1.
THE DMP(Data Management Platform)
TERMINOLOGY
GUIDE
35+ TERMS
EVERY MARKETER
SHOULD KNOW

2.
Data
Collection

3.
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Data Collection
COLLECTING DATA IS ESSENTIAL FOR A DMP TO FUNCTION
Web & App Sources
Site traffic, event tracking, app users (Mobile / Desktop)
Programmatic Platforms
Impression level data, conversions, video views from DSPs, Ad Server (Google AdWords)
NOTE
Other data collection tools
can track data too, only a
DMP can ingest a broad
range of data sources and
draw information from it.
Marketing Platforms
Content interactions (eMail, Web, Social)
Offline Sources
Offline CRM Systems, ERP systems or Point-Of-Sale / transaction systems
Other Data Collectors / Vendors / Partners
Data shared with partners / affiliates or 3rd Party data vendors (allowing to enrich data sets)

4.
Collection Methods
A DMP CAN GO BEYOND THE COOKIE LEVEL DATA
xJavaScript Tracking Tags
Tracking Pixel (1x1)
Raw Databases C, etc.)
Server-To-Server (S2S)
Mobile SDK

5.
Data Normalization
ONCE DATA HAS BEEN COLLECTED ITS TIME TO “NORMALIZE”
1 Gather IDs
Delete redundant or useless data
Transfer the source’s data schema to the DMP data schema
Enriching data with additional data points
2
3
4
NOTE
The Data normalization and
enrichment stage provides
two main Benefits. It organizes
various data sets into a
common format and
improves data value and
quality.

6.
Data Enrichment
AFTER THE NORMALIZATION STAGE, EACH USER IS ASSIGNED WITH A UNIQUE ID AND
CONNECTED TO ITS EXCISTING ATTRIBUTES. ATTRIBUTES CAN INCLUDE THE FOLLOWING:
Age
Gender
Location
Browser History
Interest
Purchase History

7.
Profile Building
PROFILE BUILDING IS AN ESSENTIALS PART OF THE NORMALIZATION AND ENRICHMENT
PROCESS, AS IT IS RESPONSIBLE FOR TRANSFORMING THE COLLECTED DATA INTO EVENTS
AND PROFILES WHICH ARE CURTAIL FOR SEGMENTATION
Incoming events /
attributes
Existing
Profiles
Outcome of the
mergers
Cookie ID: #001002
Email: Muffin@gmail.com
Event type: Signin
Cookie ID: #001002
Interests: Dogs, Fashion
Last Product Viewed: X & Y
Email: Muffin@gmail.com
Age: 20-25
Profile # 99912
Profile # 88888
Cookie ID: #001002
Interests: Dogs, Fashion
Last Product Viewed: X & Y
Email: Muffin@gmail.com
Age: 20-25
Profile # 55555

8.
Quality In = Quality Out
Golden Data Rule

9.
Segmentation
& Activation

10.
Audience Segments
A GROUP OF PEOPLE (SITE VISITOR, APP USERS, ETC.) THAT HAVE BEEN ANONYMOUSLY
IDENTIFIED AS SHARING A WIDE RANGE OF ATTRIBUTES (DEMO, TECHNO ETC.) ATTRIBUTES
CAN BE SELECTED ACROSS MULTIPLE DATA SOURCES AND ASSEMBLED USING TO DIFFERENT
APPROACHES.
Boolean Rules Algorithmic Lookalikes

11.
Audience Analysis
IN MOST CASES THIS IS PART OF THE AUDIENCE SEGMENTATION PROCESS. THE
EVALUATION CRITERIAS VARY BASED ON THE SEGMENTATION APPROACH
(BOOLEAN VS. ALGORITHMIC LOOKALIKES). YET, MEDIA SPECIFIC
VARIABLES SUCH AS TOTAL TARGETABLE AUDIENCES SIZE, MEDIA
COST PER AUDIENCE ARE ALSO VARIABLES THAT NEED TO
BE CONSIDERED WHEN CONDUCTING AN ANALYSIS AND
PLANNING FOR SUCCESS.

12.
Data Activation
AFTER ALL OF THE SEGMENTS ARE CREATED, IT’S TIME TO ACTIVATE. DMP AUDIENCES ARE
ACTIVATED BY PUSHING AUDIENCES (SEGMENTS) TO MEDIA ACTIVATION PARTNERS (DSP,
SOCIAL ETC.)
DMP
Search
Video
Email +
Direct Mail
Social Mobile
Premium +
Portals
Programmatic
Display
Programmatic
TV

13.
DMP
Taxonomy

14.
DMP Taxonomy
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A SYSTEM FOR NAMING AND ORGANIZING INFORMATION GROUPS BASED
ON THEIR SIMILARITIES
Car Sales Website Airline Ecommerce

15.
15
DMP 101
Recency /
Frequency

16.
Recency / Frequency
Recency
Refers to “how long ago” a
given event occurred
NOTE
Most DMP’s have a 30 day
recency window to activate on
audiences. When using
audiences for Analysis only
some DMP’s allow you to select
a recency window to up to 90
Days.
Frequency
Defines how often a given
event must have occurred for the
data to be subject of a given
category
Example
Segment A includes users that viewed
at least 5 product pages (frequency) in the
last 30 days (recency) on dotcom.

