This presentation is an introduction into data driven design. It provides you with some basic knowledge about Google Analytics. And shows how to use Google Analytics to evaluate your implemented designs. Read the full article on: http://www.sodastudio.nl/kennis-ideeen/google-analytics-data-driven-design-presentatie

1. HowtouseGoogle
Analyticsfordata
drivendesign
an introduction into Google Analytics

2. Inthispresentation
This presentation is an introduction into data driven
design. It provides you with some basic knowledge
about Google Analytics. And shows how to use Google
Analytics to evaluate your implemented designs.
After this presentation you are familiar with the
glossary of (Google) Analytics. You will be able to gain
relevant data from Google Analytics. And we provide
you with some basic takeaways to implement data
driven design in your projects.

3. Tableofcontent
• Part 1: Data driven design? A short introduction.
• Part 2: Google Analytics: The who, what & where.
• Part 3: How to use in a project: setting up your data for
succes.
• Part 4: Analytics myths: busting some misconceptions.

4. Part1
Datadrivendesign?
A short introduction

5. understand the data and applying it for the betterment of product
and consumer understanding.
We, as webdesigners, have a desire to move forward in the right way.
To make sure that the right decision is made we try to

6. Whatisdatadrivendesign?
• Quantitative vs Qualitative data
• Track, track and track some more.
• Numbers leave patterns, patterns tell stories
• Understanding opportunities vs issues

7. 1.
Quantitative data shows the who, what,
when and where. Qualitative is non-
numerical data that demonstrates the
why or how.
Quantitative vs Qualitative

8. 2.
When it comes to data-driven design, the
more data you have at your disposal the
better; but only when that data is
organised and manageable. Make sure
you’re tracking your most important
webpage elements (e.g. buy now button)
first.
Tracking data

9. 3.
Start by looking at the data you have.
Whether this is web page visits, goal
completions or customer feedback. Look
for common occurrences and try to
correlate these numbers (e.g. a high exit
rate in a sales funnel and a lot of users
that enter the information page may
indicate an issue).
Numbers leave patterns, patterns
tell stories

10. 4.
By assessing and ranking issues and
opportunities together, you can begin to
identify where to add more research
effort and which to work on first.
Opportunities vs issues

11. The who, what and where
Part2
Googleanalytics

12. Due to the vast amount of features it has become the most used
Why Google Analytics?
It’s a free and powerful tool that provides a lot of quantitative data.
web analytics tool.

13. Glossary

14. The user’s activity on your site (including just the loading of a single page).
Bounce
The number of times a visitor enters a domain on a page but leaves before viewing any
other page in the domain, divided by the total number of views of that page. Also
generally expressed as a percentage.
Bounce rate
An activity carried out by the user which fulfils the intended web page purpose
(product purchase, download, newsletter subscription etc.)
Conversion
Google Analytics uses a lot of terms that need some explanation to fully
understand what the data is telling you. So here is a short but
comprehensive glossary of the metric terms used in Google Analytics
Glossary

15. The total number of pages viewed. Repeated views of a single page are counted.
However, for an accurate number, it’s important to look at unique pageviews because a
single visitor can trigger multiple pageviews in one session.
Page views
The average number of pages viewed during a visit to your site.
Pages/Session
A page is loaded or reloaded by a user.
Page impression
A group of interactions a single user has within a given time frame on your website.
Sessions
The number of times a visitor leaves your domain from a page, divided by that page’s
total views. Generally expressed as a percentage.
Exit rate
The number of times visitors entered your site through a specified page or set of pages.
Entrances

16. The total number of distinct devices that have accessed your site.
Users
The percentage of visits that were first time visits (from people who had never visited
your site before).
New sessions
The total number of visits to your site, from unique or repeat visitors.
Visits
The number of unduplicated visitors to your website over the course of a specified
time period.
Unique visitors

17. Navigation

18. The Google analytics interface can be quite a
daunting thing to understand. In the following
slides we will explain where what kind of
information can be found.
Navigation

19. Dashboard
Create your own custom
dashboard with widgets.

20. Intelligence Events
Custom alerts for specific
events (change in number of
sessions, conversions, etc..).

21. Real-Time
Pretty self-explanatory…

22. Audience
Who (demographics, location,
devices, etc..) has viewed your
website.

23. Acquisition
How did the visitors navigate to
your website? Which channels
did they use?

24. Behavior
What did the visitors do on
your website? E.g. navigation
flows and search queries.

25. Conversions
Did they convert? Which route
did they take and how much
time did they spend on
reaching their goal?

26. Crunchingnumbers

27. It’s possible to add another layer of
information to most of the graphs & tables by
adding a segment. This will make it possible to
compare multiple types of information.
E.g, in the following slides we show how to add a segment to
compare all sessions (all traffic) with the mobile- and tablet traffic.
Adding segments

