Anna-Katharina Knarr, Head of Account Management at Trbo, and Tobias Roth, Digital Conversion Manager at Galeria Kaufhof, present "Addressing Users Successfully with the Help of Dynamic Segmentation". They explain and demonstrate how bolstering segmentation with cutting-edge technology can make mass messaging feel personal and relevant. Find us at www.heroesofcrm.com And follow us on: YouTube: https://www.youtube.com/channel/UCaTC-I6-FOpst6iQ_Z1Y5cA Facebook: https://www.facebook.com/heroesofcrm/ Twitter: https://twitter.com/heroesofcrm Instagram: @heroesofcrm

1. Galeria Kaufhof & trbo
Addressing Users Successfully with the
Help of Dynamic Segmentation
Anna-Katharina Knarr, trbo GmbH
Head of Account Management
Tobias Roth, Galeria Kaufhof
Digital Conversion Manager

2. 2
Agenda
1) Introduction (Dynamic) Segmentation
2) (Dynamic) Segmentation in Action: Galeria
Kaufhof
3) What’s next?

3. Introduction
(Dynamic) Segmentation

4. 4
Issues in E-Commerce

5. 5
Segmentation in Personalization
❖ Personalization does not always have to
mean addressing each individual user 1:1
❖ Classification of users with similar interests,
preferences, behaviour into (dynamic)
segments
❖ Machine learning is used to distinguish
between permanent and temporary
interests (dynamic segments)

6. 6
Dynamic vs. Static Segments
❖ Static segments are used to group users
according to their previous actions
❖ Dynamic segments are formed in realtime.
A user can move from one segment to the
other with a single click.

7. Dynamic Segments
Use Cases

8. 8
Brand Affinity
❖ If the user is interested in certain brands,
they can be clearly highlighted when
entering the shop.
Use Case
Adjustment of the start page through
teaser areas that reflect the user
behaviour by means of dynamic
segments in order to pick up the user
both during and after a session and thus
acquire a loyal customer.

9. 9
Brand Affinity

10. 10
Dynamic Purchasing Behavior
❖ The change between the individual
segments depends on various factors, such
as the length of stay and other aspects.
Use Case
Dynamic segments distinguish the purchasing
behaviour of the user into impulsive,
temporary and permanent interests.
e.g. a man is looking for a gift for his girlfriend.

11. 11
Dynamic Purchasing Behavior

12. 12
Affinity Main Category
❖ The dynamic segment assigns user behavior
to certain top categories.
Use Case
Certain content is shown to the
user according to his segment.

13. 13
Affinity Main Category

14. 14
Further Use of Data
❖ Push the dynamic interests as Custom
Audiences to Google Analytics for retargeting
or also for transmission to other partners, such
as FINDOLOGIC for optimizing the search or to
CrossEngage for data orchestration.

15. (Dynamic) Segments in Action:
Galeria Kaufhof

16. 16
Example 1: Daily Deals
(“Tagesdeals”)
❖ Ongoing campaigns
❖ Special offers on Sundays and Tuesdays
❖ Offers on certain categories, teased by
newsletter
❖ Banners with offers specifically tailored to
the segment are shown only to certain
segments (e.g. children's fashion).

17. 17
❖ Daily Deal: 20% on the categories watches,
suitcases, sports, jackets and women’s shoes, 15%
on kitchenware
❖ Segments were used to address relevant target
groups → 3 campaigns on the basis of these
segments
➢ Control group: No segmentation
➢ 1st Segment: User with interest in watches
➢ 2nd Segment: User with interest in sports
❖ The numbers prove that segmentation is worth it
Example 1: Daily Deals
(“Tagesdeals”) on Sunday

18. Example 1: Daily Deals
(“Tagesdeals”)

19. 19
Campaign Addressed Users Conversion Rate User Value
First Segment over 60.000 1.87 % Double that of third
segment
2nd Segment over 20.000 3.3 % Double that of Top
Segment
Control Group (no
segments)
over 450.000 1.37 %
Example 1: Daily Deals
(“Tagesdeals”) on Sunday

20. 20
❖ CTR, Conversion Rate and Revenue increased
through segmentation
❖ Setup effort for campaign is low → creation of a
campaign for the top segment, then adjustment
of date, wording and other segments
❖ In most day deals we achieved better results with
segmented playout than with non-segmented
playout → overall the Conversion Rate was
increased by 20%
Example 1: Daily Deals
(“Tagesdeals”)- Insights

