Whether you’re an executive, marketer, or developer, you’re likely in on the secret that digital customer experiences matter more than ever. Despite this, it can feel increasingly daunting to design the amazing experiences your customers desire — and that perform for your business.
Leaning on his decades of experience as a digital operator, Matty Wishnow, Managing Director of Experience Design & Optimization at Accenture Interactive and Founder of Clearhead, will share key principles for data-driven experience design.
Using real world examples, Matty will share how these principles enable enterprises to transform customer experiences through evidence-based design and a focus on solving the biggest problems your customers face.
18. Today evidence-based design is defined by
Wikipedia as:
Evidence-based Design
"Evidence-based design is a process for the conscientious, explicit, and
judicious use of current best evidence from research and practice in making
critical decisions, together with an informed client, about the design of each
individual and unique project".
19. Level 1
Informed design decisions based on available literature on
environmental research, based on applicability, such as the use
of a state of the art technology or strategy based on the physical
setting of the project
Level 2
Design decisions based on predictive performance and
measurable outcomes, rather than subjective decisions based on
random choice.
Level 3
Results reported publicly, with the objective of moving
information on the methods and results moving information
beyond the design team.
Evidence-Based Design for
Multiple Building Types By Kirk
Hamilton
Start with problems. Identify the problems the project is trying to
solve and for which the facility design plays an important role
(for example, adding or upgrading technology, expanding
services to meet growing market demand, replacing aging
infrastructure
Encourage simulation and testing, assuming the patient's
perspective when making lighting and energy models and
computer visualizations.
A white paper from the Center for
Health Design identifies ten
strategies to aid EBD decision-
making
Evidence-based Design
20. Principles of
Evidence-based Design
Good design solves problems1
4 Good design is an experiment
5 Good design is iterative
3 Good design is measurable
Good design is research6
Good design is curious9
Good design is confident10
Good design listens7
Good design enables user control8
2 Good design does no harm
21. Two core principles have
survived
Good design solves problems1
2 Good design does no harm
22. Problems
The Physics of ROI. Value is created in
proportion to the size of the problems you(r
design) solve(s) for your customers.
Value goes up as problems go down.
As problems go down, value goes up.
Value
Problems
Value
Problems
23. Problem
Solution
Mapping
A unifying framework for optimizing user experience around
a common set of goals, problems, and solution hypotheses —
researched and validated with data.
problems
goals
product roadmap
design
hypotheses experiments outcomes
25. Goal
Increase view cart to checkout clicks by
15%.
Problem
There are too many prominent actions
that encourage people to pursue lower
value actions on the view cart page.
Hypotheses
I believe if we remove the distraction of
banners and buttons, the promo code
form, reduce h1 copy size and introduce
additional payment options, users will
be more likely to click checkout.
A Wolverine World Wide Case Study
v0
26. v1v0
Outcome
Despite (because of) the many
changes, we found only a slight
uptick in checkouts at low
confidence interval.Additionally,
orders were flat across the control
and variation.
We also found a disproportionate number of
people clicking on the checkout with Amazon
option, which was prioritized in the variation.
A WolverineWorldWide Case Study
27. v1
A WolverineWorldWide Case Study
Goal
Increase view cart to checkout clicks by
15%
Problem
The CTAs on the cart are
distracting.
New Solution Hypothesis
I believe if we iterate on the last
variation by adding back a “Continue
Shopping” option, display an open
promo code form and “right size” the
Amazon pay option, users will be more
likely to click “Checkout.”
New Problems
By removing “continue shopping,”
makingAmazon pay prominent and
collapsing the promo code box, we
created net new problems for many
customers.
28. v1.1v1
Problem Solved!
We found that nearly 4% more users
proceeded to checkout (with 99%
confidence) and 8% more users
completed their purchase (95%
confidence) when we solved more
problems than we created.
A WolverineWorldWide Case Study
35. How conversion
optimization can hurt
your business
• Faster but less valuable purchases
• Less qualified conversions
• Shifting from left to right pocket
• Pleasing few but frustrating many
• Easier to buy but harder to explore
38. This exposes three truisms:
Optimization is
misorganized and
misconceived in most
businesses.
Many businesses practice
conversion optimization
but NOT experience
optimization.
Conversion optimization
does NOT equal
experience optimization.
40. Experimentation Personalization
Maximization
A B C 2
MVT ABN Targeting Customization Algorithmic
multivariate a/b testing
cherry
picking
User segment
or
A
1
?
B
C
D
E
F
C
B
A1 A2 A3 A4
B1 B2 B3 B4
C1 C2 C3 C4
D1 D2 D3 D4
21 3
A
41. The Ocean of Personalization
The Beach of
Personal Experiences
42. Don’t start here Start here
Buy new tech
//
Build a data layer or lake
//
Golden view of a customer
//
You have to have smart segmentation
//
You have to engineer for dynamic 1:1
experiences
The experience
//
The relevancy problem
//
The user’s control
//
The conversation
//
Knowing vs guessing
43. The Beach of Personal Experience Design
User Control
Conversation
Implicit
Explicit
Content
UX Design
Data & Signal
In
Content &
Experiences
Out
44. Personal
Experience
Design is...
A personal experience is one that listens to the user
implicitly or explicitly and uses those signals to
adapt content and experiences for greater relevancy
or personal utility.
Good personal experience design values
transparency, user control and conversation.
48. Conversion
Optimization is a
constrained concept.
Experience Optimization creates
value by solving Problems MOST
Worth Solving.
Design and
Experimentation are
not assimilated in
organization or
process.
Evidence-based design unifies both
in thinking and practice..
Conversion
Optimization is a
constrained concept.
Experience Optimization creates
value by solving Problems MOST
Worth Solving.
Personalization is an
unswimmable ocean
of data and tech.
Personal Experience Design is the
beach for relevance and
conversation.
Design and
Experimentation are
not assimilated in
organization or
process.
Evidence-based design unifies both
in thinking and practice.