44. eInk Reading Machine
Gold-A
Kobo2 Purchase frequency is increasing
Jun-2010
overall. eBook buying is
accelerating.
Fiction
100% Paid
45. eInk Reading Machine
Gold-A
A customer who starts in
Kobo2 June 2010 buys 44% more in
their first month as a customer
Jun-2010
than a customer who started
Fiction Dec 2009.
100% Paid
46. eInk Reading Machine
Gold-A
Kobo2
A customer joining Nov. 2010
buys 70% more in their first
Jun-2010 month than a Dec 2009
customer.
Fiction
100% Paid
55. Small-screen Reader
Bronze-E Largest segment in terms of numbers
iPhone Cohort
Gold
Nov-10
Silver
Romance Bronze
paid+free
56. Small-screen Reader
Bronze-E Largest segment in terms of numbers
iPhone Cohort
Gold
Nov-10
Silver
1st Day Average 1 order /
Romance Bronze $15 $11 month
paid+free
61. Actual Selling Price vs. Purchasing Platform
Can$10.00
8.84 8.53
Can$7.50 7.80 7.92 7.85 7.82
Bronze-E 7.42
6.81
Can$5.00
iPhone P
Can$2.50
Nov-10
Can$0
All
d
der
p
oid
b
ne
rry
iPa
kto
We
Romance
o
kbe
r
Rea
iPh
And
Des
c
oe
Bla
Kob
50% paid
62. Actual Selling Price vs. Purchasing Platform
Can$10.00
8.84 8.53
Can$7.50 7.80 7.92 7.85 7.82
Bronze-E 7.42
6.81
Can$5.00
iPhone P
Can$2.50
Nov-10
Can$0
All
d
der
p
oid
b
ne
rry
iPa
kto
We
Romance
o
kbe
r
Rea
iPh
And
Des
c
oe
Bla
Kob
50% paid
63. Actual Selling Price vs. Purchasing Platform
Can$10.00
8.84 8.53
Can$7.50 7.80 7.92 7.85 7.82
Bronze-E 7.42
6.81
Can$5.00
iPhone P
Can$2.50
Nov-10
Can$0
All
d
der
p
oid
b
ne
rry
iPa
kto
We
Romance
o
kbe
r
Rea
iPh
And
Des
c
oe
Bla
Kob
50% paid
64. Actual Selling Price vs. Purchasing Platform
Can$10.00
8.84 8.53
Can$7.50 7.80 7.92 7.85 7.82
Bronze-E 7.42
6.81
Can$5.00
iPhone P
Can$2.50
Nov-10
Can$0
All
d
der
p
oid
b
ne
rry
iPa
kto
We
Romance
o
kbe
r
Rea
iPh
And
Des
c
oe
Bla
Kob
50% paid
65. Actual Selling Price vs. Purchasing Platform
Can$10.00
8.84 8.53
Can$7.50 7.80 7.92 7.85 7.82
Bronze-E 7.42
6.81
Can$5.00
iPhone P
Can$2.50
Nov-10
Can$0
All
d
der
p
oid
b
ne
rry
iPa
kto
We
Romance
o
kbe
r
Rea
iPh
And
Des
c
oe
Bla
Kob
50% paid
80. iPad Socialite
Gold-B Not as good as the Reading Machine, but
still pretty great.
iPad
Dec-10
General
90% paid
81. iPad Socialite
Gold-B Not as good as the Reading Machine, but
still pretty great.
iPad
Cohort
Dec-10 Gold
Silver
General
Bronze
90% paid
82. iPad Socialite
Gold-B Not as good as the Reading Machine, but
still pretty great.
