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TV + Google YouTube
Complementary in a Cross Media Campaign Strategy
Executive Summary
Light TV viewers are valuable and a significant part of
your audience…and they are the future
2
YouTube/GDN delivers efficient effective reach to
light TV viewers
3
Shift TV dollars to YouTube/GDN to cost effectively
supplement exposure to the Light TV viewers
4
1
2
Light TV viewers are not reached effectively on TV but
they are watching online
Agenda
The Marketplace
The Methodology
The Results
The Opportunity
1
2
3
4
3
Nielsen TV Viewership Quintiles P2+ ~ 20% buckets (hrs per day)
But not everyone is watching 5 hours per day
Light
0–1.6
Heavy
7.3+
Heavy-Med
4.6 – 7.3
Med
3.0 – 4.6
Light-Med
1.6 – 3.0
~59mm US TV
owning persons 2+
(61mm incl zero viewer)
~3% share of TV viewing ~48% share of TV viewing
4
The Heaviest TV Viewers Watch Significantly
More TV Now Than 5 Years Ago
Average minutes per day watching TV-Heaviest Quintile
2007 2008 2009
Source: P2+, Nielsen National People Meter Sample, Q1 2010 and Q1 2011
5
583 583
620
612
610
600
591
623
580
570
590
630
2010 2011
…While the Lightest Viewers Have Not
Changed Their TV Habits in 5 Years.
Average minutes per day watching TV-Lightest Quintile
2007 2008 2009
Source: P2+, Nielsen National People Meter Sample, Q1 2010 and Q1 2011
6
38 38 39 39 39
100
90
80
70
60
50
40
30
20
10
0
2010 2011
1.5X more Light TV Viewers than Heavy TV Viewers in A18-49
31% of the valuable A18-49 audience
watches less than 2 hours of TV daily
31%
12%
Lightest Light Medium Medium Medium Heavy Heavy
Adults 18-49
Source: Nielsen Q1 2011
7
than heavy TV viewers
as likely to own a Volvo
more likely to own a Volvo S60
Light TV viewers are…
Source: MRI8
Lightest and Heaviest TV Viewers
Indexes show stark contrast in audience composition
Young
& diverse
College
education
Income
over $100K
Broadcast
Only TV
Older
High school
education
Lower
Income
Couch
Potatoes
9
This group is more likely than others to…
Who Falls within the Lightest TV
Viewing Quintiles?
• Be young
• Be ethnically diverse
• Be educated (4+ years of college)
• Have a household income of $100K+
• Pursue a managerial/professional
career track
• Have children under 18 in the
household
• Watch only Broadcast TV, stream
video online
• Integrate devices and the internet
into their lives
• Be more interested in non-TV forms
of media entertainment (more
interested in gaming and less
interested in DVR)
• Create content online
Demographics Media Consumption
10
The Research Methodology
What are we trying to accomplish?
11
Can we prove that YouTube + the Google Display Network…
are complementary to TV
in cross media video strategy
efficiently reach people you didn’t reach on TV
deliver effective frequency to desirable
audiences that are hard to reach on TV
Goal:
12
Nielsen Online Panel
Group exposed to YouTube/GDN ad
Nielsen Data Fusion
Nielsen TV Panel
Group exposed to TV ad
Total Campaign Reach13
Data Fusion
Methodology:
Fit a nonlinear function to the
progressive reach vs TRP curve
TRPs
Extrapolate TV to TV + online reach
->Incremental TV TRPs
Incremental TRPs x Average CPP
->TV Incremental Cost
Reach
TV
progressive
reach curve
Online incremental reach
incremental
TV TRPs
Methodology:
Incremental Reach Forecast
14
Campaign: Data Sources
National TV
• Broadcast: English
• Cable: English
1
TV Campaign
Local Spot TV
7 month TV campaign and 1 month Google YouTube display
and video campaign
Adult 30-39 target
Budget – 99% TV + 1% Google YouTube display/video
