Ruben Mak, Team Lead Data Science at Greenhouse Group showed a live demo of a light-weight recommendation algorithm for banner ads, built using Snowplow, which measures viewable time and optimizes dynamic content. The demo is aimed at challenging people to think in a different way about retargeting and making offers more personally relevant. He also mentioned Eneco, one of the Netherlands’ largest energy providers, as an example of how they optimise their marketing communications across the customer journey. Presented on 5 April 2017.

1. DATA
HUB
MARKETING
AGENCIES
TECH
HUB
CREATIVE
HUB

2. DATA
HUB
MARKETING
AGENCIES
TECH
HUB
CREATIVE
HUB

4. DEMO
bit.ly/foonhouse

5. COLLECT EXTRACT ACT
Data
What can we know
about the consumer?
Insights
What does the
consumer wants to
achieve?
Accordingly
How can we help the
consumer achieve this?

6. COLLECT EXTRACT ACT
2 1 3

7. EXTRACT1

8. INNOVATION & PRIVACY

10. Campaign optimisation
Across the full customer journey

11. CORPORATE CONTENT
IN JOURNEY?

13. COLLECT2

14. DATALAYER

17. DATALAYER

19. DATA ENTERED
0 RETRIES
NUMBER CHANGED
CLICKED [+] ONCE
HOUSETYPE CHANGED 3X
POSSIBLE CONFUSING ICON?
TOTAL TIME SPENT IN BANNER: 34s
IDLE TIME: 7s, ON HOUSETYPE
TOTAL: 2

21. DEMO
DATA LOGGING

22. ACT3

23. PERSONALISATION

24. AND
MORE
DMP

26. DAG 1 DAG 2 DAG 3
No relevant new
offer
=
No ad

27. DEMO
bit.ly/relevantads

28. COLLECT EXTRACT ACT
DMP
DATA LAYER
On-site
personalisation