China: Data Driven User Engagement and Acquisition

China

A look at the Opportunities in: Optimization, Segmentation, Targeting, CRM, Users Profiling.

Innovation

Strategy

Data

Data Driven User Engagement

and Acquisition

Media Optimization:

The Opportunity

Page 2 Data Strategy and Innovation

Advanced Technologies


1. CPM = Cost per Thousand

Richer data

CPM1 is gone

Data, technology, media and campaign optimization give us enormous potential to make spend more efficient

and to be more consumer relevant


Data Optimization:

The Opportunity


1. Websites, apps, databases, media, social networks, micro blogs, emails, forums, bbs, offline events, newspapers, magazines, outdoor, etc… most of these activities/media/platforms provide a huge amount of powerful data to be leveraged by the organization.

•  Platforms: plenty of useful data1 •  Data value: underestimated and

not made actionable

•  Easy to improve and make it scalable across the organization


Media and Data

Optimization:

The Opportunity


For Paid Media this means: Assigning budget in a scientific way and optimizing by using data driven solutions giving positive impact on spending, performances, and achievable goals/metrics.


For Unpaid media this means: Keeping users highly engaged providing them with the right content, at the right time, in the right place.


So, what does this look like

today?


The Online Media landscape

in Europe

•  Complex and sophisticated

•  Opportunity to operate similarly in China within a simpler environment


Source: http://www.lumapartners.com/lumascapes/display-ad-tech-lumascape/


2014 Global Display

Advertising Ecosystem

How this looks in China

today...


Source: http://www.rtbchina.com/rtb-redefines-media-buying-china.html (April 2012)


The Online Media landscape

in China

DMP (Data Management Platforms) On site optimization


Ad Serving / DSP (Demand Side Platforms)

Some of the “Global/Local”

Players

Targeting

Data and Optimization

Re-targeting Behavioral targeting Smart Ads

Frequency capping Trading desks Data

suppliers

Demand Side Platform

(DSP)

Audience Expansion (Look alike modeling)


Key Terminologies

Smart Ads: every ad is personalized and optimized for its viewer Retargeting: identify users who did a previous action (whether on 1st or 3rd party websites), and expose them to a specific ad accordingly Behavioral Targeting: profiling users according to their online activities (also offline where possible). Audience Expansion: analyzes converters and identifies similar profiles DSP (Demand Side Platform): centralized media buying focused on users rather than sites. Data Suppliers: provide data on online/offline consumers

Trading Desk: buy and optimize media and audience using DSP Frequency Capping: limit the times a user is exposed to an ad


Some Key Terminologies


Users:

Engagement, Optimization

and Acquisition


4 Key Audience/Target

Opportunities

1.  Registered users 2. Client and/or

Partner Database

3. Referrals

4. Unregistered Users and New Users Acquisition

Action

Decision

No Yes Follow


Diagram Definitions

Main goal:

persuade already registered users1 to activate their account and complete their profile.

Follow up:

regular targeted emails based on their declared information and web behavior to keep them highly engaged.

1.  Registered users


1. In this specific case once a user registers, will need a further step to activate his account (mainly will need to click on a link sent to his email address)

Objectives

Registered user

Coming from

platform X?

Send activation msg

Check point 2

Action 3

Check point 3 Action 4

Profile complete

d?

Action 7

Regular emails (opted in) based on

behavior, or on site

targeting (opted out)

Engagement

score evaluati

on

Action 6



1.  Registered users

N.B. Most of the original content in the boxes (actions and decisions) has been replaced with generic content. For more details feel free to contact me: http://www.marcodecesaris.com

Action Plan

Main goal:

target new prospects1 and increase number of registrations. Leverage existing Client’s database(s)

More:

In order to expand users’ profile (and get to know more and better about our users – including social connections2) would be worthy doing db match with external data partners.

Follow up:

Build a lookalike model1 and identify similar users (potential converters).

2. Client and/or Partner Database


Objectives

1.  Building a lookalike model based on client’s db, would allow to identify a converter’s profile. Then similar users could be found within the client db, within the partners’ db or even across the internet. This would allow to identify new prospects and increase number of registrations.

