The document discusses strategies for increasing user engagement and retention through seductive design. It provides examples of how music application iLike used feedback loops, challenges, and social proof to increase user interaction. It also discusses how delivering unexpected value like games helped motivate continued use. The document advocates designing for human psychology by leveraging curiosity, control, and novelty to remove friction and increase motivation for using a product or service.

1. The Art & Science of
Seductive
INTERACTIONS
STEPHEN P. ANDERSON

3. ?

4. STEPHEN P.
ANDERSON
poetpainter.com
I help businesses with
‘Product Strategy
& Design’ needs

5. STEPHEN P.
ANDERSON
poetpainter.com
I help businesses with
@stephenanderson
‘Product Strategy
& Design’ needs

6. occ asional quick
refere nces to the
>
The Art & Science of
Seductive
INTERACTIONS

13. Q: Why did this work?

14. Q: Why did this work?
levels

15. Q: Why did this work?
levels
challenges

16. Q: Why did this work?
levels
challenges

17. hold that thought...

19. +
great product
does fine in
usability testing
no obvious
problems

20. + -
great product high bounce rate
does fine in low adoption
usability testing
not enough
no obvious registered users
problems
undifferentiated
from the
competition

21. + -
“I’m a great app,
if people would just
get to know me...”
great product high bounce rate
does fine in low adoption
usability testing
not enough
no obvious registered users
problems
undifferentiated
from the
competition

22. Seduction

23. Seduction
the process of deliberately enticing a person
to engage in some sort of behavior,
frequently sexual in nature

24. Seduction
the process of deliberately enticing a person
to engage in some sort of behavior,
frequently sexual in nature

25. “GETTING TO FIRST BASE”

26. “GETTING TO FIRST BASE”

27. HOW DO I ...
GET PEOPLE TO SPEND
MORE THAN 2 MINUTES
WITH OUR SERVICE
“GETTING TO FIRST BASE”

28. HOW DO I ...
GET PEOPLE TO SPEND
MORE THAN 2 MINUTES
WITH OUR SERVICE STAND OUT FROM
THE COMPETITION
“GETTING TO FIRST BASE”

29. HOW DO I ...
INCREASE # OF
GET PEOPLE TO SPEND REGISTERED USERS
MORE THAN 2 MINUTES
WITH OUR SERVICE STAND OUT FROM
THE COMPETITION
“GETTING TO FIRST BASE”

30. HOW DO I ...
INCREASE # OF
GET PEOPLE TO SPEND REGISTERED USERS
MORE THAN 2 MINUTES
WITH OUR SERVICE INCREASE USAGE
STAND OUT FROM
& ADOPTION
THE COMPETITION
“GETTING TO FIRST BASE”

31. 2008
Research for a
MUSIC APPLICATION

32. DO WE HAVE A NY “BETA-JUNKIES ” IN THE ROOM?

33. A Few...
“hey, check this out!”
Lots of...
“meh...”

34. iLike
TM

41. (What I expected)
List your favorite bands, separated by commas:

50. x10

51. USER GOALS
I had a great
time clicking
iLike gained lots of
data about my musical
bands I like tastes & preferences

53. Q: Why did this work?

54. Q: Why did this work?
feedback loop
Our actions will modif y subsequent results

55. Q: Why did this work?
feedback loop
Our actions will modif y subsequent results

56. Q: Why did this work?

57. Q: Why did this work?

58. Q:iosity did this work?
cur Why

59. Q:iosity did this work?
cur Why
visual
imager y

60. Q:iosity did this work?
cur Why
visual
imager y
rn ion
te it
at gn
p o
r ec

61. Q:iosity did this work?
cur Why
visual
imager y
recog
nition
rn ion over re
p o te it
at gn call
r ec

62. Q: Why did this work?

63. But wait, there’s more!

73. USER GOALS
I had a great
time playing
iLike gained lots of
data about my musical
tastes, preferences &
music games knowledge

74. Q: Why did this work?

75. se nsor y
eQ: e rience this work?
xpWhy did

76. se nsor y
eQ: e rience this work?
xpWhy did
points

77. se nsor y
eQ: e rience this work?
xpWhy did
points
v els
le

78. se nsor y
eQ: e rience this work?
xpWhy did
points
v els
le appro
challepriate
nges

