Published on February 19, 2009
30,000,000 Downloads?! (Actually, it’s a fair bit more than that by now.) • Since AppStore launch, Pinch Media has provided developers with an analyUcs library to monitor app usage – unique users, sessions, usage Ume, etc. • Since AppStore launch we’ve also been collecUng every bit of detail possible from the AppStore – rankings, price changes, you name it – and tying it back to our analyUcs. • Our stuﬀ’s in a few hundred applicaUons right now – it’s been in the #1 free and paid applicaUon several Umes each, and has been in at least ten of the top 100 free applicaUons for a while now. • With all of this data, you learn a few things.
ApplicaUon Rankings (How does the AppStore work, anyway?) For every ranked list on the AppStore, here’s a good rule of thumb: 24‐hour rolling window of units downloaded (So bunch up your publicity.)
What do you get by appearing on a list? • Appearing on a top 100 list increases daily new users by an average of 2.3x. • Greater gains result from appearing in the top 25 and top 10 lists – more variable, but oaen an order of magnitude. • However, it’s not permanent. Apple’s AppStore is structured for maximum turnover.
Case Study A: Well‐Timed Price Cut
Case Study B: Not‐So‐Well Timed
Case Study C: CounterproducUve?
In general… • Don’t mess with a posiUve download trend. • Decreasing price is oaen worthwhile. • Aaer you’ve been broadly exposed, experiments have less eﬀect. The average price cut increased demand by 130%. The average price increase drops demand to 25%.
What do I need to get on a list? For free applicaUons: Top 25 Top 100 six months ago 10,000 1,000 three months ago 11,000 1,500 today 20,000 5,000 (Apple had a big Christmas!)
Case Study D: Happy Holidays
Do I have a community? (aka ‘How much is my app used?’) • So you’ve got a million downloads – congrats! But what percentage use your applicaUon the next day? The day aaer? • The biggest applicaUons in our system have +3MM downloads – but what kind of acUve user base does a download translate into?
Free ApplicaHons ‐ Usage Over Time 25.00% Users Returning (% of Day 0) 20.00% 15.00% 10.00% 5.00% 0.00% 1 11 21 31 41 51 61 71 81 91 Days Since First Used
Paid ApplicaHons ‐ Usage Over Time 35.0% Users Returning (% of Day 0) 30.0% 25.0% 20.0% 15.0% 10.0% 5.0% 0.0% 1 11 21 31 41 51 61 71 81 91 Age Since First Used
ApplicaHons By Category ‐ Usage Over Time 30.0% Entertainment Users Returning (% of Day 0) Games 25.0% Sports Lifestyle 20.0% UUliUes 15.0% 10.0% 5.0% 0.0% 1 4 7 19 25 28 31 37 49 55 58 61 67 79 85 88 91 97 100 10 13 16 22 34 40 43 46 52 64 70 73 76 82 94 Days Since First Use
In other words… • Users stop using the average applicaUons prely quickly. Long‐term audiences are generally 1% of total downloads. • Paid applicaUons generally retain their users longer than free applicaUons, although the drop‐oﬀ is sUll prely steep. • Sports seems beler at retaining users over the short term; entertainment at retaining users over the long term.
How long are they using it? • For certain applicaUons, the length of Ume users use the applicaUon is important. • Branded applicaUons care deeply about engagement. • ApplicaUons showing ads periodically also care about session length, for obvious reasons. • In general, every second the app’s open is a second it can be seen by or recommended to others.
So should I give it away or not? • Anyone browsing the top free applicaUons knows that adverUsing is an opUon. • The biggest player is AdMob, but Pinch Media has some partnerships with ad networks that supply some of these ads. • However… I used to be much more enthusiasUc about adverUsing than I am today. Here’s why:
Total ApplicaHon Runs Since First Use 12 10 Total ApplicaHon Runs 8 6 4 2 0 1 11 21 31 41 51 61 71 81 Days Since First Use
Average ‘free vs. paid’ raUos: • for total unique users: 7.5 to 1 • for total number of Umes used: 6.6 to 1 • for total Ume spent using the applicaUon: 3.9 to 1
ExtrapolaUng… • Assume free applicaUons are run, at most, a dozen Umes per user. • We see free applicaUons run, on average, 6.6 Umes as oaen as paid applicaUons. • A paid applicaUon returns at least $0.70 / user. • Doing the math – 12 x 6.6 = 80 sessions. • Can the average applica/on make more than $0.70 oﬀ adver/sing in 80 sessions?
Answer: Hell no. Earning $0.70 in 80 sessions requires revenue of $8.75 per thousand runs. If you can show one ad per session, that’s an $8.75 CPM. Right now, with the ad market how it is, adverUsing rates of $0.50‐$2.00 CPM are much more typical. The typical applicaUon would have to bombard its users with ads to beat the money it’d make from paid sales.
But adverUsing isn’t always a bad idea. • Some applicaUons beneﬁt from network eﬀects, and get far more than 6.6x the users they’d get if they charged. • Some applicaUons are excepUonally ‘sUcky’ – users use the app far more than average. • Some applicaUons – generally, ones catering to people with money – can command beler adverUsing rates than usual.
CumulaHve ApplicaHon Runs Since First Use, By Decile 45 40 35 30 ApplicaHon Runs 25 20 15 10 5 0 1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96 Days Since First Used
CumulaHve ApplicaHon Runs Since First Use, By Decile CPM 45 < $2.00 40 35 30 ApplicaHon Runs 25 20 15 ~ $7.00 10 ~ $15.00 5 ~ $35.00 0 1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96 Days Since First Used
To sum up… • Only a few (<5%) high‐performing applicaUons are suitable for adverUsing right now, and you don’t know if you’ve got one unUl aaer launch. • In other words ‐ unless there’s something inherent about the app that screams free, sell it. • Install analyUcs in your applicaUon and watch your sessions per user over Ume. Within a few weeks, you’ll know if you’ve got a sUcky applicaUon. • Only release an ad‐supported version when you have data strongly indicaUng success.
Again, summing up ‐ • Usage Ume declines by almost a third in the ﬁrst month aaer use, stabilizing at just under ﬁve minutes. • Paid applicaUons see slightly more use soon aaer installaUon, and are used for slightly longer periods. • The biggest usage diﬀerenUator is category – games are used for longer periods than any other type of applicaUon.
This was actually a sneak preview • AppStore‐wide reports are being generated daily and will be incorporated into Pinch Media’s reporUng site in the near future. • Any applicaUon using our analyUcs library and acUvely sending in data gets access to all ecosystem‐wide reporUng for free. • Pinch Media wants to know what else you want baked into this reporUng.
QuesUons? You can always reach me at: email@example.com 646‐330‐8540 If you’ve got a technical quesUon, firstname.lastname@example.org goes to the enUre company. You can see a demo at demo.pinchmedia.com, or just get started at developer.pinchmedia.com.
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