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1
Collecting Reading Data
presented by
Andrew Rhomberg
CEO Jellybooks
@arhomberg
@Jellybooks
©Antonio Roselló
Part I
Why?©Li Dandan
The Unknown Reader…
3
Despite the digital
transformation of the
publishing industry,
authors & publisher
still cannot meas...
It doesn‘t really matter, does it?
4
If readers buy and pay
for books (revenue)
does it matter if they
read them or not
(e...
Part II
How to Collect Reading Data?
Online Content = Web Analytics
6
• Google Analytics
• Kissmetrics
• Mixpanel
• Optimizely
• Adobe Site Catalyst
• Flurry A...
What is an E-Book?
• An E-Book is 90% HTML = “web page”
• Reading application (iBooks, Kindle) = “Browser”
But, but, but:
...
8
Amazon, Apple & Google collect
vast amounts of reading app/device data,
but don‘t share this with publishers.
9
Solution is…
3
10
3
=
HTML 5 + CSS 3 + JS
A key feature of ePub 3 is the support for Javascript,
as well as HTML5 support for offline sto...
... and the data connection?
Engage readers!
When the reader clicks on a
link at end of chapter/book
(styled as a button),...
Readers use familiar Apps
Test reader are recruited based on whether they
already used one of the apps supported by JBKS
1...
“Google Analytics for Ebooks”
13
1. Modified ebook (ePub3 format) distributed to users,
who read on their existing reading...
Part III
Execution
ePub Modification by Jellybooks
• We receive a regular ePub 3
file from publisher
• We modify it with candy.js to
record r...
Format 1: Distribution via Email
16
Format 2: Invitation-only Web Page
17
Survey Follow-up
18
not finishedfinished
Part IV
Visualising Data
KPIs of a Book
20
1. Completion Rate
how many readers finish?
2. Velocity
fast read or slow read?
3. Recommendation factor...
KPI – 1
Completion Rate
21
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
F
F
F
2
4
6
8
10
12
14
16
18
20
22
24
26
28
B
B
Displayed like Table of Conten...
23
Completion Rate - Example
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
F
1
3
5
7
9
11
13
15
17
19
21
23
25
27
29
31
33
3...
24CR: 80% excellent CR: 62% very good
Completion Rate – Examples
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
F
1
3
5
7
9
1...
25
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
F
F
1
3
5
7
9
11
13
15
17
19
B
B
CR: 30% good CR: 20% poor
0% 10% 20% 30% 4...
26
Completion rate – Example
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
F
1
5
9
13
17
21
25
29
33
37
41
45
49
53
57
61
65...
Completion Rate
• Does the book keep
reader’s attention?
• Rate is measured as
percentage relative to
those who start read...
KPI - 2
Velocity
28
Example A – Fast Read
29
The majority of users read this ebook on a smartphone
female, 27 female, 25 female, 48
Example B - slow read
30
male, 26
31
3.7
9.1
10.1
10.4
12.4
12.5
12.8
13.1
14.1
14.4
15.1
16.1
17.5
18.5
20.8
21.6
24.7
26.2
26.8
27.6
32.1
0 7 14 21 28 35
...
Velocity
• Measure of whether
readers glued to the pages
• Are readers coming back
daily/hourly or are they
distracted by ...
KPI - 3
Recommendation Factor
33
34
Would you recommend this book
to a friend?
0 = not all likely 5 = neutral 10 = Extremely likely
0 1 2 3 4 5 6 7 8 9 10
...
35
NPS for Individual Books
“The book was great and I have read
other books by this author. In addition,
I have probably r...
Audience Insights
Demographic Factors
36
37
Demographic Breakdown of CR
Average CR 35%
Gender
male 34%
female 35%
Age
<35 0%
35-45 25%
>45 54%
Profile of a Book
Everything in one Slide
38
An Anonymous Example
“I really want to read the next book.“
“Even as a forty-something woman, I find myself really
enjoyin...
Get a taste for data candy…
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Collecting Ebook Reading Data - Moneyball for Publishers or how we research the way we read

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Dbw_collecting_reading_data_v_3

