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Decisions are influenced by the environment in which the choices are presented. In fact, no choice is made in a vacuum, as there is no neutral way to present choices. Presenting choices in certain ways, even unintentionally, can "nudge" people to change their behavior in predictable ways. "Nudging" is a concept from behavioral economics that describes how even minor changes to decision environments (e.g., setting defaults) can influence decision outcomes-typically without the decision-maker noticing this influence. The more decisions people make using digital devices, the more the software engineer becomes a choice architect who knowingly or unknowingly influences people's decisions. Thus, we extend the nudging concept to the digital environment, defining "digital nudging" as the use of user-interface design elements to guide people's behavior in digital choice environments, and present a digital nudge design process to help online choice architects take nudging principles into consideration when designing digital choice environments like Web sites and apps.
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JULY 2018 | VOL. 61 | NO. 7 | COMMUNICATIONS OF THE ACM 67
LIFE IS FULL of choices, often in digital environments.
People interact with e-government applications; trade
financial products online; buy products in Web shops;
book hotel rooms on mobile booking apps; and make
decisions based on content presented in organizational
information systems. All such choices are influenced by
the choice environment, as reflected
in this comment: “What is chosen of-
ten depends upon how the choice is
presented.”16 Why? People have cogni-
tive limitations, so their rationality is
bounded,27 and heuristics and biases
drive their decision making.34 Design-
ers of choice environments, or “choice
architects,”32 can thus use these heu-
ristics and biases to manipulate the
choice environment to subtly guide us-
ers’ behavior by gently “nudging” them
toward certain choices.
These observations are more than
theory. We are being nudged every
day of our lives. Supermarkets posi-
tion items with the highest markups
at eye level to nudge customers into
making unplanned purchases. Like-
wise, supermarkets limit the number
of units customers are allowed to buy,
DOI:10.1145/3213765
Designers can create designs that nudge
users toward the most desirable option.
BY CHRISTOPH SCHNEIDER, MARKUS WEINMANN,
AND JAN VOM BROCKE
Digital
Nudging:
Guiding Online
User Choices
through
Interface Design
key insights
˽ Heuristics and biases influence offline
and online behavior.
˽ User-interface design influences choices,
even unintentionally.
˽ Thorough design and testing can help
achieve a designer’s intended behavioral
effects.
68 COMMUNICATIONS OF THE ACM | JULY 2018 | VOL. 61 | NO. 7
contributed articles
thereby influencing their buying de-
cisions; customers subconsciously
anchor their decisions on the maxi-
mum number and adjust downward
from there, resulting in purchases of
greater quantities.36 This effect has
been demonstrated in the context
of everyday items; for example, in-
troducing a quantity limit of 12 cans
of soup helped double the average
quantity purchased from 3.3 to seven
cans.36 Nudges are not, however, used
only by marketers trying to sell more
products or services; for example,
when asking people to consent to be-
ing an organ donor, simply changing
defaults can influence people’s choic-
es. Setting the default to “dissent,”
whereby donors have to opt out, rath-
er than “consent” whereby donors
have to opt in, can nearly double the
percentage of organ donors.15 These
examples show that largely impercep-
tible nudges are effective in a variety
of offline contexts.
As in offline environments, online
environments offer no neutral way to
present choices. Any user interface,
from organizational website to mobile
app, can thus be viewed as a digital
choice environment.37 Digital choice
environments nudge people by delib-
erately presenting choices or organiz-
ing workflows, making digital nudg-
ing—“the use of user-interface design
elements to guide people’s behavior
in digital choice environments”37—a
powerful tool in any choice architect’s
toolbox. Choosing the most effective
nudge involves trade-offs, however,
because predicting the consequences
of implementing certain nudges is not
always possible.
Existing guidelines for implement-
ing nudges have been developed pri-
marily for offline environments, and
digital nudging has only recently
begun to attract programmer inter-
est; see, for example, Gregor and
Lee-Archer10 and Weinmann et al.37
In addition, guidelines that are effec-
tive offline may not always be directly
transferred to a digital context; for ex-
ample, online users are more willing
to disclose information but are also
more cautious about accepting de-
fault options.2 To this end, this article
shows how designers can consider the
effects of nudges when designing digi-
tal choice environments.
