Business likes numbers, so UX professionals are eager to translate user experience into data. This is done in order to find common ground with business, but also in order to measure the effectiveness of their work. However, shallow interpretation of data can lead to false conclusions and wrong design decisions.

1. WHEN
NUMBERS
ARETRICKY
Anna Jozanis
Designer’s point of view on data

3. DATA-DRIVEN

4. DATA-DRIVEN
EVERYTHING

5. TOO MUCHTRUST

6. Test name: Result: Reference range: Unit:
9,50 <7,8 mmol/lBlood glucose
(1 hour after glucose load)

7. DATA IS
NOT ENOUGH

8. ?QUESTIONS

9. The designers most
important tool is
the question.
ERIKA HALL

10. .
TRUST

11. Add to cart
Summary
Delivery form
Go to checkout
Purchase
DESKTOP MOBILE WEB
disclaimer:All data in the presentation is fake and used only to demonstrate the topic.

12. Add to cart
Summary
Delivery form
Go to checkout
Purchase
disclaimer:All data in the presentation is fake and used only to demonstrate the topic.

13. Add
to
cart
Summary
Delivery form
Go
to
checkout
Purchase
Log in

14. Add to cart
to buy now
for later
to buy in
a different channel

15. Add to cart Log in
to buy now
for later
to buy in
a different channel
saving password
resetting password
guest checkout

16. DATA
lower mobile conversion rates
RESEARCH
switching channels
forgetting passwords
mobile laziness

17. You can’t interpret
data correctly without
understanding
the story behind it.

18. A B

19. Home
Purchase Confirmation
Offer Page
Listing
Delivery Form
Purchase
A B
disclaimer:All data in the presentation is fake and used only to demonstrate the topic.

20. disclaimer:All data in the presentation is fake and used only to demonstrate the topic.
Home
Purchase Confirmation
Offer Page
Listing
Delivery Form
Purchase

21. NEW OFFER PAGE
1
2
10
9
3 5
4 6
7
8
DELIVERY
COST

22. OLD OFFER PAGE
1
2
9
3 5
4 6
7
8
10
DELIVERY COST

23. PURCHASE CONFIRMATION
1
2
9
3
4
7
10
DELIVERY COST

24. Offer page performs better
RESEARCH
People can’t find all details
on offer page
People abandon checkout
DATA

25. Don’t stop exploring
what’s beneath the data
even if it looks like
you did a good job.

26. Good designers want
to be proved wrong,
bad designers hope
to be proved right.
ANDY BUDD

27. NET PROMOTER SCORE
0 1 2 3 4 5 6 7 8 9 10
DETRACTORS PASSIVES PROMOTERS
% - % =NET PROMOTER SCORE

28. NetPromoterScore
Users of
Payment
Method #1
Users of
Payment
Method #2
Users of
Payment
Method #3
Users of
Payment
Method #4
disclaimer:All data in the presentation is fake and used only to demonstrate the topic.

29. CSAT
Search
Comparing Offers
Offer Selection
Checkout and Payment
How would you rate the recent product experience?

30. Search
Average Payment Method #4 users
Comparing
Offers
Offer
Selection
Checkout and
Payment
disclaimer:All data in the presentation is fake and used only to demonstrate the topic.

31. All users
Payment Method #4 users
Average age People under 30
disclaimer:All data in the presentation is fake and used only to demonstrate the topic.

32. NetPromoterScore
Users
over 30
Users
under 30
Users of Payment
Method #4
disclaimer:All data in the presentation is fake and used only to demonstrate the topic.

33. CORRELATION
≠
CAUSATION

34. Never consider
data alone to avoid
spurious correlation.

35. The best designers
never stop at
the first inference.
JARED SPOOL

36. DNADATA

37. MORE AND MORE
DATA

38. DISTRACTION

39. GOOD METRICS

40. SIMPLE

41. COMPARABLE
SIMPLE

42. ACTIONABLE
COMPARABLE
SIMPLE

43. VANITY

44. JOURNEY

45. DATA-DRIVEN

46. INSIGHT-DRIVEN

47. INSIGHT-DRIVEN
anna.jozanis@allegro.pl
linkedin.com/in/jozanka
START BEING