This document provides an overview of developing an effective analytics strategy, covering key topics such as: - Understanding why an analytics strategy is important for gaining insights from data - Defining the right questions to ask of your data to address business objectives - Implementing the right metrics and processes to optimize performance based on data - Ensuring the right technology, data, people and culture are in place to execute the strategy - Tips for reporting data to different stakeholders and developing the right analytics team The presentation emphasizes that an analytics strategy should start by defining business goals and questions, and focus on using data insights to drive tangible improvements rather than just reporting metrics. Both qualitative and quantitative data are important to

1. Your Smarter
Data Analytics
Strategy
Clark Boyd, October 2017

2. Hello!
I’m Clark Boyd
I am a digital marketing
consultant and I’m here to
talk analytics strategy.
You can find me at:
@clarkboyd
clarkboyd.digital

3. 1.
What We’ll Cover
Today

4. Our Agenda
◎ Why do you need an analytics strategy?
◎ How analytics works
◎ Defining the right questions
◎ You can’t optimize what you don’t measure
◎ Putting it into practice
◎ Culture ≥ technology
◎ The people & skills you need
◎ Key tips and takeaways

5. 2.
The Importance of
an Analytics
Strategy

6. 499,999,999,999
Moments processed by Google Analytics each
day

7. What Analytics Can Tell Us
● Which channels drive the most conversions?
● What are your leaking buckets (places where people leave
your website)?
● Whether people use multiple devices before purchasing
your products?
● What are the look-to-buy ratios for your individual products
and product categories?
● What landing pages need to be improved and in which
channel?

8. Why We Need a Clear, Documented Strategy

9. The Main Analytics Strategy Challenges

10. The Main Analytics Strategy Challenges

11. The Main Analytics Strategy Opportunity

12. Categories of Analysis

14. Predictive Analytics in Action: Fort Defiance

15. Prescriptive Analytics in Action: Hopper

16. Adaptive Analytics in Action: Walmart

17. The Three Core Elements of an Analytics Strategy
TechnologyData People

18. “
Analytics is not about dashboards.
It is about driving tangible
improvement against business
outcomes.

19. 3.
How
analytics
works

20. The Hierarchy of User-Session-Hit

21. Adobe vs. Google Analytics Terminology
Source: SEER Interactive

22. JavaScript Code
Event Hit

23. Hits are a Subset of Sessions

24. Sample Code For A ‘Hit’

25. Cross-Domain Tracking

26. Standard Analytics Dimensions

27. Dimension-Metric Pairings
https://developers.google.com/analytics/devguides/reporting/core/dimsmets

29. 4. Defining the
right
questions.

30. “
Data without context is
meaningless.
Web Analytics 2.0

31. Analytics and Attribution

32. Analytics and Attribution
Analytics
Tells us where visitors came from, how long they spent on site,
which products they browsed or purchased.
Attribution
Helps identify patterns and trends across all marketing channels and allows
us to give value to the contributions of each activity.

33. Irrelevant Data

34. Confusing Data

35. “
Where is the knowledge we have
lost in information?
T.S. Eliot

36. Examples of Good Questions
● How can we deliver a better experience for customers on a
mobile device?
● Are we creating products that align with modern consumer
demand?
● Do customers return to our site to make a purchase after
viewing our blog content?
● Does my direct mail activity affect traffic levels from
specific territories?

37. Areas of Investigation
Potential Issue Example Questions
Data Sources
- Where does our data come from?
- What data do we need to address our
challenges and objectives?
Data Quality
- Is the data structured or unstructured?
- Are there gaps in the data sets?
Data Governance
- Who is responsible for managing the data?
- What data privacy issues do we need to
tackle?
Internal Processes
- How can we evaluate the effectiveness of
our analytics strategy? Is relevant data
available?

38. Natural Language Processing

39. Tip: Work Backwards to Gain Insights

40. Objective: Improve content marketing
effectiveness
Goal Question Answer
Generate more
traffic from our
content editorial
calendar
When do people
engage with our
content?
Visits/shares by day
and time of day

41. Objective: Move into New Markets
Goal Question Answer
Identify and
capitalize on
international growth
markets
In which territories
do people engage
with our site and
buy products?
Pages per session by
country; sales by
territory

42. The Process for Defining ‘Good’ Questions
1. Business
Objectives
2. Digital
Goals
3. Campaign
Measurement

43. Analytics:
Opportunities and
Frameworks

44. Dimension-Metric Pairings

45. The Analytics Strategy Framework
Source: PwC

46. Putting the Plan into Action
Source: PwC

47. 5.
You Can’t Optimize
What You Don’t
Measure

48. What we see
Typically, we look
at a dashboard or
just a few key
metrics.
What exists
However, analytics
can tell us so much
more about what
really drives people
to make decisions.
We just need to
know where to
look.

49. Deciding on KPI’s
KPIs have to be structured:
● to provide insight on the right business questions
● to define responses to deviations
● to build consensus on the metrics to be tracked
● to align analytics process to the right business teams

50. An Essential (but tricky) Metric

51. RFM Analysis
Source: Blastam

52. Implementing CLV

53. Client ID versus User ID
Google will
automatically assign a
Client ID to each device.
That brings with it
some measurement
challenges.
However, there is an
option to implement a
User ID.

54. Implementing User ID Tracking
1. Enable User ID at the property level of Google Analytics and
create a User ID view
2. Include information in the site’s privacy policy. Website
owners are required to inform visitors that User ID
information is being tracked but is not personally
identifiable.
3. Set the User ID to track on all authenticated sessions. This is
where help is needed from a developer to tag all pages on
the website
4. Ensure sure the User ID is not recording when users are not
logged in.