  1. 1. 1 Collecting Reading Data presented by Andrew Rhomberg CEO Jellybooks @arhomberg @Jellybooks ©Antonio Roselló
  2. 2. Part I Why?©Li Dandan
  3. 3. The Unknown Reader… 3 Despite the digital transformation of the publishing industry, authors & publisher still cannot measure reader engagement! Do consumers read the books they buy?
  4. 4. It doesn‘t really matter, does it? 4 If readers buy and pay for books (revenue) does it matter if they read them or not (engagement)? Ah, but are publishers selling paper or are they offering entertainment and education?©Frederic Bordoni
  5. 5. Part II How to Collect Reading Data?
  6. 6. Online Content = Web Analytics 6 • Google Analytics • Kissmetrics • Mixpanel • Optimizely • Adobe Site Catalyst • Flurry Analytics Use of log files (Server), tracking pixels und Javascript tags for the collection of data.
  7. 7. What is an E-Book? • An E-Book is 90% HTML = “web page” • Reading application (iBooks, Kindle) = “Browser” But, but, but: • server log files = Amazon, Apple, Google, etc. And content is processed/read offline • application logs = Apple, Amazon etc. 7
  8. 8. 8 Amazon, Apple & Google collect vast amounts of reading app/device data, but don‘t share this with publishers.
  9. 9. 9 Solution is… 3
  10. 10. 10 3 = HTML 5 + CSS 3 + JS A key feature of ePub 3 is the support for Javascript, as well as HTML5 support for offline storage of data.
  11. 11. ... and the data connection? Engage readers! When the reader clicks on a link at end of chapter/book (styled as a button), a data connection with Jellybooks is established = user opt-in 11
  12. 12. Readers use familiar Apps Test reader are recruited based on whether they already used one of the apps supported by JBKS 12 iBooks iOS ADE Windows Ebook Reader Android
  13. 13. “Google Analytics for Ebooks” 13 1. Modified ebook (ePub3 format) distributed to users, who read on their existing reading device or app 2. Embedded Javascript software tracks (offline) reading 3. Readers click on button at end of chapter/end of ebook to upload/sync data to Jellybooks 4. Data Visualisation for Author/Agent/Publisher
  14. 14. Part III Execution
  15. 15. ePub Modification by Jellybooks • We receive a regular ePub 3 file from publisher • We modify it with candy.js to record reading data • We automatically insert sync buttons to extract data • We make sure user is aware of the modification via identifiers like “candy stripe” 15
  16. 16. Format 1: Distribution via Email 16
  17. 17. Format 2: Invitation-only Web Page 17
  18. 18. Survey Follow-up 18 not finishedfinished
  19. 19. Part IV Visualising Data
  20. 20. KPIs of a Book 20 1. Completion Rate how many readers finish? 2. Velocity fast read or slow read? 3. Recommendation factor do readers rave or rant? and more…
  21. 21. KPI – 1 Completion Rate 21
  22. 22. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% F F F 2 4 6 8 10 12 14 16 18 20 22 24 26 28 B B Displayed like Table of Contents Each horizontal bar = completion rate for a particular chapter narrative front- and back matter 22 Completion Ratebookchapters
  23. 23. 23 Completion Rate - Example 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% F 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 B B B 20% drop off within first 5 chapters - “not my kind of book” 80% finish book, straight through
  24. 24. 24CR: 80% excellent CR: 62% very good Completion Rate – Examples 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% F 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 B B B 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% F 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 B
  25. 25. 25 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% F F 1 3 5 7 9 11 13 15 17 19 B B CR: 30% good CR: 20% poor 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% F F F 1 3 5 7 9 11 13 15 17 19 21 23 25 27 B B B Completion Rate – Examples
  26. 26. 26 Completion rate – Example 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% F 1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 B A lot of “flipping” (jumping between chapters), which is typical of book titles readers find “have to read” but that don’t hold their attention… Rapid decline of reader engagement in first 100 pages
  27. 27. Completion Rate • Does the book keep reader’s attention? • Rate is measured as percentage relative to those who start reading • Unlike ratings (subjective), this is an observational KPI 27
  28. 28. KPI - 2 Velocity 28
  29. 29. Example A – Fast Read 29 The majority of users read this ebook on a smartphone female, 27 female, 25 female, 48
  30. 30. Example B - slow read 30 male, 26
  31. 31. 31 3.7 9.1 10.1 10.4 12.4 12.5 12.8 13.1 14.1 14.4 15.1 16.1 17.5 18.5 20.8 21.6 24.7 26.2 26.8 27.6 32.1 0 7 14 21 28 35 Ranking by Velocity Days Quick Slow
  32. 32. Velocity • Measure of whether readers glued to the pages • Are readers coming back daily/hourly or are they distracted by other books, movies, social media etc.? • Measure of how “digestible” content is for readers. 32
  33. 33. KPI - 3 Recommendation Factor 33
  34. 34. 34 Would you recommend this book to a friend? 0 = not all likely 5 = neutral 10 = Extremely likely 0 1 2 3 4 5 6 7 8 9 10 Recommendation Factor = Promoters (%) (9s and 10s) Detractors (%) (0 through 6s) -
  35. 35. 35 NPS for Individual Books “The book was great and I have read other books by this author. In addition, I have probably recommended this book to at least a dozen people because it was that good.” Promoters (9,10s) 97 81% Neutrals (7s, 8s) 10 8% Detractors (0-6s) 13 11% Recommendation Factor (Net Promoter Score) 70%
  36. 36. Audience Insights Demographic Factors 36
  37. 37. 37 Demographic Breakdown of CR Average CR 35% Gender male 34% female 35% Age <35 0% 35-45 25% >45 54%
  38. 38. Profile of a Book Everything in one Slide 38
  39. 39. An Anonymous Example “I really want to read the next book.“ “Even as a forty-something woman, I find myself really enjoying YA dystopian fiction.” 39 Male CR 29% NPS 32% Velocity 10 d Price Tolerance $6.27 Completion rate 61% female CR 66% <35 CR 50% >45 CR 78% 35-45 CR 56% gripping (32%) entertaining (32%) good (20%)great (28%)
  40. 40. Get a taste for data candy…

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