Un sales deck pour une DMP

1. SALES
DECK

2. 02
TABLE OF
CONTENTS
PART I
We Have a Big
(Data) problem
• Context
• Opportunity
• Solution
Purpose
PART II
From Chaos To Order
• Real Business Life Stories
• Positioning / Elevator Pitch
• Value Proposition /
PART III
mediarithmics
Platform
• Use Cases
• Key Features
• Roadmap
PART IV
Benefits
• Benefits for the CMO
• Benefits for the CMO’s
Colleagues
PART V
Next Step
Annexes
• Cases Studies
• Questions to ask when
choosing a platform
• Glossary
03 1
7
2
1
24
1
3
07

3. 03
PART I
WE HAVE A
BIG (DATA)
PROBLEM

4. 04
INSIDE, THE DATA HAS IMPLOSED
• For marketers, to locate, unify, activate and interprete the data still
remains a challenge.
• The customer journey intersects numerous teams throughout the
company and external business/data ecosystems.
• The cost for companies of poor data quality increase.
Context
Explosion Outside,
Implosion Inside
OUTSIDE, THE DATA HAS EXPLODED
• GAFA have fundamentally changed the way we do busines thanks to
technology and data.
• Digital disrupters upgrade the ideal customer experience almots daily.
• Customers were given new ways to interact with company and dictate
the terms of engagement with businesses like never before.
$
15
million
The cost of poor data
quality on average for
companies annually,
according to Gartner.

5. 05
The Bottom Line :
55%
The percent of data in organizations
that is dark— meaning companies
don’t know about or use that data3
33%
The percent of companies unable to
get value from a new system or
technology due to data quality problems2
12%
The amount of revenue an average
company loses due to bad data1
(1)How to 33% Overcome the Top Four Data
(2)Quality Practice Challenges, Gartner, 2018. 2020 Global Data Management Research, Experian, 2020).
(3)The State of Dark Data, Splunk, 2019)
Opportunity
The Opportunity Became a
Problem for CMOs
Digital champions have made data use appear so easy that we forget the
complexity involved.
Pressure from the top management for marketing ROI increases.
Technology and organizational silos reinforce.
To many marketing tools coexist inside the organizations.
Scattered internal expertise delay optimized use of data.
Data solutions focusing only on single use case (Analytics, CRM, A/B
Testing, DMP…), not dedicated to a specific industry, proliferate.
Costly and long integration projects go on forever.
Lack of lasting support by data solution providers let CMOs clue less.

6. 06 Solution
To Own Your Data Destinity
Prepare to a Multifaced Effort
1. How to leverage your customer data and increase your competitive
advantage ?
2. How to unify the data you have already collected into a single,
persistent, and robust customer view ?
3. How to unify customer data and make it accessible and actionable in real
time by your team ?
4. How to comply with the laws of the European Union (GRPD) ?
5. How to prepare to a cookieless world ?
6. How to select a scalable, flexible and secure platform ?
7. How not to become technology dependent a new time ?
The Hard Thing about
Hard Facts
A growing number of strategic
and difficult questions is
cascading.
?
?

7. 07
PART II
FROM CHAOS
TO ORDER(S)

8. 08 Real Business Life Stories
mediarithmics Excels in Reconciling of
Data, Technologies, Silos, Business Needs
Canal+
Canal+ wanted to emancipate for
siloed activities so that they can
launch data offers in a TCFv2.0 world.
Canal+ launched new data
offers in a TCFv2.0 world.
TF
1
TF1 wanted to replace Adobe with a
future-proof data-platform.
TF1 works with a new
generation DMP platform.
Channel4
Channel4 wanted to offer audience
profiling to its advertisers so that they
can optimized their ad campaigns, in a
cookieless way.
Channel4 proposes a high
value added offer through a
self-service platform.
Fnac-
Darty
Fnac-Darty wanted to build an all-in-
clusive advertising offer for brands so
that they can take full benefits of their
abundant clients’ data
Fnac-Darty proposes a
self-service platform to the
advertisers.
Prisma
Media
Prisma Media wanted to get better
knowledge of its customers so that
they can both improve acquisition and
monetization strategies.
Prisma Media has a platform
to centralize and activate
reconciled customers’ data
for highest ROI.
They Trust Us

9. 09 Purpose
We Put Sustainability into
Data Cacophony
mediarithmics optimize data use for business, helping companies to embed
the business potential of their data ecosystem responsibly, because data massive
collection is highly impacting for sustainability, climate and environment.
Data For
Social Good
A data roadmap
decarbonization
is mandatory.
Gilles Chetelat
January, 2022.
Optimise Responsible Environment

10. 10 Positionning
We Are Dedicated to Your Industry
mediarithmics is the best reconciler
(of data, technologies, silos, IT and business needs)
among the Data Platforms, for the media.

