What is the value of returning users - and should we start reducing ads shown to long-time users as a “reward” (basically because these users are not likely to click on ads anyway because “banner blindness” has set in fully)
It is an irony of this ad/app space that the MAJORITY of the revenue is earned from NEW users - this is especially true for apps which have poor retention. So the worse an app is, the MORE it depends on the new users.
New users ALSO tend to click more on ads - as becomes clear to many developers as they see how new user/returning user percentage seems to be directly related to the revenue for that day. Or whenever they change something in the app - or issue a new app - the revenue per DAU seems to be higher (perhaps because of the higher percentage of new users). It seems new users tend to click all over the place - compared to returning users. In addition, “banner blindness” is all familiar to us - as we tune out ads on web browsers on desktops - though on apps it maybe harder to ignore a flashing banner ad etc.
It would be great if Google Developer Console showed a graph for (new user/returning user) for easier graphical sense.
So some variation in revenue can occur due to variations in new user/returning user as well.
I ran an experiment using Leadbolt HTML AppWall - since this uses a URL which can be changed, I changed the url that was used depending on “how many days since installed”.
1st day - 68% of impressions - 71% of clicks - $0.97 eCPM - $0.03 CPC - 3.76% CTR
2nd day - 5% of impressions - 5% of clicks - $0.17 eCPM - $0.00 CPC - 3.58% CTR
3rd day - 3% of impressions - 3% of clicks - $0.09 eCPM - $0.00 CPC - 3.23% CTR
4th day - 2% of impressions - 2% of clicks - $1.74 eCPM - $0.04 CPC - 4.21% CTR
5th day - 1.5% of impressions - 1.5% of clicks - $1.00 eCPM - $0.03 CPC - 3.74% CTR
6th day+ - 20% of impressions - 17% of clicks - $0.89 eCPM - $0.03 CPC - 3.09% CTR
NOTE: the 6th url includes day 6 and all subsequent days (i.e. including the “long tail” of users). You can see that this is significant i.e. 20% of impressions - though their click-rate is much lower. Conversely, for first day users, the click-rate is higher than expected (because of the newness of the UI factor for new users).
The other variation between days and in CPC/CTR is not that relevant (since it varies between apps). So only look at the very obvious differences (not the subtle ones - as those can be just because of random variation because of low impression numbers).
The patterns which ARE dominant are that:
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first day has highest impressions (for apps with a lot of returning users this will obviously be much lower for the first day - versus all other days visited)
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you can see the exponential fall off in users (as they return less often over time) (day 6+ is a sum of day 6, 7, 8 …)
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the pattern that CPC is near-zero for day 2 and day 3 is similar with other app (so maybe significant) - however CTR is high - so the reason is that the ads were low paying (so how is this in any way correlated ? - unless Leadbolt is offloading low-paying ads to returning users who come back on day 2 or 3 ?)
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it answers the question “should we keep showing ads since the user interest will drop off over time” - the answer is that for day 6+ (i.e. day 6, 7, … to infinity) the revenue potential is 17% of total revenue or so - which is significant. So EVEN jaded, bored returning users will earn you significant revenue.
NOTE: what this statistic DOES NOT RESOLVE is the question of how revenue goes down by REPEATED return to app - for that ANOTHER experiment would have to be done - where the url changes NOT by the day of return to app (after first install), but by the COUNT of every new day that returned to app. This will help disambiguate whether users who return to app after using app 10 times are equally valuable or not. This statistic could be used to therefore REWARD returning users so after they have used the app 10 times (say) then there are no more ads shown (if your statistic shows that users who have used app more than 10 times are UNLIKELY to ever click on an ad again - i.e. the “banner blindness” is fully active for them).
If you have statistics about how well returning users (those who have used your app more than 5 or 10 times i.e. on 5 or 10 different days - not on the same day) - then let me know.
Thanks.