79. Q: Why did this work?

80. Did you notice... It
wasn’t the usability
that makes it great?

81. INCREASING
MOTIVATION
Psychology
REMOVING
FRICTION
(Joshua Porter)
Usability

82. INCREASING
MOTIVATION
Psychology
REMOVING
FRICTION
(Joshua Porter)
Usability

84. ckse:
uirci What do we know about people?
Qex
E

85. ckse:
uirci What do we know about people?
Qex
E we're curious
we're also afraid of change
we seek out patterns
we like to order and organize things
we're intensely self-centered
we're lazy
we're highly visual thinkers and learners
we like to be the hero of the story
we respond to our name and other first person cues
we don't like to make choices, but we like choice
we like to be in control (and we like to be guided)
we find novelty and surprise interesting
...and so on

86. http://www.flickr.com/photos/laurafries/172143362/

89. social proo
f
People follow the
others. lead of similar

90. social proo
f
People follow the
others. lead of similar

92. i ckse:
urci What do we know about people?
Qe
Ex
we're curious
we're also afraid of change
we seek out patterns
we like to order and organize things
we're intensely self-centered
we're lazy
we're highly visual thinkers and learners
we like to be the hero of the story
we respond to our name and other first person cues
we don't like to make choices, but we like choice
we like to be in control (and we like to be guided)
we find novelty and surprise interesting
...and so on

93. i ckse:
urci What do we know about people?
Qe
Ex
we're curious
we're also afraid of change
we seek out patterns
we like to order and organize things
we're intensely self-centered
we're lazy
we're highly visual thinkers and learners
we like to be the hero of the story
we respond to our name and other first person cues
we don't like to make choices, but we like choice
we like to be in control (and we like to be guided)
we find novelty and surprise interesting
...and so on

94. Being A Tease.

103. Curious?

104. Playing Hard To Get.

105. “private beta”

106. “private beta”
+
“social proof”

107. “private beta”
+
“social proof”
=
WHOA!

112. www.rypple.com

117. 60% - 70% of Sabre employees
actively use the system each
month
60% of questions asked are
answered within one hour of
posting (90% in 24 hours)
Average of 30 page views per
employee user visit
Each question posted to the
community receives an average of
nine answers

118. 60% - 70% of Sabre employees
repu tation
actively use the system each
month
60% of questions asked are
answered within one hour of
posting (90% in 24 hours)
Average of 30 page views per
employee user visit
Each question posted to the
community receives an average of
nine answers

119. 60% - 70% of Sabre employees
repu tation
actively use the system each
month
60% of questions asked are
points
answered within one hour of
posting (90% in 24 hours)
Average of 30 page views per
employee user visit
Each question posted to the
community receives an average of
nine answers

120. 60% - 70% of Sabre employees
repu tation
actively use the system each
month
60% of questions asked are
points
answered within one hour of
posting (90% in 24 hours)
Average of 30 page views per
employee user visit
v els
le Each question posted to the
community receives an average of
nine answers

121. 60% - 70% of Sabre employees
repu tation
actively use the system each
month
60% of questions asked are
points
answered within one hour of
posting (90% in 24 hours)
limit
Average of 30 page views per
employee user visit du ed
ratio
v s question posted to the
elEach n
le community receives an average of
nine answers

122. 60% - 70% of Sabre employees
actively use the system each
month
60% of questions asked are
answered within one hour of
posting (90% in 24 hours)
Average of 30 page views per
employee user visit
Each question posted to the
community receives an average of
nine answers

123. Taking A Chance.

130. ck ge:
uilen
Qal
C h
Design the user interface
that let’s you sync a video file
(from a presentation) with
the accompanying slides.

131. NE AK PRE VIEW!!!
S

132. Q: Why DOES this work?

133. Q: Why DOES this work?
ownership
bias

134. Q: Why DOES this work?
ownership
bias
playfu lness

135. Q: Why DOES this work?
ownership
bias feedback
loops
playfu lness

136. Q: Why DOES this work?

137. On Friskiness,
Gifts & Pleasant
Surprises.

138. DELIGHTERS
Matt Jones

139. DELIGHTERS
Matt Jones

140. APP FOR FREQUENT
TRAVELLERS
Matt Biddulph

141. “serendipity”

142. “Personal Velocity”