2.  Identifying social connections could be leveraged for acquiring new prospects through social targeting.

Client DB or Partner DB

Has the user got

a profile?


Create profile Action 1




Action Plan




Defining the Opportunity

1.  For example it could be used for geo-targeting with household income level indicators. 2.  N.B. Part of the content has been removed. This database could be used for interest based targeting, on and off line geo targeting. 3.  Possibility of creating partnerships with specific enterprises and get access to their customers: e.g. “pampers” (families with babies).



Data Partner

Objectives: new users acquisition, refining existing

users profile

Main Databases:

1. National Address Database – X Millions records, covers all the household addresses in China1

2. National Magazines Subscription Database – Y Millions records. It includes addresses and […]2

3. National Small and Medium Size Enterprise Database – Z Millions records. It includes the type of industry and contact of the enterprise3

N.B. Some of the content in this slide has been removed (e.g. information in the NATIONAL MAGAZINES SUBSCRIPTION DATABASE). For more details feel free to contact me: http://www.marcodecesaris.com

Main goal: Leveraging the data once we know users are interested in our brand, products, services1.

3. Referrals


1.  The assumption is that first we collect users’ data on a hub website, not on the official branded website. E.g. We could collect users data on a game platform sponsored by Brand X. Then Brand X will use the users data in order to promote its products/services to the different users who explicitly agreed on the data usage policy.

Objectives 1/2

Follow up: Targeting registered users with specific messages about client’s products or services (through banner on the hub1 website for example).


3. Referrals

Follow up: Referring those users to Client’s website (rather than to the initial hub1 for example)

1.  The assumption is that we collect users’ data on a hub website, not on the official branded website. E.g. We could collect users data on a game platform sponsored by Brand X. Then Brand X will use the users data in order to promote its products/services to the different users who explicitly agreed on the data usage policy.

Objectives 2/2

Referrals

Has the user got

a profile?

Action 1

Send brand (no hub) email

accordingly

Action 2

Check Point 1


3. Referrals


Action Plan


Getting closer to

Global Best Practices

LOW HIGH Accountability & Effectiveness

CPD/CPM CPM/CPC/CPA CPM/CPC/CPA CPM with CPC or CPA goal

Site Specific

Ad Network (Vertical) Ad Exchange DSP Real-

Time Bidding


Evolved Online Media

Strategy

Main goal:

Unlock the potential of Smart Advertising/DSP/Data

Providers, by targeting unregistered users (on and offline)

according to their 3rd party profile, 3rd party behavior

and/or engagement with hub/brand/client website.

Follow up:

Paid media1, Unpaid media2

4. Unregistered Users and New Users Acquisition


Tapping into

“Smarter Data” - Objectives

1.  Such as: Accuen, Xaxis, MediaMind, Ipinyou, Google DoubleClick, Dratio, AdSame, MyThings, CognitiveMatch, Yahoo Dapper, Criteo, etc… 2.  Such as: Omniture Test and Target, Hubspot

Off-site On-Site



So, even if we don’t know

these users…

We can learn about them…



Off-site: Media

Hub Ad

Target Audience: Male, 20-40 years old, interested in Finance and Sport.

Publisher 1 site

N.B. Part of the information in this slide (figures, vendor’s name, publisher’s name, and percentages) has been voluntarily replaced with generic names and characters (e.g. X%, a%, x, y, Vendor 1, Publisher 3, etc…). For more details feel free to contact me http://www.marcodecesaris.com



Hub site

Home Page

Page 1

Page 2

Registration started

Example.

Off-site: Media

1.  User lands on Publisher 1 site (where we bought display ads). User qualifies to be served our ad.

2.  Our Ad (Hub Ad) is served to the user.

3.  User clicks on “Hub Ad” and lands on our “Hub site”.

1

21

2

3

3

HubAd

Publisher 1 site




Hub site

Home Page

Page 1

Page 2


Example.

