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@jmspool
Jared M. Spool
Is Design 

Metrically Opposed?
@jmspool
Jared M. Spool
Is Design 

Metrically Opposed?
1Are we
measuring the
right thing?
@ @ @ @ @ @ @ @ @ @ @
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33 Email Addresses
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77 Email Addresses
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33 Email Addresses 77 Email Addresses
More email addresses are better
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All email addresses are equal
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More email addresses are better
All email addresses are equal
Inferences
Observations
Inferences
Observations
Design DecisionsInferencesObservations
Design Decisions
Inferences
Observations
Design DecisionsInferencesObservations
More email
addresses are
better
2nd variant had
more email
addresses
Use 2nd variant
Design DecisionsInferencesObservations
Why we think
it happened?
What did we
see?
How will we
improve the
design?
Log file filled with “ ” (blanks)
Enter button focus was broken
Didn’t enter any search text
Was looking for advanced search
Log file is broken
Design DecisionsInferencesObservations
Broken focus
Log file
contained
blanks
Fix Focus
No search text
Advanced
search
Log file bug
Add label to
search box
Build advanced

search feature
Fix bug
The best designers
never stop at the
first inference.
Log file
contained
blanks
Design DecisionsInferencesObservations
Broken focus Fix Focus
No search text
Advanced
search
Log file bug
Add label to
search box
Build advanced

search feature
Fix bug
Users didn’t
know to
type query
into box
Log file
contained
blanks
Research turns
inferences into
observations.
2Useless
measures &
silly metrics
SnapChat AirBNB Uber Facebook
MarketValuation
InstancesofletterEonhomepage
Counting the letter E is a stupid metric.
Measure:
Metric:
Analytic:
Something we can count.
A measure we track.
A measure software tracks.
Time on page
Time on page
Bounce rate
% Exit
Pageviews
Sessions w/search
Time after search
% Search Refinements
Bounce rate
What should we do differently?
“
R.H. Coase,
British economist
If you torture data
long enough, it will
confess to anything
you’d like.”
What Google Analytics
can’t tell you:
‣What content was useful?
‣What people found confusing?
‣Who is your site’s biggest spender?
‣What do big spenders do that others don’t?
‣What should you do to improve your content?
‣Why did someone click?
What Google Analytics
can’t tell you:
Why?
Conversion Rate
M
MATHEMATICAL CONTENT
CONTAINS SOME FORMULAIC MATERIAL

MAY BE INAPPROPRIATE FOR DESIGNERS
THIS PRESENTATIONHAS

Conversion Rate
Conversion Rate
# of people who purchase
# of people who visited
=
1.0 %
10,000
1,000,000
=
Conversion Rate
# of people who purchase
# of people who visited
=
Conversion Rate
1.0 %
10,000
1,000,000
=
2.0 %
20,000
1,000,000
=
2.0 %
10,000
500,000
=
10,000
Conversion Rate
1,000,000
=
1,000,000
=
500,000
=
10,000
=
x $100
$1,000,000
20,000 x $100
$2,000,000
=
=
10,000 x $100
$1,000,000
1.0 %
2.0 %
2.0 %
10,00010,000
20,00020,000
10,00010,000
Conversion Rate
20,000
1,000,000
=
10,000
500,000
=
$2,000,000=
= $1,000,000
20,000
10,000
2.0 %
2.0 %
What should we design for?
$2,000,000
$1,000,000
2.0 %
2.0 %
Conversion Rate? Money?
Conversion Rate
Conversion Rate
# of people who purchase
# of people who visited
=
Visit Visit Visit Purchase
Conversion Rate = 25 % ?
Conversion Rate = 100 % ?
What conversion rate can’t
tell you:
Why?
Delightful
Amazing
Awesome
Excellent
Remarkable
Incredible
Satisfactory
Satisfactory
Edible
Achieving satisfaction
is too low a bar to set
for our designs.
We can do better.
Satisfied
Satisfied
Neutral
Dissatisfied
Dissatisfied
Extremely
Somewhat
Somewhat
Extremely
SatisfactionSurveyScale
DelightedExtremely
DelightedSomewhat
FrustratedSomewhat
FrustratedExtremely
Satisfied
Delight/FrustrationSurveyScale
Pro tip:
Nothing says “we
don’t care” like a
page of 10-point
satisfaction scales.
10-point scales make
noise feel like
science.
What satisfaction surveys
and Net Promoter Score
can’t tell you:
Why?
We need metrics that
help us improve our
users’ experience.
3A measured
experience.
Customerjourneymap
☺
☹
Searchingforahotel
Reviewingtheproperty
Reviewingroomrates
Startbooking
Guestinformation
Billinginformation
Paymentinformation
Confirmbooking
Done!
☹
Thingsusersfindfrustrating
Content that is confusing
☹ Incomplete information
☹ Can’t remember password
☹ Hidden features
☹ Hidden navigation
☹ Confusing navigation
☹ Error messages
Thingsthatusersfindfrustrating
Phone numbers can’t have dashes or spaces.
☹ Error messages
The credit card security code is required (again).
Username and password do not match.
Pro tip:
Customize analytics
by counting error
message deliveries.
Case study:
Improve checkout process for a 