iPad
Cohort
Dec-10 1st Day Average 4.5 orders /
Gold $22 $16 month
Silver
General
Bronze
90% paid
100. Average Time in App vs. “Time of Day” Awards
60%
45%
30%
15%
0%
-15%
-30%
-45%
-60%
mute
ch
hift
Hour
time
or Lun
yard S
Prime
e Com
Happy
ooks f
Grave
Kill th
I Eat B
101. Average Time in App vs. “Time of Day” Awards
60%
45%
30%
15%
0%
-15%
-30%
-45%
-60%
mute
ch
hift
Hour
time
or Lun
yard S
Prime
e Com
Happy
ooks f
Grave
Kill th
I Eat B
102. Average Time in App vs. “Time of Day” Awards
60%
7-9am
45%
30%
15%
0%
-15%
-30%
-45%
-60%
mute
ch
hift
Hour
time
or Lun
yard S
Prime
e Com
Happy
ooks f
Grave
Kill th
I Eat B
103. Average Time in App vs. “Time of Day” Awards
60%
m m-n o o n
-9a 9a
7
45%
30%
15%
0%
-15%
-30%
-45%
-60%
mute
ch
hift
Hour
time
or Lun
yard S
Prime
e Com
Happy
ooks f
Grave
Kill th
I Eat B
104. Average Time in App vs. “Time of Day” Awards
60%
m m-n o o n
-9a 9a
7
45%
12 -2pm
30%
15%
0%
-15%
-30%
-45%
-60%
mute
ch
hift
Hour
time
or Lun
yard S
Prime
e Com
Happy
ooks f
Grave
Kill th
I Eat B
105. Average Time in App vs. “Time of Day” Awards
60%
m m-n o o n
-9a 9a
7
45%
12 -2pm
30%
2- 4pm
15%
0%
-15%
-30%
-45%
-60%
mute
ch
hift
Hour
time
or Lun
yard S
Prime
e Com
Happy
ooks f
Grave
Kill th
I Eat B
106. Average Time in App vs. “Time of Day” Awards
60%
45%
30%
15%
0%
-15%
-30%
-45%
-60%
mute
ch
hift
Hour
time
or Lun
yard S
Prime
e Com
Happy
ooks f
Grave
Kill th
I Eat B
107. Average Time in App vs. “Time of Day” Awards
60%
45%
30%
15%
0%
-15%
-30%
-45%
-60%
mute
ch
hift
Hour
time
or Lun
yard S
Prime
e Com
Happy
ooks f
Grave
Kill th
I Eat B
108. Average Time in App vs. “Time of Day” Awards
60%
45%
30%
15% 6-8pm
0%
-15%
-30%
-45%
-60%
mute
ch
hift
Hour
time
or Lun
yard S
Prime
e Com
Happy
ooks f
Grave
Kill th
I Eat B
109. Average Time in App vs. “Time of Day” Awards
60%
45%
30%
15% 6-8pm am
12-1
0%
-15%
-30%
-45%
-60%
mute
ch
hift
Hour
time
or Lun
yard S
Prime
e Com
Happy
ooks f
Grave
Kill th
I Eat B
110. Average Time in App vs. “Time of Day” Awards
60%
45%
30%
15% 6-8pm am
12-1 8-10pm
0%
-15%
-30%
-45%
-60%
mute
ch
hift
Hour
time
or Lun
yard S
Prime
e Com
Happy
ooks f
Grave
Kill th
I Eat B
111. Average Time in App vs. “Time of Day” Awards
60%
45%
30%
15% 6-8pm am
12-1 8-10pm0-12pm
0% 1
-15%
-30%
-45%
-60%
mute
ch
hift
Hour
time
or Lun
yard S
Prime
e Com
Happy
ooks f
Grave
Kill th
I Eat B
112. Bet
ter
i nB
ed
Prim
etim
e
Sle
epin
g In
Hap
py H
our
Afte
rno
o nR
ush
Hou
r
Pla
ying
Hoo
ky
I Ea
t Bo
oks
for
Lun
ch
Kill
the
Com
mu
te
Number of Awards Issued
Gra
vey
ard
Shi
ft
Wit
chin
gH
our
113. Bet
ter
i nB
ed
Prim
etim
e
Sle
epin
g In
Hap
py H
our
Afte
rno
o nR
ush
Hou
r
Pla
ying
Hoo
ky
I Ea
t Bo
oks
for
Lun
ch
Kill
the
Com
mu
te
Number of Awards Issued
Gra
vey
ard
Shi
ft
Wit
chin
gH
our
114. 1
Bet
ter
i nB 0-1
ed
Prim
2pm
etim
e
Sle
epin
g In
Hap
py H
our
Afte
rno
o nR
ush
Hou
r
Pla
ying
Hoo
ky
I Ea
t Bo
oks
for
Lun
ch
Kill
the
Com
mu
te
Number of Awards Issued
Gra
vey
ard
Shi
ft
Wit
chin
gH
our
115. 1
Bet
ter
i nB 0-1
ed
Prim
etim
e
8-10
Sle
epin
g In
2pm pm
Hap
py H
our
Afte
rno
o nR
ush
Hou
r
Pla
ying
Hoo
ky
I Ea
t Bo
oks
for
Lun
ch
Kill
the
Com
mu
te
Number of Awards Issued
Gra
vey
ard
Shi
ft
Wit
chin
gH
our
123. Free Books Accessed
The Freegan
Bronze-F
Website
Apr-10
Web
ne
roid
iPad
ed
ktop
rry
der
iPho
wer
kbe
a
And
Des
eRe
-po
Blac
Fiction
o
o
Kob
Kob
100% free
127. Customers with Free Books
The Freegan
Bronze-F
Website
Apr-10
Fiction
e
es
es
es
es
es
es
es
es
im
im
im
im
im
im
im
im
tim
1t
2t
3t
4t
5t
6t
7t
8t
9+
100% free Number of Free Books in Library
Customers with FreeBooks
128. Customers with Free Books
eBook
Training wheels
The Freegan
Bronze-F
Website
Apr-10
Fiction
e
es
es
es
es
es
es
es
es
im
im
im
im
im
im
im
im
tim
1t
2t
3t
4t
5t
6t
7t
8t
9+
100% free Number of Free Books in Library
Customers with FreeBooks
129. Customers with Free Books
eBook
Training wheels
The Freegan
Bronze-F “I Jane
Austen”
Website
Apr-10
Fiction
e
es
es
es
es
es
es
es
es
im
im
im
im
im
im
im
im
tim
1t
2t
3t
4t
5t
6t
7t
8t
9+
