iPhone AppStore Secrets - Pinch Media
- 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.
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