CDP Master Class - Jakub Otrząsek, Media.Monks

MASTER
CLASS
AUCKLAND, NEW ZEALAND ~ AUGUST 21 - 22, 2023
DIGIMARCONNEWZEALAND.CO.NZ | #DigiMarConNZ
Jakub Otrząsek
VP OF DATA, ASIA PACIFIC
MEDIA.MONKS
Master Class 1

© 2023 Media.Monks. All rights reserved. Any copying or use of this
confidential information is strictly prohibited without the express
written permission of Media.Monks.
CDP fundamentals

Media.Monks Proprietary & Confidential 3
Jakub Otrząsek
VP of Analytics APAC
Brought by

Proprietary & Confidential 5
Content
01 An Introduction to Us
02 First Party Data Strategy
03 CDP Vision / Goal
04 The Plan
05 Goldmine
06 Questions

An Introduction
to Us

Within a single P&L,
we are continuing
to add a depth of capabilities
and experience across regions
and verticals — and integrating
continually as we build.
May 2018
MediaMonks joins S4
April 2019
Caramel joins MM
Aug 2019
IMA joins MM
June 2019
Biztech joins MM
April 2019
Caramel joins MH
Nov 2019
Whitebalance joins MM
Oct 2019
Datalicious joins MH
Jan 2020
Circus joins MM
Sept 2020
Dare.Win joins MM
May 2020
Digodat joins MH
July 2020
Orca Pacific joins MH
Aug 2020
Brightblue joins MH
Oct 2019
Conversion Works joins MH
Dec 2018
Media.Monks joins S4
Oct 2019
Firewood joins MM
Jan 2021
Metric Theory joins MH
Jan 2021
Decoded joins MM
Jan 2021
STAUD STUDIOS joins MM
Jan 2021
TOMORROW joins MM
June 2020
Lens10 joins MH
March 2021
Jam3 joins MM
July 2021
Destined joins MH
September 2021
Cashmere joins MH

Governance & Standardisation
Strategy
Data Digital Media Content Tech
Insights & intelligence to inform every stage
of the customer journey
Stories, interfaces and experiences that
create the brand
Transparency & effectiveness to reach people
(not just personas) at scale
The architecture that underpins every
moment in the customer experience
Planning & Strategy Brand Advisory
Security & Privacy
Business Intelligence & Management
Personalisation, Relevance, & Testing
Audience & Customer Insights (CLTV)
1st Party Data
Cloud Architecture & Deployment
Social (Paid or Organic)
Search (Paid or Organic)
Display (Biddable or Direct)
Video (Digital or Traditional)
OOH (Traditional or DOOH)
Email
Audio (Traditional or Digital)
Specialised (Niche)
Social
Campaigns & Experiences
Web Production
Film & Content
Digital Experiences Solutions (Platforms)
Automation
Ecommerce
Tooling & Operations
Software
Broadcast & Live
AOR
Virtual Events
Adaptation & Transcreating
Mobile APPS
Retail
Experiential
Performance Marketing
R&D and Innovation

We see the opportunity...
To provide practical services to benefit your
organisation and meet business goals. We think
data and speak media, and can create positive
impacts with insights in activations.

We consolidate tech, media and
content to deliver a singular
experience for your customers
How brands tell their brand
story, product proposition or
ways they can assist.
The inputs that define how, when and
where brands decide to show up. Reactive
and proactive.
The moments where
consumers and businesses
are showing up, increasingly
digital and quite often only for
a fleeting moment.
We’re all busy after all.

First Party Data
strategy

02 03 04
01
The rise and
importance of 0PD
and 1PD
Desire to break
down data silos in
enterprise
DMPs inability to
track users cross-
channel
Technical savvy
marketing
organisations
Rapid accelerations in digital and e-commerce growth are
intensifying existing data problems, driving the need for a single
solution to bring together data
Challenges the market face today...

02
01
Do I prioritise
getting more
customers?
Do I grow revenue
from existing
customers?
How do I grow MY business?
How do I design a
value exchange?

The
Opportunity
Why is data
important?

