Automation is taking an ever bigger role in our work as PPC Specialists. This is the presentation that Nils Sickman and Mark Meijs gave on how they use automation for the PPC Campaigns for Thomas Cook NL. This presentation was given during the DDMA afternoon update on 12-4-2018.

1. Thomas Cook & Automation
April 12 2018

2. Mark Meijs
Sr. PPC Consultant
iProspect
Nils Sickman
Sr. PPC Specialist
Thomas Cook NL
Hello!
- 2 -

3. Agenda
❖ Adopting automation in PPC
➢ Why?
➢ How?
❖ Where do we stand
➢ What are challenges?
➢ What are the next steps?
❖ Conclusion

4. Introducing Thomas Cook:
Neckermann & Vrij Uit
Al e 45 ja ti
De s al n a ak es
Thomas Cook NL
- 4 -

5. Who wants to manually advertise on +5k daily changing accommodations?
Large variety of offers
Hotel types
● Differentiated hotels;
● 6 own hotel brands → for every audience the right hotel:

6. We have to automate to succeed.
Different holiday types, accommodations and places
Large holiday
variety
Text
Text
Dynamic market
Huge volumes
Offers and prices change every day
- 6 -
Automation &
Cooperation
High search volumes in the market especially during peak periods

7. Combining the power of 3 to win @ PPC
Combining:
1) Internal knowledge
2) PPC knowledge & learnings
3) New Beta’s and AI
External
Expert
Knowledge
Internal
Expert
Knowledge
Innovating
Partners
Winning
@ PPC
- 7 -

8. There is no I in team
- 8 -

9. Agenda
❖ Adopting automation in PPC
➢ Why?
➢ How?
❖ Where do we stand
➢ What are blockers?
➢ What are the next steps?
❖ Conclusion

10. The key to better performance is automation & innovation
Campaign Creation
2
Bidding
3
Optimizing
4
Experimenting
5
Innovating
1
The key to better performance
- 10 -
Automation Testing and Innovation

11. Tailor made automated campaign creation
Key benefits:
● Highly Customizable (tailor made)
● Scalable (in Excel)
● Cross engine
● Time saving
- 11 -

12. Using the full power of DoubleClick
Developments in the last 6 months:
● Automating bids & bid adjustments via newest
DS algorithm (V2)
● Custom Build dynamic DDA model (in DS)
● Combining business data in online bid tool
- 12 -

13. Automating optimizations via Scripts
A sneak peak into our script collection:
● Budget cap checker
● RLSA Conflict script
● Bid shaver script
Example bidshaver script:
● Branded CPC -45%
● Maximizing impression share
● Fighting off Branded bidding (e.g. neckermann.com)
● Time saving
- 13 -

14. Optimizing via advanced toolingFor every challenge there is a solution..
- 14 -

15. Optimizing via advanced toolingHowever, these are the tools we use!
Ad TestingAuditing & AlertsBid Automation
Advanced PPC
Optimization
Feed
optimization
Competition
Analysis
Automated
Reporting
Campaign
automation
- 15 -

16. Agenda
❖ Adopting automation in PPC
➢ Why?
➢ How?
❖ Where do we stand
➢ What are our challenges?
➢ What are the next steps?
❖ Conclusion