100% free Number of Free Books in Library
Customers with FreeBooks
130. Customers with Free Books
eBook
Training wheels
The Freegan
Bronze-F “I Jane
Austen”
Website
Apr-10
Fiction
e
es
es
es
es
es
es
es
es
im
im
im
im
im
im
im
im
tim
1t
2t
3t
4t
5t
6t
7t
8t
9+
100% free Number of Free Books in Library
Customers with FreeBooks
131. Customers with Free Books
eBook
Training wheels
The Freegan
Bronze-F “I Jane
Austen” “Freegans”
Website
Apr-10
Fiction
e
es
es
es
es
es
es
es
es
im
im
im
im
im
im
im
im
tim
1t
2t
3t
4t
5t
6t
7t
8t
9+
100% free Number of Free Books in Library
Customers with FreeBooks
132. 1t
im
e
2t
im
es
100% free
3t
im
es
4t
im
es
5t
im
es
6t
im
es
Customers with FreeBooks
7t
im
es
8t
im
es
9-1
4t
im
es
15
Number of Free Books in Library
-25
Customers with Free Books
tim
26 es
-50
tim
51 es
-10
0t
Mo im
re es
tha
n1
00
tim
es
133. 1t
im
e
2t
im
es
100% free
3t
im
es
4t
im
es
5t
im
es
6t
im
es
Customers with FreeBooks
7t
im
es
“Freegans”
8t
im
es
9-1
4t
im
es
15
Number of Free Books in Library
-25
Customers with Free Books
tim
26 es
-50
tim
51 es
-10
0t
Mo im
re es
tha
n1
00
tim
es
134. Customers with Free Books
Freegan
Librarians
“Freegans”
e
es
es
es
es
es
es
es
es
es
es
es
es
im
im
im
im
im
im
im
im
im
tim
tim
im
tim
1t
2t
3t
4t
5t
6t
7t
8t
4t
0t
-25
-50
00
9-1
-10
n1
15
26
51
tha
Number of Free Books in Library
re
100% free
Mo
Customers with FreeBooks
135. Customers with Free Books
Freegan Freegan
Librarians Hoarders
“Freegans”
e
es
es
es
es
es
es
es
es
es
es
es
es
im
im
im
im
im
im
im
im
im
tim
tim
im
tim
1t
2t
3t
4t
5t
6t
7t
8t
4t
0t
-25
-50
00
9-1
-10
n1
15
26
51
tha
Number of Free Books in Library
re
100% free
Mo
Customers with FreeBooks
We’re doing a ton of stuff with social, but having now seen 5 social presentations, we may come out of this all feeling that “Hell is other readers.”\n
\n
\n
\n
\n
\n
3rd most popular eReading app for the iPhone (# 34,300 employees, #, #)\nAlso The first ebookstore for the (#)\n
…\nThe first ebookstore for (#)\n
…\nThe first eInk device for (#)\n
\nThe first ebookstore in the (#)\n
(cloud)\n
We are obsessed with reading, with the reader, with how they behave, about their characteristics. \n
Making assumptions about the “typical” digital reader is incredibly difficult. Instead, we try to look for meaningful segments, smaller groups that do have some consistent behaviours.\n
\n
\n
Because it isn’t just how is a consumer from the UK different than a consumer from HK.\n
Or do you sell differently to a romance buyer in UK than a thriller reader in Hong Kong.\n
or is there a difference between a reader who...\n\n
or is there a difference between a reader who...\n\n
or is there a difference between a reader who...\n\n
or is there a difference between a reader who...\n\n
or is there a difference between a reader who...\n\n
or is there a difference between a reader who...\n\n
or is there a difference between a reader who...\n\n
or is there a difference between a reader who...\n\n
or is there a difference between a reader who...\n\n
or is there a difference between a reader who...\n\n
or is there a difference between a reader who...\n\n
or is there a difference between a reader who...\n\n
or is there a difference between a reader who...\n\n
or is there a difference between a reader who...\n\n
or is there a difference between a reader who...\n\n
or is there a difference between a reader who...\n\n
or is there a difference between a reader who...\n\n
or is there a difference between a reader who...\n\n
or is there a difference between a reader who...\n\n
or is there a difference between a reader who...\n\n
it gets complicated. So to give a sense of the way that we look at some of these different combinations, I’ve pulled out some samples.\n
\n
I’ll spend a bit of time with each one. We’ll look at some of the data that is especially relevant to that user and along the way, you’ll hopefully get a sense of both what we’re finding interesting right now and how our understanding of the digital reading is evolving.\n\n