11. 1
1
Elevator Pitch
We Offer Five Key
Differentiators
Our 5 Key
Success Factors :
Scalability
of volumes
Plurality
of data
Synchronicity
of eco-systems
Customization
of use cases
01
02
03
04
05
For the CMOs who needs to increase their marketing
efficiency and MartTech effort, mediarithmics is an
in- novative SAAS Platform which connects your
company data with multiple other data ecosystems.
Contrary to DMP, CDP and others data solutions,
mediarithmics offers global scalability, data plurality,
permanent synchronicity, use cases customization, and
compatibility between marketing tools.
Compatibility
of technologies

12. 1
2
Value Proposition
We Unleash The Business Potential
of Your Data Ecosystem
We unleash companies’ business potential by reconciling data, technologies,
silos, business needs, then improving their marketing efficiency and their
MarTech effort, providing scalability, exhaustivity, synchronicity, customization,
compatibility, all in one SAAS Platform.

13. 1
3
PART III
MEDIARITHMICS
PLATFORM

14. 14 Use Cases
Top 5 Proven Examples of How
to Use mediarithmics
01
Drive acquisition
for paying services.
04
Swift and effective
campaign execution.
02
Hyper-segmentation
with high volumes
of data.
05
Innovation (additional
use cases, new
offers).
03
Synchronization of data
wherever they come
from with every other
marketing tools (AdTech,
analytics, CRM, e-
commerce, clienteling…),
supporting multiple teams.

15. 15 Key Features
A Features Set Fully Dedicated
to Your Industry
Synchronicity Reconcile user identity, consents and data
Completeness
A Data SAAS Platform offering : Allowing to :
Capture all kind of user data from anywhere
Customization Adapt to your current and future own use cases
Bridges Connect your data with multiple other data ecosystems
Scalability Sustain your data volume growth

16. 16 Roadmap
A Roadmap Co-Constructed With
Your Industry
Funnel analytics
Release status upgraded from Alpha to Beta beginning of May
New upgrades include : improved usability, split by device ...
Release note to come!
Standard segment builder
Release status upgraded from Alpha to Beta beginning of May
New upgrades include : UI for audience features management, folders ...
Release note to come!
Automations
Planned beta release by end of May
New upgrades include : scenario analytics, advanced trigger queries, feed presets ...
Device tracking and
targeting (without 3rd
party cookies)
Data
vizualization
experience
Retail
MDM / Single customer view
Ready to use templates
Multi-app
front end
SSO
Database
enhancements &
usage monitoring

17. 1
7
PART IV
BENEFIT
S

18. 18 Benefits For The CMO
Focus on Marketing More Than
on Technology
TRANSFORM YOUR MARKETING
Switch easily from your historical
solution with an easy set-up
Leverage on your data science effort
bringing your own algorithms
Manage more than 10 billions user
profiles and prepare to scale
Reinforce security
Stay compliant
BY…
Activating up to date data
Connecting all your marketing tools
(advertising, analytics, CRM…)
Targeting individuals, not devices
Using your own marketing scenarios
Getting a 360° view of the users
Improving customer experience
Catching new marketing opportunities
Making marketing analysis reliable
Forgetting limitations
FOCUSING ON ROI
Optimize your MarTech budget
Increase your marketing efficiency
Acquire new clients
Grow ARPU
Boost monetization
Innovate (new use
cases)
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+

19. 19 Benefits For The Chief Data Officer
Empower Your Data Science
+
+
+
+
+
+
Recover data resources thanks to new marketing autonomy (e.g.
for segments creation)
Improve allocation of your data scientists to most value added
missions
Empower data processing thanks to real-time data streaming
towards data lakes (GCP, Azure, AWS)
Inject your homemade algorithms into the platform
Code easily (OTQL) and explore data conveniently
Secure your data compliance

20. 20 Benefits For The CMO’s colleagues
Getting Buy-In at the C-Level
CEO
+ Business growth
+ Additional revenues
+ Increased marketing efficiencies
+ Reinforced competitive advantage
CIO
CTO
+ Security and risk mitigation
+ Bottom line impact
(Return on IT Investments)
+ Increased IT operational efficiencies
CFO
+ Optimized marketing expenses
+ Increased gross profit
+ Improved average gross margin
+ Data compliance
+ Better data qualities and
efficiencies
+ Improved data utilizations

21. 2
1
PART V
NEXT
STE
P

22. 22 Macro Process
Maximize Your Chance
of Success
01
Align Stakeholders
Assemble the team
Establish cross-functional roles
Identify owners
04
Define Action Plan
Set Expectations
Prioritize Objectives
02
Formulate Strategy
Set objectives
Select data sources
Set up process
05
Measure Progress
Schedule measurement
Asses results
Fine tune and iterate
03
Determine Segments
Set user identification strategy
Integrate channels