Figure 1. The decoy effect in reward-based crowdfunding; screenshot shows the decoy
condition.
Figure 2. The decoy effect in reward-based crowdfunding; adding a decoy option can make
another option more attractive.
69%
31%
Reward 1
Reward 2
31
%
68%
Reward 2
Decoy
1
%
Reward Menu 1
Reward Menu 2
Reward 1: e-book ($10)
Reward 2: e-book and hardcover ($20)
Reward 1: e-book ($10)
Decoy: hardcover ($10)
Reward 2: e-book and hardcover ($20)
Figure 3. The scarcity effect in reward-based crowdfunding; limiting either reward changes
pledging behavior of potential backers.
69%
31%
Reward 1
Reward 2
Reward Menu 1
Reward Menu 2
Reward 1: screen credit ($10) only five left
Reward 2: DVD/Blu-ray ($50)
Reward 1: screen credit ($10)
Reward 2: DVD/Blu-ray ($50) only five left
30
%
70
%
Reward 1
Reward 2
JULY 2018 | VOL. 61 | NO. 7 | COMMUNICATIONS OF THE ACM 69
contributed articles
an e-book in return for a $10 pledge or
both an e-book and a hardcover book
for a $20 pledge, most backers chose
to pledge $10. However, when a third
option—a decoy nudge—was included
that offered only the hardcover book in
return for a $20 pledge (see Figure 1),
most backers chose to pledge $20 to
receive both the e-book and the hard-
cover book. Including the decoy option
thus led many backers to move from
the $10 pledge to the $20 pledge (see
Figure 2).
Scarcity effect. People tend to per-
ceive scarce items as more attractive
or desirable.9 In the context of crowd-
funding (N = 166), the researchers
showed that limiting the availability
of rewards—a “scarcity nudge”—can
lead them to choose a particular re-
Guiding Choices
As in offline contexts, online decision
making is almost always influenced by
heuristics and biases; consequently,
the concept of digital nudging applies
not only to online consumers’ decision
making but also to various other con-
texts, from e-health systems to social
media apps to organizational infor-
mation systems. Whereas such factors
as presenting reviews or highlighting
markdowns are well known for hav-
ing a strong effect on user behavior
in general, digital nudges influence
decisions at the point and moment of
decision making.a,22 In particular, digi-
tal nudging works by either modifying
what is presented—the content of a
choice6,35—or how it is presented—the
visualization of a choice—as in, say,
changing the design of the user inter-
face.16 For example, the mobile pay-
ment app Square presents a “tipping”
option by default, so customers must
select “no tipping” if they prefer not
to give a tip; this modification is likely
an attempt to nudge people into giving
tips, motivating them to tip even where
tipping is uncommon.3
To illustrate the effects of digital
nudges, we briefly explore the results of
a series of experiments in the context
of reward-based crowdfunding.28,33,38
In reward-based crowdfunding, proj-
ect creators collect small amounts of
money from a large number of people,
or “backers.” Backers pledge money
for projects and receive non-financial
a Digital nudging, with its focus on the design
of digital choice environments, can be viewed
as a subset of persuasive computing/technol-
ogy, which is generally defined as technology
designed to change attitudes or behaviors and
includes aspects of human-computer interac-
tion beyond interface design.8,26
rewards in return (such as an e-book).1
To test how digital nudges influence
backers’ pledges, researchers at the
University of Liechtenstein modified
the content and/or visualization of a
choice environment to nudge back-
ers toward a particular option through
three particular heuristics and biases,
known as the “decoy effect,”33 “scarcity
effect,”38 and “middle-option bias.”28
Decoy effect. The decoy effect in-
creases an option’s attractiveness by
presenting the option alongside an
unattractive option no one would rea-
sonably choose—the decoy.13 In a study
conducted in the context of crowdfund-
ing (N = 96), the researchers showed
how decoys can nudge users to select
certain rewards;33 when backers were
presented with a choice of receiving
Figure 4. The middle-option bias in reward-based crowdfunding; even when the investment scale is increased, backers tended to select the
middle option.
