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Intern Project - Tech
- 1. Intern Project -Final run-through 7/28/2016
- 2. Team Technology AKA ‘NotoriousData’ Desean Front End Developer Zach Finance Gus Product Manager Niket Software Engineer Shamanth Business Analyst
- 3. Monetizing Data by IncreasingConversion through Travel Recommendations
- 4. 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
- 5. Overview ResourcesProject Goal Specification Analyzesearch and booking data to identify user patterns and make monetizable recommendations Air Hotel Rental Car Package Cruise Retail SOPQ OPQ Priceline Group priceline.com Data: June 21 ,2016 - July 21, 2016 Booking records 1.2 Million, Searches records 263 Million Tony Padovano Chief of Staff for CTO Dan O’Connor Principal Insights Analyst Zachary Horne Solutions Architect Tools Mentors
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- 7. 1. Timeline 2. Insights 3.Ideas 4. Execution/Recommendation
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- 9. 2016 Today Week 1 Milestone 1 Planning Milestone2 SQL Query Milestone 3 Data analysis Milestone 4 Findings from data Milestone 5 SlackBot Milestone 6 Recommendations June 20 - June 24Task 1 June 27 - July 1Task 2 July 4 - July 8Task 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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- 11. © 2016 priceline.com DataAnalysis 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) matched 2. Travel Dates +/- 2 Days of check-in and check-out dates 3. Area ID/City ID Matched
- 12. 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 PercentofTotalHotelSearches
- 13. 25% of customersreturn to search for hotels on multiple days. Customers could be considering alternate plans, or looking for better deals during this time. PercentofTotalHotelSearches Number of Search Days Data Analysis Trends
- 14. 35%+ of customerssearch multiple cities before booking. These customers might be more flexible in their travel plans. PercentofTotalHotelSearches Number of Cities Data Analysis Trends
- 15. © 2016 priceline.com InsightsSummary • 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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- 17. © 2016 priceline.com TableauDemo https://nw-tabprq- 201.corp.pcln.com/#/site/finance/workbooks/1576/v iews
- 18. Makes and Confirms Bookings Traditional TravelAgency Online Travel Agency OTA? Assists in Searching Shares Advice and Knowledge Booking Engine Search Engine Recommendation Engine
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- 20. © 2016 priceline.com SlackbotLive Demo
- 21. © 2016 priceline.com PotentialCustomer Facing Applications of Bots
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- 25. Recommendation Engine API HotelListings Search Request www.priceline.com/stay/#/search/hotels/
- 26. Impact ★ Multisource ValueCreation ★ 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 Step A/B Testing Using Existing Engine
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