23. 23
PART V
CONTACT

24. 24
PART VI
ANNEXE
S
01
Cases Studies
03
Glossary
04
Features, Advantages,
Benefits
02
Questions to ask when
choosing a platform
25
34
37
49

25. 25
THE CHALLENGES
How to face regulatory and
technological changes ?
How to create CRM/AdSales use-cases
with a lack od data ?
How to integrate multiple data stacks
and tools into a data lake.
How to manage strong security
requirements ?
THE RESULTS
Successful switch from Bluekai to
Mediarithmics in only 8 weeks
Rapid data volumes increase : 3 billion
events collected per month
Up to 133% more targeting
opportunities
Improved data analysis (connection
with Azure Datalake)
HOW WE HELPED
Making the link between CRM, 3rd
party and online data to cover all TF1’s
use-cases
Responding to cookieless issue with
Edge and ID ingestions
Allowing interfacing with the whole
TF1’s ecosystem.
Executive Summary As a TV channel,
TF1 wanted to replace Adobe with a
future-proof data-platform. mediarith-
mics implemented the next-gen solution.
Case Study
How one of the main French retailers
empowered cross-brands digital strategies

26. 26
THE CHALLENGES
How to handle siloed activities ?
How to manage and ageing DMP not
delivering enough ?
How to prepare to a cookieless world ?
How to take into account machine
learning as strategic component of
Vivendi Group (head quarter).
THE RESULTS
Successful switch from Bluekai to
Mediarithmics in only 6 weeks
Ad hoc architecture for Canal+
ecosystem and consents tracking
requests
Hundreds of audiences activated
Machine learning use into campaigns
HOW WE HELPED
Connecting Vivendi’s brands
Multiplying use-cases activation
opportunities
Providing a comprehensive 360° view
of users
Making analytics serving both AdSales
and CRM teams
Industrializing machine learning
capabilities
Executive Summary As a TV channel,
Canal+ wanted to emancipate for siloed
activities so that they can launch data
offers in a TCFv2.0 world. mediarithmics
set up a power delivery DMP.
Case Study
How one of the main French retailers
empowered cross-brands digital strategies

27. 27
THE CHALLENGES
How to create a platform enabling
advertisers and agencies to load their
data ?
How to offer media planning
customization tools ?
How to enable proprietary machine
learning algorithms customization ?
How to self-prepare to a cookieless
ecosystem ?
THE RESULTS
A high value-added offer launched on
the market by Channel4
23 million active users qualified in real
time
1 billion events collected per month
A new stream of revenues
HOW WE HELPED
Collecting data from AWS and beyond
Loading customer data from 3rd parties
(agencies and advertisers)
Matching data between Channel4 and
customer data
Industrializing scoring and look-alike
algorithms.
Executive Summary As TV network,
Channel4 wanted to offer audience profiling
to its advertisers so that they can optimized
their ad campaigns, in a cookieless way.
mediarithmics built their new self-service
platform
Case Study
How one of the main French retailers
empowered cross-brands digital strategies

28. 28
THE CHALLENGES
How to consolidate data collection
from millions of online/offline
customers?
How to enhance audience extension on
a single platform empower broader
targetings
How to reconcile and make available
the most granular data from customers’
interactions?
How to empower activation for
advertisers?
THE RESULTS
Enabled partnership with Converteo,
Xandr and Criteo
Built of an autonomous platform for
advertisers brands (MyRetailink)
Empowered wider customers’ insights
collection in real-time
Improved audience extension and
substantial increase of the reach
HOW WE HELPED
Building activatable segments with the
36 million clients data lake base
Maximizing ID matching between
Retailink and various open Web
inventory sources
Enabling settling on-site
personalization and open Web
activation
Executive Summary As a major European
retailer, Fnac-Darty wanted to build an
all-inclusive advertising offer for brands so
that they can take full benefits of their
abundant clients’ data. mediarithmics
empowered the building of Retailink and the
MyRetailink self-service platform.
Case Study
How one of the main French retailers
empowered cross-brands digital strategies

29. 29
THE CHALLENGES
Cross-sites profile reconciliation
Building a real time advertising engine
for delivering personalized ads
Get more granular customers’ insights
Find a solution to the end of 3rd-party
cookies
THE RESULTS
Multiplied per 10 the reach levels
200+ EDGE computing segments
activated over the period
New real-time insights engine
3,5 Billions Ad Inventory per month
HOW WE HELPED
Providing a best-in-class EDGE
computing solution
Enabling segment modular building
Collecting advanced cross-sites
insights
Delivering customizable interface to
adapt to Webedia’s segmentation
Executive Summary As a big media web-
site network, Webedia wanted to improve
its monetization engine and insight genera-
tion so that they can build a unique adverti-
sing offer. mediarithmics managed to take
Webedia’s data strategy to the next level.
Case Study
How one of the main French retailers
empowered cross-brands digital strategies