Reward Menu 1
(Inexpensive Scale)
Reward Menu 2
(Moderate Scale)
Reward Menu 3
(Expensive Scale)
18
%
49
%
$5
$10
33
%
$15
30
%
49
%
$10
$15
21
%
$20
30
%
37
%
$15
$20
34
%
$25
Figure 5. Designing digital nudges follows a cycle; based on Datta and Mullainathan5 and Ly et al.19
70 COMMUNICATIONS OF THE ACM | JULY 2018 | VOL. 61 | NO. 7
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$15, $20, $25. The researchers told the
participants that their pledge would
be doubled as a reward if the project
would be successful. However, irrespec-
tive of the scale, most backers tended to
choose the middle option, and by shift-
ing the scales, the researchers could
nudge the participants toward selecting
rewards associated with higher pledge
amounts (see Figure 4).
These examples show that designers
can create digital nudges on the basis
of psychological principles of human
decision making to influence people’s
online behavior. Unintended effects
may arise, however, if designers of digi-
tal choice environments are unaware
of the principles. For example, in the
context of crowdfunding, presenting
decoys or limiting the availability of
rewards without considering their ef-
fect can unintentionally lead backers
to select lower-price rewards; that is,
as virtually all user-interface design
decisions influence user behavior,20,30
designers must understand the effects
of their designs so they can choose
whether to nudge users or reduce the
effects of nudges.
Designing a Digital Nudge
While a number of researchers have
suggested guidelines for selecting
and implementing nudges in offline
contexts,5,6,16,19,21,31 information sys-
tems present unique opportunities
for harnessing the power of nudging.
For example, Web technologies allow
real-time tracking and analysis of user
behavior, as well as personalization
of the user interface, and both can help
test and optimize the effectiveness of
digital nudges; moreover, mobile apps
can provide a wealth of information
about the context (such as location and
movement) in which a choice is made.
Given these advantages, information
systems allow rapid content modifi-
cation and visualization to achieve the
desired nudging effect.
Drawing on guidelines for imple-
menting nudges in offline contexts,
we now highlight how designers can
create digital nudges by exploiting
the inherent advantages of informa-
tion systems. Just as developing an
information system follows a cycle, as
in, say, the systems development life
cycle—planning, analysis, design, and
implementation—so does designing
choices to nudge users (see Figure 5)—
define the goal, understand the users,
design the nudge, and test the nudge.
We discuss each step in turn, focusing
on the decisions designers must make.
Step 1: Define the goal. Designers
must first understand an organiza-
tion’s overall goals and keep them in
mind when designing particular choice
situations. For instance, the goal of an e-
commerce platform is to increase sales,
the goal of a governmental taxing au-
thority’s platform is to make filing taxes
easier and encourage citizens to be hon-
est, and the goal of project creators on
crowdfunding platforms is to increase
pledges and overall donation amounts.
These goals determine how choices are
to be designed, particularly the type
of choice to be made. For example,
subscribing to a newsletter is a binary
choice—yes/no, agree/disagree—select-
ing between items is a discrete choice,
and donating monetary amounts is a
continuous choice, though it could also
be presented as a discrete choice. The
type of choice determines the nudge to
be used (see the table here). The choice
architect, however, must consider not
only the goals but also the ethical im-
ward.38 For a fictitious movie project,
backers were offered a choice between
two rewards: pledge $10 to be listed in
the screen credits or pledge $50 to re-
ceive the movie on a DVD/Blu-ray disc
(see Figure 3). When the availability of
the low-price reward was limited, 69%
of the backers chose that reward, as in
Figure 3, left side, whereas when the
availability of the high-price reward
was limited, 70% chose that reward,
as in Figure 3, right side. Merely pre-
senting information about the limited
availability of either reward, even the
higher-price one, thus caused more
backers to choose that reward.
Middle-option bias. People present-
ed with three or more options (ordered
sequentially, as by price) tend to select
the middle option.4 Testing the effect of
the middle-option bias in the context of
crowdfunding (N = 282), the research-
ers showed that backers can be nudged
into choosing the reward presented in
the middle.28 They tested it by varying
the pledges of the offered rewards by,
in particular, shifting the scales such
that Condition 1: $5, $10, $15; Condi-
tion 2: $10, $15, $20, and Condition 3:
Applying the digital nudging design cycle (selected examples).