major e-commerce site.
Shippinginformation
Billinginformation
Paymentinformation
Confirmpurchase
Done!
100%
50%
Pageviews
Shippinginformation
Billinginformation
Paymentinformation
Confirmpurchase
50%
Pageviews
Shopforproduct
ReviewShoppingCart100%
Done!
Shippinginformation
Billinginformation
Paymentinformation
Confirmpurchase
50%
Pageviews
Shopforproduct
ReviewShoppingCart
Logintoaccount
Requestpasswordreset
Clickonlinkinemailtoreset
Putinnewpassword
100%
Done!
Shippinginformation
Billinginformation
Paymentinformation
Confirmpurchase
50%
Pageviews
Shopforproduct
ReviewShoppingCart
Logintoaccount
Requestpasswordreset
Clickonlinkinemailtoreset
Putinnewpassword
100%
Done!
Lost revenue from
account sign-in issues:
$300,000,000per year
The team built a guest checkout (no sign-in required).
Recovered the $300,000,000 within 1 year.
Qualitative usability research
$300,000,000
Quantitative custom metrics
+
Mostimportantcustommetric:
Unrealized shopping cart value from password issues.
Qualitative findings
must drive our
quantitative research
agenda.
The team’s initial
inferences
‣The checkout steps were where we’d find the
biggest improvement.
‣It was “normal” to lose customers before checkout.
‣Cart review went straight to checkout without
additional steps.
‣All of the screens were instrumented.
Shippinginformation
Billinginformation
Paymentinformation
Confirmpurchase
50%
Pageviews
Shopforproduct
ReviewShoppingCart
Logintoaccount
Requestpasswordreset
Clickonlinkinemailtoreset
Putinnewpassword
100%
Done!
Shippinginformation
Billinginformation
Paymentinformation
Confirmpurchase
50%
Pageviews
Shopforproduct
ReviewShoppingCart
Logintoaccount
Requestpasswordreset
Clickonlinkinemailtoreset
Putinnewpassword
100%
Done!
☺
☹
Focus quantitative research on frustration.
Observations trump
inferences.
“Analytics are controlled by a
different group.”
Nolongeracceptable:
Owned by the UXTeam
Owned by theAnalyticsTeam
Under new management: the
UX Team
DJ Patil, Former US Chief Data Scientist
“Analytics are controlled by a
different group.”
Data science is now an essential
skill for every UX team.
Nolongeracceptable:
Continually question what the
metric is trying to tell you.
Nolongeracceptable:
“I don’t understand what the
metrics mean.”
Keep the numbers simple,so you
can focus on the behaviors.
Nolongeracceptable:
“I’m not good with numbers.”
Applying targeted
metrics to qualitative
research: a powerful
addition to the UX
designer’s toolkit.
4Who collects
the metrics?
Design:
The Rendering
of Intent
Myspace
MonthlyActiveUsers
Market Valuation
Pinterest
Whatsapp
Snapchat
LinkedIn
Twitter
YouTube
Tumblr
Instagram
0
1,000,000,000
$0 $40,000,000,000
“
Robert Fabricant
The medium of
design is behavior”
Design must drive
metric collection, not
the other way around.
Is Design
Metrically Opposed?
‣We need metrics that help us improve the experience.
‣Avoid jumping from observations to inference too soon.
‣ Make sure you’re testing alternative inferences.
‣Customize metrics to match experience objectives.
‣Data science is now an essential UX skill.
@jmspool
Go ahead! Follow me on the Twitters.
jspool@uie.com
Find me at:
Copyright © 2015 User Interface Engineering
Don’t forget to connect to me on the LinkedIn.
uie.com

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