28. Step 1
Audience
(You can add segments to each
of the information categories).

29. Step 2
Select: ‘Add Segment’

30. Step 3
Select the type(s) of information
you wish to view in the graph /
table.

31. Step 4
Analyse the data.

32. Importsegments

33. Lots of custom made segments are available
from the Google Analytics community. These
segments can be imported and can give new
insights in your data, such as additional info
about social media traffic or the level of
engagement.
Import segments

34. Step 1
Select: ‘Add Segment’

35. Step 2
Select ‘import from gallery’

36. Step 3
Select ‘import’ for the desired plugin

37. Filtermetrics

38. Filters allow you to isolate certain results in
the data charts. E.g. these filters can be added
to find pages with a high bounce rate, low exit
rate or a high page value.
In the following slides we show how to add a filter to find all
pages with a bounce rate less than 60%.
Filter metrics

39. Step 1
Select: ‘Advanced’

40. Step 2
Select include or exclude
and the value type (e.g.
exit rate, bounce rate,
unique pageviews).

41. Step 3
Select: ‘Advanced’

42. Step 4
Select value and apply

43. Step 5 (optional)
Add a segment to further
focus your data.

44. Goals

45. Goals measure how well the site or app fulfils
a target objective (convert). Google Analytics
defines micro goals (e.g. step 1 in a sales
funnel) and end goals (e.g. checking out).
Goals

46. With a destination goal (e.g. buying a product)
you can specify the path you expect the
traffic to take. You can view information about
this funnel in the Goal Flow and Funnel
reports.
In the following slides we will show you a couple of ways to view
the goal data in Google Analytics.
Destination goals

47. Conversions page
This example shows all the completion
data in one graph and one table. A bit
messy in my opinion. Luckily there is
another way to view this data..

48. Funnel visualisation
Shows all the stats about the sales funnel
in one easy to understand page!

49. Micro goal #1
Amount of completions of the
first micro goal (e.g. first step of
the funnel)..

50. Micro goal
Open the dropdown to view
another micro goal timeline.

51. Funnel visualisation
This shows the conversion
rate and the amount of
people that enter and leave
each step of the sales funnel.

52. Setting up your data for succes
Part3
Howtouseinaproject

53. Thingtotakeinconsideration
• Key to succes: be specific
• Focus your efforts
• Develop a common language
• Quantitative & qualitative
• The definition of succes is not always the same
• Keep your data clean

54. The best kind of data is the kind that answers
a specific question that can lead directly to a
change in design.
E.g. questions such as “how is the website
performing?” won’t help you to improve your
designs. Questions such as “in which step of
the sales funnel do mobile visitors drop out?”
are much more specific.
Key to succes: be specific

55. You can’t isolate variables when looking
across big aggregated metrics (e.g. overall page
views or downloads). This makes it difficult to
draw conclusions from your data.
Key to succes: be specific

56. “All data in aggregate is crap”
– Avinash Kaushik

57. Analysing data can be resource-intensive.
Don’t just track pages and elements.
Always use specific, empirical data — don’t
offer “high-level” metrics. Find data points that
answer specific design questions and, thus,
illustrate whether design or content changes
worked.
Focus your efforts

58. Develop a common language with the
analytics tool and your project team.
Educate your team so that they understand
the importance of metrics.
Develop a common language

59. Use quantitative and qualitative data together
while redesigning a page. Qualitative data will
help you to answer the ‘why’ of the
‘what’ (quantitative data).
Quantitative & Qualitative

60. Take the goals of individual pages and
different users into consideration. A returning
visitor might have different needs from a new
visitor, a redirected visitor might have different
needs from a visitor from an organic search.
The definition of succes is not always the same

61. Polluted data will affect your design choices.
Exclude your own traffic from reports and
install spam blocking plugins to prevent (SEO)
spam traffic filling up your data reports.
Keep your data clean

62. Busting some misconceptions
Part4
Analyticsmyths

63. Often people assume the bounce rate
represents people who land on your site and
leave straightaway. However, the number
indicates the percentage of visitors that leave
your website without visiting another page. So
for single page websites a high bounce rate is
inevitable.
A high bounce rate is an awful thing

64. The unique visitors count the number of
cookies dropped in a browser. Often people
assume this shows the amount of people (and
therefore size of audience) that are engaging
on their website however this metric cannot
indicate unique browser or even computers.
Unique visitors are people

65. The average visit duration report
underestimates the actual time sped on a site.
The calculation used does not account for the
time sped on the last page they view before
leaving the site. So this report shows the
average time sped navigating the site.
Average Visit Duration reports shows
how long people spend on a site.

66. Direct traffic shows the traffic from sources
that are not indexed by search engines like:
emails, instant message services, links in
offline documents, redirect pages, bookmarks
or a javascript link.
Direct traffic comes from typing the address
into an address bar

67. Inconclusion

68. Conclusion
• Analytics are a great way to get information about the
performance of a web service.
• Be specific, gather your data empirically.
• Always use the quantitative data in combination with
the qualitative data for the best results.

69. Statisticsmaybedull,
butithasitsmoments.
Questions? E-mail me at mark@sodastudio.nl
Good luck!