The document provides an overview of an analytics guide covering fundamentals, intermediate, and advanced analytics topics. It includes sections on bounce rate, filters, devices, experiments, trends, attribution, conversion paths, and attribution models. The guide contains over 14,000 words and 73 tips across 8 categories and 3 levels to help users understand and leverage analytics features.

1. The A-Z of useful analytics
Kherrin Wade
Digital Media Account Director,
Adido
@digiKherrin
#letsdodigital

2. introduction to analytics
analytics alphabet concept
fundamentals
intermediate
advanced
agenda
questions

3. the analytics alphabet

4. the analytics alphabet…
…in numbers
75 man hours
14,654 words written
73 tips
63 pages
8 categories
3 levels
2 people
#passion

6. the guide
fundamentals
If you’re using analytics, you should at least be aware of
all these features and tips
For regular users of analytics who want to get that little
bit more into the detail
Key insights for the direct response marketer – taking
conversion analysis that little bit further
intermediate
advanced
setup
ecommerce
content
metrics / KPIs
audience
insight
traffic sources
goals / conversions

7. fundamentals

8. bounce rate
“The percentage of visitors who only visit one page during a session”

9. good or bad bounce rate?
All visits
60% bounce rate
Direct visits
25% bounce rate
Email visits
80% bounce rate

10. good or bad bounce rate?
All visits
68% bounce rate
Organic visits
68% bounce rate
Twitter visits
86% bounce rate

11. good or bad bounce rate?
All visits
95% bounce rate
Time on page
10:13

12. duration (avg. visit)
What is the purpose of
your website?
Does performance vary
by traffic source or
visitor type?

13. positive or negative
interpretation?
Time on site
5 minutes (High)
Avg. page views
7 (High)

14. positive or negative
interpretation?
Time on site
3 minutes (High)
Avg. page views
2 (Low)

15. positive or negative
interpretation?
Time on site
30 seconds (Low)
Avg. page views
1 (Low)

16. direct
Direct will only be credited with the goal
conversion (in GA standard reports) if it is
the only channel in a user’s journey to
conversion.

17. direct

18. filters
Should always have two analytics profiles (Views) setup for any website
1) Completely un-touched (no filters)
2) One with company IPs filtered out
Why bother?
 Testing
 100% data capture
 Prevent internal visits from skewing
site performance and decision making

19. New visit(or)s
• If you have a website, like an
industry blog, which has a high % of
new visitors you have to review why
it’s so high, because ideally you
would want returning visitors to
dominate.
• If you have an Ecommerce
website with a low % of new
visitors but you’re not generating
enough sales revenue, you should
assess you traffic sources and
campaigns to see how you can drive
more new visitors.

20. intermediate

21. annotations

22. devices

23. devices

24. devices

25. devices

26. devices

27. devices

28. experiments
Test different versions of landing pages (up to 5) to
improve performance in a controlled environment.
In an experiment you can control:
• the % of visitors who visit your test page(s) vs.
control page
• objective of the test – goal / ecommerce /
site usage
• test duration
• traffic sources entered into the experiment
(controlled by the URL).

29. trends
Comparisons give you context:
• look at the same data point over two time periods
• look at 2 data points in parallel
…to understand if the trends you are seeing are replicated across all metrics on your
site.
Data segmentation can provide reasons:
• identify which traffic source / campaign / keyword / device caused a shift

30. y?

31. advanced

32. attribution

33. conversion (goal) paths
Useful views for interpretation include:
• Looking at how often different traffic source
patterns emerge.
• Find out:
• How many visits come from the same source
• Which traffic sources drive more first visits or
last
• Discovering what keywords tend to overlap with
another traffic source or with other keywords
(either before or after each other).

34. conversion (goal) paths

35. conversion (goal) paths

36. conversion (goal) paths

37. model comparison tool
Last interaction – any last action visit to the site (any source can be credited)
– the default setting.
Last non-direct click - any last action visit to the site, except if the last action
was a direct visit. This is useful if you believe direct visits wouldn’t have
happened without other digital channel support.
Last Adwords click – when the last action was an Adwords click (useful to
compare against last action to understand the % of last clicks which were via
Adwords)
First Interaction – any first action visit to the site (any source can be
credited). This is useful if you’re running awareness driving campaigns and want
to attribute credit for this effort.
Linear – all actions in the user journey are given equal credit for the
conversion. This is useful if you believe each touch point in a user journey is
equally important.

38. who gets the credit?

39. who gets the credit?

40. who gets the credit?

41. who gets the credit?

42. who gets the credit?

43. who gets the credit?

44. who gets the credit?

45. who gets the credit?

46. who gets the credit?

47. who gets the credit?

48. who gets the credit?

49. who gets the credit?
1. Last interaction?
2. First interaction?
3. Last Adwords click?
4. Linear?
And, would you turn off
any channel?

51. questions?

52. Thank you
Kherrin Wade
Digital Media Account Director,
Adido
@digiKherrin
kherrin.wade@adi.do