30. 30
THE CHALLENGES
4 million monthly readers
Extend subscribers’ base
Capitalize on existing readers
Improve acquisition of new readers
THE RESULTS
x3 Increase subscriptions on known
donors
x3 Increase subscriptions on new
donors x3
Revitalized the scalable data strategy
360° view of the customer consolidated
60 billion data points collected per year
HOW WE HELPED
Building stronger addressable
segments
Empowering more advanced
personalization of marketing actions
Strengthening customers’ insights
generation
Settling stronger orchestration
Executive Summary As a major North
American publisher, La Presse wanted to
capitalize on its enormous amounts of
first-party data so that they can improve
acquisition and loyalty. mediarithmics
provided them with new means to
capitalize on their first-party data.
Case Study
How one of the main French retailers
empowered cross-brands digital strategies

31. 3
1
THE CHALLENGES
Bridging the gap between the group’s
publishers to leverage insights
Strengthening their advertising offer
through more precise targeting
Organizing first-party data collection to
anticipate the end of cookies
Using the customers’ data to provide
them with accurate and innovative
contents
THE RESULTS
Improved personalized customers’
interactions
Data science teams working efficiently
with editors ones to deliver more
accurate contents
Took monetization of Prisma’s audience
to the next level, both on internal and
external activation
HOW WE HELPED
Getting a 360° view of the Prisma
readers.
Ingesting their home made algorithm.
Displaying campaigns on Prisma
inventory and in audience extension
Matching cookies
ExecutiveSummary As a big media group, Prisma
Media wanted to get better knowledge of its
customers so that they can both improve acquisition
and monetization strategies, but also settle better and
morepersonalizedcontent strategies.mediarith- mics
brought them a platform to centralize and activate
reconciled customers’ data for highest ROIs.
Case Study
How one of the main French retailers
empowered cross-brands digital strategies

32. 32
THE CHALLENGES
As an agency, Havas did not have much
1st party data and needed to build a
powerful tool enabling the storage and
modelling of multiple sources of
external data.
Offer their final client the opportunity to
mix 1st party data, 3rd party data and
panelists extrapolated data (Yougov,
Kantar) in order to run data + media
campaigns and provide enriched
insights to their customers.
THE RESULTS
Converged final user is able to get
much more insights (geo/socio-de-
mo/psycho/behavioral) for the users
provided by the customer
Real time synchronization of every
events, profiles
Converged can ingest the data within
their Power BI and is able to generate
analytics dashboards
HOW WE HELPED
Droping data partner files within data
partner dedicated S3 bucket provided
by mediarithmics
Converting ids using ID5
Ingesting partners data within a
dedicated compartment in a datamart
of a dedicated country
Transmit it to activation partners
(DSP/SSP)
Executive Summary As a big international
agency group, Havas wanted to provide its
clients with much enriched data. media-
rithmics brought them a platform to widely
strengthen Havas’ advertising offer.
Case Study
How one of the main French retailers
empowered cross-brands digital strategies

33. 33
THE CHALLENGES
Groupe Mulliez is one of the top global
retail leader in the world. Around 20
Mulliez brands belongs to Valiuz
project. 150M loyalty cards.
Objectives of the alliance: CRM based
project aiming at gathering all brands
data in a same ecosystem in order to
help brands optimize their direct
marketing strategies.
Valiuz computes cross-brands scores
and shares them to each brand. Every
time a client navigates on a Mulliez
brand, scores must be updated.
To avoid cannibalization between
brands Valiuz calculates scores around
purchase behavior rather than around
purchase interest (cross channel
affinity, preferred time of shopping,
location, life moments).
THE RESULTS
360° customer knowledge /cross-brand
scoring.
Increase of identified visits, thus more
reach for marketing teams.
Many cross-brands use cases
empowered:
• Loyalty/CRM scenarios in place
• Post visit emailing
• Abandonned basket
• Acquisition scenarios
HOW WE HELPED
Thanks to mediarithmics cross-CDP
capabilities, Valiuz has been able to
develop its project by providing
separate environments to each brand.
Within mediarithmics:
• Ingestion of Mulliez brands naviga-
tion data (anonymous / logged)
• Ingestion of Mulliez brand offline
tickets (millions of tickets every day)
• Profile matching capabilities (1st
and 2nd party) in order to transform
anonymous visit into customer-base-
de visit
• Data Activation towards for
different purposes.
A few brands also have access to their
own CDP in order to perform their use
cases
Case Study
How one of the main French retailers
empowered cross-brands digital strategies
Executive Summary As a big retail group,
Valiuz wanted to get better knowledge of
its customers over its various big brands.
mediarithmics brought them a platform to
centralize and activate several strategical
use cases.

