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Big Data & Analytics Innovation Summit
Nikolay Novozhilov, Wego.com
Following the user – discovering
the value of big data
About Wego
Wego compares hotel and airfares from
hundreds of leading travel sites from all
around the world on one simple screen
Wego was founded in 2005 in Singapore
Everybody is building
infrastructure for Big Data
… but where is the value?
“This is my Big Data!
How big is yours?”
Common path: “Start with a problem!”
The Problem
“Our ability to collect, store and
process data is growing faster than
our ability to ask good questions”
Can we do any proactive analytics?
User path seems like a good idea!
… but is it?
1. Landing page 2. Search results 3. Handoff
Look for the most common
paths… combinatorics kills you!
All revenue-generating
users have unique paths
Popular and bad solution - reduce details
Bounced user
Different approach: Look at
individual user story
User path
(way of analytics)
User story
(way of agile)
How does it work in practice?
Relational
tables with
events
Denormalized
sparse table
Natural language
generation
Human-readable
story
Final “user story”
• Visitor from SA with tablet came in
using organic search (google.com).
• Did a flight search from Jeddah to
Paris from 2015-02-06 to 2015-02-23
for 1 adult
• Did a flight search from Jeddah to
Dubai from 2015-02-06 to 2015-02-23
for 1 adult
• Did a flight search from Dubai to Paris
from 2015-02-06 to 2015-02-23 for 1
adult
• Clicked on airtickets.com for 1378 USD
How does it work? Lessons learned
You can include as many details as possible
User story allows to guess user’s motivation (can’t
be simulated!)
Most users will walk away silently but some - will
keep trying repeatedly and will show you the
problem
But do stats later! Don’t rely on user stories for
actions
Just random users will be a little boring. Look at
active users/revenue generating/returning users.
What I saw in my data?
Travel planning cycle and it’s length
Specific patterns like “leg” searches
Specific patterns for different
countries/languages
Bugs in Data and in Product
Technical details for geeks
Storage for events - Google BigQuery
Generating natural language – SQL query
Visualization – Google Spreadsheets
This is just one tool in the tool box but
often overlooked
Contacts
Blog: www.novozhilov.co
Email: nik@wego.com

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Following the User – Discovering the Value of Big Data

  • 1. Big Data & Analytics Innovation Summit Nikolay Novozhilov, Wego.com Following the user – discovering the value of big data
  • 2. About Wego Wego compares hotel and airfares from hundreds of leading travel sites from all around the world on one simple screen Wego was founded in 2005 in Singapore
  • 3. Everybody is building infrastructure for Big Data … but where is the value? “This is my Big Data! How big is yours?”
  • 4. Common path: “Start with a problem!”
  • 5. The Problem “Our ability to collect, store and process data is growing faster than our ability to ask good questions”
  • 6. Can we do any proactive analytics?
  • 7. User path seems like a good idea! … but is it? 1. Landing page 2. Search results 3. Handoff
  • 8. Look for the most common paths… combinatorics kills you! All revenue-generating users have unique paths Popular and bad solution - reduce details Bounced user
  • 9. Different approach: Look at individual user story User path (way of analytics) User story (way of agile)
  • 10. How does it work in practice? Relational tables with events Denormalized sparse table Natural language generation Human-readable story
  • 11. Final “user story” • Visitor from SA with tablet came in using organic search (google.com). • Did a flight search from Jeddah to Paris from 2015-02-06 to 2015-02-23 for 1 adult • Did a flight search from Jeddah to Dubai from 2015-02-06 to 2015-02-23 for 1 adult • Did a flight search from Dubai to Paris from 2015-02-06 to 2015-02-23 for 1 adult • Clicked on airtickets.com for 1378 USD
  • 12. How does it work? Lessons learned You can include as many details as possible User story allows to guess user’s motivation (can’t be simulated!) Most users will walk away silently but some - will keep trying repeatedly and will show you the problem But do stats later! Don’t rely on user stories for actions Just random users will be a little boring. Look at active users/revenue generating/returning users.
  • 13. What I saw in my data? Travel planning cycle and it’s length Specific patterns like “leg” searches Specific patterns for different countries/languages Bugs in Data and in Product
  • 14. Technical details for geeks Storage for events - Google BigQuery Generating natural language – SQL query Visualization – Google Spreadsheets
  • 15. This is just one tool in the tool box but often overlooked

Editor's Notes

  1. Analysis is a servant. Data as an actor, as a source of inspiration?
  2. Bugs in Data, Bugs in Product, Gutt feeling of your user