We have seen a lot of rankings in our lifes, not only in WebApps but also in different devices, usually as part of a gamification implementation. But is it being really effective? In fact, the majority of rankings implementations are wrong, and can even make your application less attractive. You may never get on the top of the ranking and never find a real challenge against other users, and those are just some of the major problems. Different algorithms are applied and developed to make ranking attractive, some of those by big companies as Sony, Microsoft, Nintendo and others, and we are able to use them in our development process too. That said, how should we proceed? How can we use Rankings effectively to help us to build better and engaging applications? Simple, watch this talk!

1. Rankings:
you’re doing it wrong.

2. João Moura
github.com/joaomdmoura
twitter.com/joaomdmoura
speakerdeck.com/joaomdmoura

4. largest city in Brazil
southern hemisphere

7. RubySource

10. Why?
where and how?

11. #Everything is
Software

12. Young Entrepreneurs
are developing
new applications
for
young audiences

13. Gartner Research:
Over 70% of Global 2000
Organisations Will Have at Least
One Gamified Application
by 2014
(source: Christy Pettey, Gartner press release, http://www.gartner.com/newsroom/id/1844115)

14. Gartner Research:
By 2014, 80% of Current Gamified
Applications will fail to Meet
Business Objectives Primarily Due
to Poor Design
(source: Christy Pettey, Gartner press release, http://www.gartner.com/newsroom/id/2251015)

15. Objective
order and distinguish

16. Factor
how skilled relevant

17. Ranking
Behavior
Relevancy

18. Ranking
Behavior
Relevancy

19. Problem
! wrong relavancy!

20. “I want to be the
best user ever!”

21. 1
2 3
1000
2000
1500

22. 1
2 3
1000
2000
1500

23. 1
2 3
1000
2000
1500
10

24. 1
2 3
4
1000
2000
1500
10

25. 1
2 3
4
1000
2000
1500
10

26. 1
2 3
4
1000
2000
1500
10

27. Consequence
objective X reality

28. Humans
Want to prove themselves

29. Skill
!= history

30. Rankings
isn’t child's play

31. Possible
algorithms

32. Algorithm is an finite
sequence of well defined
instructions, that can be
executed mechanically in
an finit amount of time with
an finit effort.

33. Elo
rating

34. Rating
game

35. Rating
game
Ra = Rb

36. precision
Nø
matches

37. Microsoft
yeah, Microsoft

38. Microsoft
yeah, Microsoft

39. +

40. TRuESKILL

41. True Skill
Elo rating on steroids

42. rating {
SKILL distrust

43. distrust
USER game
SKILL

44. 2000
1500
100
500

45. 2000
1150000
500

46. distrust SKILL

47. distrust SKILL

48. distrust SKILL

49. x
challenge
SKILL distrust

50. WIN LOST
difficulty

51. Microsoft
Yes, it’s patented

52. Sigma
Ruby, Ruby, Ruby ♪

53. Considerate
Skill
Distrust
Expectation
Assertiveness

54. 100.times {
user_1.won (user_1.rating - user_2.rating)
user_2.lost (user_2.rating - user_1.rating)
user_2.won (user_2.rating - user_3.rating)
user_3.lost (user_3.rating - user_2.rating)
user_3.won (user_3.rating - user_4.rating)
user_4.lost (user_4.rating - user_3.rating)
}

55. 2.times {
user_5.won (user_5.rating - user_2.rating)
user_2.lost (user_2.rating - user_5.rating)
}
2.times {
user_5.won (user_5.rating - user_1.rating)
user_1.lost (user_1.rating - user_5.rating)
}
expect(User.ranking.first).to eq user_5

57. Easy
x.rating
x.position
x.matches
x.won(difficulty)
x.lost(difficulty)

58. CodePong
Devs also practice sports

59. Conclusion

60. Conclusion
1. Everybody wanna play

61. Conclusion
1. Everybody wanna play
2. Productivity gets low

62. It happens to
Developers and it
will happens the same
to your Users.

63. Review
Possibilities
Relevancy
Algorithms
Sigma
Ping Pong is cool!

65. Thank you! @joaomdmoura