I’ll spend a bit of time with each one. We’ll look at some of the data that is especially relevant to that user and along the way, you’ll hopefully get a sense of both what we’re finding interesting right now and how our understanding of the digital reading is evolving.\n\n
I’ll spend a bit of time with each one. We’ll look at some of the data that is especially relevant to that user and along the way, you’ll hopefully get a sense of both what we’re finding interesting right now and how our understanding of the digital reading is evolving.\n\n
I’ll spend a bit of time with each one. We’ll look at some of the data that is especially relevant to that user and along the way, you’ll hopefully get a sense of both what we’re finding interesting right now and how our understanding of the digital reading is evolving.\n\n
She is an eInk Reading Machine. And here are some of the things we know about her.\n\n
She is an eInk Reading Machine. And here are some of the things we know about her.\n\n
She is an eInk Reading Machine. And here are some of the things we know about her.\n\n
She is an eInk Reading Machine. And here are some of the things we know about her.\n\n
She is an eInk Reading Machine. And here are some of the things we know about her.\n\n
She is an eInk Reading Machine. And here are some of the things we know about her.\n\n
She is an eInk Reading Machine. And here are some of the things we know about her.\n\n
\n\n
\n\n
\n\n
\n\n
She has been with us since June 2010. She probably had a first edition Kobo eReader and has since upgraded to a 2nd edition Kobo. We look at when people joined very closely and are starting to see some interesting patterns there. Generally, we can say that (#)\n\n
\n\n
\n\n
The last one is important. Our suspicion is that we’re not just moving more people from print to digital. We’re moving more heavy readers from print to digital more quickly.\n\n
\n\n
She also tends to buy just about everything she reads. Now we distort that a bit by preloading free books onto the eReader, but as far as her ongoing consumption goes, she’s a full on customer with a big focus on new releases.\n\n
\n\n
\n\n
\n\n
\n\n
Talk about why -- lots of testing, app trialing, large percentage of apps that are installed are not used.\n\n
\n\n
(#) Smartphone users, generally, are much more sensitive to price than those on (#) larger-screen devices.\n(#) Android sits in between them because we see both phone and tablet users through the same platform. And the Web is almost exactly the same as the average, which makes sense because people buy on the web for all of their devices.\n\n\n\n
(#) Smartphone users, generally, are much more sensitive to price than those on (#) larger-screen devices.\n(#) Android sits in between them because we see both phone and tablet users through the same platform. And the Web is almost exactly the same as the average, which makes sense because people buy on the web for all of their devices.\n\n\n\n
(#) Smartphone users, generally, are much more sensitive to price than those on (#) larger-screen devices.\n(#) Android sits in between them because we see both phone and tablet users through the same platform. And the Web is almost exactly the same as the average, which makes sense because people buy on the web for all of their devices.\n\n\n\n
(#) Smartphone users, generally, are much more sensitive to price than those on (#) larger-screen devices.\n(#) Android sits in between them because we see both phone and tablet users through the same platform. And the Web is almost exactly the same as the average, which makes sense because people buy on the web for all of their devices.\n\n\n\n
(#) Smartphone users, generally, are much more sensitive to price than those on (#) larger-screen devices.\n(#) Android sits in between them because we see both phone and tablet users through the same platform. And the Web is almost exactly the same as the average, which makes sense because people buy on the web for all of their devices.\n\n\n\n