For modern marketers today, there is more
data than ever before, however it can be hard
to know how to activate and use this data to
improve the consumer experience and a
brand's position in market

The ability to deliver relevant experiences
to customers at multiple moments across
the purchase journey—achieve cost
savings of up to 30% and revenue
increases of as much as 20%
Source: BCG, Responsible Marketing with First Party Data, 06/18/2020

Sharing Learnings Enhancing Product Scaleable Audiences
The opportunity is to make
data available, accurate and actionable
to improve the consumer experience
Analyse multiple data inputs
Automate analysis via dashboarding
solutions
Optimise audience segmentation
Optimise media performance with data
Integrate learnings into media plan
There is a need to intertwine your
marketing activities with your product.
This supports value exchange and
addition of touch points to the data
model

Strategy
CRAWL WALK RUN FLY
Unified customer
profile
Actionable customer
insights
Outbound channel
optimisation
Digital media
optimisation
Owned Media
Optimisation
Cross-channel
orchestration
Automated
interactions
Advanced
analytics
→ AI/ML
→ Predictive
model
Next best
experiences
First Party data journey
→ Clear goals
→ Data access and
confidence
→ Vendor selection
→ Processes Design
→ Implementation Plan
→ Training and enablement
→ Ongoing experimentation
Help you progress through maturity to
achieve ROI at each step.

CDP
Vision / goal

To achieve these goals,
Marketer needs to address...
Technology
People Process
Our
focus
today
● Adoption
● Change Management
● Training
● Adherence
● Governance
● Execution
● Architecture
● Integration
● Activation
● Reporting

02 03
01
Siloed and various
consumer data
sources
Challenges in Data
Integration &
Stitching
Lack of Marketing
User Interface
headache
Continued digital innovation and growth are intensifying existing
data problems, driving the need for a single solution to bring
together data
Technology Challenges today...

ID Resolution
Join keys or consistent identifiers
across many data sources to
unify/create a Single Customer
View.
Advanced Analytics
Attribute and segment customers
using defined or custom machine
learning models. Deterministic,
forecasted and predictive analytics.
Activation
Report and forecast customer profiles
using a UI or custom dashboards.
Push custom audience segments to
marketing destinations for activation
and personalisation.
Data Management
Use existing/new tags, integrations, pre-
built/custom APIs, and endpoints to ingest
raw data from offline and online data
sources.
Creating a connected consumer experience
Centralised repository of customer data and activity built around a unique ID to enable tangible business outcomes through advanced
analytics, personalisation and activation.
CDP

Out-of-Control Data Sprawl Low Data Quality Limited Data Access
Ad hoc naming
conventions
! Lack of Data plans
!
Join keys not
normalized
No data dictionary
! !
Unpredictable latency
!
Undetected data errors
!
Regional
discrepancies
! Duplicate data
!
Unclear or missing
cost data
Data pipeline
downtime
! !
No partner data
quality SLAs
!
Especially if data lives in many different platforms (and teams) and the
collection points are spread across the entire customer journey.

A CDP combines data from multiple sources to create a
single, unified view of a customer...
Share segment-level
data to other
systems for precision
targeting or analysis
Consolidating 0PD and
1PD from multiple data
sources in a central
location
A unification of events to create a
Single Customer View (SCV)
via ID Resolution
Acting on data to deliver
personalised
communications in real-
time.
...and acts on data to deliver relevant content to users at scale.

Data Source
Data Source
Data Source
Data Source
Data Source
Data Source
Real time event
ingestion
Anonymous
space
Segment
membership
management
Activation
Layer
Use Case
Destination A
Batch ingestion
Named prospects
and customers
Use Case
Destination B
Use Case
Destination N
Building a seamless
architecture from data
collection to activation
Identity resolution
Segment builder

How a CDP brings business value:
Increasing the focus on high value / high potential customers
Increase focus on high profitable products and service
Expand sales and advertising channels
Improve total customer experience
Improve effectiveness of marketing, advertising and sales
processes
Tailor marketing and sales approaches to customer segments
Tailor marketing and sales approaches to customer segments
Improve access to information and analytical tools
Improve brand strength and good will
Increase volume of sales by:

How a CDP brings business value:
Retain and Grow current
Samsung customer base by:
Increase focus on high value customers
Rationalise Customer portfolio
Increase emphasis on account/relationship development
Increase emphasis on customer satisfaction
Improve understanding of customer needs
Improve understanding of current customer satisfaction
Improve responsiveness to customer feedback / complains
Proactively manage transition events (life events, support
requests)
Increase focus on most profitable products and services
Increase focus on the most effective sale and advertising
channels
Increase focus on expansion of customer relationships
Improve understanding of churn/defection candidates
Improve retention and win-back processes

