This document discusses Expedia's efforts to personalize email communications through leveraging customer data. It describes how Expedia segments customers based on demographics, actions, signals, loyalty, and email response data. Expedia uses this data in a personalized decision engine to dynamically match customers to relevant messaging modules and campaigns. The goal is to optimize response rates and continually improve personalization through machine learning.

1. Leveraging Data for Email Personalization

2. Brand Expedia
• Our Mission: To revolutionize travel through the power of technology
• Who we are: The world’s largest full-service online travel agency, helping travelers easily plan and book
travel with the widest selection of vacation packages, flights, hotels, rental cars, cruises and in-destination
activities, attractions, and services
• Fun Facts: We send 170 people on a trip every minute of every day & sell enough tickets to fill more than
six hundred 737 airplanes every day.
• Bill Nye breaks down the science of Travel with @Expedia. Watch here http://bit.ly/2qx2w3u

3. MADEE, you qualify for ½ off hotels! 
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4. Right message, Right time & Relevant content
Our customer contact strategy aims to provide contextualized personalization for a unified omni-
channel conversation with customers
How do we personalize?
• Demographics – account details such as adult, child, home airport
• Intentional actions - purchase, search, abandon
• Signals – inferences based on what have you searched for, where & engagement level
• Loyalty - business traveler, travel arranger, leisure, tier status, airline affinity
• Email response data - do you open & not click? how many emails do you open in a week?
• Personalize content based on device type
We have built an internal personalized decision engine with the ability to scale recommendation of
email content at a subscriber level (signals, preferences, propensities) to optimize response rate and
learn to improve subsequent communications
Inspire
Plan
Experience
Engage

5. Operationalizing Personalization
• Marketers create segments – group of people who we want to target
• Marketers create messaging modules – content you want to send tagged with type of content
• Modules are matched with segments and tagged with priority
• Marketers create a campaign template with all possible message modules they want to send to uber target
• Internal decision making machine will dynamically populate campaign templates with modules and determine
the priority based on historical performance (at customer level)
• Campaign will deploy and response data will be used in machine learning algorithm for future emails
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6. Building an Email with Personalization
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7. What have we learned?
• Customers change everyday. We need to be as close to real-time data as possible when
customers are engaged with us to provide relevant content
• We need to personalize our communications based off of multiple sources of data – not just
shopping behavior
• We have moved away from handling campaigns with regional owners to global campaigns
• We are gaining efficiencies by not having to consistently update ALL segments & modules. We
now only add new as needed for testing or reduce when performance declines
• Continuity of the message matters. We strive to create an E2E experience.

8. What problems are we working to solve?
• Continuing to gain more real time customer data
• Enhancing our algorithms with machine learning from email response data
• Use module level data to enhance campaign content at a customer level
• Onboard additional brands to platforms
• Integrating with global controls to process all communications including service emails, SMS & Push
• Scale for global audience size & data processing
Inspire Plan Experience Engage

9. Thank You!
And please subscribe for Expedia.com emails 
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