china: data driven user engagement and acquisition
DESCRIPTION
Leveraging Data and Technologies for Marketing and Advertising in order to create opportunities in Optimization, Segmentation, Targeting, CRM, Users Profiling.TRANSCRIPT
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
Page 3 Data Strategy and Innovation
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
Page 4 Data Strategy and Innovation
Data Optimization:
The Opportunity
Page 5 Data Strategy and Innovation
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
Page 6 Data Strategy and Innovation
Media and Data
Optimization:
The Opportunity
Page 7 Data Strategy and Innovation
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.
Page 8 Data Strategy and Innovation
For Unpaid media this means: Keeping users highly engaged providing them with the right content, at the right time, in the right place.
Page 9 Data Strategy and Innovation
So, what does this look like
today?
Page 10 Data Strategy and Innovation
The Online Media landscape
in Europe
• Complex and sophisticated
• Opportunity to operate similarly in China within a simpler environment
Page 11 Data Strategy and Innovation
Source: http://www.lumapartners.com/lumascapes/display-ad-tech-lumascape/
Page 12 Data Strategy and Innovation
2014 Global Display
Advertising Ecosystem
How this looks in China
today...
Page 13 Data Strategy and Innovation
Source: http://www.rtbchina.com/rtb-redefines-media-buying-china.html (April 2012)
Page 14 Data Strategy and Innovation
The Online Media landscape
in China
DMP (Data Management Platforms) On site optimization
Page 15 Data Strategy and Innovation
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)
Page 16 Data Strategy and Innovation
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
Page 17 Data Strategy and Innovation
Some Key Terminologies
Page 18 Data Strategy and Innovation
Users:
Engagement, Optimization
and Acquisition
Page 19 Data Strategy and Innovation
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
Page 20 Data Strategy and Innovation
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
Page 21 Data Strategy and Innovation
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
Check point 4 Action 5
Page 22 Data Strategy and Innovation
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
Page 23 Data Strategy and Innovation
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?
Check point 1 Action 2
Create profile Action 1
Check point 2 Action 3
Page 24 Data Strategy and Innovation
2. Client and/or Partner Database
Action Plan
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
Page 25 Data Strategy and Innovation
2. Client and/or Partner Database
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).
Page 26 Data Strategy and Innovation
2. Client and/or Partner Database
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
Page 27 Data Strategy and Innovation
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).
Page 28 Data Strategy and Innovation
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
Page 29 Data Strategy and Innovation
3. Referrals
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
Page 30 Data Strategy and Innovation
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
Page 31 Data Strategy and Innovation
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
Page 32 Data Strategy and Innovation
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
Page 33 Data Strategy and Innovation
4. Unregistered Users and New Users Acquisition
So, even if we don’t know
these users…
We can learn about them…
Page 34 Data Strategy and Innovation
4. Unregistered Users and New Users Acquisition
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
Page 35 Data Strategy and Innovation
4. Unregistered Users and New Users Acquisition
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
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
Page 36 Data Strategy and Innovation
4. Unregistered Users and New Users Acquisition
Hub site
Home Page
Page 1
Page 2
Registration started
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
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
Page 37 Data Strategy and Innovation
4. Unregistered Users and New Users Acquisition
Registration completed
Example.
Off-site: Media
HubAd
Publisher 1 site Hub site
Home Page
Page 1
Page 2
Registration started
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
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
Page 38 Data Strategy and Innovation
4. Unregistered Users and New Users Acquisition
Hub site
Home Page
Page 1
Page 2
Registration started
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.
Page 39 Data Strategy and Innovation
4. Unregistered Users and New Users Acquisition
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
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
Page 40 Data Strategy and Innovation
4. Unregistered Users and New Users Acquisition Opportunity.
Vendor 1: adserving in China
Major Publishers
• Publisher 1
• Publisher 2
• Publisher 3
• Publisher 4
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
Page 41 Data Strategy and Innovation
4. Unregistered Users and New Users Acquisition Opportunity.
Vendor 2: adserving in China
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
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
Page 42 Data Strategy and Innovation
4. Unregistered Users and New Users Acquisition Opportunity.
Vendor 3: adserving in China
Case study
X times higher CTR than past campaigns
Y times more cost-effective traffic driving
Audience reach: XX% - YY%
Page 43 Data Strategy and Innovation
4. Unregistered Users and New Users Acquisition
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
Page 44 Data Strategy and Innovation
4. Unregistered Users and New Users Acquisition
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
Page 45 Data Strategy and Innovation
Summary
Page 46 Data Strategy and Innovation
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
Page 47 Data Strategy and Innovation
Minimum Budget Required
元元
元元 元元
元元 元元 元元 元元
元元
元
元
Page 48 Data Strategy and Innovation
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
Page 49 Data Strategy and Innovation
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
Page 50 Data Strategy and Innovation
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
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
Page 51 Data Strategy and Innovation
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
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
Page 52 Data Strategy and Innovation
Media Spending Timeline
(by month)
Page 53 Data Strategy and Innovation
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:
Page 54 Data Strategy and Innovation
About me
Page 55 Data Strategy and Innovation
http://www.linkedin.com/in/marcodecesaris
Contact details
Marco De Cesaris
Page 56 Data Strategy and Innovation
Backup
Page 57 Data Strategy and Innovation
Vendors:
Cost and Timeline
Vendor 1
Ad Serving and Retargeting
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
Page 58 Data Strategy and Innovation
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%
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
Page 59 Data Strategy and Innovation
Vendor 1
元
Vendor 2
Ad Serving and Retargeting
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
Page 60 Data Strategy and Innovation
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
¥ ¥ ¥ ¥ ¥
¥ ¥ ¥ ¥ ¥
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
Page 61 Data Strategy and Innovation
Vendor 2 Reach: YY%
Vendor 3
New Ad Technologies
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
Page 62 Data Strategy and Innovation
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
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
Page 63 Data Strategy and Innovation
Vendor 3 Reach: ZZ%
Vendor 4
New Ad Technologies
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
Page 64 Data Strategy and Innovation
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
¥ ¥ ¥ ¥ ¥
?
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
Page 65 Data Strategy and Innovation
Vendor 4 Reach: JJ%
Vendor 5
New Ad Technologies
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
Page 66 Data Strategy and Innovation
TIMELINE: x working days to setup
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%
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
Page 67 Data Strategy and Innovation
Vendor 5 Reach: XX%
Vendor 6
OFF-LINE
Data Partnership
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
Page 68 Data Strategy and Innovation
TIMELINE: x working days to setup
COST: y-z RMB per record
BUDGET: min. X RMB per campaign (assuming 1 campaign per month)
y-z ¥
¥ ¥ ¥ ¥ ¥ M1 M2 M3 M4 M5
¥ ¥ ¥ ¥ ¥
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
Page 69 Data Strategy and Innovation
Reach: >Y Mio
Vendor 6
In House Optimization: Site and CRM
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
Page 70 Data Strategy and Innovation
Vendor 7
TIMELINE: x working days to setup
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 ¥
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
Page 71 Data Strategy and Innovation
Vendor 7
¥ ¥ ¥ ¥ ¥ M1 M2 M3 M4 M5
Page 72 Data Strategy and Innovation
Page 73 Data Strategy and Innovation
Credits
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Page 74 Data Strategy and Innovation
Credits
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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
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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
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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.
Page 77 Data Strategy and Innovation
Other Credits
Page 5: http://www.gooddata.com/images/uploads/big-data-image.jpg
Page 78 Data Strategy and Innovation
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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
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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
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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
Page 81 Data Strategy and Innovation
Other Credits