PAPIs: Connect 2015 talk about using machine learning with ecommerce to generate revenue and improve the user experience.

1. MachineLearning
&
Ecommerce
byDavidJones-TechnicalDirector-ResolveDigital

3. Machinelearning&Ecommerce
better.together.

6. PredictiveAPIs
makeitfeellikeyouhaveyourown
teamofMLexperts

7. Personalised
recommendations

8. Abandonedcartemails

9. Customisedcontent

10. Leadscoring

11. Emailmarketing

13. BenefitsofMLinEcommerce
Morevisitorswithlongersessionduration
Improvedretention
Higherconversionrates
Largerordersize
Bottomline,morerevenue.

14. machinelearninginecommerce
deeplyenhancescustomerexperiences

15. CustomersexpectMLfeatures
Eveniftheydon’tknowwhatMLis

17. Realworldexample:
UnitedCellars

18. Goal:Increaserevenue
Solution:Productrecommendations
Implementation:PredictiveAPIs

19. 16kproductviews
60korders
3kproductratings

20. 79000rowsSmalldata

21. Anydatathatlinks
customerstoproducts

22. Optimisedatacollection
Initiallyhadnodataforloggedoutusers

23. PredictionIO
Opensourcemachinelearningserver
Ecommercetemplates
Usesestablishedimplementationofalgorithms
Evaluationmetrics
Productionready

24. Storefront<->ProcessingQueue<->PredictionIO

25. PAPIProductionTips
Monitorperformance
Cachewhererealtimeisnotneeded
Deriveddataislowrisk

26. Bricks&mortarretail
inspiresanecommerceexperiencewithML

27. Withwine
tastepreferencesarediverse
peopleusuallypreferredorwhite

28. A/BTESTwithGoogleAnalytics

30. FilterPredictionsAvoidanythingthatlessensrelevance
Don’tshowoutofstockproducts

31. A/BTestResults
45%longeraveragesession
22%increaseinconversionrate
37%increaseinaverageordersize

32. 71%MoreRevenue

33. Wheretonext?
Predictivefeaturesinmorechannels
Introducenewpredictivefeatures

34. Conclusion

35. 1
Smalldatacanbeenough
Qualityiskey

36. 2
PredictiveAPIs
areawesome

37. 3
MachineLearning
ishighlyeffectivewith
Ecommerce

38. BusinessLeaders
Startaproject
UsePredictiveAPIs
Thetimingisperfect

39. resolve.digital/papis
DavidJones,@d_jones