\n
\n
It’s an area with a huge number of factors and very hard to generalize\n(#-circle) Smartphones see a lot of people who use for a while, but then migrate to another platform. Or who use it as a second reading platform supplementing an eInk or tablet device.\nBut it isn’t screensize. # iPad users come and go while Android users stick around.\nAnd (#) eInk devices and dedicated eReaders generally outperform multi-function devices in terms of overall user longevity\n
It’s an area with a huge number of factors and very hard to generalize\n(#-circle) Smartphones see a lot of people who use for a while, but then migrate to another platform. Or who use it as a second reading platform supplementing an eInk or tablet device.\nBut it isn’t screensize. # iPad users come and go while Android users stick around.\nAnd (#) eInk devices and dedicated eReaders generally outperform multi-function devices in terms of overall user longevity\n
It’s an area with a huge number of factors and very hard to generalize\n(#-circle) Smartphones see a lot of people who use for a while, but then migrate to another platform. Or who use it as a second reading platform supplementing an eInk or tablet device.\nBut it isn’t screensize. # iPad users come and go while Android users stick around.\nAnd (#) eInk devices and dedicated eReaders generally outperform multi-function devices in terms of overall user longevity\n
It’s an area with a huge number of factors and very hard to generalize\n(#-circle) Smartphones see a lot of people who use for a while, but then migrate to another platform. Or who use it as a second reading platform supplementing an eInk or tablet device.\nBut it isn’t screensize. # iPad users come and go while Android users stick around.\nAnd (#) eInk devices and dedicated eReaders generally outperform multi-function devices in terms of overall user longevity\n
While eInk consumers are big fiction readers generally, Small screen readers are especially strong consumers of genre fiction sub-categories like sci-fi, fantasy and mystery. But especially (#) romance.\n
They also have a strong propensity to go hunting for free titles, but we’ll talk more about that in a bit.\n
\n
\n
\n
\n
This person is an iPad user who came on in December. That means we know even more about this user than we do about users on other platforms. As many of you know...\n
\n
Reading Life, a social experience integrated into our reading experience for iPad.\n
\n
\n
\n
\n
\n
\n
\n
\n
One of the options that you have is to connect to Facebook so that you can share some of the events from your reading life with your friends. People that turn this on\n
spend 33% more time in app, most of it reading.\n
We also give badges and awards to people depending on the time of day they read, whether it’s on the way to work\n
or at night in bed\n
or at lunch time.\n
\n
((explain what this shows...)\nThe biggest surprise we found in looking at this data was that our assumptions about when and how long people read were completely wrong.\n* ((had thought - late nights, more reading. Daytime, more time-pressured.))\nWhen we looked at people who were consistently reading during the day #\nKill the Commute (#) Sleeping In (#) I Eat Books for Lunch (#) Playing Hooky (#) - they were spending way more time reading (#)\n
((explain what this shows...)\nThe biggest surprise we found in looking at this data was that our assumptions about when and how long people read were completely wrong.\n* ((had thought - late nights, more reading. Daytime, more time-pressured.))\nWhen we looked at people who were consistently reading during the day #\nKill the Commute (#) Sleeping In (#) I Eat Books for Lunch (#) Playing Hooky (#) - they were spending way more time reading (#)\n
