On the Google Play Store I have always used the number of total cumulative installs as part of my growth plan.
However, I am no longer able to see "cumulative total installs". Show only "Active Installations".
It seems that Google has changed the organization again, so much so that the answers of 2019/2020 are not useful.
How can I see them?
In order to get cumulative total download on Google Play Console, I had to:
Search for “Statistics” tab
Change the report configuration a bit. First, click “Installed
audience” (the default metric), and navigate the menu as following:
Users > User Acquisitions > New Users
Click the “Edit” button And change the “Events” to “Unique Users“. This ensures that the final report will not be over-counted if you’ve had a significant number of users who have uninstalled and re-installed your app over time.
Also adjust the metric calculation to “Cumulative“. This means each
data point along your time series will be equal to your total
installs accumulated up until that day.
On your main dashboard, set your time range to "Lifetime". Then you will see the total installs in the "New users acquired" section
Related
I am running a Web Performance test in Visual studio 2013 Ultimate version, I need some clarification on my scenario:
I have a Login web test case, its using data source and running a
test case for 10 different user.
I also have a Load test which is using above web test case and
running it for 50 constant user.
I also have a "Percentage of new users" value set to 100
Does the above settings mean my Load test will run the web test for 50 concurrent users and it will each user will be randomly selected from data source of the web test ?
If the login web test has a data source containing 10 different users and the load test is running it for 50 constant users then each data source entry will be logged in for (on average) 5 virtual users at any point throughout the test.
When the Percentage of new users is 100: Whenever a virtual user finishes a web test that user finishes and a new virtual user is started so that the number of virtual users remains correct.
When the Percentage of new users is 0: Whenever a virtual user finishes a web test that user stays active so that the number of virtual users remains correct.
When the Percentage of new users is between 0 and 100: Whenever a virtual user finishes a web test a decision is made, based on the percentage, as to whether the current user finishes and a new user starts or whether the user stays active.
The points above about Percentage of new users should be interpreted to match the load pattern required. If the required number of virtual users differs from the actual number then new virtual users are created or existing users stopped as necessary. At the very start of a test run there are zero virtual users so enough are created to make the required number for a constant load or the initial number for a step load. At the end of a test run the required number is zero so users finish. (During the cool down period the required number is zero, so users and their tests are allowed to finish naturally. At the real end of the run the test just stops, all running tests and their users are just terminated.)
When a virtual user starts a new test values are read from the data source and (for Sequential and Unique accesses) the data source pointer is moved to the next entry. Thus with 10 data source entries and 50 virtual users with Sequential access we expect the first data source entry to be used by virtual user numbers 1, 11, 21, 31 and 41. Similarly the second entry will be used by 2, 12, 22, 32 and 42. And so on. If the data access is Random then you would expect each data source entry to be used by 5 virtual users, but as the entries are chosen randomly some are likely to be used by more than 5 and some less than 5 at any point in time. Over the whole duration of the test you should expect each data source value to be used approximately the same number of times.
Having 10 data source entries for 50 users is valid provided the system being tested allows a user to log in from multiple computers at the same time. (Note that each of these user will also log in from the same IP address, this can be changed but it can be complicated.) Generally I would recommend that the number of different logins in the data source exceeds the number of virtual users. Having at least twice as many would be good.
Two good sources of further information are the Content Index for Visual Studio Web Tests and Load Tests
and the Visual Studio Performance Testing Quick Reference Guide.
i published my first app on Google Play and i can't figure out how to count the total of downloads by users.
It lets me to choose between currents installations and uninstallations per day, but none that tells me the total of downloads since the publishing of the app.
To count the total of downloads i take the number of installations and i substract the total of uninstallations (i get it making the sum of uninstallations of every day!)
How to figure out the total of downloads in an easier way?
You need to code for that if you want exact number of download.
create a webservice as the app starts by sending serial number of device to server.
keep the record over there.
There are couple of apps at the Windows Phone Store which are automatically updating phone lock screen by a custom interval, lets say 1, 2, 4 or more hours.
I did some search over internet to find some articles or best practice to implement custom update interval, which is bigger than 30 minutes but without any result.
Maybe you know some code snippets or reference on articles ?
Thanks in advance!
As you have already found, the periodic agents are invoked once every 30 mins. However, you can simply do nothing until your desired update period has passed then execute your update.
You already have access to your app's isolated storage from within your background agent. You can simply store a counter in some file to track the time that has passed and once it meets your requirement you can execute your update and reset the counter.
I am using to test my web server https://buyandbrag.in .
I have tested it for 100 users. But the main server is not showing like it is crowded or not.
I want to know whether it is really pressuring the main server(a cloud server I am using).Or just use the client resourse where the tool is installed.
Yes as mentioned you should be monitoring both servers to see how they handle the load. The simplest way to do this is with TOP (if your server OS is *NIX) also you should be watching the network activity i.e. Bandwidth, connection status (time wait, close wait and so on).
Also if your using apache keep an eye on the logs you should see the requests being logged there
Good luck with the tests
I want to know "how many users my website can handele ?",when I tested with 50 threads ,the cpu usage of my server increased but not the connections log(It showed just 2 connections).also the bandwidth usage is not that much
Firstly what connections are you referring to? Apache, DB etc?
Secondly if you want to see how many users your current setup can hand you need to create a profile or traffic model of what an average user will do on your site.
For example:
Say 90% of the time they will search for something
5% of the time they will purchase x
5% of the time they login.
Once you have your "Traffic Model" defined, implement it in jMeter then start increasing your load in increments i.e. running your load test for 10mins with x users, after 10mins increment that number and so on until you find your breaking point.
If you graph your responses you should see two main things:
1) The optimum response time / number of users before the service degrades
2) The tipping point i.e. at what point you start returning 503's etc
Now you'll have enough data to scale your site or to start making performance improvements from a code point of view.
Is it possible to change the resolution time calculation to start not with the issue creation time, but rather with the time when an issue was transferred into a certain state?
The use case is as follows - We use a kanban-ish development method, where we create most issues/featues/stories in a backlog upfront; thus, this kills the usefulness of the resolution time gadget. In our case, the lead/resolution time should rather be calculated using the time where an issue has been pulled to the selected issues.
As this calculation is the basis for multiple gadgets, maybe it could be changed per gadget in order to avoid unforeseen issues with other gadgets?
There is a service level management tool SLAdiator (http://sladiator.com) which calculates resolution / reaction times based on the duration that ticket has spent in a certain status (or statuses). You can view these tickets online as well as get reports.