This document discusses practical use cases for data-driven digital marketing. It provides two case studies: 1) For Eurotunnel, audience segmentation was used to better target customers based on location, booking horizon, and vehicle type. This improved acquisition rates and ROI. 2) For Carglass, dynamic creative optimization (DCO) was implemented to automate ad creation and delivery based on variables like product, brand, and language. This reduced production costs while allowing more ad testing and personalization early in the customer funnel. The document emphasizes leveraging first-party data to gain customer insights, build audience profiles, and personalize the customer experience across digital channels. This improves marketing performance metrics like conversion rates and

1. From data collection
to action:
Practical use-cases

2. MAXIME VANDENBUSSCHE
eBusiness Consulting Manager
WHO ARE WE?
FREDERIC PALELLA
eBusiness Consultant
FOOD
&
DRINK
SEMETIS
BUFFAL
OOOOO
AUTHOR
(to be)
REAL
MADRID
TECH

3. Data-Driven Digital Media Agency
Connecting digital advertising & business intelligence with data

4. Our services
We offer unique capabilities in the
management of digital advertising &
digital business intelligence, data being
their connector
DIGITAL ADVERTISING DIGITAL BUSINESS INTELLIGENCE
data

5. Facing digital marketing evolutions
with our DNA
#open #share #knowledge
Business minded
Transparent & technology agnostic
Data & technology-driven

6. Our 4-step model

7. collection unification
activation insights
The 4 core capabilities of your future architecture
1 2
34

8. The 4 core capabilities of your future architecture
1
2
4
3

9. Case 1: Eurotunnel
Audience segmentation

10. A short introduction to Eurotunnel

11. The Challenge of Eurotunnel
Eurotunnel presence in the Benelux is still in an early-stage business compared to the UK
and France. The steps toward business growth:
• Market development: expansion of the potential market to new customers or new
users
• Market penetration: Competing to capture a greater share of an established
customer base

12. Our own data
How are we going to achieve
market growth on the continent?
Leverage our own data and
audiences

13. Audiences or segments are
clusters of users that have
common denominators

14. Leveraging the full potential of audiences
What most implementations
look like
What implementations should
look like
audiences
generic
messages
messa
ges
audien
ces
audiences relevant
messages
reasons

15. Data pools for acquisition & retention
BRAND
FARE FINDER
TRAVEL OPTIONS
PERSONAL DETAILS
PAYMENT
SALE
POST SALE FLOW
ACQUISITION
WEB SCORING
SYSTEM
RETENTION
IN HOUSE
SCORING SYSTEM

16. Predicting based on collected data
Profile A
Profile B
Profile C
Message A
Message B
Message C
The objective of the audience-based approach is to determine a profile based on what we can measure in
the funnel. This allows us to tailor a message to each audience, increasing our impact on user that entered
the funnel but did not buy.

17. Impacting ROI & retention through
improved acquisition
As a consequence, our delivered messages are more relevant to the customers:
(1) So we can convert / acquire more users (within the same volume)
Immediate impact - With a more granular segmentation, we’ll also be able to have a better prioritization of
remarketing budgets
Profile A
Profile B
Profile C
High ROI
Medium ROI
Low ROI
High investment
Medium investment
No investment
(2) So we can be more relevant after the sale so we can retain the customer

18. How do we get there?

19. Leveraging the backend - Checkout

20. Building a future-proof infrastructure
Tag Management
System
Analytics Tool
Ad Server DSP
dataLayer
Tag Management Implementation
Audience Data Integration
Implementing tag management structure cross-countries
Ensuring consistency and good naming convention
Mapping all the steps of the different funnels of Eurotunnel
Creating of multi-funnel step dataLayer tracking
Enhanced ecommerce implementation
Funnel tracking improvement
Integrating multiple data sources (CRM, Sitecore,..)
Pushing data sources to relevant advertising platform
Integrating custom Javascript to identify last source before
conversion

21. From data to audience clusters
Sales
data
Profile building
Remarketing with
adequate message

22. Retrieving
consumer insights
for future
informed
decision making
digital
marketing
We created dimensions and
metrics for all variables available
in the backend in the Web
Analytics tool. We conducted an
analysis to discover the key
revenue denominators

23. Location is a key variable
Provinces closed to the coast are the biggest sales generators. Brussels is the cheapest in
terms of acquisition. The further away the location to the terminal, the higher the AOV.
Province #Sales Revenue CPA AOV Distance
South Holland
1000 € 200.000 € 5,37 € 200
321 km
Flemish Brabant
978 € 185.771 € 3,95 € 190
216 km
Antwerp
974 € 183.082 € 5,70 € 188
204 km
East Flanders
889 € 176.429 € 5,75 € 199
151 km
West Flanders
864 € 173.680 € 4,87 € 201
123 km
Brussels
767 € 152.431 € 3,73 € 199
198 km
North Brabant
756 € 177.894 € 4,87 € 235
296 km
North Holland
725 € 144.379 € 5,67 € 199
390 km

24. Booking horizon & vehicle type
CAR VAN CAMPER
URGENT
SHORT
TERM
LONG
TERM
URGENT
SHORT
TERM
LONG
TERM
URGENT
SHORT
TERM
LONG
TERM
VEHICLE TYPE BOOKING HORIZON % REVENUE ROI
CAR URGENT 22% 3.2
CAR SHORT TERM 15% 1.8
CAR LONG TERM 10% 2.4
VAN URGENT 15% 2.3
VAN SHORT TERM 10% 1.9
VAN LONG TERM 8% 3.1
CAMPERVAN & MINIBUS URGENT 3% 3.1
CAMPERVAN & MINIBUS SHORT TERM 5% 2.4
CAMPERVAN & MINIBUS LONG TERM 12% 2.2

25. Pushing those dimensions into your
platforms to create audiences

26. Bottom line impact
CONVERSION RATE
+ 13 %
over last 2 years
RETURN ON INVESTMENT
+ 18 %
over last 2 years

27. Case 2: Carglass
Increase funnel conversion rate
through DCO

28. Top Belgian brand
Willingness to explore &
improve
Changing market conditions
Increasing competition
The Problem

29. Main Challenges

30. Main Challenges
High volume of combinations Possibility to test and adapt
Option to test at least 2 call to
action variables.
2 call to action variations
1680 banner variations
15 top car brands
2 product possibilities
2 languages
7 formats
2 weather types
840 banner variations
*
*
*
* *

31. Huge production costs
No need to say that the
production of (at least) 840
banners is a time consuming
and thus expensive task.
Moreover, this approach isn’t
easy to scale as more brands
become available.
Increased risk of error
As all tasks are manual, the
risk of errors being introduced
in high. Moreover, as multiple
stakeholders are involved the
process can be heavy / slow.
Main Challenges

32. Dynamic Creative Automation
Use DoubleClick Studio in order to automate
the asset creation, assembly and delivery
process using a transparent build-up process.
The Solution

33. Variable 1 = repair / replace
Variable 2 = car brand
We decided on 2 variables that make a
difference visually and are also at the start of
the funnel to be able to personalize early on
Variables
The Variables

34. Different animations based on product
The Variables

35. WHEN IT ALL COMES TOGETHER

36. Variables and content come together in
a feed
Based on the variables, the banners
dynamically load in the content
matching the scenario
The feed

37. ZOOM IN ON EXAMPLE
The feed

38. Video

39. What’s next?

40. DCO for Video

41. Take-aways

42. Take-aways
Your own data (GA) can be leveraged in many different ways
#1 Segment your data to discover new business opportunities
#2 Use your data to personalize your messaging
#3 Explore new digital KPI’s to make business decisions

43. Thank you