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Meet Optimizely X
Recommendations
Deliver recommended products and content
Chris Tiutan
Product Marketing Manager
Jon Noronha
Director, Product Management
Agenda
Introducing Optimizely X
Recommendations overview
Demo
How it works
Use cases
Q&A
Experimentation is at the core of every discovery
Science Athletics Business Politics
10,000
2012 2013 2014 20152011
Adobe
Google
Oracle
#1 Experimentation Platform
5,000
Websites
Experimentation Platform
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
Hands-off ROI
Powered by machine learning
Not a black box
Deliver recommended
products and content
app.optimizely.com
Optimizely X
Recommendations
Demo
How it works
No product feed required
Viewed
Derby Tier Backpack
at 1:10pm
Viewed
Dawson Trolley Bag
at 1:14pm
Viewed
Five Panel Hat
at 4:15pm
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
Use cases
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
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
Questions?
Request a demo
optimizely.com/request-demo
Join our community
community.optimizely.com
Thank you

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Meet Optimizely X Recommendations

  • 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
  • 5.
  • 6.
  • 7.
  • 8. 10,000 2012 2013 2014 20152011 Adobe Google Oracle #1 Experimentation Platform 5,000 Websites
  • 9.
  • 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
  • 14.
  • 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
  • 18.
  • 19.
  • 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
  • 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
  • 24.
  • 25.
  • 26.
  • 27. Questions? Request a demo optimizely.com/request-demo Join our community community.optimizely.com