Off-site: Media

1.  User visits several pages in our “Hub site”, and starts the registration process on the registration page.

2.  User leaves the “Hub site” without completing the registration.

4

5

4

5

Publisher 2 site Hub site

Complete Registrati

on




Registration completed

Example.

Off-site: Media

HubAd

Publisher 1 site Hub site

Home Page

Page 1

Page 2


1.  Later on the same user visits Publisher 2 site, and the user (cookie) is recognized by the ad serving system, and a customized ad is served accordingly.

2.  User clicks on the ad and land directly on the registration page of our “Hub site”.

6

7

6

7

HubAd

Publisher 1 site Publisher 2 site Hub site

Complete Registrati

on




Hub site

Home Page

Page 1

Page 2


Registration completed

Example.

Off-site: Media 1.  User completes the

registration process starting from the point where he left during the previous visit.

8

8

Despite the user being not registered with us, the system is able to identify the user once again across the network and then facilitates the final registration by serving a customized message at the right time in the right place.



Who are

the best

smart players

to partner with

in China?

Major Adnetworks

•  Ad Network 1

•  Ad Network 2

•  Ad Network 3

•  Ad Network 4

Major Publishers

•  Publisher 1

•  Publisher 2

•  Publisher 3

•  Publisher 4



4. Unregistered Users and New Users Acquisition Opportunity.

Vendor 1: adserving in China

Major Publishers

•  Publisher 1

•  Publisher 2

•  Publisher 3

•  Publisher 4





Buying the audience is more efficient

than buying inventory

Vendor 3 IS: A platform combining data, media, technology & strategy A means to enhance optimization and conversion A tool providing more efficiency, greater control & deeper insights Vendor 3 is NOT: A 3rd party company An account servicing team





Case study

X times higher CTR than past campaigns

Y times more cost-effective traffic driving

Audience reach: XX% - YY%



On-site

1. Case study: Targeted content results in xxx% increase in registration completions; Customized content drives response rate up yy%; Click-through rates on homepage content slot jump zzz% N.B. Part of the information in this slide (figures, vendor’s name, and percentages) has been voluntarily replaced with generic names and characters (e.g. X%, a%, x, y, Vendor 1, etc…). For more details feel free to contact me http://www.marcodecesaris.com



Our website

Home Page

Our website

Sporty Red Car

Features: bla bla bla bla bla Engine: bla bla bla bla bka bka Wheels: bla bla bla bla bla Price: bla bla bla bla bla bla bla

Example.

On-site retargeting

2

3

3. User clicks on the onsite banner and lands on the Sporty Red Car page.

3 1.  User searches for “sporty red car” on Baidu and click on the link.

2. User lands on our Home Page and according to the search keyword an onsite customized banner is displayed (sporty red car)

21

1

• Opportunity exists for players to adopt and leverage these advanced marketing technologies in the Chinese market

• To meet Client’s objective, there is the potential to see media spend work harder through optimization

•  Improve performance both in terms

of cost per acquisitions and engagement


Summary


What Are The Performances

And The Cost Involved?

Minimum Recommended Budget (monthly or by campaign)

Performances from previous case studies

Vendor 1 CPA: 8% of display

Vendor 2 w/o Vendor 2 w Vendor 2

CTR 0.05%-0.1% 1.5%-2%

Vendor 3

CPM: - 85% VS planned CPC: - 61% VS planned Impressions: + 683% VS planned Clicks: + 255% VS planned

Vendor 4 # registrations: +1000%

Vendor 5

w/o Vendor 5 w Vendor 5

CTR 0.68% 1.30%

CR 0.71% 1.09%

Vendor 6 N/A

Vendor 7 CR: 108% increase

元 = X RMB = no min budget required

N.B. Part of the information in this slide (figures, indicative budget, vendor’s name, and percentages) has been voluntarily replaced with generic names and characters (e.g. X%, a%, x, y, Vendor 1, etc…). For more details feel free to contact me http://www.marcodecesaris.com


Minimum Budget Required

元元

元元元元

元元元元元元元元

元元

元

元


Recommendations

Testing these new data and technologies for marketing

and advertising

with a minimum budget.

