Go over a few case studies which have had a great impact on travel experience for users and the technology behind them. Usage of machine learning to provide personalized sorting of search results which in turn increased the propensity to buy. Collecting and analyzing Site experimentation data. Marketing Channel Optimization and Campaign effectiveness Data platform that enables all of our use cases

1. Revolutionizing Travel through Data
@orbitz
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2. @ragskashyap
Agenda
1. Data platform evolution
2. Business problems solved
3. Leveraging ML, Descriptive
and Predictive Analytics
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3. @ragskashyap
Raghu Kashyap
• Tech Person
@orbitz
• https://github.com/
ragskashyap
• http://
kashyaps.com
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4. @ragskashyap 4

5. @ragskashyap
Orbitz Worldwide
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6. @ragskashyap
Contributions by @orbitz
Open Source
• Graphite http://
graphite.readthedocs.org/en/
latest/overview.html
• ERMA - https://github.com/
erma/erma/wiki
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7. @ragskashyap
Travel
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• World’s Fastest
Growing Sector
• Data is growing
exponetially

8. @ragskashyap
Business Challenges
• Multi Dimensional analysis
• Access to data
• Controlled environment
• Speed
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9. @ragskashyap
Addressing Biz Problems - Owwlytics 1.0
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10. @ragskashyap
Life time Value?
• CLTV
• Acquisition
• Retention
• Top 10% of
customers value
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11. @ragskashyap
Channel Attribution
• Allocation Matters
• Last click
• Time decay
• Equal attribution
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12. @ragskashyap
EFX - Every Freakin X
• Hotel sorting is everything to
selling vs NOT selling
• Lot of factors are important
and considered to decide
what we display and where
we display
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13. @ragskashyap
Predicting Hotel Stay
• Duration of Stay
• Seasonality
• Location
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14. @ragskashyap
Tools Around Big Data
• Complement the tools
that we use at SOC
• Leverage business
expertise and hand
over the tools to make
quick decisions
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15. @ragskashyap
Tools around Big Data
• HDFS, Flume and
Log4J
• HGrep
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16. @ragskashyap
What did we learn from owwlytics 1.0 ?
• Decentralized vs Centralized
Decentralization
• Data Governance
• Scalability
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17. @ragskashyap
EDW and Data science -Owwlytics 2.0
1.Current cluster stats: Available
~4PB
2.12x 4TB , 2.6Ghz 6-Core, 15MB
Cache), 128GB RAM17

18. @ragskashyap
City Recommender (labs.orbitz.com)
•Tool for travelers to
find new places to
visit based on
places similar
travelers visited
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19. @ragskashyap
SEO the underdog
• Multi Touch
• Attribution
• Influence
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20. @ragskashyap
Cache optimization
• Test Results
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21. @ragskashyap
Keywords and $$$
HIGH$COST$
&$COMPETITION$
LOW$COST$&$
COMPETITION$
HIGH$PROBABILITY$
OF$CONVERSION$
LOW$PROBABILITY$
OF$CONVERSION$
KEYWORD$PHRASE$CURVE$
LONG$TAIL$PPC$
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22. @ragskashyap
Owwlytics 3.0
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23. @ragskashyap
Real time Analytics
• Redshift, AWS
• Kibana
• Landing page optimization
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24. @ragskashyap
3 Things to take away
1. Insights and actions are way more important
than data storage and retrieval.
2.Vision and executing the strategy towards your
data platform and usage is the key differentiator
3.Weigh your options right with “Buy vs Build”
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25. @ragskashyap
Optimize your Journey towards the destination
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