intern project - tech
TRANSCRIPT
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Intern Project - Final run-through7/28/2016
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Team Technology AKA ‘Notorious Data’
Desean
Front End Developer
Zach
FinanceGus
Product Manager Niket
Software EngineerShamanth
Business Analyst
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Monetizing Data byIncreasing Conversion through Travel Recommendations
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Customers Love Recommendations
40%40 million / 100 million
75%62 million / 83 million
?13 million unique users / month
Sources: Spotify,Statistica, Kissmetrics, Priceline
http://www.slideshare.net/upload
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Overview
ResourcesProject Goal Specification
Analyze search and booking data to identify user patterns
and make monetizable recommendations
Air Hotel Rental Car Package Cruise
Retail SOPQ OPQ
PricelineGroup priceline.com
Data: June 21 ,2016 - July 21, 2016Booking records 1.2 Million, Searches records 263 Million
Tony PadovanoChief of Staff for CTO
Dan O’ConnorPrincipal Insights Analyst
Zachary HorneSolutions Architect
Tools
Mentors
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Agenda
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1. Timeline2. Insights3. Ideas4. Execution/Recommendation
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Timeline
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2016
Today
Week 1
Milestone 1Planning
Milestone 2SQL Query
Milestone 3Data analysis Milestone
4Findings from dataMilestone
5SlackBotMilestone 6Recommendations
June 20 - June 24Task 1
June 27 - July 1Task 2
July 4 - July 8 Task 3
July 11 - July 15Task 4
July 18 - July 22Task 5
July 25 - July 29Task 6
Week 2 Week 3 Week 4 Week 5 Week 6
1. Understand data 2. Analyze data 3. Visualize data
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Insights
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© 2016 priceline.com
Data Analysis Methodology
To better understand customer search behavior, we mapped searches to bookings...
How did we map a search to a booking?
1. Site Server ID (Cookie) matched2. Travel Dates +/- 2 Days of check-in and check-out dates3. Area ID/City ID Matched
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Data Analysis Trends
80% of customers search for hotels multiple times before booking.
Customers search more than once, perhaps looking for a better price or considering travel alternatives.
Number of Hotel Searches
Perc
ent o
f Tot
al H
otel
Sea
rche
s
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25% of customers return to search for hotels on multiple days.
Customers could be considering alternate plans, or looking for better deals during this time.
Perc
ent o
f Tot
al H
otel
Sea
rche
sNumber of Search Days
Data Analysis Trends
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35%+ of customers search multiple cities before booking.
These customers might be more flexible in their travel plans.
Perc
ent o
f Tot
al H
otel
Sea
rche
s
Number of Cities
Data Analysis Trends
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© 2016 priceline.com
Insights Summary
• Many customers search for hotels:– Multiple times– In multiple cities– From multiple properties
• Data allows us to…– See which destinations have the most flexible travelers
– See what other destinations customers have considered
– And the same for specific hotels
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Ideas
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© 2016 priceline.com
Tableau Demo
https://nw-tabprq-201.corp.pcln.com/#/site/finance/workbooks/1576/views
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Makes and Confirms Bookings
Traditional Travel Agency Online Travel Agency
OTA?
Assists in Searching
Shares Advice and Knowledge
Booking Engine
Search Engine
Recommendation Engine
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Execution/Recommendation
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© 2016 priceline.com
Slackbot Live Demo
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© 2016 priceline.com
Potential Customer Facing Applications of Bots
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Destination Recommendation
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Hotel Recommendation
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Technical Details
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Recommendation Engine API
Hotel Listings Search Request
www.priceline.com/stay/#/search/hotels/
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Impact
★ Multisource Value Creation
★ Valuable Destination and Property Insights for MDMs
★ Unique Site Feature with Potential to Drive Direct Traffic
★ Value Add can Increase Repeat Propensity
5.5% ? Average New Customer 12 Month Repeat Propensity
★ Increase Conversion by Offering Relevant and Compelling Recommendations
★ Increase Customer Engagement via Interactive features
1.4% ? Average Hotel Retail Conversion
Next StepA/B TestingUsing Existing Engine
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Q&A
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