15
+
2
Google (YT/GDN) Campaign
YouTube & Google Display Network
•Homepage Masthead
•YouTube Homepage Remarketing – GDN
•GDN Lifestyle
•YouTube Media
The Results
16
YouTube + GDN Add Complementary…
Reach Frequency Efficiency
17
Volvo’s YouTube/GDN Campaign
Reached 4.9% of Adults 30-39
4.9% Adults 30-39
Almost 2 Million People
TV failed to reach 30% of the lightest
viewers – 38% of incremental reach comes
from this group
With 1.4% of the budget, online delivered
5.7% of the TV reach
18
17% of target is very hard to reach on TV
Disparity between distribution of TV TRPs
and adult 30-39 audience
17%
12%
6%
19%
26%
37%
20% 21%
22%
20%
Lightest Light Medium Medium Medium Heavy Heavy
TV TRPs
Adults 30-39 population
19
TV impression distribution weighted to
heavy viewers
YouTube Reaches a More Balanced Audience
YouTube
adds TRPs
to the
lighter TV
viewers
6%
12%
19%
26%
37%
10%
19%
29%
18%
23%
Light Medium Light Medium Heavy Medium Heavy
TV TRPS YTTRPs
20
YouTube + GDN Adds Complementary…
Reach Frequency Efficiency
21
TV skews heavy but online delivers
impressions more evenly
Average Frequency
(Group exposed to both TV and YT)
TV not enough
7.5
13.8 14.6
16.9
30.4
2.5
3.9 4
2.4
40
35
3.8
30
0
5
10
15
20
25
Lightest Light Medium Medium Medium Heavy Heavy
9+ Effective Frequency
22
YouTube + GDN Adds Complementary…
Reach Frequency Efficiency
23
TV
YouTube + GDN delivered incremental
reach at 65% less than the cost of TV
Cost Per Incremental Reach
$373.7 K
$1,075 K
24
TV
YouTube + GDN delivered incremental
reach to the lightest TV viewing Adult
30-39 at 74% less than the cost of TV
Cost Per Incremental Reach
$373.7 K
$1,435 K
25
TV
YouTube + GDN delivered TRPs to the
lightest TV viewing Adult 30-39 at 33%
less than the Cost per Point of TV
$38 K
Cost Per Point
26
$57 K
People 2-17
Persons 18-24
Persons 25-34
Persons 35-49
Persons 50-54 Persons
55+
Improve Efficiency
Less reach spillover to older audiences on YouTube +
GDN
TV Online
People 2-17
Persons 18-24
Persons 25-34
Persons 35-49
Persons
50-54
Persons 55+
Older
Younger
Persons 30-39
30-39
Target
Note: Distribution of reach27
30-39
Target
The Opportunity
28
Reach A Complementary Audience
Cost to reach to lightest TV viewers 30-39 is more efficient on YouTube/
GDN
100
29
27
TV Lightest TV Viewer
Opportunity to reach light TV
viewers more efficiently on
YouTube + GDN…
So how do you reach them?
Better distribute TRPs across the quintiles
HeavyHeavy-MedMed
Less waste
More balanced
media delivery
Similar or Increased
reach to a valuable
light TV viewing
audience
Light
Shift budget
out of heavy
skewing TV
networks
Light-Med
TV + YT Cross Media
Video Planning
30
Viewership Across TV Networks Is Diverse
Some networks over-index for heaviest TV viewers and under-index to
light TV viewers
125
175
225
275
325
5 10 15 20
Index to light TV viewers
25 30
IndextoheavyTVviewers
HEAVY SKEW
NETWORKS
High disparity of
reach between
Heavy and Light
Viewers
LESS HEAVY SKEW
NETWORKS
31
More even reach to
Heavy and Light
Viewers
You could shift out of
cable into broadcast,
but that is expensive -
broadcast CPM is ~3x
the cable CPM
Improve Efficiency
Nick at Nite (heavy skew) vs ABC (less heavy skew)
Entertainment
0
0 20 40 60 80 100 120 140
Index to Light Viewers
Note: Bubble size represents % of total impressions
Source: Nielsen Monitor Plus and Nielsen National People Meter
Note: On the graph, the top 10 networks most skewed to heavy TV viewers and the top 10 networks
least skewed to heavy networks are displayed.