17.
17
DMP 101
Data Types &
Management

18.
Data Onboarding
THE PROCESS OF TAKING CUSTOMER IDENTIFIERS (EMAIL ADDRESS, PHONE NUMBER ETC.)
AND TRANSLATING IT INTO A TARGETABLE COOKIE OR DEIVCE ID (IDFA OR ADID)
Upload
Data files are send to
onboarder
Anonymization
The onboarder anonymizes
any Personal Idenitfiable
Information (PII) matches it to
a cookie or device ID
Push to Platforms
Lastly, the cookie and device
IDs are sent to the marketing
platform that

19.
Cookie Syncing
THE PROCESS OF CREATING AND MATCHING USER IDS ON THE BASIS OF 1ST, 2ND AND 3RD
PARTY COOKIES. THIS HELPS FACILITATE THE EXCHANGE OF DATA BETWEEN PLATFORMS
AND MAKES IT POSSIBLE TO IDENTIFY A CUSTOMER PROFILE WITHIN A DSP, DMP OR AD
EXCHANGE.

20.
Data Types
A DMP CAN PROCESS MANY TYPES OF INFORMATION AND USE IT IN MANY DIFFERENT
WAYS. IN GENERAL WE CAN CLASSIFY THIS INFORMATION INTO 3 DATA TYPES:
2nd PARTY DATA
Data owned by a
partner but shared with
your organization.
1ST PARTY DATA
Data collected and owned
by your organization.
PII: Personal Identifiable
Information such as name,
address, email etc.
3rd PARTY DATA
Data generated and owned
by other parties/vendors.
Anonymous: No personal
information linked by cookie or
device ID.

21.
Tag Management
A tag management system helps users to manage various tags in one place. In
addition it allows all site tags on a page to be loaded into a single container tag, which
reduces lading time and prevents any interfering with other content on the page.
Multiple Tags on Page Single Tag Container
holding multiple tags

22.
More Related
Terms

23.
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More Terms I
Audience Suppression
Excluding a list of people (Audience) from
receiving a certain ad / being part of a
campaign.
x
Look-alike Modelling
Excluding a list of people (Audience) from
receiving a certain ad / being part of a
campaign.
x
Match Rates
Refers to the number of records in one data set
(CRM File) that is being matched up with the
records of another data set (DMP/ DSP etc.)
x
Offline Data
Data that is stored in an “offline” system like a
CRM, POS System or email marketing platform.
In most cases it contains PII.
x
Online Data
Data that is collected and stored in digital
marketing platforms such as DMPs, DSPs, or ad
servers. Data is tied to anonymous devices via
cookies or device IDs.
x
PII
Personally Identifiable information is data that can
be used to identify a individual e.g. First and Last
name, email, address etc.

24.
x
More Terms II
Ad Exchange
A marketplace where advertisers and publishers
buy and sell ad inventory using automated
processes like real-time bidding
x
Attribution Modeling
Identifying what marketing actions and channels
that led a individual to make a purchase.
x
Cross-Device
Refers to the method of reaching a customer
across different desktop browsers, smartphones,
tablets and other addressable connected
devices.
x
Data Integration
Refers to the process of combining data sets that
are housed in different applications and systems in
order to have one unified view of a customer.
x
Demand-Side Platform (DSP)
A software solution that automates the buying of
ad inventory such as display, video, mobile and
search ads.
x
1 to 1 Marketing
Delivering a customized experience that caters to
the preferences of a single customer, rather than a
broader user group or segment.

25.
x
More Terms III
Marketing Stack aka “Stack”
Refers to all technology that is being used to
manage and operate a companies marketing
activates.
x
People-Based Marketing
The philosophy of targeting real people – not
devices, channels or browsers. Sounds obvious
but can be challenging without the right stack.
x
Programmatic Advertising
The automation of buying, positioning and mix
optimizing of media inventory by making real-
time decisions about price, placement and
timing.
x
Real-Time Bidding (RTB)
Refers to the automated system of auctioning
media inventory between publishers and
advertisers.
x
API
An “Application Programming Interface” is a list of
commands as well as the format of those
commands that one system can send to another.
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Confused
The feeling that most marketers encounter when
onboarding a DMP across multiple datasets, teams
and/or organizations.

26.
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THANK YOU
DMP 101
@eddywiEddy Widerker