Step 1 Step 2 Step 3
Type of choice
to be influenced
Heuristic/Bias Example design elements and
user-interface patterns and possible
nudges and mechanisms
Binary (yes/no) Status quo bias (defaults) Radio buttons (with default choice)
Discrete choice
(such as two products)
Status quo bias (defaults) Use of defaults in
Radio buttons
Check boxes
Dropdown menus
Decoy effect Presentation of decoy option(s) in
Radio buttons
Check boxes
Dropdown menus
Primacy and recency effect Positioning of presentation
of desired option(s)
Earlier (primacy)
Later (recency)
Middle-option bias Addition of higher- and lower-price
alternatives around preferred option
Ordering of alternatives
Modification of the option scale
Continuous Anchoring and adjustment Variation of slider endpoints
Use of default slider position
Predefined values in text boxes for quantities
Status quo bias (defaults) Use of default slider position
Any type of choice Norms Display of popularity (social norms)
Display of honesty codes (moral norms)
Scarcity effect (loss aversion) Use of default slider position
JULY 2018 | VOL. 61 | NO. 7 | COMMUNICATIONS OF THE ACM 71
contributed articles
the heuristics and biases at play;
see the table for examples. For ex-
ample, a commonly used nudge in
binary choices is to preselect the
desired option to exploit the status
quo bias. When attempting to nudge
people in discrete choices, choice
architects can choose from a variety
of nudges to nudge people toward a
desired option. For example, in the
context of crowdfunding, with the
goal of increasing pledge amounts,
choice architects could present the
desired reward option as the default
option; add (unattractive) choices as
decoys; present the desired option
first or last to leverage primacy and
recency effects; or arrange the op-
tions so as to present the preferred
reward as the middle option. When
attempting to nudge people in con-
tinuous choices (such as when solic-
iting monetary donations), choice
architects could pre-populate input
fields (text boxes) with a particular
value so as to exploit the “anchor-
ing and adjustment” effect. Like-
wise, when using a slider to elicit
numerical responses, the position of
the slider and the slider endpoints
serve as implicit anchors. Present-
ing others’ choices next to rewards
to leverage people’s tendency to con-
form to norms or presenting limited
availability of rewards to exploit the
plications of deliberately nudging peo-
ple into making particular choices, as
nudging people toward decisions that
are detrimental to them or their wellbe-
ing is unethical and might thus back-
fire, leading to long-term negative ef-
fects for the organization providing the
choice.30 In short, overall organizational
goals and ethical considerations drive
the design of choice situations, a high-
level step that influences all subsequent
design decisions.
Step 2: Understand the users. Peo-
ple’s decision making is susceptible to
heuristics and biases. Heuristics, com-
monly defined as “rules of thumb,”14
can facilitate human decision making
by reducing the amount of informa-
tion to be processed when addressing
simple, recurrent problems. Converse-
ly, heuristics can influence decisions
negatively by introducing cognitive
biases—systematic errors—when one
faces complex judgments or decisions
that should require more extensive
deliberation.7 Researchers have stud-
ied a wide range of psychological ef-
fects that subconsciously influence
people’s behavior and decision mak-
ing.b In addition to the middle-option
bias, decoy effect, and scarcity effect
described earlier, common heuristics
like the “anchoring-and-adjustment”
heuristic, or people being influenced
by an externally provided value, even
if unrelated; the “availability” heuris-
tic, or people being influenced by the
vividness of events that are more easily
remembered; and the “representative-
ness” heuristic, or people relying on
stereotypes when encountering and
assessing novel situations,34 influence
how alternatives are evaluated and
what options are ultimately selected.
Other heuristics and biases that can
have a strong effect on choices in-
clude the “status quo bias,” or people
tending to favor the status quo so they
are less inclined to change default
options;18 the “primacy and recency
effect,” or people recalling options
presented first or last more vividly,
so those options have a stronger in-
fluence on choice;24 and “appeals to
b See Stanovich20 for a taxonomy of rational think-
ing errors and biases; see also Wikipedia for an
extensive list of cognitive biases that influence
people’s online and offline behavior (https://
en.wikipedia.org/wiki/List_of_cognitive_biases).
norms,” or people tending to be influ-
enced by the behavior of others.23 Un-
derstanding these heuristics and bi-
ases and the potential effects of digital
nudges can thus help designers guide
people’s online choices and avoid the
trap of inadvertently nudging them
into decisions that might not align
with the organization’s overall goals.