34. 34 ANNEXE B
Questions To Ask
When Chousing a Platform 1/3
1. Can the solution reconcile user identity, consents and data?
2. Can the solution capture all kind of data from anywhere (multi-channel, multi-devices)?
3. Can the solution allow to replicate your existing marketing use cases, scenarios, automations?
4. Can the solution connect you data with any other data eco-systems?
5. Can the solution can sustain your growth of volume od data?
6. Can the solution perform at the scale you require?
7. Can the solution adapt to your business with the capability to customize features such as
segmentation?
8. Does the solution leverage artificial intelligence (AI) and machine learning (ML)?
9. Does an enterprise solution track both anonymous visitors and known customers across devices?
10. Does an enterprise solution offer flexible and ideally unlimited data collection and retention?

35. 35 ANNEXE B
Questions To Ask
When Chousing a Platform 2/3
11.Does an enterprise solution integrate with all data sources you need to bring together?
12. Does an enterprise solution offer access to all raw data for all data types without requiring
external data warehouses?
13. Does an enterprise solution provide the capability to orchestrate omnichannel campaigns with
personalized engagement in real time?
14. Does an enterprise solution offer a flexible way to develop customer segments?
15.How much assistance does an enterprise solution require from IT?
16. Can an enterprise solution process all data types and formats that you want to unify?
17.Can it process the most complex analysis and segments you need in your project?
18.Does an enterprise solution have artificial intelligence and machine learning engines?
19. What type of security should the solution have?
20. Does the solution match with your organization’s data maturity?

36. 36 ANNEXE B
Questions To Ask
When Chousing a Platform 3/3
21.Can your solution connect all your marketing tools (advertising, analytics, CRM…)?
22. Do the solution increase autonomy of the marketing team?
23. Can the technology deliver identity resolution?
24. Do the platform offer enough look alike options?
25. Will you be able to activating up to date data?
26. Can you have a comprehensible 360° view of the users?
27. Can you improving your customer experience thanks to the solution?
28. Can you catch new marketing opportunities?
29. Can you improve marketing analysis reliability?
30. Do the solution free you from limitations or not?
31.Will you experiment an easy set-up?

37. 37 ANNEXE C
Glossary
A
ADTECH
Any system used to support advertising
activities; in particular, systems that
work with digital media.
ANALYTICS
Analytics is used to describe statistical
and mathematical data analysis that
AD EXCHANGE
An ad exchange is a technology platform
where buyers and sellers connect to sell
and purchase ad inventory. It lodge in the
middle of the advertising transaction
process between supply side platforms
(SSPs) (publishers) and demand side
platforms (DSPs).
AVERAGE REVENUE PER USER (ARPU)
The Average Revenue Per User is the
average amount of revenue generated
by each active user of your app over a
given period of time.
clusters, segments, scores and predicts
what scenarios are most likely to happen.
APPLICATION PROGRAM INTERFACE (API)
A method for communicating between
systems (or between components of the
same system) that makes requests
(“calls”) for the other system to send data
or take an action.
ARTIFICIAL INTELLIGENCE
Computer processes that mimic human
thought processes.
ATTRIBUTES
Attributes allow you to define the
important characteristics that represent
a visitor’s habits, preferences, actions,
and engagement with your brand.
ATTRIBUTION
The process of estimating the revenue
(or other measure) caused by a
particular marketing contact (or other
interac- tion with a customer).
AUDIENCES
A group of visitor profiles that share a
set of attribute conditions. The more
conditions you use to create an
audience, the more specific your
audience. Audiences are used to trigger
actions.

38. 38 ANNEXE C
Glossary
B
BATCH PROCESSING
Processing a set of data that is accumu-
lated over time and fed into the system
at once, such as a file containing all
transactions during the previous day.
This precludes immediate response to
events reflected in the data, such as
someone visiting a website.
BEHAVIORAL DATA
Data describing individual actions, such
as purchases, web page views, and
customer service calls; one person be
associated with many behaviors of the
same type.
C
CALIFORNIA CONSUMER PROTECTION
ACT (CCPA)
A California regulation that restricts
how personal data is collected and
used; it gives individuals rights to reject
commercial use of their data.
CHURN
The Churn rate is the rate at which a
company loses customers annually.
CLIENT-SIDE TRACKING
Delivery of data is commonly accompli-
shed through tags, one of the most
popular ways to transmit data from web
pages. This type of tracking
involves the user’s browser (client)
CLOUD
Cloud computing is a style of compu-
ting in which scalable and elastic IT-en-
abled capabilities are delivered as a
service using internet technologies.
directly sending data to a server. The
method is used for collecting and
sharing data from your website to your
marketing technology vendors and is
referred to as tag management.
COOKIE
A permanent code placed in a file on a
computer’s hard disk generated by a
website that the computer user has
visited. The code uniquely identifies, or
“registers,” that user and can be
accessed for number of marketing and
site-tracking purposes.