Bringing data to life
Consumer Profiling Smart Segmentation Personalized Marketing Communication
Consumer Lifetime
Value Optimization
Propensity to Convert
Modeling
Sentiment Analysis
Attribution Modeling Marketing Spend
Optimisation
Trend Spotting
Accelerating
Qualification & Innovation
Consumer Insights for
Demand Forecasting
Level 4
Level 3
Level 2
Level 1
Ecommerce product
recommendations and promotions

The Plan

5 steps to deploy any CDP
Inputs: Raw unstructured data for the same user across different Samsung sources
Capture and ingestion of data from zero, 1st, 2nd, and 3rd party data sources using APIs, a
Cloud Endpoint and native integrations, to ensure all semi-structured event data is
captured
Data Source
Storage of captured data indefinitely (subject to lookback, PII constraints, legislation)
Ingestion
Unification of events from many sources to individuals (ID Resolution Process = Unified
Profile), and the structuring of records into analytical schema
ID resolution
Outputs: Golden Record of structured data for the same user across different sources, associated with an individual
Front-end analysis of structured data
Sharing of data from the CDP, to destinations for use case execution
Activation /
Destinations
Segmentation
1
2
3
4
5

Data
Sources
01
Core component of each CDP is the
ability to connect with multiple data
sources

Data Sources
Data sources may be divided into various logical groups such as:
Ownership and network
availability
SAS - Adobe Analytics or on premise Hadoop instance
Granularity level and
contextualisation
Data may be available on a user level, campaign level or product level.
Structure and taxonomy Campaign may mean different things in different systems and may have different structure in each data source.
Lag Time from a moment of data collection to its availability may vary from a few seconds to more than 24h.
Regionality and reusability
For example, the facebook API will authenticate to multiple accounts, whereas you may have one hadoop
instance which can serve the whole globe.
Volume
It is a different challenge to process a 1GB of data and 1TB, often higher quotas will be required which will
increase overhead on communication and maintenance with vendors.

Data Sources
Data can be extracted from data sources by different means:
Data in different systems is represented in different formats
JSON, CSV etc - and these data formats may have different structures
(field like date can be stored in hundreds of different ways).
Data source can initiate the transfer of data (file sent to your FTP) or you
need to initiate the data transfer (an API call request)
Data may be delivered as batch or
per event basis

Ingestion
Once data sources are connected,
information needs to be processed in order
to land in a CDP
02

Data will either be streamed in at a “event/hit/row” level or come in at scheduled batches:
Data Pulling
Batches could be pulled, that is
a request made from the CDP
to the Data Source
Data Pushing
Batches could be pushed, that
is a Data Source sending data
to a CDP ingestion endpoint
Streaming
Streamed data is pushed or
subscribed to, meaning that it is
sent to the CDP via a data
source continuously
1 2 3
Direct to CDP
Streamed data could also be
in the form of a pixel or tag
provided by the CDP,
meaning that it comes
straight from a users’ device
to the CDP
4
Ingestion
Data sources will come in many different forms and by
multiple methods.
Ingestion is the process of taking these various formats and
normalizing them into a standardized data architecture that
can be processed efficiently.

Generalized data about
the user (e.g. name,
email, gender, LTV, any
defining “trait” that
isn’t likely to change)
User Level Event Metadata
Individual actions, such
as:
- purchases
- page views
- clicks
Non user specific data,
but generalized insights
(users in X region like Y
product)
Data scopes need to be defined:
Data may have a lookback window, typically 7 or 30 days, where
metrics can change as additional data flows in.
Ingestion

Tips!

Complexity
It can become very quickly a
complex task. Off the shelf solutions
likely will not be able to deliver
against complex requirements.
Implementation of complex
requirements will make overall
solution more fragile.
The more varied the data scopes
(event vs user), the more complex it
will grow.
Effort
Ingestion is easy to start with and
overall the solution can be kept
relatively simple, though over time it
will likely evolve to a complex
system of rules.
Maintenance
If built well, maintenance can be
kept to a minimum, though lack of
documentation on each platform,
and lack of error handling could
easily turn this into a nightmare.
Ingestion Considerations
!
High
Medium
Low

ID
Resolution
To make CDP an effective investment it
needs to create and maintain Single
Customer View.
03

ID Resolution
“Golden
Record”
User
Profiles
Metadata
Repository
Unique
User ID
Confidence
Level
Joining
User profiles may be linked to anonymous identifiers for an
extended period of time. When they get merged with a
recognised profile, predefined rules will be used to determine the
degree of valid retrospective stitching.
Product ownership data (e.g. type, sku, features, expected
lifespace) will need to be linked to a user profile
The ID resolution system is responsible for creating a user
record known as the “ Golden Record” that identifies a user.
The Golden Record is created by joining data from the data
sources.
A metadata repository is linked to the user profile to
enable rules based id matching algorithms.
The matching algorithm may merge or split user
profiles based on this metadata.
To achieve this join, the source data needs to be
cleaned to meet specified quality standards.
A unique user id acts as the primary key for the user
profile. Secondary identifiers (e.g. email, phone, ga id)
are associated with the profile
A confidence level is calculated based on the likelihood
that certain events belong to the same person.

