There’s a lot of noise about big data and cutting edge algorithms optimisations. Returning to the basics, this presentation shows you might not need as much data as you think to get real world benefits. Learn about machine learning in ecommerce, PredictionIO and how we used off the shelf, well implemented algorithms to get a 71% increase in revenue with an online wine retailer.

1. BigWinswithSmallData:
PredictionIOinEcommerce
byDavidJones(@d_jones)-TechnicalDirector-ResolveDigital

2. Comic by @d_jones. Inspired by xkcd.

4. Machinelearning&Ecommerce
better.together.

7. PredictiveAPIs
makeitfeellikeyouhaveyourown
teamofMLexperts

8. Personalised
recommendations

9. Abandonedcartemails

10. Leadscoring

11. Emailmarketing

13. BenefitsofMLinEcommerce
Morevisitorswithlongersessionduration
Improvedretention
Higherconversionrates
Largerordersize
Bottomline,morerevenue.

14. machinelearninginecommerce
deeplyenhancescustomerexperiences

15. CustomersexpectMLfeatures
Eveniftheydon’tknowwhatMLis

16. Realworldexample:
UnitedCellars

17. Goal:Increaserevenue
Solution:Productrecommendations
Implementation:PredictiveAPIs

18. 16kproductviews
60korders
3kproductratings

19. 79000rowsSmalldata

20. Anydatathatlinks
customerstoproducts

21. Optimisedatacollection
Initiallyhadnodataforloggedoutusers

22. PredictionIO
Opensourcemachinelearningserver
Ecommercetemplates
Evaluationmetrics
Productionready

23. WhyPredictionIO?
ActiveOpenSourceproject
Productivityfocused
Built-insupportforApacheSparkMLlib
OpinionatedDASEarchitecture:
DataSourceandPreparator,Algorithm,Serving,Evaluator

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. resolve.digital/papis2015
DavidJones,@d_jones