143. 2008 Personal annual report for Stephen Anderson
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Austin Miami San Francisco Seattle Mountain View New York Franklin Minneapolis
Mar 07 to Mar 11 Apr 10 to Apr 14 Apr 20 to Apr 22 Aug 21 to Aug 23 September 24 Sep 24 to Sep 26 Nov 06 to Nov 09 Dec 09 to Dec 11
You took 17 trips in 2008, which added In 2008, you spent
up to 55,753 km or 15% of the
distance to the moon.
323 43
In 2008, you mostly coincided with:
You have 52 travellers in your network. They travelled a
total of 1,753,265 km in 2008, and everyone on Dopplr
Kevin travelled a total of 1331.4 million km or 8.9 AU in 2008:
the approximate distance to Saturn from the Earth as
in Austin, Miami and San Francisco
of January 2009.
Peter
Your personal velocity for 2008 was 6.36
in Austin, Miami and Berkeley km/h, which is about the same as a duck. You spent the longest in Minneapolis, Jesse Spalding Your carbon for 2008
has a tip:
Jay Lots of great farmer's markets in the summer!
The 5 most popular cities in your network are San
in Minneapolis Minneapolis Farmer's Market on Lyndale Ave and
Francisco, Austin, New York, Miami and Chicago.
Cesar Chavez Ave or Nicollet Mall
Chris http://www.mplsfarmersmarket.com/
in Miami and San Francisco Mill City Farmer's Market on Chicago Ave and 2nd St.
The furthest distance you travelled was to New York S
Brandon (4,120 km from Mountain View), which is the 2nd most ...
popular city on Dopplr. The shortest distance you 6,606 kg CO2
in Miami and San Francisco travelled was to Austin (322 km from Plano), which is See more on the city page for Minneapolis on Dopplr. Based on figures from Fueleconomy.gov, 1 x Hummer
the 21st most popular city on Dopplr. H3 4WD truck produces nearly 10 metric tonnes of
CO2 a year. The visualisation above uses this figure to
illustrate your carbon from Dopplr as calculated by our
friends at http://amee.cc and is an approximation only.
The city images above sourced from Flickr and are used under a Creative Commons Attribution Licence: by pusgums, brickell by alexdecarvalho, Passing Under The Golden Gate Bridge by Dawn Endico, Seattle, Washington by fddi1, Apple I keyboard by Marcin
Wichary, smokin by mudpig and Spoonbridge and Cherry by TimWilson.

144. 2008 Personal annual report for Stephen Anderson
an Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Austin Miami San Francisco Seattle Mountain View New York Franklin Minneapolis
This month Dopplr delightfully surprised
Mar 07 to Mar 11 Apr 10 to Apr 14 Apr 20 to Apr 22 Aug 21 to Aug 23 September 24 Sep 24 to Sep 26 Nov 06 to Nov 09 Dec 09 to Dec 11
ou took 17 trips in 2008, which added
me, supplying me with something I didn’t
In 2008, you spent
know I ne43 ed. The result: I’m now a
ed
p to 55,753 km or 15% of the
istance to the moon.
323
n 2008, you mostly coincided with:
more loyal Dopplr user.
You have 52 travellers in your network. They travelled a
total of 1,753,265 km in 2008, and everyone on Dopplr
Kevin travelled a total of 1331.4 million km or 8.9 AU in 2008:
the approximate distance to Saturn from the Earth as
in Austin, Miami and San Francisco
of January 2009.
Peter
Your personal velocity for 2008 was 6.36
in Austin, Miami and Berkeley km/h, which is about the same as a duck. You spent the longest in Minneapolis, Jesse Spalding Your carbon for 2008
has a tip:
Jay Lots of great farmer's markets in the summer!
The 5 most popular cities in your network are San
in Minneapolis Minneapolis Farmer's Market on Lyndale Ave and
Francisco, Austin, New York, Miami and Chicago.
Cesar Chavez Ave or Nicollet Mall
Chris http://www.mplsfarmersmarket.com/
in Miami and San Francisco Mill City Farmer's Market on Chicago Ave and 2nd St.
The furthest distance you travelled was to New York S
Brandon (4,120 km from Mountain View), which is the 2nd most ...
popular city on Dopplr. The shortest distance you 6,606 kg CO2
in Miami and San Francisco travelled was to Austin (322 km from Plano), which is See more on the city page for Minneapolis on Dopplr. Based on figures from Fueleconomy.gov, 1 x Hummer
the 21st most popular city on Dopplr. H3 4WD truck produces nearly 10 metric tonnes of
CO2 a year. The visualisation above uses this figure to
illustrate your carbon from Dopplr as calculated by our
friends at http://amee.cc and is an approximation only.
The city images above sourced from Flickr and are used under a Creative Commons Attribution Licence: by pusgums, brickell by alexdecarvalho, Passing Under The Golden Gate Bridge by Dawn Endico, Seattle, Washington by fddi1, Apple I keyboard by Marcin
Wichary, smokin by mudpig and Spoonbridge and Cherry by TimWilson.
Brandon Schauer

145. Q: Why DOES this work?

146. Q: Why DOES this work?
pattern
recognition

147. Q: Why DOES this work?
pattern
recognition
playfu lness

148. Q: Why DOES this work?
pattern
recognition
gifting
playfu lness

149. Q: Why DOES this work?

150. brains pay attention to what brains
care about, not necessarily what
the conscious mind cares about.

