Presentation from eMetrics London providing an alternative view of Campaign Attribution and why the current popular approach can never work. All presented using football as an analogy.

1. Campaign Attribution is Broken
So how do we maximise ROI on marketing spend?

2. Who am I?
 G’day, I’m Peter...
 I am Australian – with a strong aussie accent
 Founder of L3 Analytics
 Also Founder of MeasureCamp
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3. I intend to cover 4 areas*
1. Review visitor behaviour & touch points
 How campaign attribution treats them
2. My debate with campaign attribution fans
3. Always focus on the business questions
4. My recommended approaches**
* Using an extended version of Matthew Tod’s football (soccer)
analogy to make my points
** I don’t have a case study to prove these work ***
*** Yet...
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4. VISITOR BEHAVIOUR
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5. The Field of Play
RIO (location of the game)

6. Who gets the credit for a goal (conversion)?
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7. 1. Last Click Attribution
Final touch
scores goal &
gets all credit
RIO (location of the game)

8. Who gets the credit for a goal (conversion)?
 The “Goal Scorer”
 Last click attribution
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9. 2. First Click / Weighted Attribution Models
Midfield play
set up the goal
for the striker
Multiple players
contributed to the
goal & may deserve
some credit
RIO

10. Who gets the credit?
 The “Goal Scorer”
 Last click attribution
 Midfield passes
 First click / weighted attribution / descending
attribution / whatever allows you to pick the winner...
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11. 3. Ad Tracking Models
Ad tracking
networks don’t
capture all online
touch points
RIO

12. Who gets the credit?
 The “Goal Scorer”
 Last click attribution
 Midfield passes
 First click / weighted attribution / descending
attribution / whatever allows you to pick the winner...
 Ignoring players
 An issue with traditional ad tracking tools
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13. 4. Multiple Devices
Play started on
the other side of
the pitch & these
players deserve
credit too
Work (or smart Home (computer)
RIO
phone, tablet, etc)

14. Who gets the credit?
 The “Goal Scorer”
 Last click attribution
 Midfield passes
 First click / weighted attribution / descending
attribution / whatever allows you to pick the winner...
 Ignoring players
 An issue with traditional ad tracking tools
 Initiators of the passage of play
 You simply can’t ignore the issue of multiple devices
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15. 5. Offline Touch Points
Ball forced out by
defender & other
players provided
alternative
attacking options –
also deserve credit
RIO

16. Who gets the credit?
 The “Goal Scorer”
 Last click attribution
 Midfield passes
 First click / weighted attribution / descending
attribution / whatever allows you to pick the winner...
 Ignoring players
 An issue with traditional ad tracking tools
 Initiators of the passage of play
 You simply can’t ignore the issue of multiple devices
 Defenders caused the error & ran in support
 Offline touch points can’t be captured in any tool,
however powerful (or big the data is)
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17. Let’s look at a scenario
Kevin Hillstrom (MineThatData) wrote this scenario &
asked – How should this purchase be attributed?
http://blog.minethatdata.com/2012/10/your-opinion-wanted-attribution.html
 Nine varied answers, most very precise
 Lets have a flick through
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18. THE DEBATE
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19. Defining the Debate
 Campaign attribution tools only capture a part of
the visitor journey
 All, half, most, a minority of the journey – it depends...
 If all visitors login, you will get more (multiple devices)
 But it is just not possible to get the full visitor
journey, however powerful (expensive) the tool is
or how big the data is
 Let’s clarify what I believe the debate should be
“Is the data being captured sufficient to provide the
intelligence for informed business decisions?”
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20. Current Majority Opinion
Invest in the right tools &
throw enough resources at
the problem – and it will
can be solved!!
Image from SmartInsights blog
This is Digital Analytics – we
work with the data we have Image from Adobe SiteCatalyst blog
In sporting terms
“Point to the
Scoreboard”
Quotes from Tagman case study
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21. My Viewpoint - No
 This is not a sampling size issue
 e.g. We don’t have 100% accuracy but we can use the
trends
 It is incomplete data
 Scale of the problem is unknown
 Data available can be misleading
 Risk of wrong decisions is too large
 Paul Postance: “it could be done better” is not an
insult. It’s a mindset to make things better.
 Change the conversation from which model is
most accurate to how to optimise spend
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22. BUSINESS QUESTIONS
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23. What do we really need to know?
 Do we really need campaign attribution models?
 No – they are simply the most obvious solution to the
business problem
 Let’s focus on the business problems, not the
technology
 There are three business intelligence requirements...
1. What do I report to the business?
2. How much do I pay agencies for the last period?
3. How do I optimise future marketing spend?
 Why hunt for a single solution – use the best
approach to answer each requirement
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24. A 4th Question – from the CEO
Did we win?
RIO ROI (only location they care about)

25. RECOMMENDED
APPROACHES
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26. Business Performance reporting
 Pick a single approach & stick to it
 I don’t care which (last click is simplest)
 What is important is that
 The business understands the approach
 A change in performance can be easily identified
 and reacted to!!
 Football analogy – who scored the goals
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27. Evaluate Agency Performance
 Define business objective for each campaign
 Is it awareness, research, conversion, etc
 Define what success looks like
 KPIs & targets
 Agree payment on this basis
 Football analogy – performance based payments
 Goals, tackles, minutes played, crosses, accurate
crosses
 Business
 Impressions, TVRs, visits, non bounce visits, visits that
create a basket, leads, sales, increase in NPS
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28. Don’t say this can’t be done...
 Not saying it would be easy
 But wouldn’t a campaign
equivalent of this be incredibly
useful/actionable?
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29. Optimise Marketing Spend
 Remind me – how do we optimise again?
 Objectives | Evaluation | Hypothesis | Test
 Football analogy – simultaneous games
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30. Optimise Marketing Spend
 Business equivalent – test campaigns
 How to test campaigns
 Different campaigns in different geographical regions
 Hold out tests
 Switch off/on keywords
 Pick similar trending products & promote half
 Measure impact from offline on online & vice versa
 Learn what impact of campaign really is
 Optimise spend using these learnings
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31. HAVE I CONVINCED
ANYONE???
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32. Summary
 Campaign attribution is broken
 Simply can’t capture all touch points
 Instead of wasting money on impossible, invest
resources in the difficult
 Focus on the real business intelligence
requirements
 Be consistent in internal reporting
 Evaluate performance against predefined
objectives & targets specific to campaign
 Test to discover what works best
 Adjust spend to maximise profitability
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33. THANK YOU
I can be found at
• peteroneill@l3analytics.com
• @peter_oneill
• +44 7843 617 347
• www.linkedin.com/in/peteroneill
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