32
500ESPNEWS
Fox Business NewBsravAo&E
200VNeertsIwunsdoerkpendent Film
WE: Women’s
Nick at Nite
USA Network
Channel Discovery Channel
VH1
TLC
TNT
Syfy
CBS Speed
HGTV
ABC
MTV
BBC-America
100
300
400
Ex – Nick at
Nite indexes 600
heavy/light
viewers by
~20x
Ex – ABC
indexes
heavy/light
by ~2.6 x
IndextoHeavyViewers
85% TV / 15% YouTube + GDN
33%
Shift budget
from heavy
skewing TV
networks to
online
7%
14%
21%
26%
Lightest Light Medium Medium
Medium Heavy
Cross Media Campaign TRPs
Heavy
A&E, Bravo, ESPNews,
Fox Business Network,
Independent Film
Channel, Nick at
Nite, TNT, USA, VS, WE
6%
12%
19%
26%
37%
Lightest Light
Medium
Medium Medium
Heavy
Heavy
Cross Media Campaign TRPs
33
16% in TRPs to
heaviest TV viewers
10% in TRPs to the
lightest TV viewer
Scenario: TRP distribution shift
Remember that TV impression distribution weighted to heavy viewers…
while YouTube reaches a more balanced audience?
99% TV / 1% YouTube + GDN
Thank you
34
Appendix
35
YouTube builds efficient incremental
reach to TV
YouTube helps build reach at higher efficiency
(higher reach per TRP due to increasing saturation of the TV reach curve)
Total Reach
TV would have required
57.0 TRPs to realize the
same total campaign reach
+ 0.32 %pts YouTube
86.4%
TV + YouTube
reach
86.0%
TV reach
100
90
80
70
60
50
40
30
20
10
0
36
TRPs
0 50 100 150 200
METHODOLOGY: Nielsen Data Fusion in a nutshell
Fused Database using
Common Demo
Variables and Media
Usage
Fusion Using
Common Person
characteristics
Variables and Media
Usage
Nielsen
TV panel
Step 2 –
Online + TV fusion
Nielsen Online
Home Panel
Nielsen Online
Work Panel
Step 1 –
Home + Work online
fusion
37
METHODOLOGY: Nielsen Monitor Plus
38
Nielsen’s Monitor Plus’s system has electronic devices, which identify new
copies (via an audio and digital signature). These advertisements are crossed
against a database of known advertisements in the marketplace and matched
up to the particular brand/campaign.
For this analysis, Nielsen compares this known/tracked ad schedule against
agency data to confirm that all advertisement buys are accounted for.
Costs: Every network provides broad daypart valuation for their content. By
isolating each individual campaign, Nielsen is able to cross this activity against
the network costs to provide a topline average of costs. Usually, considering
bulk purchasing and make-goods, these costs are over-estimating the costs of
TV, but typically, these over-estimations are equal across all brands.

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Why Shift TV dollars to YouTube

  • 1. TV + Google YouTube Complementary in a Cross Media Campaign Strategy
  • 2. Executive Summary Light TV viewers are valuable and a significant part of your audience…and they are the future 2 YouTube/GDN delivers efficient effective reach to light TV viewers 3 Shift TV dollars to YouTube/GDN to cost effectively supplement exposure to the Light TV viewers 4 1 2 Light TV viewers are not reached effectively on TV but they are watching online
  • 3. Agenda The Marketplace The Methodology The Results The Opportunity 1 2 3 4 3
  • 4. Nielsen TV Viewership Quintiles P2+ ~ 20% buckets (hrs per day) But not everyone is watching 5 hours per day Light 0–1.6 Heavy 7.3+ Heavy-Med 4.6 – 7.3 Med 3.0 – 4.6 Light-Med 1.6 – 3.0 ~59mm US TV owning persons 2+ (61mm incl zero viewer) ~3% share of TV viewing ~48% share of TV viewing 4
  • 5. The Heaviest TV Viewers Watch Significantly More TV Now Than 5 Years Ago Average minutes per day watching TV-Heaviest Quintile 2007 2008 2009 Source: P2+, Nielsen National People Meter Sample, Q1 2010 and Q1 2011 5 583 583 620 612 610 600 591 623 580 570 590 630 2010 2011
  • 6. …While the Lightest Viewers Have Not Changed Their TV Habits in 5 Years. Average minutes per day watching TV-Lightest Quintile 2007 2008 2009 Source: P2+, Nielsen National People Meter Sample, Q1 2010 and Q1 2011 6 38 38 39 39 39 100 90 80 70 60 50 40 30 20 10 0 2010 2011
