A Useful Metric

A Useful Metric

I was playing around with the numbers with my metrics and came across a meaningful calculation that I felt was quite revealing about the usage of games/apps (more so on mobile devices than PC but it would hold equally as well with these but the results would look different).

Typically things like DAU, MAU an stickability are thrown around along with D7 retention and so on.

This is a similar metric that is dead easy to calculate and gives away a fair amount of information on how your product is being used in the marketplace.

Take a particular period of time, eg 10 days.
Obtain the total number of unique users of your product in that time (separating by IP address while not a perfect fit will work)...eg 100 users.
For each day in that period count the number of unique users (use the same method, ie IP address - note any errors due to IPs being reassigned etc will even out in the wash)...eg

Day 1 10 users, Day 2 15 Users, Day 3 5 Users, Day 4 25 Users etc etc...sum them all up.

Divide the sum of your daily unique users (each day) by the total users for the period, call this figure D.

D is the average number of days, for the period, that users use your app for.

It will range between a minimum value of 1 and a maximum value of the period being looked at.

Something to note - this figure is amazingly stable. Unlike stickability which uses monthly active users - you can use figures from the entire life of your product to get an average value as most likely it won't change (once the product itself is stable).

The figure is similar in nature to the D7 retention and other figures like it and gives a rough idea of how engaged your users are with your product.

My own app has a value greater than 2 but less than 2.5. This means that most users use the app on the day of install, the following day and a handful use it the 3rd and subsequent days.

This is fairly normal - from what I've seen of various curves usage of games and apps is such that the fall off from install to inactive happens fairly quickly typically - especially on the mobile market, less so on desktop but it still occurs with a similar pattern on desktop.

So to summarise:

U = Total Users For Period
V = Sum of Daily Unique Users For Same Period (as U)
D = Avg Days Spent On App Per User = V / U

Simple characteristic to determine values - IP Address of User.

Results - Close to 1 = poor quality, Higher is better.