Download - BEA 2014 - Data Driven Marketing - Engaging Readers & Driving Sales

Data Driven Marketing:Engaging Readers &

Driving SalesBook Expo America 2014 #BEAData

Fauzia Burke Founder and President, FSB Associates

www.fsbassociates.com @FauziaBurke

“You don’t have to be good with

numbersto love #Data”

@FauziaBurke

#BEAData

“Data is not about numbers, it’s about

patterns.”

@FauziaBurke

#BEAData

@FauziaBurke

#BEAData By Domo.com

Kate Rados

Tom Thompson !

Elizabeth Dimarco

@FauziaBurke

#BEAData

Panelists

Data1. Type

2. Method

3. Reason

4. Use

5. Surprises

@FauziaBurke

#BEAData

Kate Rados

Tom Thompson !

Elizabeth Dimarco

@FauziaBurke

#BEAData

Panelists

Data Driven Marketing: Engaging Readers & Driving Sales

@KateRados | #BEAData

#BEAData

#BEAData

Jersey City Moms Meetup Group

#BEAData

Some Ways We Collect Reader Data

•  Site Registration •  Sweepstakes •  Sales •  Surveys •  Email Activity •  Comments and Social Reactions

#BEAData

Some Ways We Use Reader Data for Marketing Efforts

•  Alert Readers to a Local Author Event •  Customize Email Messaging for New Releases

or Promotions •  Reach Readers Where they Read: Community

Sites, Social, Mobile, Email Newsletters, In-Person Events

•  New Online Products: Apps, Downloads, Articles, Giveaways

#BEAData

•  Year-Long Survey •  Questions:

– Who Makes Up the RIF Audience? – Where Do They Get Book

Recommendations? – How Do They Enter Our Weekly Sweeps? – What Types of Books Do They Enjoy?

#BEAData

#BEAData

Data = Audience Compass •  Readers give us data with every interaction, informing us

how they want to communicate and learn about our books.

•  You can customize your conversation based on what a reader reveals.

•  Data is not the only information upon which to base audience development strategy.

•  Reader engagement is a balance of art and science.

Thanks!

@KateRados | #BEAData

THE DATA-‐DRIVEN CAMPAIGN

RATIONAL MARKETING IN A MESSY WORLD

#BEAData [email protected]



[email protected]


Known Knowns

Known Unknowns

Unknown Unknowns

Unknown Knowns


[email protected]

•  Impressions: CPMs for networks v. niche sites v.

premium sites v. super premium sites •  Clicks: CTRs for web v. mobile v. network v. newslePers

•  CPC: Cost per click •  Engagements: In-‐ad views, tweets, posts, emails

•  Conversions: Email sign-‐ups, downloads, purchases, etc.

KNOWN KNOWNS What We Measure

[email protected]

•  Impressions: CPMs for networks v. niche sites v. premium

sites v. super premium sites •  Clicks: CTRs for Web v. Mobile v. Network v. NewslePers

•  CPC: Cost per click •  Engagements: Views, tweets, posts, emails

•  Conversions: Email sign-‐ups, downloads, purchases, etc.

Site Reports, 3rd Party Server Data

KNOWN KNOWNS How We Measure

[email protected]

•  Frequency to conversion •  Path length… •  Time lag… •  Revenue per placement

KNOWN KNOWNS (Part 2) What We Could Measure: Conversion Metrics

[email protected]

Machine learning can inform ad targe@ng by tes@ng and evolving the user profile with demographic, psychographic, behavioral data

KNOWN KNOWNS (Part 2) What We Could Measure: User Profile

[email protected]

KNOWN KNOWNS How We Measure Conversion

& Customer Profile Data

[email protected]

KNOWN KNOWNS How We Measure Conversion

& Customer Profile Data

Site Tags (“Cookies”)

3rd Party Data

Deep Learning Algorithms

Audience Extension “Look-‐alike modeling”

[email protected]

•  Past performance is no guarantee of future results.

•  Why do they (or don’t they) click? Product v. Placement v. Crea@ve v. Timing

•  Display effect: ComScore and IAB studies

•  Which part of the markeLng pie got the sale? Adver@sing, PR, reviews, social, or all-‐the-‐above?

KNOWN UNKNOWNS

[email protected]

•  French Economists •  Bots and Bad Guys •  Unicorns and Sea Monsters •  Amazon

UNKNOWN UNKNOWNS

[email protected]

UNKNOWN KNOWNS

[email protected]

DIGITAL REPORTING

•  CONFIRMS site-‐reported data •  TRACKS effec@ve CTR, CPM, CPA •  MEASURES campaign performance against compe@@ve set

•  DELIVERS ac@onable data •  INFORMS ongoing and future campaigns

[email protected]

Thank you

Tom Thompson

tom@[email protected] @tomthompson

Thank you!

#BEAData [email protected]

BooksILove

The mobile place for conversations between friends

about books.

© 2014, BooksILove™ www.booksilove.com

What types of data do we collect?

Data from readers who are talking about and

recommending books to their friends.


How do we collect it?

•  Readers use our mobile app. •  We get data directly from

readers about the books they love.

•  We’re creating the ultimate focus group.


Why do we collect it? •  Create apples-to-apples comparative data •  See conversational trends ahead of buying

trends •  Gain insights about personal

recommendations


How can it be used to make better marketing decisions? Can help understand: •  Why readers love a book •  Which specific elements of a book are

most loved •  How reader perceptions of one book

compare to another •  What are reader trends •  Who are a book’s fans and evangelists


What has surprised us so far?


We expected:

Clever Page-turning Suspenseful Thrilling


What We Got

Reader 1 Reader 2 Reader 3

Suspenseful

Provocative

Thrilling

Authentic

Believable

Poignant

Surprising

Clever

Plausible

Thoughtful


We expected:

Passionate Inspiring Heart-Breaking Authentic


What We Got


Suspenseful

Passionate

Thrilling

Breath-taking

Authentic

Inspiring

Heart-breaking

Page-turning

Intriguing

Thoughtful


We expected:

Provocative Technical Plausible Hair-raising


What We Got


Suspenseful

Audacious

Thrilling

Provocative

Authentic

Technical

Believable

Page-turning

Plausible

Clever

Surprising


Summary of "readers’ book descriptors


Suspenseful (3)

Passionate

Audacious

Breath-taking

Thrilling (3)

Provocative (3)

Authentic (3)

Heart-breaking

Technical

Inspiring

Believable (2)

Poignant

Page-turning (3)

Plausible

Clever (2)

Surprising (2)

Intriguing

Thoughtful


How the data has surprised us

Readers repeatedly select the same tiles across the

books they love


BooksILove


Download - BEA 2014 - Data Driven Marketing - Engaging Readers & Driving Sales

Top Related