39. 39 ANNEXE C
Glossary
COOKIE MATCHING
Cookie Matching allows to match
information in a cookie, such as an ID
assigned to a user that browsed your
website, with a corresponding bidder-
specific Google User ID, and
construct user lists that can help you
make more effective bidding choices.
CONVERSION RATE OPTIMIZATION (CRO)
Conversion rate optimization, or CRO,
CONSENT MANAGEMENT
The process of collecting, classifying,
retaining, accessing, and updating
individual consent for data use under
privacy regulations. Consent
Management System/Platform software
that manages the consent management
process. May be a stand-alone system or
part of a larger product such as a CDP.
is a form of ecommerce marketing that
uses data and best practices to increase
the percentage of online visitors who
complete a desired behavior.
CUSTOMER DATA PLATFORM (CDP)
A CDP is a technology that collects
data in a governed way from sources
like web, mobile, in store, call center,
and IoT sources, unifies it to create
accurate customer profiles in real time,
then makes it accessible to and actio-
nable for other tools and technology).
CUSTOMER DATA SUPPLY CHAIN
The collection of tools and strategies
that handle customer data
standardization and collection, vendor
integration and optimization,
omnichannel profile enrichment,
campaign action triggers,
and data management for business
intelligence teams.
CUSTOMER LIFETIME VALUE (CLV)
Customer lifetime value is the amount
of money a customer is expected to
spend with your company (buying
products or services) over their lifetime
with your company.
D
DATA ACTIVATION
making use of data; specifically, sharing
customer data with systems that will use
it for analytics, personalization, or
marketing campaigns.

40. 40 ANNEXE C
Glossary
DATA CLEANSING
The process of making data more
usable through error correction,
standardization, transformations, and
other processes. Exact steps will
depend on the intended purpose.
DATA ENRICHMENT
The process of adding new information
to customer data, most often by impor-
ting third-party data and appending it to
existing customer profiles
DATA DRIVEN MARKETING
Data-driven marketing is the use of data
acquired through customer interactions
and third parties to gain insight on
customer motivations, preferences and
behaviors.
DARK DATA
Dark data stands for the information
assets organizations collect, process
and store during regular business
activities, but generally fail to use for
other purposes (for example, analytics,
business relationships and direct
monetizing). Similar to dark matter in
phy- sics, dark data often comprises
most organizations’ universe of
information assets. Thus, organizations
often retain dark data for compliance
purposes only. Storing and securing
data typical- ly incurs more expense (and
sometimes greater risk) than value.
DATA GOVERNANCE
The process of controlling how data is
collected and used in a system, with
particular focus on ensuring data quality.
DATA LAKE
A data lake is a concept consisting of a
collection of storage instances of various
data assets. These assets are stored in a
near-exact, or even exact, copy of the
source format and are in addition to the
originating data stores.
DATA INTEGRATION
The discipline of data integration
comprises the practices, architectural
techniques and tools for achieving the
consistent access and delivery of data
across the spectrum of data subject
areas and data structure types in the
enterprise to meet the data
consumption requirements of all
applications and business processes.

41. 41 ANNEXE C
Glossary
DATA MANAGEMENT
Data management (DM) consists of the
practices, architectural techniques, and
tools for achieving consistent access to
and delivery of data across the spectrum
of data subject areas and data structure
types in the enterprise, to meet the data
consumption requirements of all
applications and business processes.
DATA MANAGEMENT PLATEFORM (DMP)
A Data Management Plateform provides
a centralized dataset that aggregates
cookie browsing behavior (unknown
prospects) to create large, de-identified
audiences for ad targeting across digital
channels.
DATA MART
A Data Mart is defined as a subset of
Data Warehouse that is focused on a
single functional area of an
organization. Data Mart helps to
enhance user’s response time due to a
reduction in the volume of data.
DATA STANDARDIZATION
The process of placing data in a
consistent format so that all instances
of the same item are the same; can be
achieved through rules or a
standardized data layers.
DATA TRANSFORMATION
The process of converting data from one
format to another. Enables disparate data
to be combined. Example : alter the
structure and format of raw data as
needed, mapping, parsing, imputation,
indexation, encryption, anonymization,
filtering, aggregation, ordering, modeling…
DATA WAREHOUSE
A massive database where the structure
is defined before the data is captured.
Think a gigantic Excel spreadsheet, with
DATA VISUALIZATION
Data visualization is the practice of
using software tools to display informa-
tion in graphical form, rather than as
raw data that could be more difficult to
understand. By representing different
kinds of data visually, individuals and
teams can readily identify insights and
patterns in the stores of information.
This is particularly crucial in the age of
Big Data, which requires organizations
to be able to effectively interpret large
amounts of information, often in rapid
fashion. Data visualization usually
includes 3D graphics or rendering, and
is a crucial tool in the fields of marke-
ting, data science, and data analytics.

