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Conversion rate optimization using big data and data science
The document discusses conversion rate optimization using big data and data science. It describes 3 opportunities for optimization: 1) user path analysis to understand customer journeys, 2) A/B testing using big data to experiment with variations, and 3) applying data science techniques. The solution framework involves collecting data from the web server, logs, tags and storing it in a big data framework. Real-time, customized recommendations can then be generated based on properties, users, sessions, clicks and login identity.
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Similar to Conversion rate optimization using big data and data science
Conversion rate optimization using big data and data science
- 1. CONVERSION RATE OPTIMIZATION USING BIGDATA AND DATA SCIENCE David Stephenson, Ph.D. david@dsiAnalytics.com Hilversum, The Netherlands
- 2. David Stephenson, Ph.D. FounderDSI Analytics Professor: Applied Analytics Head of Global Business Analytics Department Head A.I. Analytics Consulting & Program Development Department Foundation
- 3.
- 4. Introduction Opportunities to OptimizeConversion Rates 1. User Path Analysis 2. A/B Testing with Big Data 3. Data Science The Solution Framework Conclusion and Questions Agenda CONVERSION RATE OPTIMIZATION BIG DATA AND DATA SCIENCE
- 5. Just Conversion Data Whenyou care enough to do absolutely nothing Marketing Campaigns Online Searches Returning Customers Conversion ?? Landing Page
- 6. Web Analytics Data ”Icare a little bit more” Landing Page Item ViewsMicro Conversions Conversion
- 7. Full Session Level(Big) Data ”I really want to understand my customer” 10 sec 45 sec 90 sec 200 sec … . Marketing Campaign Conversion
- 8. Introduction Opportunities to OptimizeConversion Rates 1. User Path Analysis 2. A/B Testing with Big Data 3. Data Science The Solution Framework Conclusion and Questions Agenda CONVERSION RATE OPTIMIZATION BIG DATA AND DATA SCIENCE
- 9. A/B Testing Insight ThroughExperimentation
- 10. Responding Intelligently The CROChallenge
- 11. Introduction Opportunities to OptimizeConversion Rates 1. User Path Analysis 2. A/B Testing with Big Data 3. Data Science The Solution Framework Conclusion and Questions Agenda CONVERSION RATE OPTIMIZATION BIG DATA AND DATA SCIENCE
- 12. Quantifying Appeal ofInventory Click Through Rates 200x
- 13. Quantifying Sell-ability ofInventory Conversion Rates 36x
- 14. Maximizing Expected Revenue QuantifyingContent Value Search Result Click Thru Rate Item View Book Rate Booking Value Expected Value Search Result Item 11% 0.80% 650 € 0.57 € 8% 0.43% 700 € 0.24 € 9% 1.02% 900 € 0.83 € Note: numbers above are for illustration only
- 15. Introduction Opportunities to OptimizeConversion Rates 1. User Path Analysis 2. A/B Testing with Big Data 3. Data Science The Solution Framework Conclusion and Questions Agenda CONVERSION RATE OPTIMIZATION BIG DATA AND DATA SCIENCE
- 16. Data Architecture The SolutionFramework Browser Web Server Web Logs JS Tags Big Data Framework Message Queue Web Analytics Data Architecture The Solution Framework
- 17. Two Week Deployment TheSolution Framework Browser Web Server Web Logs GA Tags Big Query Message Queue GA Server
- 18. Properties Users Sessions Clicks Login Identity Real-Time,Customized Recommendations
- 19. Introduction Opportunities to OptimizeConversion Rates 1. User Path Analysis 2. A/B Testing with Big Data 3. Data Science The Solution Framework Conclusion and Questions Agenda CONVERSION RATE OPTIMIZATION BIG DATA AND DATA SCIENCE
- 20.