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iPhone AppStore Secrets - Pinch Media

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What we've learned from 30,000,000+ downloads - AppStore structure, average active user base, suitability of advertising vs. paid application sales, average session time, and more....

What we've learned from 30,000,000+ downloads - AppStore structure, average active user base, suitability of advertising vs. paid application sales, average session time, and more.

For more information, contact Pinch Media at www.pinchmedia.com or e-mail support@pinchmedia.com.

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15 of 35 Post a comment

  • Full Name Full Name Comment goes here.
    Are you sure you want to
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  • Awesome doc with great applications. Thanks for very interesting post. http://www.mobileappsdevelopmentteam.com
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  • iOS6 is going to revolutionize the use of iPhone applications. A quick review of features expected from iOS6
    http://www.slideshare.net/SojoSolutions/features-ofios6
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  • You can get realtime stats by country, genre or segment here: http://iosappstats.com/
    Are you sure you want to
    Your message goes here
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  • you can try iBestTips app, i found this app in appstore. It contains many helpful tips and it is total Free
    http://itunes.apple.com/us/app/ibesttips/id452280871?ls=1&mt=8
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  • What's the source of your stats? I have been researching on this same topic for a while and no seems to know or clue about how Apple ranks the apps. I assume you are using your experience :-). Anyway, I still think you shared some good info. Thanks!

    Saidul Islam from
    http://tukulogics.com/
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iPhone AppStore Secrets - Pinch Media iPhone AppStore Secrets - Pinch Media Presentation Transcript

  • ‘AppStore
Secrets’
 (What
We’ve
Learned
From
30,000,000
Downloads)

 Greg
Yardley
 Co‐Founder
&
CEO
 greg@pinchmedia.com
 646‐330‐8540

  • 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:
 greg@pinchmedia.com
 646‐330‐8540
 If
you’ve
got
a
technical
quesUon,

 support@pinchmedia.com
goes
to
the
 enUre
company.
 You
can
see
a
demo
at
demo.pinchmedia.com,
or
 just
get
started
at
developer.pinchmedia.com.