Goal: improving KPIs of X%. N.B. Part of the information in this slide (figures, vendor’s name, and percentages) has been voluntarily replaced with generic names and characters (e.g. X%, a%, x, y, Vendor 1, etc…). For more details feel free to contact me http://www.marcodecesaris.com


Minimum budget required: YY RMB

Target: X% KPIs improvement

N.B. Part of the information in this slide (figures, vendor’s name, and percentages) has been voluntarily replaced with generic names and characters (e.g. X%, a%, x, y, Vendor 1, etc…). For more details feel free to contact me http://www.marcodecesaris.com


CPC (RMB)

CPV (RMB)

CPL (RMB)

Average hub historical campaign performances

x y z

TARGET by using the suggested data/ad technologies

(1-J%)x (1-J%)y (1-J%)z

Ad/Data Technology Budget allocated (RMB)

Vendor 1 X RMB (over y months)

Vendor 2 X RMB (over z months)

Vendor 3 X RMB (over z months)

Vendor 4 X RMB + production cost

Vendor 5 X RMB ( j campaigns)

Vendor 6 X RMB ( j campaigns)

TOTAL XX RMB



Budget Allocation

No Data/Ad Technology Duration M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 M12

1.1 Vendor 1 x months

1.2 Vendor 2 y campaigns

2 Vendor 3 y months

3 Vendor 4 y months

4 Vendor 5 y months

5 Vendor 6 y months

DSP

DMP

AS

DSP

AS

AS



Media Spending Timeline

(by month)


Thank You

EXPERTISES:

Data Strategy & Planning, Custom Data Solutions, Marketing Technologies, Advertising, Advanced Targeting, Optimization, Smart Advertising,

DSPs,

Measurement, CRM,

Social Media, Marketing,

Insights and Analytics,, Innovation.

COMPANIES/CLIENTS I worked for:


About me


http://www.linkedin.com/in/marcodecesaris

Contact details

Marco De Cesaris


Backup


Vendors:

Cost and Timeline

Vendor 1

Ad Serving and Retargeting



TIMELINE: from x to y working days to setup

COST: it varies between X% of media spend and CPM model if creative size > 40Kb

BUDGET: no minimum budget required

<ZKb YYY: X%

>=ZKb CPM

Reach: XX%



Vendor 1

元

Vendor 2

Ad Serving and Retargeting



TIMELINE: from x to y working days to setup

COST: Client usually pay by CPM. Vendor 2 will put down the media list, the CPM price, the estimated CPC, impressions, and estimated clicks etc in the media plan.

CPM: X to Y RMB

CPC: Z to J RMB

BUDGET: suggestion is to spend X RMB per campaign (assuming 1 campaign per month) ¥ ¥ ¥ ¥ ¥

M1 M2 M3 M4 M5

¥ ¥ ¥ ¥ ¥

¥ ¥ ¥ ¥ ¥



Vendor 2 Reach: YY%

Vendor 3

New Ad Technologies



TIMELINE: x working days to setup

COST: min y%; max z% of media spend

AS: a% M&A: b% AC: y%

BUDGET: recommendation is to spend J RMB over k months

¥ ¥ ¥ ¥ ¥ M1 M2 M3 M4 M5



Vendor 3 Reach: ZZ%

Vendor 4

New Ad Technologies



TIMELINE: x to y working days to setup

COST: vendor 4 will make profit out of the media spent. Details not released.

BUDGET: min. Z RMB per month

¥ ¥ ¥ ¥ ¥ M1 M2 M3 M4 M5

¥ ¥ ¥ ¥ ¥

?



