Event: SoCal UX Camp 2016 Presented by: David LaFontaine This is a hands-on exploration on how to move beyond the basics with Google Analytics. Why should designers have to deal with all these confusing spreadsheets, numbers, charts and graphs? Well, without at least a decent grasp of how to read web analytics, creative professionals are going to continue to lose control of their creations, because to decision-makers, the charts and graphs and spreadsheets seem to be the very essence of unassailable logic. Worse,designers will lose out on the opportunity to make what their sites better, by gaining insights into the needs, desires and motivations of their users. Too many digital experiences are being carefully crafted by UX Designers to "surprise and delight" users -- only to lose that human essence at the end, when final decisions are made, based solely upon surface-level analysis of audience behavior. It need not be so. In fact, we desperately need to start putting the "human touch" back into what we create. Because the alternative is just so much over-processed brainmush. Slideshows, listicles and clickbait are not what we were put on this earth to create nor consume.

1. Analytics
(AKA “Everything you ever wanted to know
about Google Analytics, but were afraid to ask
(so you made the intern do it)
Apropos that this is
At the end of the day

7. What we will learn today
1. Why should designers have to deal with
web analytics
2. What should I be looking for in the
analytics?
3. How do I customize things so I only see
what I need to see, instead of all that
clutter?
4. What is a “Creative Data Scientist”

8. Special Bonus
How scammers selling fake magic swords in
online games are used by data scientists to
catch money-launderers and drug cartels

9. Do we really hafta learn analytics?

10. Analytics
“Every decision is driven by data.
Everyone in the company is aware
of it. You’d get laughed out of a
meeting if you proposed
something that didn’t have data
to back it up.”
--Alan Resnikoff, FanDuel,
Giant Creative Holdings

12. When numbers alone rule…

14. I guess that’s a
solution…

15. When creatives are unchecked…

17. Early Analytics
In the 20s, newspaper owners were so desperate to figure
out what people were actually reading that they hired
private detectives to shadow them and look over their
shoulders. Or even to collect the papers at the end of the
tram ride, to see what page the paper was open to.
Of course, back then, people had rather … different
habits with regards to chewing tobacco and spitting...

18. What Gallup did…

19. What people say...
0
10
20
30
40
50
60

20. What analytics tell us they do…
• Less than 25% of the people even look at pg. 1
• Nobody – but nobody – likes quality content as
much as they say. Front-page stories were read
as much as the stuff on the back page.
• The most read: a comic strip. Read by 90% of
the male audience.
• For women, the most-read were the style
section and red-carpet photos of celebs

22. Led astray by the data...
Al Jazeera America believed the polls &
surveys that INSISTED that 40-50 million people
in the U.S. wanted in-depth journalism.
They spent $500 million to build a newsroom &
TV channel to deliver high-quality, original
content for this mass audience.

23. Less than
20,000 avg.
audience
“Observer
Effect”

24. Users are like children
They say: They do:
• Stuff themselves with
candy

25. Left-brain Thinkers
Logic, analysis, linear, sequencing,
thinking in words, organizing facts,
pattern recognition
(Image source Paul Downey, Creative Commons)
Right-brain Thinkers
Imagination, feelings, visualizations,
intuition, creativity, rhythm and tone,
sensations
(Image source: Jamiecat, Creative Commons)
Bridging the Great Divide

26. Analytics will not turn you into
an android
Image source: March Barkowski, Creative Commons

27. Data-Driven
Decisions made only based upon
statistics, which can be misleading.
Data-Informed
Decisions made by combining
statistics with insight and your
knowledge of human wants & needs.
Analytics shouldn’t kill creativity
Image sources: Creative Commons

28. This is not our future

29. 2. WHAT TO LOOK FOR…
Please excuse the bouncing back and forth from the browser
to the presentation. If you have access to analytics, feel free
to follow along

30. Graphs
Reporting View Nomenclature

31. Data TablesGraphs
Reporting View Nomenclature

32. Data TablesGraphs
Dimensions
Reporting View Nomenclature

33. Data TablesGraphs
MetricsDimensions
Reporting View Nomenclature

34. Otherwise known as “those little squiggly lines that
look like stock-market reports.” You can change these
to be bar charts or dynamic motion charts.
Graphs

36. The part of the Reporting page that looks like an Excel
spreadsheet. This is broken down into rows, columns
and cells.
Data Table

38. A dimension is a characteristic of your user, their
sessions or their actions that is being tracked. An
example would be the kind of device, geo-location,
date, landing page, etc. So, for example, you could use
dimensions to narrow down what people using iPhones
in Peru last month came to the tutorials page. You can
see what dimensions are being displayed – and add
other secondary dimensions by using the menus and
drop-down list.
Dimensions

40. A metric is the quantitative measurement you’re
choosing. Examples would be time spent on site,
language spoken, bounce rate, pages per session, etc.
You can select or stack the metrics by making a
selection in the drop-down menus above the graphs.
Metric

42. X-ray vision
Connect numbers to humans
Not all traffic is the same
Conversion v. engagement
What do your users do, and why
do they do it?

43. When your audience converts from being just a passive
websurfer into something more valuable by taking an
action (buying, signing up, subscribing, donating, etc.)
Conversion

44. What you point to when your site doesn’t convert users
into paying customers
Engagement

45. What you point to when your site doesn’t convert users
into paying customers
Engagement

46. Forming a connection with your audience, so that they
form a bond with your brand and your content.
Engagement

47. Conversion
A one-time interaction. Granted, this is
a powerful interaction, but it is the end
goal of a chain of events.
Engagement
Repeated use, that results in an
emotional, psychological and
sometimes near-physical tie that users
have to products.
Conversion v. Engagement

49. Who
The Art of Asking Questions

50. WhatWho
The Art of Asking Questions

51. WhenWhatWho
The Art of Asking Questions

52. Where
WhenWhatWho
The Art of Asking Questions

53. How muchWhere
WhenWhatWho
The Art of Asking Questions

55. 1. Look for top-level outliers
2. Mix & Match (‘segmenting’)
3. Go to pages & look for issues
1. Technical
2. Content & Design
4. Look at User Flow
Methodology

56. Use your “designer’s eye”

57. Use your “designer’s eye”

58. Part 3: Customizing your analytics
• You can build your own segments,
views and reports

60. Pre-rolled alternate views
• Like the open-source community,
there are thousands of users out there
who have been grinding away at
Google Analytics, coming up with their
very own “take” on what’s important

63. Handy tip: regular reminders
• Yes, we all get busy, and forget to
check the numbers.
• Luckily, you can set up regular emails
so these reports show up in your email
in-box

65. Analytics + Art = Creative Data
Scientist
You

66. Google Analytics Cheat Sheet
For more on Google Analytics
for Creative Professionals, email
dave@davidlafontaine.com
and you’ll be notified when this
e-book is published.