The document discusses the future of data-driven design, emphasizing the importance of integrating various data types—thick, big, and wide data—for personalizing services and enhancing user experiences in sectors like fashion. It highlights the role of big data and machine learning in shaping consumer behavior and stresses the need for transparency and responsible data usage. The content also outlines challenges organizations face in harnessing data effectively and proposes strategies for successful implementation.

1. GOING BEYOND
RECOMMENDATIONS
@hollielubbock

2. WHERE NEXT FOR DATA
DRIVEN DESIGN?

4. DATA IS THE FUEL FOR THE
NEXT GENERATION OF
PERSONALISED SERVICES

5. 1. DESIGN WITH DATA

6. 1. DESIGN WITH DATA
2. DESIGN BY DATA

7. 1. DESIGN WITH DATA
2. DESIGN BY DATA
3. DESIGN FOR DATA
MORE INFO
HTTPS://PROJECTSBYIF.COM/BLOG/DESIGN-FOR-DATA
HTTPS://WWW.SLIDESHARE.NET/FJORDNET/FJORD-EQUINOX-DATA-DESIGN

8. WHY NOW?

9. CHANGING EXPECTATIONS

10. WHAT I WANT, WHEN I
WANT IT, HOW I LIKE IT

11. IWWIWWIWI
MORE INFO
HTTPS://WWW.THEGUARDIAN.COM/FASHI ON/2016/FEB/14/FASHION-
INDUSTRY-IN-FLUX-END-OF-THE-RUNWAY-SHOW

12. FLUID JOURNEYS

13. IOT ALL THE THINGS

14. DIGITAL &
PHYSICAL
CHANNELS
HYPER
PERSONALISED
SERVICES
BIG DATA &
MACHINE
LEARNING
+ =
WE HOPE

15. PERSONALISATION IN
LUXURY FASHION
*Completed whilst at Code and Theory

16. DATA TO INSPIRE SERVICES

17. THICK DATA
BIG DATA WIDE DATA
WHO, WHY & HOW

18. THICK DATA = QUALITATIVE STUDIES
BIG DATA = AN EXTREMELY LARGE DATA SET
WIDE DATA = INDUSTRY TRENDS & PUBLIC DATA SETS
Wide data can also be big data depending on the size of the data set
Big data here refers to your product, marketing and customer data

19. PERSONAL SHOPPER
INTERVIEWS
STAKEHOLDER
INTERVIEWS
USER
INTERVIEWS
THICK DATA
(QUALITATIVE STUDIES)

20. THICK DATA
(QUALITATIVE STUDIES)
VOC SURVEY SHOPPING
PATTERNS
PERSONAL SHOPPER
INTERVIEWS
STAKEHOLDER
INTERVIEWS
USER
INTERVIEWS
BIG DATA
(DATA YOU HAVE GATHERED)
READING PATTERNS

21. VOC SURVEY SHOPPING
PATTERNS
PERSONAL SHOPPER
INTERVIEWS
INDUSTRY TRENDS SOCIAL HABITSCOMPETITOR
ANALYSIS
STAKEHOLDER
INTERVIEWS
SEARCH TRENDS
USER
INTERVIEWS
WIDE DATA
(INDUSTRY TRENDS, COMPETITOR ANALYSIS DIRECT
INDIRECT AND PERCEPTUAL, SEARCH TRENDS AND
SOCIAL MEDIA HABITS)
READING PATTERNS
THICK DATA
(QUALITATIVE STUDIES)
BIG DATA
(DATA YOU HAVE GATHERED)

22. THE INSIGHT
WH O N OW

23. THE INSIGHT
WHO NEXTWH O N OW

24. THE INSIGHT
WHAT TO SAYWHO NEXTWH O N OW

25. THE INSIGHT
HOW TO SAY ITWHAT TO SAYWHO NEXTWH O N OW

26. THE INSIGHT
WHE RE AND WHENHOW TO SAY ITWHAT TO SAYWHO NEXTWH O N OW

27. BEHAVIOURAL MODES
DATA ENHANCED

28. CLOTHES ARE FUNDAMENTAL TO USERS'S SENSE OF
IDENTITY. FASHION BUYING BEHAVIOURS SHIFT
DEPENDING ON THE USERS CONTEXT.

