Christian Borchert Head of Consumer & Apps moebel.de Head of Consumer & Apps at moebel.de - Moebel.de is Germany’s biggest comparison and search portal for home & living - Christian is responsible for product development of the frontend portal and mobile apps and all customer facing interfaces - Leads strategic and operational product development for Germany & international portals

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2. |E-COMMERCEEXPO 2020
Product & category recommendations and
user personalization for a metasearch engine
like moebel.de
13/02/2020
Berlin

3. |E-COMMERCEEXPO 2020
Who is moebel.de
 Biggest portal for the topic home & living & decoration in
Germany
 CPC (& lead based) revenue model
 Currently in Germany & France (more countries to come soon)
 Partner for more the than 250 online shops and local retailers
 Over 3 million active products that are constantly being
updated
 Flexible bidding based pricing model and dynamic sorting
 Connecting customers to online, multi-channel and pure offline
retailers

4. |E-COMMERCEEXPO 2020
Who am I
 Christian Borchert – Head of Consumer of Apps
 35 years old
 > 10 years digital experience (client- & consulting side)
 Responsible for product development for web & mobile
applications with a team of developers, UI & UX designers
 Mail: christian.Borchert@mobel.de
https://www.xing.com/profile/Christian_Borchert9
https://www.linkedin.com/in/christian-borchert-
87640a141/

5. |E-COMMERCEEXPO 2020
Aim of this presentation
 Teaser for personalization
opportunities
 Learn from errors moebel.de did
 Understand what you can achieve and
what you need

6. |E-COMMERCEEXPO 2020
From one to many
to
MANY TO MANY

7. |E-COMMERCEEXPO 2020
“Instead of one-way
interruption, web marketing is
about delivering useful
content at just the right
moment that a buyer needs it.”
David Meerman Scott

8. |E-COMMERCEEXPO 2020
How we reach our customers
Website
SEA
Social media Content marketing
Retargeting
SEO
Display ads

9. |E-COMMERCEEXPO 2020
 Act of delivering
personalized/
recommended items
 Can be everything you
have available
 Can be part of
segments or 1:1
 Meaningful clustering
of user base on defined
criteria
 Can be overlapping
 Criteria must be
trackable in some way
Recommendation
Some short definitions for the start
Personalisation
Combination of segments, data & hypothesis
to deliver a 1:1 approach to your users

10. |E-COMMERCEEXPO 2020
What everybody has in mind with recommendation
Product recommendation is quite easy
You totally rely on automated clusters and interaction tracking

11. |E-COMMERCEEXPO 2020
Recommendation works well
7 % revenue on
pure product
recommendations
ROI of first project
step after 3.5
month
Revenue is split onto
40 % additional and
60 % competitive1
placements
in competitive1 placement
uplift of up to 70 % on
desktop and 125 % on
mobile
1 competitive placement is in comparison to dynamic sorting

12. |E-COMMERCEEXPO 2020
Recommendations are fine but not
enough
Moebel.de is going “many to many”

13. |E-COMMERCEEXPO 2020
Limitations with a portal like moebel.de
 Users are unlikely to share personal information with
you (e.g. moebel.de account usage < 1 %) – most of the
services can be used anonymously
 You don’t have a basket, a checkout or a detail page for
products – all this would stay in contrast to a CPC
model
 Intervals for buying furniture are quite long (e.g. sofas
are bought every 7 years)
 High percentage of paid traffic
Nevertheless you have to cope with this – by making
the first click count & leverage the data you have

14. |E-COMMERCEEXPO 2020
Always start with a use case
Define hypothesis
 Define a case with major impact on business KPIs (revenue, retention, etc.)
 State the case as clear as possible
 e.g. Female customers who are second or third time buyer who with a net
income of above 4,000 € are more likely to click out on exclusive and high
priced furniture
Define the data
 Define how you are able to identify this users so that you can react to them
accordingly
…

15. |E-COMMERCEEXPO 2020
And than you see the issue with data
Datachecklist
 Net income
 Gender
 Age
 Second or third time buyer?
 Price sensitivity
 Step in customer journey
?

16. |E-COMMERCEEXPO 2020
Heads up – you know more than you think
Explicit data Implicit data or an educated guess
 New or returning user (cookie or local
storage based)
 Landing page – might indicate interest of
the user
 Email address/marketing consent (if logged
in – most likely not )
 Click history/wish list history
 Location (based on IP or location consent)
 Device type
 Current step in the purchase journey (e.g.
based on channel or keyword)
 Relevant category/categories (based on
keyword)
 All you can get from targeting your
audience on google, Facebook, etc. (age,
gender, income, price sensitivity interests,
etc.) – just connect the targeting criteria to
an (GDPR compliant) tracking

17. |E-COMMERCEEXPO 2020
Than you realize the complexity
 You have an ever increasing amount of data from tracking, user interaction, touchpoints, etc.
 The amount of segments & clusters growth exponentially
 You need more and more detailed algorithms to cope with the data
 Most likely you are not a big data & AI company and you lack the resources or need headcount
Situation
 Find partners & service providers you can work with and who enable your vison
 From moebel.de we are working with two proven vendors who went through a detailed and
transparent selection process
Solution

18. |E-COMMERCEEXPO 2020
Let’s see some ideas

19. | ‹Nr.›Name des Kunden

20. | ‹Nr.›Name des Kunden
Sofa kaufen

21. | ‹Nr.›Name des Kunden
Customer journey
purchase
category
Sofa
category 2
Schlafsofa
Wohn-
land-
schaft
Retention
new
customer

22. | ‹Nr.›Name des Kunden
Sofa kaufen günstig

23. | ‹Nr.›Name des Kunden
category
Sofa
Customer journey
purchase
category 2
Schlafsofa
Wohn-
land-
schaft
Retention
new
customer
Price segment
low

24. | ‹Nr.›Name des Kunden
Sofa kaufen günstig Hamburg

25. | ‹Nr.›Name des Kunden
category
Sofa
Customer journey
purchase
category 2
Schlafsofa
Wohn-
land-
schaft
Retention
new
customer
Price segment
low
location
Hamburg

26. | ‹Nr.›Name des Kunden
Don’t underestimate the effort
and the capabilities you will
need

27. |E-COMMERCEEXPO 2020
Things you need
Top level
commitment
 Without C-level commitment the project is doomed, as it requires staffing,
funding and expertise beyond normal operations
Expert staff
 You need people on board that can generate valid hypothesis and people
that are capable to transform them into valid cases (
Marketing power
 Face it – SEO traffic won’t pay the project bills, you need involvement of
performance marketing and possibly need to restructure your accounts to fit
the cases
Technology
 In the end it boils down to technology – you must be able to understand the
toolset (to use it) and to integrate and run it in your environment

28. |E-COMMERCEEXPO 2020
Thank you
&
Feel free to ask questions