42. 42 ANNEXE C
Glossary
rows and column titles specified in
advance. Data Warehouses are easier
to analyze than data lakes but generally
require technical data skills and
specialized software.
DEDUPLICATION
Data deduplication is a form of com-
pression that eliminates redundant data
on a subfile level, improving storage
utilization. In this process, only one copy
of the data is stored; all the redundant
data will be eliminated, leaving only a
pointer to the previous copy of the data.
Deduplication can significantly reduce
the required disk space, since only the
unique data is stored.
DEMAND SIDE PLATFORM (DSP)
Demand Side Platform is technology
marketers use to help them
programmatically buy advertising from
multiple ad exchanges and ad networks.
DISPLAY ADVERTISING
Web advertising that appears on
website or social media pages and is
purchased by contract or by bidding on
impressions. May be targeted by web
sites or by individuals.
FIRST-PARTY DATA
Personal data that an organization has
acquired directly from an individual.
F
FIRST-PARTY COOKIE
A web browser cookie set by the
domain of the website that sets the
cookie.
G
GENERAL DATA PROTECTION REGULATION
A European Union regulation that
restricts how personal data is collected,
used, and protected; it gives individuals
rights to consent, review, and demand
deletion of personal data.
GEOFENCING
Targeting of marketing and advertising
messages based on the recipient’s

43. 43 ANNEXE C
Glossary
passage into or out of a specific physical
location, such as entry to a retail store.
Sometimes used in combination with
data known about an individual.
GEOTARGETING
Targeting of marketing and advertising
messages based on the recipient’s
location, often in combination with
other data known about the individual.
GRAPHQL
GraphQL is a query language for APIs
and a runtime for fulfilling those
queries with your existing data.
GraphQL provides a complete and
understandable description of the
data in your API, gives clients the
power to ask for exactly what they
need and nothing more, makes it
easier to evolve APIs over time, and
enables powerful developer tools.
Most sites and apps attempt to keep
track of unknown users, such as using
cookies, until the user identifies
themselves, via logging in or
completing a purchase.
I
IDEAL CUSTOMER PROFILE
The set of personal data associated
with a company’s best customers.
Used to define targets for sales and
marketing efforts.
IDENTITY RESOLUTION
Refers to the various ways that cus-
tomers can engage with your brand
anonymously, then associating that
behavior back to a known customer.
IDENTITY STITCHING
The process of connecting a personal
identifier to an individual through an
intermediary personal identifier (e.g.,
new device linked to an email address
provided by a customer; the device is
associated with the customer even
though the customer has not herself
reported the connection).
INGESTION
The process of gathering data from one
system and loading it into another.

44. 44 ANNEXE C
Glossary
INTENT DATA
Data that indicates how likely a person is
to purchase a particular product.
Generally based on behaviors such as
store visits, social media comments, and
consumption of related web content.
L
LOOK ALIKE
A way of taking an audience and
expanding it to include people with
similar qualities. Lookalikes may be
used for prospecting and to ensure
you’re reaching the largest and most
relevant audience possible.
M
MACHINE LEARNING
Automated processes that build predic-
tive models with little human assistance.
K
KEY PERFORMANCE INDICATOR
A measure that correlates with
achievement of specific business goals.
Sepa- rate KPIs are often defined for
each business project or objective.
MARTECH
Marketing technology (also known as
martech) is a set of software solutions
used by marketing leaders to support
mission-critical business objectives
and drive innovation within their
organizations. Martech solutions
focus on content and customer
experience, advertising, direct
marketing, marketing management
and marke- ting data and analytics.
MARKETING AUTOMATION
Marketing automation is software that
assists marketers with customer
segmentation, customer data manage-
ment and campaign management. It
provides marketers with the ability to
offer real-time, targeted, data-driven
campaigns along with enhanced
efficiency and productivity.

45. 45 ANNEXE C
Glossary
MASTER DATA MANAGEMENT (MDM)
Master Data Management (MDM) is a
technology-enabled discipline in which
business and IT work together to ensure
the uniformity, accuracy, stewardship,
semantic consistency and accountability
of the enterprise’s official shared master
data assets. Master data is the
consistent and uniform set of identifiers
and extended attributes that describes
the core entities of the enterprise
including customers, prospects, citizens,
suppliers, sites, hierarchies and chart of
accounts.
N
NEXT BEST ACTION
The treatment that a business believes
will produce the most desirable result
for an individual customer; typically
based on a combination of rules and
predictive analytics; requires specifica-
tion of the measure that is desired.
O
OFFLINE DATA
Data collected by physical interaction
such as retail purchases, local events,
shipments, etc.
OMNICHANNEL MARKETING
A marketing program where the same
campaign lets customers interact in
whichever channels they choose.
OPEN DATA
Open data is information or content
made freely available to use and
redistribute, subject only to the
requirement to attribute it to the source.
The term also may be used more
casually to describe any data that is
shared outside the organization and
beyond its original intended use, for
example, with business partners,
customers or indus- try associations.
Formally, data desi- gnated as “open” is
subject to several conditions and
licensing that can be found at
opendefinition.org.
MULTI-CHANNEL MARKETING
A marketing program where separate
campaigns run in different channels
(email, web, etc.).

