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Reader Analytics

presented by

Andrew Rhomberg

founder

©Antonio Roselló

Part I

Reader

Analytics

Why ?©Li Dandan

It doesn‘t really matter, does it?

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Publishers are not really

in the business of selling

paper or bits and bytes.

Publishers are in the

business of selling:

• entertainment,

• inspiration,

• skill acquisition, and

• education ©Frederic Bordoni

The Unknown Reader…

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Despite the digital

transformation of the

publishing industry,

authors & publisher

still cannot measure

reader engagement!

Do consumers read

the books they buy?

Part II

Technology

Trawling the Digital Data Lake

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Amazon, Apple, Google and platform operators

collect vast amounts of reading app/device data,

but don‘t share this with publishers.

“Google Analytics for Ebooks”

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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

Readers use familiar Apps

Participating readers can use reading apps and

devices they are already familiar with:

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iBooks

iOS

ADE

Windows

Ebook Reader

Android

Data Collection from 3rd Party Apps

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iBooks Vitalsource Adobe

Digital

Editions

Ebook

Reader

Mantano Azardi Overdrive Bluefire

Cloud-

reader

iOS���� ���� ���� - ���� - ���� ����

Android- ���� ���� ���� ���� ���� ���� -

Kindle Fire- ���� - - - - - -

Windows- ���� ���� - - - ���� -

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3

=

HTML 5 + CSS 3 + JSA key feature of ePub 3 is the support for Javascript,

as well as HTML5 support for offline storage of data.

... 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

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Part III

Tansparency

User in Control

Virtual Focus Groups (ARCs)

1. By Invitation only

2. Explained on Download Page

3. Modified Cover (Candy-stripe)

4. Bookplate at front of book

5. Sync Button

6. “My Data” Page: users can view collected data

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Opt-Out/Opt-in for Retail Copies

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Part IV

Visualising Data

KPIs of a Book

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1. Completion Rate

how many readers finish?

2. Cover & Description

Delivers what it promises?

3. Recommendation factor

do readers rave or rant?

and more…

KPI – 1

Completion Rate

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Completion Rate - Example 1 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

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Completion rate – Example 20% 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

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0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

F

F

F

F

1

2

3

4

5

6

7

8

9

10

B

B

B

B

Completion rate – Example 3

Non-fiction book

Readers read introduction and

decide, it’s not really for them…

(remarkably common)

Completion Rate (narrative fiction)

• 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

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Completion Rate (most non-fiction)

• People only read the “core” and think they have “finished”

• Shorter is not always better (surprise !!)

• Reading style varies a lot for non-fiction

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KPI - 2

Velocity

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Example A – Fast Read

24The majority of users read this ebook on a smartphone

female, 27 female, 25 female, 48

Example B - slow read

25

male, 26

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.26

KPI - 3

Recommendation Factor

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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)

-

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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%

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Trade Publishers

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Pilot Partners – Professional & STM

Professional & STM

• Reading behaviour is sometimes radically

different for STM compared to trade

• What is “trade” and what is “professional” is

varies and depends on the user’s needs

• Trying to understand user journeys, not just

“pages read”

• What content are people actually accessing

• What should be “placed together”

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Reader analytics was made possible

in large part through the financial support of

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Book candy for readers, data candy for publishers.

sign up to be a test reader at jellybooks.com