Vendor 4 Reach: JJ%

Vendor 5

New Ad Technologies




COST: min y%; max z% of media spend, depending on file size and other add on

BUDGET recommended: >X RMB M1 M2 M3 M4 M5

¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥

size 1 Cost: y%

size 2 Cost: z%

Clicks tracking:

a%

Imps + clicks

tracking: b%

Add on: c%



Vendor 5 Reach: XX%

Vendor 6

OFF-LINE

Data Partnership




COST: y-z RMB per record

BUDGET: min. X RMB per campaign (assuming 1 campaign per month)

y-z ¥

¥ ¥ ¥ ¥ ¥ M1 M2 M3 M4 M5

¥ ¥ ¥ ¥ ¥



Reach: >Y Mio

Vendor 6

In House Optimization: Site and CRM



Vendor 7


COST: initial setup X RMB + Y Mio server calls Z RMB

BUDGET: minimum J RMB over the first 12 months, then K RMB per year

Y MM adcalls:

Z ¥

setup: X ¥



Vendor 7

¥ ¥ ¥ ¥ ¥ M1 M2 M3 M4 M5



Credits

Page 2: http://upload.wikimedia.org/wikipedia/commons/f/f0/DARPA_Big_Data.jpg

Page 3: http://www.flickr.com/photos/uscensusbureau/6878356946/sizes/o/

Page 4: http://www.flickr.com/photos/scobleizer/4695267529/

Page 4: http://www.flickr.com/photos/68751915@N05/6355840185/

Page 21: http://www.flickr.com/photos/gsi-r/5341765493/sizes/l/

Page 33: http://www.flickr.com/photos/rohypnol/854518562/sizes/o/

Page 34: http://www.flickr.com/photos/mkhmarketing/8468788107/sizes/o/

Page 43: http://upload.wikimedia.org/wikipedia/commons/7/75/Internet1.jpg

Page 26: http://upload.wikimedia.org/wikipedia/commons/4/4c/Clouds_double_exposure.jpg

Page 31: http://upload.wikimedia.org/wikipedia/commons/1/1c/Evolution-des-wissens.jpg

Page 44: https://www.flickr.com/photos/motosclasicas/8726158779/sizes/o/


Credits

Page 52: http://www.flickr.com/photos/32307961@N06/3525061913/sizes/o/

Page 53: http://commons.wikimedia.org/wiki/File:Ignorance_is_bliss_-_shortbread_cookie_with_a_smile.jpg

Page 54: http://farm7.staticflickr.com/6109/6290003115_7788c41563_b_d.jpg

Page 56: http://www.flickr.com/photos/pathfinderlinden/7155072088/sizes/o/

Page 58, 60: https://c2.staticflickr.com/4/3346/3573644189_4fde8bbb9e_z.jpg?zz=1

Page 49: http://www.flickr.com/photos/snre/6946913449/sizes/k/

Page 50: http://www.flickr.com/photos/teegardin/6093690339/sizes/l/

Page 51: http://www.flickr.com/photos/comedynose/5043010086/sizes/o/

Page 48: http://www.flickr.com/photos/dgoomany/4976873914/sizes/o/

Page 46: http://www.flickr.com/photos/teegardin/5912231439/sizes/o/

Page 45: http://upload.wikimedia.org/wikipedia/commons/5/5b/Checkmate.jpg


Credits

Page 76, 77, 78, 79, 80, 81: http://upload.wikimedia.org/wikipedia/commons/4/4f/Copyright-_all_rights_reserved.png

Page 72: https://www.flickr.com/photos/monana7/324669781/

Page 70: https://www.flickr.com/photos/beantin/7649183772/sizes/l/in/photostream/

Page 68: http://upload.wikimedia.org/wikipedia/commons/f/f7/Sant'Olcese-villa_Serra_di_Comago-interno.jpg


Note

The following list of images are images used in this presentation. I would like to thank the owners of

those images as those images perfectly match the content of this presentation. I tried to look

for similar images covered by cc license but it was practically impossible to find suitable ones

able to replace the below list.

Hence I decided to use those original images (or slightly adapted) where the copyright logo is clearly missing.

Despite of it, it could happen that I have to remove those images at a later stage if I am asked to do so by the owners of the images.