Product ownership and
portfolio management
Another important consideration which is indirectly related to profiling and ID resolution is product definition.
A customer's product ownership is an important dimension of the customer profile.
The ability to define and manage product features may be really important.
Including:
History of purchases
Segmentation of products (hi-end
vs low-end, categories, entry
products, upsolds)
Lifetime of products (12 months vs
5 years)
Associated warranty and other
terms (12, 24 months)

Complexity
Broad product and service offerings
combined with a complex range of
customer touch points will require a
complex implementation of data
types and matching rules.
Effort
A poor performing ID resolution
system will significant devalue the
investment in a CDP.
To ensure success, considerable
effort will be required to establish an
effective system that is able to
identify users with a sufficient
degree of reliability.
Maintenance
Ongoing tuning and adjustment of
the id resolution configuration will be
required over time as a business
changes and evolves.
ID Resolution Considerations
!
High
Medium
Low

Segmentation
It is imperative that data about Samsung
customers can be sliced and diced in
any way.
04

Segmentation
Off the shelf products may offer a set of good features in terms of
segmentation and audience building.
“Marketing Cloud” solutions can take you closer to journey automations,
though it seems most platforms struggle with AI and ML capabilities
which often needs to be run separately.

Before deploying your CDP
consider the following:

Membership management
How people are assigned to the segment, does it happen in batches or real time?
Nested Audiences; do you need to create audiences that will contain other audiences?
Cascading and journey builder; do you need to create an audience of people who reacted to a
campaign which you have not run yet?
Reporting; how to report back usage of audiences, do you to need cap the number of
audiences a particular person is included in?
1

Audience or a segment is defined as a set of
filtering conditions
Deciding how long these conditions are valid and how often they are evaluated will have significant impact
on other functionalities.
It is important to decide how these are stored and maintained
There needs to be a way to find out why someone was a part of a particular segment
2

02
01
Once the data schema is built correctly and
all data harnessing is implemented,
segmentation itself is not hard. Though for
CDP use cases it is important to implement
membership management.
As people start to work with CDPs they want
to build more complex use cases which start
to look more like marketing automation
(workflow diagrams). At that stage BI
platforms will likely start to struggle from a UI
perspective.
Media.Monks View
Effective segmentation is
challenging, before giving a
platform to the end users it is
important to design potential
segments and user flows. As CDPs
introduce new level of complexity
there needs to be a way to “x-
ray” how data was processed
from left to right.
Be prepared for questions like
“why was this person part of this
segment?”. As CDP deduplicates
customers and creates golder
records a lot of in platform
decisions will be hard to
comprehend for “operators”.
Down the track, real time use cases may
introduce computational challenges
especially in membership management.
Tip!

Complexity
It is somewhat complex to do
segmentation correctly. POC’s and
some use case may be classified as
easy, but as expectations grow
implementation will become more
complex.
Effort
It is easy to start, but maintenance
creeps very quickly. Good
documentation and taxonomy will be
at value of goal.
Maintenance
An element to look out for is overall
storage of audience definitions and
membership management which
represents backend logic.
Users may build audiences and
workflow which they do not fully
understand, this will spark questions
about overall solution (in any case).
Segmentation Considerations
!

Activation
Prepared customer segments needs to
be activated through various channels in
order to create ROI.
05

Activation
Exception Handling
Personalisation
Destinations
Aligning User Identity
Alignment of user identity
between the selected audience
and destination needs
consideration
E.g. Some destinations may
require a hashed email address
to identify users and others such
as internal channels may require
CRM sourced identity
Destinations may have different
requirements in respect of data
synchronisation
This impacts how scheduled
data synchronisation windows
are configured within the
activation system
For personalisation use cases,
user profile data will need to be
accessed in a near real time low
latency manner
Rules for exception handling will
need to be configured to address
scenarios where a destination
rejects an audience member do
to identity duplication or data
quality issues

02
01
To get started quickly use Looker, which
provides a powerful user interface for creating
filtered audiences and pushing these to GMP
channels via GA360.
Media.Monks View
Before you activate your data
make sure that you implement
safety nets from a compliance
perspective.
Activation is the last gateway
before data will leave your
environment! It is crucial to
ensure that data will be activated
for right users respecting their
privacy settings.
Audience filter configuration will need to be
captured and stored server-side to run
periodically without dependency on the
Looker UI.
Tip!

