digital leaders dinner (sydney, australia) - 6 february, 2013
DESCRIPTION
Chief Product Officer Tim Brown's presentation from Exponential Sydney's Digital Leaders Dinner, delivering insights around the future and evolution of online advertising and attribution. For more details, tweet us at @exponentialinc or visit our website: www.exponential.comTRANSCRIPT
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The digital shift
All media will be ‘digital’Global media consumption per week
Av
era
ge
ho
urs
pe
r w
ee
k
Source: Carat/World Media Trends Report 2008
0
10
20
30
40
50
60
70
80
90
1900 1920 1940 1960 1980 2000 2020
Games
Mobile
Outdoor
Cinema
Digital radio
Analogue radio
Digital TV
Analogue TV
Web
Bringing together digital audience
targeting opportunities
Context: the evolution of online
audience targeting
Untargeted
Audience: N/A Contextual
Audience: Content as a proxy to the right audience
Demographic
Audience: users with the right age/gender/location
Retargeting
Audience: users that have already visited your website
Rule-based behavioral
Audience: users with the right, manually-selected online behaviors
Predictive behavioral
Audience: users with the right, auto-selected online behaviors
Lookalike modeling
Online data overshadows
even the biggest events
www.exponential.com 8
Measurement
The click problem
The click problem – the click as a
metric of ‘success’
Conversion
behaviours
Click
behaviours
The problem with last view
The effectiveness measurement
The hierarchy of attribution
0
20
40
60
80
1 2 3 4 5
0
20
40
60
80
1 2 3 4 5 -10
10
30
50
70
1 2 3 4 5
0
10
20
30
40
50
60
70
1 2 3 4 5
0
10
20
30
40
50
60
70
1 2 3 4 5
0
10
20
30
40
50
60
70
1 2 3 4 5
Last event First event Flat
Bath-tub Time decay Custom
Game Theory and axiomatic
value attribution
Game Theory proposed by Von Neumann and
Morgenstern in Theory of Games and Economic
Behavior in 1944
Described the strategy for players in games with
cooperation or competition
Game Theory and axiomatic
value attribution
Axiomatic Value Attribution proposed in 1953
by Lloyd Shapley
A method to evaluate the ‘value’ of playing a game
Three player game example
The value of all combinations of players is known
The Shapley Value is a numerical quantity that
assigns to each player their expected marginal
contributions over all possible games
Shapley value of playing a game
Shapley value example
= $19
= $0
= $4= $7 = $6
= $7 = $15 = $9
Shapley value example
2
1 3
$7$0
$12$19
=
= $0
= $7
= $4
= $6
= $7
= $15
= $9
= $19
Calculating Shapley value
Shapley value example
$6$9
$4$19
=
= $0
= $7
= $4
= $6
= $7
= $15
= $9
= $19 2
31
Calculating Shapley value
Shapley value example
Shapley value exampleShapley value= $0
= $7
= $4
= $6
= $7
= $15
= $9
= $19
= $7.7
= $3.2
= $8.1
Shapley value example
Preliminary findings
0%
10%
20%
30%
40%
50%
60%
None 1 2 3 4 5 6 7 8 9-12 13-17 18-24 25+
Last View vs. Axiomatic attribution
Last ViewAxiomatic
Percent of conversions
Frequency of exposures
Exposure attribution (1 of 2)
0%
25%
50%
75%
100%
125%
150%
175%
200%
None 1 2 3 4 5 6 7 8 9-12 13-17 18-24 25+
Axiomatic vs. Last View attribution ratio
Frequency > 3
over-attributed by Last View
Frequency > 9
grossly over-attributed
by Last View
Frequency 1 and 2
under-attributed by Last View
Ratio
Frequency of exposures
Exposure attribution (2 of 2)
0%
25%
50%
75%
100%
125%
150%
175%
200%
None 468x60 120x600 160x600 728x90 300x250 300x600
Axiomatic vs. Last View attribution ratio
This Ad Size
under-attributed
by Last View
This Ad Size
grossly over-
attributed by
Last View
Ratio
Ad size
Ad Size attribution comparison
Conclusion
1. Targeting the right
audiences and engaging
them with high impact ad
formats works!
2. Always think about the
causal effect marketing
activity has on your end
goal
3. Start measuring and testing
these theories against new
measurement and
attribution solutions
available