((explain what this shows...)\nThe biggest surprise we found in looking at this data was that our assumptions about when and how long people read were completely wrong.\n* ((had thought - late nights, more reading. Daytime, more time-pressured.))\nWhen we looked at people who were consistently reading during the day #\nKill the Commute (#) Sleeping In (#) I Eat Books for Lunch (#) Playing Hooky (#) - they were spending way more time reading (#)\n
((explain what this shows...)\nThe biggest surprise we found in looking at this data was that our assumptions about when and how long people read were completely wrong.\n* ((had thought - late nights, more reading. Daytime, more time-pressured.))\nWhen we looked at people who were consistently reading during the day #\nKill the Commute (#) Sleeping In (#) I Eat Books for Lunch (#) Playing Hooky (#) - they were spending way more time reading (#)\n
((explain what this shows...)\nThe biggest surprise we found in looking at this data was that our assumptions about when and how long people read were completely wrong.\n* ((had thought - late nights, more reading. Daytime, more time-pressured.))\nWhen we looked at people who were consistently reading during the day #\nKill the Commute (#) Sleeping In (#) I Eat Books for Lunch (#) Playing Hooky (#) - they were spending way more time reading (#)\n
than the people reading at night (#) Happy Hour (#), Witching Hour (#), Primetime (#) and with people reading at “bedtime” Better in Bed (#) spending 42% less time reading per session than the average. This was a big shock to us. A lot of us have this preconception that the book industry is kinda powered by the bedside table, and by the almighty trinity of Beach, Bath, and Bed. But this would suggest that at least 2 of those -- Bath time and Bed time -- might not be where people spend as much time reading.\n
than the people reading at night (#) Happy Hour (#), Witching Hour (#), Primetime (#) and with people reading at “bedtime” Better in Bed (#) spending 42% less time reading per session than the average. This was a big shock to us. A lot of us have this preconception that the book industry is kinda powered by the bedside table, and by the almighty trinity of Beach, Bath, and Bed. But this would suggest that at least 2 of those -- Bath time and Bed time -- might not be where people spend as much time reading.\n
than the people reading at night (#) Happy Hour (#), Witching Hour (#), Primetime (#) and with people reading at “bedtime” Better in Bed (#) spending 42% less time reading per session than the average. This was a big shock to us. A lot of us have this preconception that the book industry is kinda powered by the bedside table, and by the almighty trinity of Beach, Bath, and Bed. But this would suggest that at least 2 of those -- Bath time and Bed time -- might not be where people spend as much time reading.\n
than the people reading at night (#) Happy Hour (#), Witching Hour (#), Primetime (#) and with people reading at “bedtime” Better in Bed (#) spending 42% less time reading per session than the average. This was a big shock to us. A lot of us have this preconception that the book industry is kinda powered by the bedside table, and by the almighty trinity of Beach, Bath, and Bed. But this would suggest that at least 2 of those -- Bath time and Bed time -- might not be where people spend as much time reading.\n
than the people reading at night (#) Happy Hour (#), Witching Hour (#), Primetime (#) and with people reading at “bedtime” Better in Bed (#) spending 42% less time reading per session than the average. This was a big shock to us. A lot of us have this preconception that the book industry is kinda powered by the bedside table, and by the almighty trinity of Beach, Bath, and Bed. But this would suggest that at least 2 of those -- Bath time and Bed time -- might not be where people spend as much time reading.\n
But where the preconception holds is that it is still the time when *the most people spend time reading. More people get their reading time in during those hours between 8pm and midnight.\nIt is also still where we see people do most of their *buying.\n