Complexity
Similarly to data sources, activation
is not a complex task, although with
activation there is a little bit more
considerations such as the format of
data and required variables that
need to be pushed to destinations.
Effort
Effort to configure activation will be
dependent on the destinations, and
the number of destinations required.
Maintenance
This area is the most prone to
break. Changes in technology,
regulations on various markets may
create a lot of challenges.
Activation Considerations
!

Destinations
CDP needs to support outbound
connectivity. Feedback loop is a
challenge.
06

Destinations
Multiple Platforms
There will likely be many platforms that you’ll want
to activate on, and they’ll have different means of
doing so
User Identification
Some, like Facebook, can be done via PII matching,
a Facebook ID, or an external ID that has been
equated with a user in Facebook before. Others
won’t be as robust
Time
Time may be a factor in activation, some user
identifiers may expire in their respective platforms
3rd Party Systems
There are also 3rd party systems that can leverage
their own user information to activate for you on
platforms. These can be expensive.
Privacy
Privacy should be a large consideration, as you may
be sharing user data collected in one system into
another that a user may not have consented for
Feedback Loop
It is hard to setup a feedback loop, and likely off the
shelf CDPs will have very limited capabilities in that
space.

02 03
01
Focus on key marketing
platforms, likely Google,
Facebook, and Amazon.
Media.Monks View
Seriously consider 3rd party
activation systems where
possible, though weigh up the
cost and the reach.
Some 3rd parties work well in
specific regions, but not in
others. These systems can be
good for matching users
based off of PII you hold, but
cannot be used directly in an
end platform.
Be cautious around 3rd party
cookies syncing which is still
commonly offered on the
market as activation medium.

Tips!

Complexity
Each platform will require a different
export format, though ultimately it is
just sending users identifiers for
activation.
Effort
Building out each connector will take
work, as they will each be unique in
terms of structure and
authentication.
Maintenance
Because each platform is handled
separately, the system will need to
be monitored for changes within
each platform’s capabilities.
Destinations Considerations
!

Reporting
and Analysis
Extremely important to use Single
Customer View data in other contexts,
how can the CDP perform as a single
source of truth?
07

Data Source
Data Source
Data Source
Data Source
Data Source
Data Source
Real time event
ingestion
Anonymous
space
Segment
membership
management
Activation
Layer
Use Case
Destination A
Batch ingestion
Named prospects
and customers
Use Case
Destination B
Use Case
Destination N
Where is reporting?
Identity resolution
Segment builder

Reporting & Analysis
Off the shelf CDPs are not that great as
reporting platforms, however there are
couple of functionalities which are worth to
keep in mind.
There needs to be a user explorer
functionality, so that a Samsung user
can check all details about particular
record.
As complexity of segments will grow and
often criteria will be indirectly applied and
membership will be based on customer’s
actions from multiple systems, it is really
important that platforms users will have an
easy way to evaluate membership
By design, feedback loop is not a part of
CDP, as media platforms (destinations) often
do not report back on the user level, it is not
certain if customer from a particular segment
actually were exposed to a campaign
Customers who reacted to the campaign
and interacted with your assets should be
recognised (through UTM alike
mechanism) and linked to segments and
destinations.
This may be a complex task which will
require a new level of discipline for
taxonomy and campaign management

01
Reporting out of CDP requires additional database structures and well thought out approach.
Documentation and elaboration of processes is equally important to help users understand why things
are happening. CDP increases complexity and help to automate things, but as there are multiple
elements which CDP depends on (data sources, ingestion algorithms, data cleansing algorithms, id
resolution etc) final segmentation and activation may have unexpected (or rather not understood)
results.
Media.Monks View
Early investment in reporting will
create “white box” environment,
where platform users can x-ray
why customers where classified
to segments. This will increase
trust and adoption of the
platform.
Tip!

