Kaizen Platform Optimization System Architecture
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The optimization system architecture of Kaizen Platform. I explain the basic optimization system and the issue, then explain our newly introduced "Kaizen Optimization Platform".
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Kaizen Platform Optimization System Architecture
- 1. 1 Optimization System Architecture 2015/07/28 BPStudy#95 Kaizen Platform, Inc. @dtaniwaki
- 2. 2 About dtaniwaki 2008 - 2011 : Trend Micro (in Taiwan) 2011 - 2014 : Tabelog, Inc. (in New York) 2014 - : Kaizen Platform, Inc. (in Tokyo) Computer Language : Ruby on Rails, Node JS, C, C++ and etc. Human Language : English, Chinese, Spanish (un poco) Interest : Scuba Diving, Rugby, Yoga Github : https://github.com/dtaniwaki
- 3. 3 What is Kaizen Platform? ROI Optimization PlatformA/B Testing Tool
- 5. 5 VariationsOriginal Web Optimization Distribution Ratio Original Variation A Variation B Variation C Variation D A B C D The best variation!
- 6. 6 Web Optimization Steps ✓ Generate JavaScript with the test condition ✓ Attach it on the customer’s page ✓ Collect visit logs by the pixel ✓ Collect conversion logs by the pixel ✓ Calculate the distribution ratio ✓ Update the JavaScript with the ratio
- 7. 7 Customer B Customer A LP / CV Web Optimization Architecture JavaScript Template LP / CV Creatives Creatives Log App Log Storage App Test Condition Distribution Ratio Test Condition Distribution Ratio Visit / Conversion Log Generate Generate 1st Party 1st Party
- 8. 8 Creatives AD Optimization The best creatives!
- 9. 9 AD Optimization Steps ✓ Generate JavaScript ✓ Submit it as 3PAS ✓ Collect impression logs by the pixel ✓ Collect click logs through the redirector ✓ Collect conversion logs by the pixel ✓ Calculate the distribution ratio ✓ Stop low performance creatives
- 10. 10 AD Optimization Architecture JavaScript Template Media (3PAS)Creatives Log App Log Storage App Distribution Ratio Impression / Conversion Log LP Redirector CV Click Log 3rd Party 3rd Party Generate Generate
- 11. 11 AD x Web Optimization AD Optimization Web Optimization Maximize the inbound Optimize with clicked banners
- 12. 12 AD x Web Optimization Steps ✓ Memorize the clicked banner ID through the redirector ✓ Get the clicked banner ID by XHR ✓ Collect logs with clicked banner ID ✓ Get the result of clicked banner by the ID
- 13. 13 Web x AD Optimization Architecture Media (3PAS) LP Redirector CV Cookie Sync APIGet clicked Banner ID AD Apps Web Apps Visit / Conversion Log w/ Banner ID Get results by Banner ID 1st Party 1st Party 3rd Party Impression / Click Log 3rd Party Generate Generate Generate
- 15. 15 Legacy Optimization A Creatives Audiences B C D CVR 30% CVR 15% CVR 20% CVR 5% Distribute based on CVR
- 16. 16 Legacy Optimization Issue ✓ The distribution ratio is calculated by overall CVR ✓ Each audience has different feeling on creatives
- 17. 17 Per-Segment Optimization Male 30sFemale 30s Male 40sFemale 40s A Creatives Audiences Gender Age Gender Age B C D Female 30s Male 30s Male 40sFemale 40s Distribute Creatives based on segments
- 18. 18 Per-Segment Optimization Steps ✓ Collect logs with audience segments ✓ Calculate the distribution ratio per segment ✓ Choose creative based on the distribution ratio of their segments
- 19. 19 Per-Segment Optimization Architecture Log App Log Storage App Creatives Distribution Ratio for Segment A Distribution Ratio for Segment B Distribution Ratio for Segment C Distribution Ratio for Segment D Log with Segment LP Generate Calculate per segment
- 20. 20 Per-Segment Optimization Issue ✓ Hard to choose from segment combinations ○ Ideal case e.g. “Male 30s”, “Female 30s”, “Male 40s” and “Female 40s” ○ Difficult case e.g. “Male”, “Female”, “30s”, “40s” “Male” x “30s”, “Male” x “40s”, “Female” x “30s”, “Female” x “40s”
- 21. 21 Kaizen Optimization Platform (a.k.a. CVR Predictor)
- 22. 22 Kaizen Optimization Platform Female x 30s Male x 50s Female x 40s A B A: 70% B: 30% Male x 40s B Female x 50s A … Big Data Machine Learning
- 23. 23 Kaizen Optimization Platform Steps ✓ Set up a scheduled batch task ✓ Upload the content into the storage ✓ Collect logs with audience segments ✓ Calculate the coefficients of estimated CVR based on the audience segments ✓ Choose the best creative based on the audience segments on the fly
- 24. 24 Kaizen Optimization Platform Architecture Audience Kaizen Optimization Platform Log Server App ServerKaizen KVS Kaizen Predictor Log Storage Kaizen Test API Web Optimization Platform Prediction Batch AD Optimization Platform Bandit Algorithm Machine Learning AD Log App Round API Variation API CVR Prediction UUID Segments Round Variation CV ABCX Male, 30s R1 V1 1 ABCY Female, 20s R1 V2 0 ... R1 Coefficients V1: { a: 0.8, b1: 0.3, b2: 0.6 } V2: { a: 0.3, b1: 0.1, b2: 0.4 } R1 Batch Options for R1 Send log w/ segments Dispatc h Web Log App V1 V2 V1 AD JS Web JS
- 25. 25 Per-Audience Optimization Device Access Time Access DoW DMP Clicked Banner Language CRM Female 40s Clicked Banner A Friday Japanese Tokyo Gender Age Place
- 26. 26 Thank You!