With Optimizely X Recommendations, powered by machine learning, you can deliver more relevant recommendations and start generating hands-off ROI. Check out this content and learn: 1. How to quickly get started without coding or a product feed 2. The possibilities of experimenting with recommendation algorithms, placements, layouts and more 3. Measurement best practices for recommendations, including revenue, engagement and more

1. Meet Optimizely X
Recommendations
Deliver recommended products and content

2. Chris Tiutan
Product Marketing Manager
Jon Noronha
Director, Product Management

3. Agenda
Introducing Optimizely X
Recommendations overview
Demo
How it works
Use cases
Q&A

4. Experimentation is at the core of every discovery
Science Athletics Business Politics

8. 10,000
2012 2013 2014 20152011
Adobe
Google
Oracle
#1 Experimentation Platform
5,000
Websites

10. Experimentation Platform

11. Optimizely X Web Experimentation
Deliver great web experiences on every device
Optimizely X Web Personalization
Deliver targeted content and experiences in real time
Optimizely X Web Recommendations
Deliver recommended products and content
Optimizely X Full Stack
Democratizing the power of deep experimentation
using Python, Java, Ruby, Node and more
Optimizely X Mobile
Deliver great mobile app experiences
Optimizely X OTT
Deliver great over-the-top TV app experiences

12. Hands-off ROI
Powered by machine learning
Not a black box
Deliver recommended
products and content
app.optimizely.com
Optimizely X
Recommendations

13. Demo

15. How it works

16. No product feed required

17. Viewed
Derby Tier Backpack
at 1:10pm
Viewed
Dawson Trolley Bag
at 1:14pm
Viewed
Five Panel Hat
at 4:15pm

20. Supported Algorithms
Co-browse: other visitors who looked at this item
also viewed these other items (ideal for PDP)
Co-buy: other visitors who purchased this item also
bought these other items (ideal for PDP, Cart)
Popular: the most frequently viewed or bought items
across the whole catalog (ideal for Homepage)
Recently viewed: you browsed these things before
(“pick up where you left off”)
User-based (coming soon): recommended for
you, based on your past behavior

21. Use cases

22. Products
Approach: drive more and bigger purchases
- Offer more alternatives
- Cross-sell with related items
- Highlight crowd favorites
- Drive discovery across the catalog
Outcomes: higher average order value, lower
abandonment rate, more purchases per session

23. Content
Approach: drive more engagement with content
- Recycle whitepapers, blog posts, infographics, and
other static content
- Deflect support calls with knowledge base articles
and community posts
- Drive traffic to the great content you already have
Outcomes: higher CTR, more pages viewed per
session, lower call center volume

27. Questions?
Request a demo
optimizely.com/request-demo
Join our community
community.optimizely.com

28. Thank you