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Ikyu’s Marketing: Over One Billion Yen in Monthly Transactions

Ikyu’s Marketing: Over One Billion Yen in Monthly Transactions

Masaru Kanno (Ikyu / Data Science Department / Data Platform Engineer)

https://tech-verse.me/ja/sessions/218
https://tech-verse.me/en/sessions/218
https://tech-verse.me/ko/sessions/218

Tech-Verse2022
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November 17, 2022
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Transcript

  1. Ikyu’s Marketing: Over One Billion Yen in Monthly Transactions Masaru

    Kanno / Ikyu
  2. None
  3. Agenda - About Ikyu - Understanding Users’ Behavior - Cases

    - Building Data Infrastructure for High-demand Data Load - Communication with Users - Future Direction - Summary
  4. Have you experienced online reservation? Check-in Site Visit Cancel Withdraw

    Reserve Reservation Site
  5. Do you understand users’ behavior?

  6. Do executives exactly understand users’ behavior?

  7. About Ikyu

  8. About Ikyu OTA (Online Travel Agent) Number of members: 16.8

    million
  9. About Ikyu Corporate Culture ・Ideas and discussions are always based

    on user-first - User-first ・Promote data democratization so that all employees can execute SQL for data analysis infrastructure ・CEO, by himself, create weekly report based on data analysis infrastructure ・Other executives extract and utilize data by themselves for business promotion - Data-driven
  10. Understanding Users’ Behavior

  11. Understanding Users’ Behavior Implementation background - Non-face-to-face business due to

    the Internet-based corporation - Users’ behavior can be recognized only through data - Access data required - Implemented Google Analytics - Challenges after implementation
  12. Understanding Users’ Behavior Challenges ・Data as of yesterday, due to

    daily data linkage - Real-time nature ・About 10% of reservation behavior data is lost - Data loss ・Huge delay in data linkage - Stability for linkage time Lower degree of freshness Lower degree of precision Lower stability
  13. Understanding Users’ Behavior Building real-time logging infrastructure

  14. Understanding Users’ Behavior After implementation ・ Enabled behavior logging analysis

    within one second - Real-time nature ・Enabled acquiring 100% of reservation behavior data - Data loss ・No latency for real-time linkage - Stability for linkage time Higher degree of freshness Higher degree of precision Improved stability
  15. Understanding Users’ Behavior Difficulties ・Time required until fully recognized by

    the product side - Cultural aspect ・Huge impact by data loss and latency, as the data is so important ・Early detection of alerts from Datadog by Slack as the metrics monitoring - Enhanced monitoring ・Very little allowance for latency, due to perpetuation against RDB and maintaining real-time policy at the same time - Technical aspect
  16. Cases

  17. Cases Real-time coupon

  18. Cases Difficulties ・Real-time policy requires securing resources at all time

    ・Resolved with SQL Server Resource Governor - Difficult to maintain stability ・One of the functions of SQL Server Enterprise Edition ・Enables control over CPU, memory, physical I/O against specific log-in information - Resource Governor ・Daily monitoring and tuning as needed ・Automatic tuning is the next challenge - Cost performance of coupons
  19. Cases Recommendation Recommendation for users who visits Camel Hotel Resort

    pages
  20. Cases Top page of personalization Best selling accommodations within two

    hours from Tokyo Best selling accommodations with hot springs in Hakone, Atami, and Izu
  21. Building Data Infrastructure for High-demand Data Load

  22. Building Data Infrastructure for High-Demand Data Load Background ・Showing the

    same result at the morning and in the afternoon ・Want to change from daily execution to hourly execution - To improve freshness of recommendation and personalization ・Takes four hours, even with parallel processing, from creation to deployment on production ・Needs new infrastructure - Computer resource issues
  23. Building Data Infrastructure for High-Demand Data Load Existing data infrastructure

