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Tailor-made personalization and recommendation - Sailendra

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Talk by Régis Lhoste during the RecsysFR meetup on March 23rd 2016.

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Tailor-made personalization and recommendation - Sailendra

  1. 1. Tailor-made personalization and recommendation Sailendra Tailor-made personalization and recommendation Tailor-made personalization and recommendation 23/03/2016 1
  2. 2. Tailor-made personalization and recommendation Sailendra 15 years of research in AI Collaboration: INRIA and LORIA Artificial intelligence Machine Learning Behavioural analysis Recommendations Activity sectorScientific experiences 23/03/2016 2
  3. 3. Tailor-made personalization and recommendation 3 Behavioral analysis and recommendations 23/03/2016
  4. 4. Tailor-made personalization and recommendation Basics of solution 23/03/2016 4 1 • Collect users’ traces from client website: • Navigation • Visited pages (category page, product page …) • Sales, add to basket, … 2 • Convert traces into user-item digital rating
  5. 5. Tailor-made personalization and recommendation Basics of solution 23/03/2016 5 3 • Choose the appropriate algorithm and adjusting it: • User based • Item based • Hybrid algorithms 4 • Add new algorithms that fit to client activity specifications • Marketing filters
  6. 6. Tailor-made personalization and recommendation Costumers cases presentation 623/03/2016
  7. 7. Tailor-made personalization and recommendation E-commerce 23/03/2016 7 e-Business
  8. 8. Tailor-made personalization and recommendation Paraforme 8 Activity area : Online sales of parapharmaceutical products Problem : low users conversion Objective : Realize additional sales 23/03/2016
  9. 9. Tailor-made personalization and recommendation Recommendations on product page 23/03/2016 9 METHOD • Generate recommendations using differents algorithms according to the visited page
  10. 10. Tailor-made personalization and recommendation Recommendations on product page 23/03/2016 10 Proposing alternative options to augment satisfaction - Cascade hybrid recommender  Content based similar item  Item based collaborative filtering  Products usually bought with the current product GOAL METHOD
  11. 11. Tailor-made personalization and recommendation Recommendations on basket pageParaforme 23/03/2016 11 Incite user to complet his basket • Cascade hybrid recommender • Products usually bought with the current product • Popular products within the community of the active user GOAL METHOD
  12. 12. Tailor-made personalization and recommendation Recommendations on basket pageParaforme 23/03/2016 12 RESULT • + 20 % of conversion
  13. 13. Tailor-made personalization and recommendation E-commerce 23/03/2016 13 Business to Business
  14. 14. Tailor-made personalization and recommendation J. Milliet 14 Activity area : drinks distributor for restaurants and bars Problem : low conversion on sales channels Objective : Increase sales 23/03/2016
  15. 15. Tailor-made personalization and recommendation Cross canal recommendations 23/03/2016 15 METHOD • Personalized recommendations in the CRM and on commercials’ tablet • Development of tailor-made filters
  16. 16. Tailor-made personalization and recommendation Cross canal recommendations 23/03/2016 16 • Customers knowlegde • Developement of customers proximity • Sales increase • Propose innovative recommendation despite the presence of many strict rulesRESULTS
  17. 17. Tailor-made personalization and recommendation Banque 23/03/2016 17 Online Bank
  18. 18. Tailor-made personalization and recommendation BforBank 18 Activity area : online bank Problem : No direct relation with customers (100% online) Objective : Simplify and understand users’ navigation paths, and predict their intentions 23/03/2016
  19. 19. Tailor-made personalization and recommendation Sales channels recommendations 19 METHOD • Analysis (clustering) of stream based on behaviors 23/03/2016
  20. 20. Tailor-made personalization and recommendation RESULTS • Optimize user navigation and simplify his path • Predict user intentions and their time • Anticipate costumer attrition and alert the bank • Adapt marketing and communication strategies by community Sales channels recommendations 2023/03/2016
  21. 21. Tailor-made personalization and recommendation23/03/2016 21 Other domains
  22. 22. Tailor-made personalization and recommendation Other domains e-Health: Satelor • Goal : secure sick and old people in their place • Way : A robot and a tablet application to monitoring user daily activities • Sailendra: – Personalizing the tablet interface – Pushing personalized behavioural advices to improve health e-Learning: Périclès • Goal : recommend personalized pedagogic resources for students • Way : an integrated framework within the web-site of the university • Sailendra: – Participation in the conception and parametring recommendation algorithm – Industrialization of algorithms stemming from the project 2223/03/2016
  23. 23. Tailor-made personalization and recommendation Conclusion 23/03/2016 23 Conclusion
  24. 24. Tailor-made personalization and recommendation Personalized and strategical support 24 Tailor-made support in relation with: Sector of activity Structure of the website Webmarketing strategy 23/03/2016
  25. 25. Tailor-made personalization and recommendation Any questions ? 2523/03/2016
  26. 26. Tailor-made personalization and recommendation 26 www.sailendra.fr regis.lhoste@sailendra.fr +33 (0)3 72 47 03 37 @SailendraSAS 23/03/2016

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