Other Credits

Page 5: http://www.gooddata.com/images/uploads/big-data-image.jpg


Other Credits

Page 7: http://www.befragungsinstitut.org/wp-content/uploads/2013/05/qm_97931741.jpg

Page 1: http://www.fromquarkstoquasars.com/wp-content/uploads/2013/02/blue-binary-code-jigsaw-puzzle.jpg

Page 6: http://www.filmofilia.com/wp-content/uploads/2011/06/moneyball_16.jpg

Page 8: http://media.cleveland.com/pdq_impact/photo/einsteinjpgjpg-4a389e85f92a0547.jpg

Page 9: http://nousygihs.files.wordpress.com/2011/03/youth_excited.jpg

Page 11: http://www.struggletovictory.com/wp-content/uploads/2012/03/Simple-4.jpg

Page 8: http://lh3.ggpht.com/_089TXf8rQcw/Si6S2nlmEVI/AAAAAAAABW0/WEkML4LGWS0/ing_2%5B4%5D.jpg?imgmax=800

Page 8: http://www.iconsdb.com/icons/download/white/accept-database-512.gif

Page 8: http://colouringbook.org/SVG/2011/COLOURINGBOOK.ORG/chovynz_money_bag_icon_black_white_line_art_scalable_vector_graphics_svg_inkscape_adobe_illustrator_clip_art_clipart_coloring_book_colouring-555px.png

Page 17: http://mystrategicplan.com/wp-content/uploads/2013/08/Glossary17.jpg


Other Credits

Page 16: http://www.bluebumblebee.co.uk/wp-content/uploads/2013/04/file0001817248786.jpg

Page 18: http://strategicsalesmarketingosmg.files.wordpress.com/2012/06/shutterstock_59234440.jpg

Page 19: http://marketwave-site.crane-west.net/wp-content/uploads/2012/01/hires.jpg

Page 20: http://michele-norris.com/wp-content/uploads/2012/02/writing-pencil.jpg

Page 22, 24, 29: http://charmedyogi.files.wordpress.com/2013/06/what-if.jpg

Page 23: http://profilesasiapacific.com/blog/wp-content/uploads/2013/05/puzzle.jpg

Page 12: http://www.sgeier.net/fractals/fractals/11/Tetris.jpg

Page 13: http://1.bp.blogspot.com/-X2AX0IVb4fA/T0hEbdVRhYI/AAAAAAAADQw/8GFG8bUv4ds/s1600/933320_13694080.jpg

Page 15: http://www.cindysfriendlytavern.com/PageArt/j0403725.jpg

Page 30: http://1.bp.blogspot.com/_JtlCE5dJtCI/SwlJbxOGq0I/AAAAAAAAAlQ/rN-_Fc7yGhI/s1600/digital+1.gif


Other Credits

Page 32: https://news.slac.stanford.edu/sites/default/files/images/announcement/data-brain.jpg

Page 39: http://cina.quotidiano.net/wp-content/uploads/2011/11/yao-ming.jpg

Page 40: http://www.ontariosystems.com/sites/default/files/Ontario_Handshake.jpg

Page 41: http://www.ips-analytics.com/uploads/media/ips_technology_partners.jpg

Page 42: http://www.msktc.org/lib/docs/Reach_Your_Audience.jpg

Page 25: http://www.sam-welch.com/wp-content/uploads/2013/03/Defining-Successful-Data-Management-Programs.jpg

Page 27: http://www.indire.it/immagini/immag/scienzets/ts731-20.jpg

Page 55: http://www.cherryprinthd.co.uk/wp-content/uploads/blog/business-cards.jpg

Page 57, 59, 61, 63, 65, 67, 69, 71: http://boeddhamagazine.nl/wp-content/uploads/2013/10/6812481635_ed463ae1fa_b-800x600.jpg

Page 62, 64, 66: http://sequoiag.com/upload/iblock/c57/c57fbdb6c2674749702f45941f8082de.jpg


Other Credits

China: Data Driven User Engagement and Acquisition

Data & Analytics

data strategy

data optimization

powerful data

innovation users

registered users page

innovation ad

data driven solutions

opportunity page