But where the preconception holds is that it is still the time when *the most people spend time reading. More people get their reading time in during those hours between 8pm and midnight.\nIt is also still where we see people do most of their *buying.\n
But where the preconception holds is that it is still the time when *the most people spend time reading. More people get their reading time in during those hours between 8pm and midnight.\nIt is also still where we see people do most of their *buying.\n
\n
\n
\n
The first thing you’ll notice is that they don’t even sit in our pricing cohorts. And they aren’t consumers per se. The freegan is like Dark Matter - they are this vast bulk of downloaders who barely show up on our radar.\n
Web is far and away the chosen content consumption platform (#) of the Freegan. ((Talk about that distribution)) Now that’s for a number of reasons...\n
\n
\n
\n
This is a graph of people who are both ebook *purchasers* and free content consumers. Most ebook buyers read (or at least start) at least 1 free book first. We see them in a few distinct groups.\n# eBook training wheels\n# I heart Jane Austen (and the Brontes and maybe a little tolstoy)\n\n
This is a graph of people who are both ebook *purchasers* and free content consumers. Most ebook buyers read (or at least start) at least 1 free book first. We see them in a few distinct groups.\n# eBook training wheels\n# I heart Jane Austen (and the Brontes and maybe a little tolstoy)\n\n
# But way at the other end we have these interesting guys we call (#) the Freegans. Most of what they read is free. They actively seek it. They look for new good free stuff.\n\n
en we go a little more fine-grained\nFreegans - just some people who can find 10 free books they like. Lots of those. Generally more functional - “these are the books I like”\nFreegan librarians. Want to have lots of books in their accounts, on their shelves. From them, we get a lot of requests for the ability to categorize their collections, more discovery options...\n# Freegan Hoarders - almost compulsive desire to stuff their library with free books. Even though they’re all available any time they want. Even though they could never read them all. In some cases, thousands of books.\n\n
en we go a little more fine-grained\nFreegans - just some people who can find 10 free books they like. Lots of those. Generally more functional - “these are the books I like”\nFreegan librarians. Want to have lots of books in their accounts, on their shelves. From them, we get a lot of requests for the ability to categorize their collections, more discovery options...\n# Freegan Hoarders - almost compulsive desire to stuff their library with free books. Even though they’re all available any time they want. Even though they could never read them all. In some cases, thousands of books.\n\n
en we go a little more fine-grained\nFreegans - just some people who can find 10 free books they like. Lots of those. Generally more functional - “these are the books I like”\nFreegan librarians. Want to have lots of books in their accounts, on their shelves. From them, we get a lot of requests for the ability to categorize their collections, more discovery options...\n# Freegan Hoarders - almost compulsive desire to stuff their library with free books. Even though they’re all available any time they want. Even though they could never read them all. In some cases, thousands of books.\n\n
\n
\n\n
\n
For the first time in a long time, we aren’t just thinking about what goes inside books or how they are designed or how they are marketed. We’re thinking about the reading experience itself. How can we make that experience easier, more enjoyable.\n
And how can we do it while keeping in mind that there are lots of different kinds of people who all have their own definition of what reading is.\n\n
When you get down to it, we are fighting for those tiny slices of people’s day. The more enjoyable we can make that, the more we can enhance that experience, the better we’ll be.\n