  24. Building Data Infrastructure for High-Demand Data Load Relations among data

    Infrastructure for high-demand data load
  25. Building Data Infrastructure for High-Demand Data Load Challenges of S3

    synchronization ・Cannot scale parallel processing due to resource restriction on input side ・Serial processing causes huge delay - Want to daily synchronize with S3 without significant delay
  26. Building Data Infrastructure for High-Demand Data Load Resolution ・Enable multiple

    output for single input ・Within ten minutes delay after implementation - Implement embulk-output-multi plug-in
  27. Building Data Infrastructure for High-Demand Data Load Difficulties - Not

    much information about the world - Need to adjust page_size setting of embulk execution argument
  28. Building Data Infrastructure for High-Demand Data Load Athena - CREATE

    TABLE AS SELECT (CTAS)
  29. Building Data Infrastructure for High-Demand Data Load Data infrastructure for

    high-demand data load
  30. Building Data Infrastructure for High-Demand Data Load Difficulties ・Limitation of

    3,500 PUT/COPY/POST/DELETE requests per second and 5,500 GET/HEAD requests per second - Amazon S3 503 Slow Down error ・Verification results showed potential limitation by the Bucket ・Avoid for a process to reach its upper limit by executing with its dedicated Bucket * Not mentioned in the reference - Verification results ・Recommend to retry and execute some time later - Official position ・ Resolved by Lambda execution with USING EXTERNAL FUNCTION - Want to use a use-defined function on Athena
  31. Building Data Infrastructure for High-Demand Data Load After countermeasure ・Provide

    more fresh data in the morning and the afternoon ・Shift from Daily execution to Hourly execution (Processing time: 10 minutes) - Resulted in higher freshness for recommendation and personalization ・Five to ten percent improvement on above-mentioned business achievement - Achievements
  32. About Communication With Users

  33. Have you ever experienced this? Useful information Useful information Useful

    information 2022/11/01 2022/11/02 2022/11/03 ・ ・ ・
  34. About Communication With Users Communication method ・Mail ・Pop-up ・Browser notification

    ・LINE delivery - Channel ・Issues after implementation - Implementing external services
  35. About Communication With Users Challenges ・Deliver mails of the same

    contents only ・Deliver only through engineers - Democratization of 1 to 1 CRM ・Requires development for each channel ・Requires development for each extension - Multi-channel enablement ・Requires data linkage with CSVs which include personal information - Security risks Lower quality of information Lower productivity Lower scalability Lower security
  36. About Communication With Users Marketing application Search by campaign name

    Status Channel Services Valid Draft Invalid Expired Mail Pop-up Browser notification LINE delivery Upgrading Not set Common Accommodation Yahoo! Travel Restaurants Spa Vic Delivery channel Services Status Campaign Timing Priority Execute on Valid from Valid to Number of delivery Updated on Updated by Common Common Common Valid Draft Draft Search by campaign name Status Channel Services Valid Draft Invalid Expired Mail Pop-up Browser notification LINE delivery Upgrading Not set Common Accommodation Yahoo! Travel Restaurants Spa Vic Delivery channel Services Status Campaign Timing Priority Execute on Valid from Valid to Number of delivery Updated on Updated by Common Common Common Valid Draft Draft
  37. About Communication With Users After countermeasure ・Add useful information for

    users ・Anyone can deliver - Democratization of 1 to 1 CRM ・Easy to scale - Multi-channel enablement ・Internal development leads no external leak - Security risks Higher quality of information Higher productivity Higher scalability Higher security
  38. About Communication With Users After countermeasure - More than fifty

    percent of open rate for mails from Ikyu (Generally between fifteen to twenty-five percent) - Reason for high open rate is not-sending unnecessary mails - Notify useful information for receiving users
  39. Future Direction

  40. Future Direction - Improvement of accommodation search experiences - Reservation

    without searches - Provide administration pages for promotion by service providers
  41. Summary

  42. Summary - User-first commitment - Results come along - Flexible

    and agile response enabled by not relying on external services - Resolving issues with data-driven approach and quickly delivering values to users are sources of the growth of Ikyu
  43. Want to completely understand users’ behavior?

  44. Thank you