Step 3: Design the nudge. Once
the goals are defined (see Step 1: De-
fine the goal) and the heuristics and
biases are understood (see Step 2:
Understand the users), the designer
can select the appropriate nudging
mechanism(s) to guide users’ deci-
sions in the designer’s intended di-
rection. Common nudging frame-
works a designer could use to select
appropriate nudges include the Be-
havior Change Technique Taxono-
my,21 NUDGE,31 MINDSPACE,6 and
Tools of a Choice Architecture.16
Selecting an appropriate nudge and
how to implement it through avail-
able design elements, or user-inter-
face patterns, is determined by both
the type of choice to be made—bi-
nary, discrete, or continuousc—and
c In most cases, the type of decision is an exter-
nality, and many decisions allow for only one
type; for example, consenting to something
(whether organ donation or signing up for a
newsletter) would normally always be a binary
choice—yes/no.
Define goals:
What is the use scenario?
What are the overall organizational goals?
What specific goals are to be achieved in this situation?
What are the ethical implications of nudging people into making a certain decision?
Understand the decision process:
What are the users’ goals?
What are the users’ decision-making processes?
What heuristics might influence users’ choices?
Design the nudge:
What types of nudges could counter the influence of biases?
What types of nudges could increase the influence of biases?
What nudges could inadvertently influence users’ choices?
How can the design of the user interface be modified to include the preferred nudges?
How can we analyze users’ behavior to adapt the choice environment dynamically?
Test the nudge:
How effective are the various nudges?
Does the effectiveness differ across users?
Do the nudges fit the context and the goals?
Do we have a thorough understanding of the users’ decision-making process?
Questions Designers
Need to Address
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contributed articles
architects have various nudge imple-
mentations at their disposal, thor-
ough testing is thus imperative for
finding the nudge that works best for
a given context and users.
Especially in light of the increasing
focus on integrating user-interface
design and agile methodologies, us-
ing discount usability techniques
(such as heuristic evaluation, as in-
troduced by Nielsen25) is often rec-
ommended to support rapid develop-
ment cycles (see, for example, Jurca et
al.17). Likewise, agile methodologies
include the quick collection of feed-
back from real users. However, such
feedback from conscious evaluations
should be integrated with caution be-
cause the effects of nudges are based
on subconscious influences on be-
havior, and experimental evaluations
can provide more reliable results. If
a particular nudge does not produce
the desired effect, a first step for
system designers is to evaluate the
nudge implementation to determine
whether the nudge is, say, too obvious
or not obvious enough (see Step 3: De-
sign the nudge). In some instances,
though, reexamining the heuristics
or biases that influence the decision-
making process (see Step 2: Under-
stand the users) or even returning to
Step 1: Define the goal and redefining
the goals may be necessary (see the
sidebar, “Questions Designers Need
to Address”).
Conclusion
Understanding digital nudges is im-
portant for the overall field of com-
puting because user-interface de-
signers create most of today’s choice
environments. With increasing
numbers of people making choices
through digital devices, user-inter-
face designers become choice ar-
chitects who knowingly or unknow-
ingly influence people’s decisions.
However, user-interface design often
focuses primarily on usability and
aesthetics, neglecting the potential
behavioral effects of alternative de-
signs. Extending the body of knowl-
edge of the computing profession
through insights into digital nudging
will help choice architects leverage
the effects of digital nudges to sup-
port organizational goals. Choice ar-
chitects can use the digital nudging
scarcity effect can be used to nudge
people in binary, discrete, or continu-
ous choices.
As the same heuristic can be ad-
dressed through multiple nudges,
in most situations, designers have
a variety of “nudge implementa-
tions” at their disposal. Unlike in
offline environments, implement-
ing nudges in digital environments
can be done at relatively low cost, as
system designers can easily modify
a system’s user interface (such as
by setting defaults, displaying/hid-
ing design elements, or providing
information on others’ pledges).