55. Macro and Micro Conversions
◎ Sales
◎ PDF download
◎ Video view
◎ Time on page
◎ Pages per session
◎ Sessions by source/medium

57. Measurement Pitfall No. 1: Bounce Rate

58. Solution: Scroll Depth Tracker
http://scrolldepth.parsnip.io/

59. 6.
Putting it into
practice

60. Connecting Analytics with BI Tools

61. Connecting Data Sources
Google Analytics has four scopes that data can live at: User, session, hit (page
and/or event), or product. A data connection will also exist at one of these four
scopes.
Marketing tools like campaign management software or email remarketing
will almost always want to connect at the Session level. In Google Analytics,
traffic sources and campaign data are session-scoped.
User data such as a CRM or a customer database will almost always want to
connect at the User level. A/B tests are usually user-scoped as well, since the
same user should be served the same test on consecutive visits. Surveys may
be user-scoped or session-scoped, depending on the type of questions being
asked and whether it’s specific to the user’s current visit to the site.
Picking the right scope is critical to making your reports work correctly.

62. Advanced Segments

63. Data Segmentation
User Type exactly matches “Returning User”
Country/Territory exactly matches “United
States”
Ecommerce Conversion Rate > "0.2%"
We base segments on the dimensions and
metrics in our Analytics reports; for example:

64. Adding Cohorts for Context

65. Mobile Paths to Purchase
There are also many ways
to segment your data to see
how device types perform.
Using ‘Path Options’ allows
us to see what role mobile
plays, beyond just bringing
more traffic over time.

66. Primary and Secondary Dimensions

67. Social Media Measurement

68. Content Marketing Measurement

69. Tip: Customize Channel Groupings

70. Content Marketing Measurement
Content groupings can help answer questions including:
● Which content delivers best against our business goals?
● Does our content gain traction over time?
● Can we say that content marketing has a positive impact on
SEO?
● Do social shares correlate with increased sales?
● When is the best time for us to promote our content on social
media?

71. Dealing with Data Sampling

73. GA Misunderstanding: Custom Segments

74. GA Essentials: Event Tracking

75. Turning Events Into Funnels

76. Tip: Download Tag Assistant
https://chrome.google.com/webstore/detail/tag-assistant-by-google/kejbdjndbnbjgmefkgdddjlbokphdefk?hl=en

77. Tip: Install the Chrome Extension
https://chrome.google.com/webstore/detail/page-analytics-by-google/fnbdnhhicmebfgdgglcdacdapkcihcoh?hl=en

78. 7. The
Attribution
Puzzle

79. Traditional Attribution Models

80. Assisted Conversions

81. Accurate Attribution: Getting Closer...

82. Data-Driven Attribution

83. The Challenges of Switching Attribution Models
● Expectations of channels are deeply ingrained; attribution
requires a willingness to adapt..
● Changing models means some channels ‘gain’ while others
‘lose’.
● No model is perfect, so we always have to accept that we are
going with the best available fit.
● It is important to frame attribution as a much more important
area of investigation than just digital marketing. Accurate
attribution gleans insight on our customers that we would
otherwise never know.

84. A Look to the Future

85. 8. Reporting to
different
stakeholders

86. “
Visualisation is the key to arriving
at profound insights, faster

87. Know Your Audience

88. Factors to Consider
◎ Frequency of report production
◎ Level of analytics literacy
◎ Content within report
◎ Structure
◎ Level of contextual analysis

89. ◎ Executive Dashboard

90. ◎ CMO Dashboard

91. ◎ Content Dashboard

92. ◎ Content Segment

93. ◎ Tech Dashboard

94. Customizing GA Dashboards
◎ Goals: Business objectives can be grouped into
one dashboard.
◎ Segments: Some stakeholders will want to zone
in on particular areas of activity or audience
segments.
◎ Content groupings: Show how different types of
content affect user behaviors.

95. Integrating Other Data Sources

96. Dashboard Examples
◎ Ecommerce dashboard
◎ Facebook dashboard

97. 9.
The Team

100. Data Has Become Everyone’s Job

101. “
A story has no beginning or end:
arbitrarily one chooses that
moment of experience from which
to look back or from which to look
ahead.
Graham Greene

102. The Core Elements of the Team

103. The Analytics Center of Excellence

104. Developing a Growth Mindset

105. Implementing an Analytics Strategy

106. Putting the Plan into Action

107. 10.
Key takeaways &
tips

108. Key takeaways: How to develop a
smarter analytics strategy
● Begin with the business objectives you want to deliver on and the questions
you want to answer.
● Data quality and data management are the building blocks of an analytics
strategy.
● Storytelling is an undervalued analytics skill. Think beyond the dashboard to
consider what the data tells you about your audience, then convey this
narrative using charts and graphs.
● Technology is essential, but so is culture. Analytics needs to be ingrained
throughout the organisation in concrete, tangible ways.
● Include a measurement plan that is ambitious but realistic, to demonstrate the
progress you have made.
● Document and share your analytics strategy with all relevant teams.

109. 2017 Gartner Magic Quadrant for Data Science Platforms
Scroll depth plugin
GA filters
Datorama: How AI is transforming marketing
Demo account
GA Chrome extension
Tag assistant
AI and predictive analytics
Some Handy Resources and Further Reading

110. Thanks!
Any questions?
You can find me at:
@clarkboyd
clarkboyd15@gmail.com