Date post: | 30-May-2015 |
Category: |
Economy & Finance |
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EKSTR
A B
LADD
ETN
ETSALG
Predictive Behavioral Targeting at ekstrabladet dkat ekstrabladet.dk
Introduction
EKSTR
A B
LAD
Maria VoigtProject Manager – ekstrabladet.dkD
ETN
ETSALG Predictive Targeting Evaluation Project
Marketing Research Department
Advertising Method Expert
Stephan NollerManaging Director – nugg.ad
Profound experience in data analysis
Founded nugg.ad in 2006
at TNS Group (Emnid, Infratest)
at industry association AGOF
Introduction to ekstrabladet.dk
EKSTR
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LAD
Part of the media concern JP/Politikens HusD
ETN
ETSALG
JP/Politikens HusLargest news site in Denmark
The site:The site:Breaking news User profile
In comparison Ekstra Bladet is like:Aftonbladet, SwedenVG NVG, NorwayBild, GermanyThe Sun, UK
The Danish Market
EKSTR
A B
LADD
ETN
ETSALG 90% of the Danish population p p
have internet access.
Danish internet populationDanish internet population4 million real users3 billion page impressions
Challenges
EKSTR
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LAD Demands for:D
ETN
ETSALG
Better results (more clicks, more sales)Documented pay-off
Is targeting the solution?Is targeting the solution?
Ekstra Bladet tested two campaigns using Predictive Behavioral Targeting (PBT) from nugg.ad
Predictive Behavioral Targeting (1/3)
EKSTR
A B
LAD 1ekstrabladet.dk/news 1 2 1
Jim | Jane | Tom Tim
DET
NETSA
LG
3
3
2
Content Channels (Measured)
ekstrabladet.dk/people 3 1 3
ekstrabladet.dk/sport 0 2 3
ekstrabladet.dk/tech 2 1 2
Step 1: Click Measurement (all Users)
Predictive Behavioral Targeting (2/3)
EKSTR
A B
LAD ekstrabladet.dk/news 1 2 1
Jim | Jane | Tom Tim
1DET
NETSA
LG
Content Channels (Measured)
ekstrabladet.dk/people 3 1 3
ekstrabladet.dk/sport 0 2 3
ekstrabladet.dk/tech 2 1 2
3
3
2
Demography(Survey)
Gender 0 1 0
Age 3 3
Product Interests(Survey)
Body Care 2 4 2
Food 0 1 2
Psychography (Survey) Trendsetter 0 2 2
Step 2: Online Survey (Sample)
Predictive Behavioral Targeting (3/3)
EKSTR
A B
LAD ekstrabladet.dk/news 1 2 1
Jim | Jane | Tom
1
Tim
DET
NETSA
LG
Content Channels (Measured)
ekstrabladet.dk/people 3 1 3
ekstrabladet.dk/sport 0 2 3
ekstrabladet.dk/tech 2 1 2
3
3
2
Demography(Survey)
Gender 0 1 0
Age 3 3
0
3
Product Interests(Survey)
Body Care 2 4 2
Food 0 1 2
2
2
Psychography (Survey) Trendsetter 0 2 2 2
Step 3a: Search for Tims nearest statistical twinpStep 3b: Tim inherits missing values from his “twin” Tom
Case Study – FDM Travels
EKSTR
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LAD Campaign: weekend holidaysD
ETN
ETSALG
Ca pa g ee e d o days
Aim: sales/purchases
Creatives:
Case Study – FDM Travels
EKSTR
A B
LAD
300
DET
NETSA
LG 200
250
Rat
e
136150
Clic
k Th
roug
h R
no PBT
100
50
100Inde
x C
PBT
0
50
HolidaysHolidays
Day 1‐2
Case Study – FDM Travels
EKSTR
A B
LAD
300
DET
NETSA
LG 200
250
Rat
e
136150
Clic
k Th
roug
h R
no PBT
100 10093
50
100Inde
x C
PBT
0
50
Holidays Plane or TrainHolidays Plane or Train Tickets
Day 1‐2 Day 3‐4
Case Study – FDM Travels
EKSTR
A B
LAD
300
DET
NETSA
LG 200
250
Rat
e
136155
150
Clic
k Th
roug
h R
no PBT
100 100 10093
50
100Inde
x C
PBT
0
50
Holidays Plane or Train Household incomeHolidays Plane or Train Tickets
Household income >54.000€ AND
(Holidays OR Plane or Train Tickets)
Day 1‐2 Day 3‐4 Day 5‐6
Case Study – FDM Travels
EKSTR
A B
LAD
300
DET
NETSA
LG 200
250
Rat
e
136155
150
Clic
k Th
roug
h R
no PBT
100 100 100 10093
106
50
100Inde
x C
PBT
0
50
Holidays Plane or Train Household income Household incomeHolidays Plane or Train Tickets
Household income >54.000€ AND
(Holidays OR Plane or Train Tickets)
Household income >54.000€
Day 1‐2 Day 3‐4 Day 5‐6 Day 7‐8
Case Study – FDM Travels
EKSTR
A B
LAD
300
DET
NETSA
LG
183200
250
Rat
e
136155
183
150
Clic
k Th
roug
h R
no PBT
100 100 100 100 10093
106
50
100Inde
x C
PBT
0
50
Holidays Plane or Train Household income Household income WomenHolidays Plane or Train Tickets
Household income >54.000€ AND
(Holidays OR Plane or Train Tickets)
Household income >54.000€
Women
Day 1‐2 Day 3‐4 Day 5‐6 Day 7‐8 Day 9‐10
Case Study – FDM Travels
EKSTR
A B
LAD
280300
DET
NETSA
LG
183200
250
Rat
e
136155
183
150
Clic
k Th
roug
h R
no PBT
100 100 100 100 100 10093
106
50
100Inde
x C
PBT
0
50
Holidays Plane or Train Household income Household income Women Holiday ANDHolidays Plane or Train Tickets
Household income >54.000€ AND
(Holidays OR Plane or Train Tickets)
Household income >54.000€
Women Holiday AND Household Income
>54.000€ AND Women
Day 1‐2 Day 3‐4 Day 5‐6 Day 7‐8 Day 9‐10 Day 11‐12
FDM Travels: Conversion Rates/Online Sales
EKSTR
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LAD
Not only click through rates increased. Also sales, which was the aim of the campaign, did.
DET
NETSA
LG
275
250
300
200
250
e
150
Con
vers
ion
Rat
e
no PBT
PBT
100100
Inde
x C
50
0
Case Study – DFDS Seaways
EKSTR
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LAD Campaign: Rockcruise competitionD
ETN
ETSALG
Aim: Click Through Rate
Creatives:
Case Study – DFDS Seaways
EKSTR
A B
LAD
300
DET
NETSA
LG
239247
200
250
118
145
125
150no PBT
100 100 100 100 100 100
118
96100
PBT
0
50
Top Article Top Article Top Article
Couples 30-49 20-29
Overall Findings
EKSTR
A B
LAD Predictive Behavioral Targeting achieves much better
results than ordinary campaignsDET
NETSA
LG
results than ordinary campaigns
Creatives and target group must be harmonizedTargeting criteria m st be combined smartlTargeting criteria must be combined smartly
Targeting helps the advertiser redefine/optimize the target grouptarget group
Publisher can offer the advertisers a better product with optimized inventorywith optimized inventory
EKSTR
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LADD
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ETSALG
Questions?