21. 21
❖ Learnings from daily deals
➢ Adjust the workload according to projected
uplift for the segments:
e.g. graphics vs. text-teaser
➢ If segments are too similar, the uplift is
reduced
➢ Schedule as a weekly task
Example 1: Daily Deals
(“Tagesdeals”) - Learnings

22. 22
Example 2: Pre-Christmas
❖ 3 campaigns during pre-Christmas time 2018
❖ Challenge: Communicating 3 campaigns at
the same time
➢ Christmas Service-Banner: Punctual delivery for
christmas (order by...)
➢ Favourite discount (“Lieblingsrabatt”): Discount
campaign for Christmas shopping showing a
promo code
➢ Payback campaign: Customers using Payback but
have not entered their number are specifically
being addressed

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Example 2: Pre-Christmas
“Lieblingsrabatt”

24. 24
Example 2: Pre-Christmas
“Weihnachtsservice”

25. 25
Example 2: Pre-Christmas
Payback

26. 26
❖ Campaigns ran simultaneously
❖ Prioritized playout: If a user fell into all
segments, measures were played out
according to priority
❖ Capping the showing to five times
❖ Users can be picked up with different
intensity, depending on the length of stay
and clicks on the page
Example 2: Pre-Christmas

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❖ No A/B-Test for these campaigns
❖ Setup effort: Playout on desktop/tablet/mobile;
predefined look & feel → approx. 1 h
➢ Payback User segment was set up approx. 1
month before campaign
➢ Favorite discount was filled adhoc (basing
on current surfing behavior in defined
categories)
➢ Christmas Service segment was filled ad hoc
and containing all users with +3 page views
Example 2: Pre-Christmas

28. 28
Example 2: Pre-Christmas
Campaign Addressed Users Conversion Rate User Value
Favorite Discount over 3 Million + 1.3 % Analogue to users
without address
Christmas Services over 200.000 + 1.38 % Analogue to users
without address
Payback over 2.000 + 7.89 % 3-fold increase

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❖ It is worthwhile to address users who have a
special interest with this campaign setup
➢ The target group may be small, but the
uplift is enormous
➢ Despite the simultaneous use of special
actions in the same period of time
Example 2: Pre-Christmas

30. (Dynamic) Segments at Kaufhof:
What’s next?

31. 31
Kaufhof: What’s next?
❖ We have established and are further working
on interfaces to other providers to access
segments from their systems.
Challenge:
Mapping

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❖ Mapping of the different segmentation types
(women vs. Damen) in all systems
❖ A Customer Data Platform (CDP) can be used
to cleanly merge elements into a main
system
Kaufhof: What’s next?

33. 33
❖ New teaser areas:
➢ Teasers are re-sorted and selected
according to segment preferences
❖ Completely Dynamic Segments:
➢ Each time a page is accessed, a new and
dynamic decision is made as to which
segment the user is in
Kaufhof: What’s next?

34. 34
❖ Shop the Look & Inspiration
Kaufhof: What’s next?

35. 35
❖ Shop the Look & Inspiration
Kaufhof: What’s next?

36. 36
❖ Shop the Look & Inspiration
Kaufhof: What’s next?

37. 37
❖ Shop the Look & Inspiration
Kaufhof: What’s next?

38. 38
❖ Shop the Look & Inspiration: Advantages
➢ BNDLA users have a higher conversion
rate than the shop average
➢ Interest-pages offer added value for
users and is rewarded with a conversion
rate increase of up to 20%
Kaufhof: What’s next?

39. Dynamic Segments
Learnings

40. 40
Learnings
❖ Dynamic segments are formed in real time
❖ In e-commerce, together with
personalization algorithms, they can have a
positive effect on
■ turnover
■ conversion rates
■ customer relations
■ average purchase value

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❖ Dynamic segments can be prioritized using
the
■ Search depth
■ Time on Site
■ According to fixed specifications
❖ A segment must be defined in such a way
that it has a meaningful size.
❖ However, small segments can lead to
significant uplifts in individual cases and
should not be generally excluded.
Learnings

42. Any Questions?
Thank You!