151. Q: What does
the brain find to what brains
brains pay attention
interesting?
care about, not necessarily what
the conscious mind cares about.

152. Q: What does
the brain find to what brains
brains pay attention
interesting?
care about, not necessarily what
Surprise, novelty,
the conscious mind cares about.
the unexpected

153. Q: What does
the brain find to what brains
brains pay attention
interesting?
care about, not necessarily what
Surprise, novelty,
the conscious mind cares about.
the unexpected
Fun, playfulness,
humor

154. Q: What does
the brain find to what brains
brains pay attention
interesting?
care about, not necessarily what
Surprise, novelty,
the conscious mind cares about.
the unexpected
Fun, playfulness,
humor
Varying visuals

155. Q: What does
the brain find to what brains
brains pay attention
interesting?
care about, not necessarily what
Surprise, novelty,
the conscious mind cares about.
the unexpected
Fun, playfulness,
humor
Varying visuals
(and more!)

156. WILL THE REAL
DOPPLR LOGO
PLEASE STAND UP?

162. WHAT?
SO WHAT?
NOW WHAT?

163. That was fun!
GREAT ONLINE
EXPERIENCE

164. Hmm... WHY was
That was fun! that fun?
GREAT ONLINE (REVERSE ENGINEERING)
EXPERIENCE

165. Hmm... WHY was
That was fun! that fun?
Aha!
GREAT ONLINE (REVERSE ENGINEERING)
EXPERIENCE

166. Hmm... WHY was
That was fun! that fun?
Aha!
GREAT ONLINE (REVERSE ENGINEERING) p sych
n
huma ology
EXPERIENCE

167. (sorry, no 9 tips or 5 lessons)

168. Hmm... WHY was
That was fun! that fun?
Aha!
GREAT ONLINE (REVERSE ENGINEERING) p sych
n
huma ology
EXPERIENCE
>
human
y
anolog psychology
m h
USEFUL TOOLS FOR CREATING..
husyc
p
n
huma ology
h an lo
gy
psyc n m cho
huma ology husy
psych p

169. socia l proof
People follow the le ad of similarreciprocity
others. People repay in kind.
authority duration effects
People defer to experts. Perception of time is subjective and
can be influenced.
scarcity
People wan t more of what they can
have less of. recognition over
recall
sensor y integration
People respond better when more of
imager y
jkjkj
the senses are engaged.

170. ???
COGNITIVE SEDUCTION:
FUN, HUMOR, PLAYFULNESS,
GAME SURPRISE, ???
MECHANICS
??? SOCIAL PSYCHOLOGY /
PERSUASION, CHOICE,
INFLUENCE SOCIAL DESIGN
???

172. How can we use { } to... [goal]
www.getmentalnotes.com

173. Social Proof Curiosity
We tend to follow the patterns of similar others When teased with a small bit of interesting
in new or unfamiliar situations. information, people will want to know more!
How can we use { } to... [goal]
To put people at ease or guide a decision, find creative When—and what—can you hold back? Reveal just enough
ways to show social activity. This can be in the form of stats to arouse interest, then tease someone into taking the next
(favorited by, number of views, comments), good positive step. You can also arouse interest by doing something unusual
reviews/ testimonials, or by providing visibility into the actions and unexpected—people will stick around long enough to
or outcomes of other users’ behaviors. determine what’s going on. Similarly, puzzles are intriguing.
See also: Bystander Effect, Testimonials, Identification See also: Pattern Recognition, Badges, Gifting
Mental Notes Sneak Preview | Find out more at www.getmentalnotes.com

174. Social Proof Curiosity
We tend to follow the patterns of similar others When teased with a small bit of interesting
in new or unfamiliar situations. information, people will want to know more!
How can we use { } to... [goal]
To put people at ease or guide a decision, find creative When—and what—can you hold back? Reveal just enough
ways to show social activity. This can be in the form of stats to arouse interest, then tease someone into taking the next
(favorited by, number of views, comments), good positive step. You can also arouse interest by doing something unusual
reviews/ testimonials, or by providing visibility into the actions and unexpected—people will stick around long enough to
or outcomes of other users’ behaviors. determine what’s going on. Similarly, puzzles are intriguing.
See also: Bystander Effect, Testimonials, Identification See also: Pattern Recognition, Badges, Gifting
Mental Notes Sneak Preview | Find out more at www.getmentalnotes.com
www.getmentalnotes.com

175. Thanks!!
Stephen P. Anderson
www.poetpainter.com
www.slideshare.net/stephenpa