The document summarizes how leading retailers like MediaMarkt, Sephora, and IKEA are personalizing customer experiences using Dynamic Yield's personalization platform. It provides examples of how a large fashion retailer fully personalized their homepage by continuously optimizing and targeting content to audience segments. It also discusses how recommendation strategies combined with predictive targeting increased revenue per user by 54.1%. The document highlights how Dynamic Yield uses machine learning to automate testing, recommendations, and predictive targeting to provide more relevant personalized experiences that boost customer engagement and sales.

1. CONFIDENTIAL
Personalization Pioneers
How mavericks like MediaMarkt,
Sephora and IKEA personalize
each touchpoint
Ander Orcasitas
Dynamic Yield
ander@dynamicyield.com

2. “Tomorrow, through personalization,
online commerce will accelerate the very
process of discovery. Amazon.com uses
the internet to create real value for its
customers and, by doing so, hopes to
create an enduring franchise, even in
established and large markets.”
– Jeff Bezos
1997 Letter to Amazon
Shareholders

3. Acquisition
For every $92 spent
acquiring customers
Onsite Personalization
Just $1 is spent
converting them
Today

4. The #1 inquiry into
Gartner is about
Personalization
Source: Gartner 2017

5. Personalization Impact:
• 5%-15% Revenue uplift
• 10% to 30% increase in marketing spend efficiency
Source: McKinsey, “Marketing’s Holy Grail: Digital Personalization at scale”

6. “Dynamic Yield is a Leader…
Marketing Leaders seeking a
scalable personalization solution
suitable for a variety of use cases
should consider Dynamic Yield”
Gartner Named Us a Leader in
Personalization Engines

7. Predictive Targeting
A/B Testing with CRM &
Browse Segmentation
Machine-Learning
Based Decisioning

13. A large fashion retailer has converted every piece of content and banner on
their Homepage into Dynamic Content, continuously optimized and
targeted at their varied audience segments. The order of the banners and
their selected variations are synchronized to guarantee an optimal and
consistent experience.
Full Homepage Personalization
Homepage
For internal use only

14. Easy Hero Banner Optimization & Personalization
Our Homepage Hero Banner is connected
to a variations feed, from which Dynamic
Yield automatically serves the most
appropriate selection of banners to each of
our most valuable segments
We Continuously Personalize the Hero Banner, Automatically

15. Affinity category sorting

17. “Just For You” Shopping Zone
15% Uplift
in revenue per session
vs. control group with
no “for you” zone

18. Social Proof & Urgency Notifications
10% Uplift
in revenue per user + 6%
uplift in total purchase

19. Loyalty based Personalization
Highlighting loyalty program with personalized messaging

20. Predictive Targeting
A/B Testing with CRM &
Browse Segmentation
Machine-Learning
Based Decisioning

21. Predictive Targeting

22. Live Results
Similar
All slots show DY similar
Similar + Bought Together
2 slots similar + 3 slots bought together
Control
No recs

23. Testing Recommendation Strategies
Similar
All slots show DY similar
Similar + Bought Together
2 slots similar + 3 slots bought together
Control
No recs
Revenue per User: (Baseline)
Revenue per User: (+27.1%)
Revenue per User: (+34.4%)

24. Recommendation Strategies with Predictive Targeting
Similar + Bought Together
To all users
Revenue per User:
+34.4%
Revenue per User:
+54.1%
Similar
Audience “PDP frequent visitors”
(39% of visitors)
Similar + Bought Together
Rest of the users
(61% of visitors)
Predictive Targeting

25. Dynamic Yield Personalization Platform
(web, mobile web, apps
emails, ads)
Personalization
Recommendations
Optimization
Messaging
Triggering
Web
Mobile Web
Mobile Apps
Email
Advertising
Segmentation
First Party
(3rd party data marketplaces,
policy controlled data sharing)
2nd & 3rd Party
(CRM, ESP, tag managers,
POS, loyalty, etc)
Enterprise Systems

26. Dynamic Yield’s Machine Learning Engine: Everything Is Tested
In order to make sure that each user
receives the optimal experience, everything
is tested in real-time.
Dynamic Yield optimizes 1:1 experiences
for hundreds of thousands of users at every
given moment.

27. Predictive Models
Probability
to Purchase
Category &
Brand Affinity
Price
Sensitivity
Expected
Lifetime Value
Increase Retention
Improve Customer
AcquisitionPredictive Modeling Engine
Optimize Conversion
Probability
to Churn

28. The Evolution of Testing with Machine Learning
Traffic Allocation
● Manual
Results
● Winner takes all
● Winning variation is
statistically significant
Traditional A/B/n
& Multivariate Testing
Classic Multi-armed
Bandit model Dynamic Yield’s Predictive Targeting
+ Automation
Traffic Allocation
● Dynamic
Results
● Winner takes all
● Lower statistical validity
+ Personalization
Traffic Allocation
● One click (Predictive Targeting)
Results
● Predictive Targeting identifies
winning variation for each
audience
● Predictive Targeting’s
suggestions are statistically
significant

29. Automated Segment-Driven Strategy Selection
Gathered information per user
Revenue
Revenue Per User
Dynamic Yield’s recommendation engine automatically assesses the relevant data for each individual user and deploys
the most appropriate recommendation strategy for optimal results.
New Users Occasional Users Frequent Users Savy Users

30. Machine Learning at the Core of Dynamic Yield
Experiment Automation
Multi-armed bandit algorithms: Estimates each variation’s probability to be best and allocates
to each variation a fraction of traffic proportional to its probability score.
Predictive Targeting
Proactively identifies opportunities in campaigns to provide users with more relevant experiences
that boost revenue and engagement.
Recommendations
Collaborative Filtering Strategy: Identifies variations most likely to convert a visitor based on the
exhibited preferences of similar visitors.
User Affinity Strategy: Recommends the highest rated variations based on a visitor’s individual
affinity profile and preferences.
Automated Strategy Selection: Our recommendations engine automatically learns which
recommendation strategies performs best for each customer for optimal engagement and results.
Predictive Audiences [In Development]
Automatically generates new, high-value segments based on a customer’s existing audiences.

31. Thank you.
ander@dynamicyield.com