29. CONTENT FRAMEWORK

32. CONTENT THAT SUPPORTS &
INSPIRES FASHION
CONFIDENCE AND DRIVES
COMMERCE

33. PUBLISHING MODEL

34. WHEN TO PUBLISH
Typical Weekday
Typical Weekend
SOCIAL MEDIA
BUYING PEAKS

35. PERSONALISATION AS
UNIQUE AS THEIR
CUSTOMERS
https://econsultancy.com/blog/68219-four-
things-brands-can-learn-about-content-marketing-
from-net-a-porter

36. DATA DRIVEN STRATEGY
FOR PERSONALISATION,
CONTENT CREATION &
DISTRIBUTION

37. WHO IS DOING IT WELL?

38. GOOGLE

39. HAS GONE FROM SIMPLY
ORGANISING THE WORLDS
INFORMATION TO
HARNESSING IT

41. NETFLIX

42. PERSONALISED RANKING, TOP-N
RANKING, TRENDING NOW, CONTINUE
WATCHING, VIDEO - VIDEO SIMILARITY,
PERSONALISED PAGE GENERATION,
SEARCH, PERSONALISED IMAGE
SELECTION

43. DATA DRIVES THE PRODUCT
&
THE CONTENT

44. THE CHALLENGES
WHY HAVEN’T WE ALL
GOT THERE?

45. GETTING THE DATA

46. DON’T UNDERSTAND
HOW PERSONAL
INFORMATION IS USED
92%
DO NOT TRUST
ORGANISATIONS TO USE
DATA RESPONSIBLY
57%
http://www.bbc.co.uk/news/business-37476335

47. OFTEN COMBING MULTIPLE
SOURCES OF DATA GIVE FAR
MORE INSIGHT THAN ONE
SET ALONE

48. UNDERSTANDING THE
DATA

49. “ALL DATA IN AGGREGATE IS CRAP.”
GOOGLE ANALYTICS EVANGELIST AVINASH KAUSHIK

50. MACHINE LEARNING LOVES
FINDING PATTERNS

51. DESIGNING IN THE
INFINITE

52. MACHINES WILL
INCREASINGLY BE
MAKING DECISIONS
WITHIN USER
EXPECTATIONS

53. “HUMAN-CENTERED DESIGN HAS EXPANDED FROM THE DESIGN
OF OBJECTS (INDUSTRIAL DESIGN) TO THE DESIGN OF
EXPERIENCES (ADDING INTERACTION DESIGN, VISUAL DESIGN,
AND THE DESIGN OF SPACES) AND THE NEXT STEP WILL BE THE
DESIGN OF SYSTEM BEHAVIOR: THE DESIGN OF THE
ALGORITHMS THAT DETERMINE THE BEHAVIOR OF AUTOMATED
OR INTELLIGENT SYSTEMS,”
HARRY WEST AT FROG

54. POSSIBLE
CONSEQUENCES

55. WHAT IF?
WHAT IF EVERYONE IN THE WORLD USED
YOUR SERVICE HOW WOULD IT CHANGE
SOCIETY?
WHAT IS THE WORST THING THAT COULD
HAPPEN IF IT GOES WRONG?

56. THE 5 THINGS TO REMEMBER

57. 1. DATA DOESN'T = INSIGHT
2. MATCH THICK DATA WITH BIG DATA & WIDE DATA
3. SET UP A DATA / MEASUREMENT STRATEGY
4. HYPOTHESISE & TEST (RIGHT DATA, RIGHT TIME)
5. BE TRANSPARENT & RESPONSIBLE WITH DATA
5 THINGS TO REMEMBER
@hollielubbock

58. https://www.katepugsley.com/