Likewise, digital environments en-
able dynamic adjustment of the op-
tions presented on the basis of cer-
tain attributes or characteristics of
the individual user (such as when
a crowdfunding platform presents
particular rewards depending on
the backers’ income, gender, or
age). Notwithstanding the choice
of nudges, designers should follow
commonly accepted design guide-
lines for the respective platforms
(such as Apple’s Human Interface
Guidelines and Microsoft’s Univer-
sal Windows Platform design guide-
lines) to ensure consistency and us-
ability.
Step 4: Test the nudge. Digital en-
vironments allow alternative designs
to be generated easily, so their effects
can be tested quickly, especially when
designing websites. The effective-
ness of digital nudges can be tested
through online experiments (such as
A/B testing and split testing). Testing
is particularly important, as the effec-
tiveness of a nudge is likely to depend
on both the context and goal of the
choice environment and the target au-
diences. For example, a digital nudge
that works well in one context (such as
a hotel-booking site like https://www.
booking.com) may not work as well
in a different context (such as a car-
hailing service like https://www.uber.
com); such differences may be due to
different target users, the unique na-
ture of the decision processes, or even
different layouts or color schemes on
the webpages; a hotel may use colors
and shapes that evoke calmness and
cleanliness, whereas a car-hailing ser-
vice may use colors and shapes that
evoke speed and efficiency. As choice
Big-data analytics
can be used to
analyze behavioral
patterns observed
in real time
to infer users’
personalities,
cognitive styles,
or even
emotional states.
JULY 2018 | VOL. 61 | NO. 7 | COMMUNICATIONS OF THE ACM 73
contributed articles
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Christoph Schneider (christoph.schneider@cityu.edu.hk)
is an assistant professor in the Department of Information
Systems at City University of Hong Kong, Kowloon, Hong
Kong SAR.
Markus Weinmann (markus.weinmann@uni.li) is an
assistant professor in the Department of Information
Systems at the University of Liechtenstein, Vaduz,
Liechtenstein.
Jan vom Brocke (jan.vom.brocke@uni.li) is a professor of
information systems, the Hilti Chair of Business Process
Management, Director of the Institute of Information
Systems, and Vice President for Research and Innovation
at the University of Liechtenstein, Vaduz, Liechtenstein.
Copyright held by the authors.
design cycle we have described here
to deliberately develop such choice
environments.
One final note of caution is that the
design of nudges should not follow a
“one-size-fits-all” approach, as their
effectiveness often depends on a de-
cision maker’s personal characteris-
tics.16 In digital environments, charac-
teristics of users and their environment
can be inferred from a large amount of
data, allowing nudges to be tailored.
System designers might design the
choice environment to be adaptive on
the basis of, say, users’ past decisions
or demographic characteristics. Like-
wise, big-data analytics can be used to
analyze behavioral patterns observed
in real time to infer users’ personali-
ties, cognitive styles, or even emotional
states.12 For example, Bayesian updat-
ing can be used to infer cognitive styles
from readily available clickstream data
and automatically match customers’
cognitive styles to the characteristics
of the website (such as through “mor-
phing”11). Designers of digital choice
environments can attempt to “morph”
digital nudges on the basis of not only
the organizational goals but also users’
personal characteristics.
Any designer of a digital choice
environment must be aware of its
effects on users’ choices. In partic-
ular, when developing a choice envi-
ronment, designers should carefully
define the goals, understand the
users, design the nudges, and test
those nudges. Following the digital-
nudging design cycle we have laid
out here can help choice architects
achieve their organizational goals
by understanding both the users
and the potential nudging effects so
intended effects can be maximized
and/or unintended effects minimized.
Acknowledgments
This work was partially supported
by research grants from the Univer-
sity of Liechtenstein (Project No. wi-
2-14), City University of Hong Kong
(Project No. 7004563), and City Uni-
versity of Hong Kong’s Digital Inno-
vation Laboratory in the Department
of Information Systems. We wish to
thank Joseph S. Valacich for valuable
comments on earlier versions, as well
as the anonymous reviewers for their
insightful comments.
Watch the authors discuss
their work in this exclusive
Communications video.
https://cacm.acm.org/videos/
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