This document discusses attribution modeling and how to move beyond simplistic single-click attribution models. It notes that the consumer purchasing journey can span many interactions over time. The current measurement model treats attribution as a single event, but the real customer path is very complex. Rather than seeking a perfect attribution model, the goal should be actionable insights that reduce uncertainty and enable better decision making. The document outlines a framework for attribution that includes discovery, testing, evaluation and iteration to generate hypotheses, test attribution models, and share learnings. It also discusses how TagMan customer and behavioral data can be used to power attribution modeling and visualization.

1. TagMan & Attribution
Adrian Nash, Head of Analytics & Insight
Logan Tod & Co
9th November 2011

2. Logan Tod & Co: Europe’s leading online optimisation
& analytics consultancy
Retail Finance Travel Technology, Media
& Consumer & Utilities & Leisure & Telecom
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3. Consider the consumer purchasing journey time
70%
purchases completed
Standard cookie window (30 days)
30%
purchases not completed
Source: Google/Nielsen
NetView – Beyond Last Click
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4. The current measurement model is very simplistic
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5. The real Single View is very complex indeed
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6. Is a single ‘best’ what now?
So attribution model the right goal ?
• Danger of diminishing returns seeking ‘perfect’ attribution
models
• Objective should be reducing uncertainty enabling better
decision making
• Actionable & repeatable insights are the real goal
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7. What does best practice look like?
“...given a choice, it‟s more important to be precise than
accurate – reproducibility is more important (especially to
management) than getting the exact number right.”
Jim Novo - 2007
Chart source – Omniture blog
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8. High level attribution framework
Evaluation & Iteration Discovery
• Hypotheses • Workshop
• Performance • Objectives
• Model „precision‟ • Final visualisation
• Knowledge sharing • Data preparation
• Accuracy
• Integration
Evaluation Discovery • Marketing Classification
• Forecasting
Testing Attribution
Testing Attribution modelling
• Hypothesis generation • Credit allocation
• Test design • Scorecards
• Success criteria • Advanced models
• Test execution • Visualisation
• Insight
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9. TagMan data > attribution insight
Customer Behavioural
TagMan Context data
data data (WA)
ETL
Quantivo
Modelling
Visualisation
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10. Questions, comments or thoughts?
Adrian Nash, Head of Insight and Analytics
@logantod
Adrian.nash@logantod.com
© 2011 28th March 2011
29 November, 2011 Page 23
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