activate a device on which the app was preinstalled or reactivate a device.
Lost users The number of users who have uninstalled the app on all devices or have not used the devices on which the app is installed for more than 30 days.
New users Users, who have installed the app for the first time.
Recurring users Users who have reinstalled the app after previously uninstalling it on all their devices. Inactive users who become active again are also taken into account here.
All users New and returning users.
Devices An Android device, which is assigned to a user. When a device is reset or is given to a different user, it is counted as new device.
Active devices The number of active devices, on which the app is installed. Devices are considered to be active, if they were turned on at least once in the past 30 days.
Acquired devices The number of devices on which users have installed the app. This also includes devices on which the app was preinstalled.
Lost devices The number of devices on which users have uninstalled the app. This also takes into account if a device is inactive, i.e. has not been used for more than 30 days.
New devices Devices, on which users have installed the app for the first time.
Reused devices Devices on which the app is installed and on which the app was previously installed. Inactive devices that are reactivated are also taken into account.
All devices New and recurring devices.
Updates by device The number of devices on which the app has been updated.
Lost devices after update The number of devices on which the app was uninstalled after it was recently updated.
Installations How often the app was installed, including the devices, on which the app was already installed before. Previous installations or reactivated devices are not considered.
Uninstallations How many times the app has been uninstalled. Inactive devices are not taken into account.
Daily active users (DAU) The number of the users, who have opened the app on a certain day.
Monthly active users (MAU) The number of users, who have opened the app in the previous 28 days.
Monthly recurring users The number of users who opened the app on a given day in the previous 28 days and on at least one other day during that time.
Acquisitions via store entry The number of users who visited the Store entry and then installed the app, and for whom the app was not previously installed on any device.
Visitors of the store entry The number of users who visited the store entry and who did not have the app installed on any device before.

The following figure contains the essential key figures relating to the download and use behaviour.

1. Jun29. Jun27. Jul24. Aug21. Sep19. Okt16. Nov14. Dez11. Jan 8. Feb 8. Mär 5. Apr 3. Mai31. Mai28. Jun26. Jul23. Aug20. Sep18. Okt15. Nov13. Dez10. Jan 7. Feb 7. Mär05M10M15M20M25M
"Downloads"Active devicesActive usersMonthly active usersDaily active usersActive users (TSI)CommentsDateNumber

Figure 14: Key figures relating to the installation (Google).

It is important to note hereby that the number of the monthly active users has only been available since October 6, 2020, and is not provided on a daily basis, but with a delay of several days.

The number of the active apps/devices is specified with 16.5 million, the number of the active users with 15.2 million, and the number of the monthly active users with 13.5 million (as of: February 26, 2022). It may initially seem surprising that the number of the active users is higher than the number of the monthly active users. A close look at the definition, however, reveals the reason: The first number indicates those users, who have actively used their smartphone, on which the CWA is installed, during the last 30 days, the second number, however, indicates those, who have actually used the CWA during the last 28 days. The difference is approximately 11%.

The share of secondary devices is 8.7%, whereby this also only includes secondary devices of the same operating system. In addition, an average ‘exchange time’ of the device of 2.9 years follows from this data (when comparing downloads and active users). This corresponds well with the value selected in the heuristic.

6.2 Apple App Store

We now provide an overview of the key figures in the Apple App Store.

Various key figures relating to the installation can likewise be accessed in the Apple App Store. In particular the number of the active devices and of the monthly active users (MAU); active in the last 30 days) are of interest for us.

Table 3: Key figures relating to downloads and use (Apple)
Key figure Definition
First-time downloads The total number of the first-time downloads of the app.
Additional downloads The total number of the additional downloads of the application. Does not contain any automatic updates or recoveries of devices.
Downloads as a whole The total number of the app downloads, including first-time downloads and additional downloads.
Installations The total number of the installations of the app on devices with iOS 8 or tvOS 9 or higher. Repeated downloads on the same device, downloads on several devices with the same Apple ID and installations with family sharing are included. The total numbers are based on app users, who consent to share their data.
Session The number of times the app was used for at least two seconds. If the app is in the background and is used again later, this counts as further session. The total numbers are based on app users, who consent to share their data.
Active devices The number of devices with at least one session during the selected time period. Based on devices with iOS 8 or tvOS 9 or higher. The total numbers are based on app users, who consent to share their data.
Active in the last 30 days The number of the active devices with at least one session in the last 30 days. The total numbers are based on app users, who have agreed to share their data.
Crashes The total number of crashes on devices running iOS 8 or tvOS 9 or later.
Deletions The number of times the app was deleted on devices running iOS 12.3 or tvOS 9 or later by users who agree to share their data. This data includes deleting the app from the Home screen and deleting the app from Manage Storage. Data from resetting or deleting content and settings from a device is not included.

The following figure contains the essential key figures relating to the download and use behaviour.
1. Jun29. Jun27. Jul24. Aug21. Sep19. Okt16. Nov14. Dez11. Jan 8. Feb 8. Mär 5. Apr 3. Mai31. Mai28. Jun26. Jul23. Aug20. Sep18. Okt15. Nov13. Dez10. Jan 7. Feb 7. Mär05M10M15M20M
"Downloads"iPhoneDesktopMonthly active users (Projection)Monthly active users (Opt-In)Active devices (Projection)Active devices (Opt-In)Active users (TSI)CommentsDateNumber24. Apr (Sa) 2021"Downloads" : 12.291.824iPhone : 9.407.450Desktop : 2.883.024Monatlich Ak... : 6.337.735Monatlich Ak... : 1.457.679Aktive Gerät... : 1.514.796Aktive Gerät... : 348.4032.0.3