17. Maturity model (Jan 2017)
Level 1 Level 2 Level 3 Level 4
Campaign creation Manual campaign creation in platform Static campaign creation through
Excel
Feed-based campaign creation
combined with static campaigns
Feed-based fully automated
campaigns
Bid management Manual bidding Rule-based bidding Algorithmic bidding Cross-engine algo-
rithmic bidding
Hygiene checks Using each platform "as is" Making use of scripts and rules within
platforms
to automate campaign management
tasks
Using technology to automate
management tasks across multiple
accounts
Using technology to automate
manage-
ment tasks across accounts and
platforms, and proactively send alerts
on tasks across accounts and
platforms
Reporting & dashboarding Manual reporting:
- downloading (manual)
- aggregation (manual)
- visualizing (manual)
Semi-automated reporting using
templates:
- downloading (scheduled)
- aggregation (semi-macro)
- visualizing (auto / template)
Fully automated reporting using
standard dashboards (not flexible)
Fully automated reporting using
custom dashboards (flexible)
Data management No integration of data between
systems / platforms
Fragmented data management
allowing some cross-platform data
analysis
Data from the most important
marketing and service platforms is
integrated and used to personalize
advertising, content and services
All necessary data is managed from
one central location and can be
accessed by all relevant parties /
platforms that need this data to
optimize decision making and
marketing spend
Measurement & attribution No conversions are measured Conversions are measured
Credit is attributed to the last ad click
Conversions are measured
Credit is attributed over multiple ad
clicks inside the search environment
(rule-based or data-driven)
Conversions are measured
Credit is attributed over multiple ad
clicks over all marketing channels
(rule-based or data-driven)- 17 -

18. Maturity model (Jan 2018)
Level 1 Level 2 Level 3 Level 4
Campaign creation Manual campaign creation in platform Static campaign creation through
Excel
Feed-based campaign creation
combined with static campaigns
Feed-based fully automated
campaigns
Bid management Manual bidding Rule-based bidding Algorithmic bidding Cross-engine algo-
rithmic bidding
Hygiene checks Using each platform "as is" Making use of scripts and rules within
platforms
to automate campaign management
tasks
Using technology to automate
management tasks across multiple
accounts
Using technology to automate
manage-
ment tasks across accounts and
platforms, and proactively send alerts
on tasks across accounts and
platforms
Reporting & dashboarding Manual reporting:
- downloading (manual)
- aggregation (manual)
- visualizing (manual)
Semi-automated reporting using
templates:
- downloading (scheduled)
- aggregation (semi-macro)
- visualizing (auto / template)
Fully automated reporting using
standard dashboards (not flexible)
Fully automated reporting using
custom dashboards (flexible)
Data management No integration of data between
systems / platforms
Fragmented data management
allowing some cross-platform data
analysis
Data from the most important
marketing and service platforms is
integrated and used to personalize
advertising, content and services
All necessary data is managed from
one central location and can be
accessed by all relevant parties /
platforms that need this data to
optimize decision making and
marketing spend
Measurement & attribution No conversions are measured Conversions are measured
Credit is attributed to the last ad click
Conversions are measured
Credit is attributed over multiple ad
clicks inside the search environment
(rule-based or data-driven)
Conversions are measured
Credit is attributed over multiple ad
clicks over all marketing channels
(rule-based or data-driven)- 18 -

19. Biggest challenge: Data Management
Priorities
Non PPC factors (besides ROAS) need to
be taken into account
Product Feed
Far from optimal product feed
Be Flexible and use your ‘’Farmers Sense’’
Issue
Combining iActivate, Supershift &
Channable to get a flexible feed outcome
The
solution
Impact
Data Management
1 central data feed
Key data is stored in seperate data feeds
- 19 -

20. Leaping forward in 2018
Device targets in automated bidding
Data Management
Next steps
Expanding Feed Based DSA
Incorporate margin & availability in
automated bidding
H2 2018
June 2018
- 20 -
This Month
June 2018
Device targets in automated bidding
Data Management
Expanding Feed Based DSA
Incorporate e.g. margin & availability in
automated bidding Q3 2018

21. Agenda
❖ Adopting automation in PPC
➢ Why?
➢ How?
❖ Where do we stand
➢ What are our challenges?
➢ What are the next steps?
❖ Conclusion

22. Automation made our life easier!
1 Adopt an automating mindset.
Use Tooling and Scripts to make your life easier.
Truly work together with your colleagues and partners.
2
3
- 22 -

23. Which tasks can and should you automate?
Homework:
● Map tasks that you can and should automate
● Prioritize tasks and make a weighted selection
○ Impact vs effort analysis
Which tasks can you automate in the next 2 months to
improve your PPC results?
- 23 -

24. Thank you!