The document discusses how to effectively use Google Analytics for attribution modeling and outlines various tools like multi-channel funnels and data-driven attribution. It highlights the limitations of traditional attribution methods, such as ignoring offline impacts and cross-device behaviors, emphasizing the need for optimization through controlled testing. The author suggests using multi-channel funnels to analyze the role of different channels in conversions and advocates for tailored testing to improve campaign effectiveness.

1. Attribution with Google Analytics.
How to do it… and why you shouldn’t!.
Dara Fitzgerald
Head of Insight
www.freshegg.co.uk
@darafitzgerald

2. Multi-session conversion analysis.
The tools available.

3. The tools available.
• Multi-Channel Funnels
• Attribution Modelling Tool
• Data-Driven Attribution (Premium only)

4. Multi-Channel Funnels.
MCF includes assisted conversions metric.
43% of conversions are assisted here.

5. Multi-Channel Funnels.
• Conversion tracking required (Goals and/or Ecommerce)
• Ensure correct campaign tagging or the data is meaningless
• AdWords auto-tagging
• Manual campaign parameters (URL builder)
•
• utm_source
• utm_medium
• utm_campaign
E.g.
http://www.abc.com/?utm_source=mailer&utm_medium=email&utm_campaign=sep13

6. Multi-Channel Funnels.
Tailored
channel
groupings

7. Multi-Channel Funnels.
Assisted and last
are not mutually
exclusive!
i.e. channels can
assist & close the
same conversions

8. Multi-Channel Funnels.
Organic true assist
AND
Change to ‘include’ for organic self assist segment

9. Multi-Channel Funnels.

10. Multi-Channel Funnels.
PPC contribution

11. Attribution Modelling Tool.
Linear
Credit split evenly across the entire conversion path.
Time Decay
Credit reduces back from the point of conversion.
Position Based
First & last click heavily weighted; remainder split in the middle.

12. Attribution Modelling Tool.
Compare up to 3 different models

13. Data-Driven Attribution (Premium only).
• Algorithmic models
• Includes non-converting paths
• Transparency for model behaviour
• Channel weights are based on
the impact that channel has on
conversion probability
• Data from AdWords, GDN, DFA
and cost import are available for
ROI analysis

14. Data-Driven Attribution (Premium only).
Prove value of upper funnel activity
The dash indicates this channel
did not appear in this path position
% reflects the overall weighting of a
channel at a particular position in the path

15. What’s wrong with all this?

16. #1. Offline impact.
But purchase is
completed offline
Online campaign
drives awareness
Attribution = 

17. #2. Cross-device purchase paths.
A single user…
Purchases on
home laptop
Compares prices
on work PC
Browses on mobile
en route to work
Attribution = 

18. #3. The big issue.
Point of initial conversion
Acquisition
Display
Organic
CRM activity
PPC
Attribution focusses on acquisition only.
Email
Social
Retention is ignored.
It should focus on lifetime value impact.
Email

19. So, what should we be doing?

20. Optimisation through controlled testing.
• Audience profiling, segmentation and conversion path analysis inform
tests
• Testing is needed to determine causation. Customers predisposed to
purchase need to be separated from incremental effect of advertising
• Attribution tools don’t make decisions; they inform the tests that
determine decisions

21. Optimisation through controlled testing.
Control Group
100,000 visits
Test Group
100,000 visits
Normal exposure
100,000 visits
Normal exposure
90,000 visits (90%)
Test exposure
10,000 visits (10%)
2.0% conversion
= £100,000 net profit
2.1% conversion
= £94,500 net profit
3.0% conversion
= £13,000 net profit
Net per visit: £1
Net per visit: £1.05
Net per visit: £1.30

22. Optimisation through controlled testing.
• There are considerable challenges to this approach
• Splitting out test and control groups can be difficult and significant
samples are required
• The biggest issue is testing the impact of combinations of channels as it
is not easily possible to share targeting data across all channels.
• Remember testing should not be confined to acquisition channels but
should also apply to retention

23. Summary.

24. Summary.
• Use MCF to better understand each channel’s role in conversion. Form
hypotheses for testing
• Don’t mix different activities together, e.g. email newsletters and sales emails.
Customise channel groupings in MCF as much as possible
• Don’t treat all conversions as equal. Look at paths for different conversion types
separately
• Split true and self-assists for each channel and look at total channel contribution
• Universal Analytics promises to greatly enhance possibilities for Customer
Lifetime Value (CLV) measurement and optimisation
• Run controlled tests to determine incremental value

25. Thank You!
Dara Fitzgerald
Head of Insight
www.freshegg.co.uk
@darafitzgerald