46. 46 ANNEXE C
Glossary
model built from a historical dataset to
a new dataset in order to uncover
practical insights that will help solve a
business problem.
provider, personalization tool or
another type of execution system.
S
SCALABILITY
Scalability is the measure of a system’s
ability to increase or decrease in perfor-
mance and cost in response to changes
in application and system processing
demands. Examples would include how
well a hardware system performs when
the number of users is increased, how
well a database withstands growing
numbers of queries, or how well an
operating system performs on different
classes of hardware. Enterprises that are
growing rapidly should pay special
attention to scalability when evaluating
hardware and software.
SECOND-PARTY DATA
Personal data that an organization has
acquired through a direct relationship
with the organization that collected it
as first-party data.
SINGLE VIEW OF THE CUSTOMER
An aggregated, holistic view of the data
an organization retains on its customers
discernible at the individual level.
STRUCTURED DATA
Data that is presented and stored in a
SUPPLY SIDE PLATFORM (SSP)
A supply-side platform (SSP) is an
adtech software that helps publishers
and other advertisers automate the
management, selling, and optimization
of ad inventory (audio, video, display,
mobile) on their web and mobile
properties. SSP is also known as a
sell-side platform.
SERVER-SIDE TRACKING
Server-side data management, also
known as cloud delivery, is when a
pixel or tag sends data into your web
server (or a different type of server),
then your web server passes that data
to the destination system/server. This
data could be used by a marketing
automation platform, analytics
SCORING
In machine learning, scoring is the
process of applying an algorithmic

47. 47 ANNEXE C
Glossary
relationship with an organization that
acquired it directly or indirectly.
fixed format where each element is in a
specified location, such as the columns
of a relational database table or the
fields of a data file.
USER POINT
A User Point is a marketing
representation of the user.
T
TAG MANAGEMENT SYSTEM
A technology that makes it simple for
users to implement, manage, and
maintain tags on their digital properties
with an easy to use web interface.
THIRD-PARTY DATA
Personal data that an organization has
acquired through a marketplace
U
UNSTRUCTURED DATA
Data that is presented and stored in a
format where the elements are not
defined, such as a block of text, video,
or audio files.
USE CASE
A description of the steps that an agent
takes to complete a business task. Used
to illustrate the capabilities a system
needs to support a task and to illustrate
the tasks a system may support.
V
VISITOR STITCHING
When a CDP automatically combines
the attributes from related profiles from
different channels into a new master
profile that replaces the others

48. 48 ANNEXE C
Glossary
and deliberately shares, such as privacy
or contact preferences.
W
WALLED GARDEN
On the internet, a walled garden is an
environment that controls the user's
access to network-based content and
services. In effect, the walled garden
directs the user's navigation within
particular areas to enable access to a
selection of material or prevent access
to other material.
Z
ZERO-PARTY DATA
Any data that a customer proactively

49. 49 ANNEXE D
mediarithmics’s Features /Advantages / Benefits
FEATURES
mediarithmics is:
• An Unified Marketing Infrastructure
Offering:
• Completeness
• Synchronicity
• Customization
• Bridges
• Scalability
With Such "Features"
• Data Collection and Processing
• Collection
• Session aggregation
• Deduplication
• Ingestion
• Scheduling
• Progress Feedback
• Storage and Modelling
• Datamart
• UserPoint
• Identity Resolution
• GraphQL
• Querying
• Machine Learning Function
• Audience Creation
• Automations
• Data delivery
• Reconseling
ADVANTAGES
• Cumul the benefits of both big data and data
solutions
• Capture all kind of user data
• Reconcile user identity, consents, and data
• Adapt to your current and future own use cases
• Connect your data with multiple other data
ecosystems
• Grow your data ecosystem
• Get an unified view of the customer
• Have a more updated data on customer
• Deepen deduplication
• Have an automatic scale up
• Track jobs status
• Store all your data in one place
• Create a marketing representation of the users
Identify individuals
• Model data internally without technical skills
• Simplify your queries
• Manage each mutation in data
• React in real time to platform or user events
•Reconcile data within any tools in various
eco-systems
BENEFITS
• Work with fresh data
• Don't miss anymore data
• Target individuals, not devices
• Use your own marketing scenarios
• Connect all your marketing tools
(advertising, analytics, CRM…)
• Don't be faced to limitations
• Make marketing analysis reliable
• Increase marketing efficiency
• Comply with the data privacy regulation
(GDPR, PIPEDA...)
• Have persistent data quality
• Avoid errors
• Have all your data available anytime
• Get a 360° view of the users
• Enhance customer experience
• Focus only on useful information
• Time savings
• Activate up to date data
• Catch new marketing opportunities
• Increase marketing efficiency