Complexity
Some initial reports may be easy
and fast to build. Though the
dynamic nature of the CDP
introduces a lot of challenges which
will lead to user’s confusion. Good
documentation and explanations are
a must.
Effort
It is advised to invest in good
designs and frontload the effort
which should be followed by really
good documentation and set of
presentation explaining different
mechanisms in the database (e.g.
how Golden Records are
populated).
Maintenance
If designed right from the beginning
technical maintenance should not
be that time consuming, but ongoing
effort will be required to meet
demand for feature/change
requests. It is expected that platform
users will raise a lot of questions
and overall challenge the way the
platform works.
Reporting & Analysis Considerations
!

Other
Considerations
Some other “good to know” things
08

Other Considerations
What records are allowed to send to the CDP?
1
Once records are in the CDP, can they be activated in every channel?
2
Are all subsidiaries using the same platforms? If not, how will this affect the number of data sources that will need to
be handled?
3
Does your brand have clean, consistent data with a global taxonomy or will regions/countries have to be developed
separately?
4
What is your’s global approach to privacy?
5
What governance process have you in place?
6
What is the QA process for development & maintenance of queries and structures
7
How you ensure a robust safety net is implemented?
8

Goldmine

The typical cloud solution, simplified
Data is collected and value is extracted
Unrealised Potential
Activated
Data
Text based data from
spreadsheets and application
database sources are typically
well understood and mined
Raw Data Formats
CSV files
Spreadsheets
Images
Chat logs
CCTV
PDF documents
Videos
Emails, messages
Data Storage & Computation Value Out
Invoices
Call recordings
Application Databases
Unstructured data Structured data
Larger files or rich media assets may be stored or
available for manual reference but are rarely computed
& activated for advanced use cases, often due to
complexity or cost restraints
This is Cloud.Monks point of differentiation.
Let us explain…
Value derived from those well
structured assets and automation
of resulting workflows is the
promise of every SI

Despite the price of gold not being at
the same highs seen in the 80s (2022
avg = $1902/oz) once abandoned
mines are being re-mined.
Not because there is new gold.
Because the means of production
(ie technology) has improved such
that it now profitable to re-mine for
small particulates once deemed too
costly to refine.
Populations migrated and entire
townships were settled around
newly discovered gold deposits.
Upwards of 80,000 gold mines
were established throughout
Australia (18,000 in Victoria
alone!). The avg price of gold
was ~$19/oz ($450 accounting
for inflation)
1910s -1960s 1960s - 1990s 1990s - present day
Did you know?
There are 80,000 abandoned gold mines in Australia
As inflation and global trade took
hold in the post-war era, the
price of gold increased from
$275/oz in 1970 to highs of
$2,300/oz (!) in the mid 80s.
That’s close to a 1000%
increase in the price of gold.
Mines are plundered until it is no
longer profitable to mine that
location for the effort and cost
expended.
Ultimately the vast majority of these
gold mines were closed, and the era
of the Australian gold rush ended
over the course of the mid 20th
century.
1850s - 1910s
The Gold Rush Mines Abandoned Economic Inflation Technology Advances

= Next-Gen Cloud
Powered by tech, use cases re-
mining unstructured digital
assets have already realised
great outcomes for our
Enterprise clients.
And there is so much more
for us to (re-)mine.
Cool story! What does this have to do with cloud?
Every business has their abandoned data mine
A business is like a plot of land
with mineable resources. The
obvious assets are often well
extracted. That business could
be sitting on a goldmine of
valuable data insights, but not
even know it.
Existing Images. PDFs. Recordings.
This is the abundant gold mine.
Clients may even identify use cases
for these assets, but critically, they
fail when hitting a blocker related
to cost, complexity or
governance.
Cloud Platforms offer a next
generation suite of solutions that
pair perfectly with customer
focused solutions, well suited to
organisations rich in digital
assets
= Unrealised Potential Cloud.Monks
Specialisation
= Well Mined Assets
Typical Data Collection &
Value Extraction
Many Abandoned Use
Cases
Cloud Platform
Extract $$$ re-mining
unstructured digital
assets

The point of differentiation
Cloud.Monks are here to re-mine for gold
Unrealised Potential
Activated
Data
Raw Data Formats
CSV files
Spreadsheets
Images
Chat logs
CCTV
PDF documents
Videos
Emails, messages
Data Storage & Computation Value Out
Invoices
Call recordings
Application Databases
Unstructured data structured
Multi Moment
Success with Cloud.Monks
(BCG maturity framework)
Hunt for those
abandoned gold mines!

Question
Time ;-)

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touch

CDP Master Class - Jakub Otrząsek, Media.Monks

CDP Master Class - Jakub Otrząsek, Media.Monks

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