  • 7. 1.5X more Light TV Viewers than Heavy TV Viewers in A18-49 31% of the valuable A18-49 audience watches less than 2 hours of TV daily 31% 12% Lightest Light Medium Medium Medium Heavy Heavy Adults 18-49 Source: Nielsen Q1 2011 7
  • 8. than heavy TV viewers as likely to own a Volvo more likely to own a Volvo S60 Light TV viewers are… Source: MRI8
  • 9. Lightest and Heaviest TV Viewers Indexes show stark contrast in audience composition Young & diverse College education Income over $100K Broadcast Only TV Older High school education Lower Income Couch Potatoes 9
  • 10. This group is more likely than others to… Who Falls within the Lightest TV Viewing Quintiles? • Be young • Be ethnically diverse • Be educated (4+ years of college) • Have a household income of $100K+ • Pursue a managerial/professional career track • Have children under 18 in the household • Watch only Broadcast TV, stream video online • Integrate devices and the internet into their lives • Be more interested in non-TV forms of media entertainment (more interested in gaming and less interested in DVR) • Create content online Demographics Media Consumption 10
  • 11. The Research Methodology What are we trying to accomplish? 11
  • 12. Can we prove that YouTube + the Google Display Network… are complementary to TV in cross media video strategy efficiently reach people you didn’t reach on TV deliver effective frequency to desirable audiences that are hard to reach on TV Goal: 12
  • 13. Nielsen Online Panel Group exposed to YouTube/GDN ad Nielsen Data Fusion Nielsen TV Panel Group exposed to TV ad Total Campaign Reach13 Data Fusion Methodology:
  • 14. Fit a nonlinear function to the progressive reach vs TRP curve TRPs Extrapolate TV to TV + online reach ->Incremental TV TRPs Incremental TRPs x Average CPP ->TV Incremental Cost Reach TV progressive reach curve Online incremental reach incremental TV TRPs Methodology: Incremental Reach Forecast 14
  • 15. Campaign: Data Sources National TV • Broadcast: English • Cable: English 1 TV Campaign Local Spot TV 7 month TV campaign and 1 month Google YouTube display and video campaign Adult 30-39 target Budget – 99% TV + 1% Google YouTube display/video 15 + 2 Google (YT/GDN) Campaign YouTube & Google Display Network •Homepage Masthead •YouTube Homepage Remarketing – GDN •GDN Lifestyle •YouTube Media
  • 17. YouTube + GDN Add Complementary… Reach Frequency Efficiency 17
  • 18. Volvo’s YouTube/GDN Campaign Reached 4.9% of Adults 30-39 4.9% Adults 30-39 Almost 2 Million People TV failed to reach 30% of the lightest viewers – 38% of incremental reach comes from this group With 1.4% of the budget, online delivered 5.7% of the TV reach 18
  • 19. 17% of target is very hard to reach on TV Disparity between distribution of TV TRPs and adult 30-39 audience 17% 12% 6% 19% 26% 37% 20% 21% 22% 20% Lightest Light Medium Medium Medium Heavy Heavy TV TRPs Adults 30-39 population 19
  • 20. TV impression distribution weighted to heavy viewers YouTube Reaches a More Balanced Audience YouTube adds TRPs to the lighter TV viewers 6% 12% 19% 26% 37% 10% 19% 29% 18% 23% Light Medium Light Medium Heavy Medium Heavy TV TRPS YTTRPs 20
  • 21. YouTube + GDN Adds Complementary… Reach Frequency Efficiency 21
  • 22. TV skews heavy but online delivers impressions more evenly Average Frequency (Group exposed to both TV and YT) TV not enough 7.5 13.8 14.6 16.9 30.4 2.5 3.9 4 2.4 40 35 3.8 30 0 5 10 15 20 25 Lightest Light Medium Medium Medium Heavy Heavy 9+ Effective Frequency 22
  • 23. YouTube + GDN Adds Complementary… Reach Frequency Efficiency 23
  • 24. TV YouTube + GDN delivered incremental reach at 65% less than the cost of TV Cost Per Incremental Reach $373.7 K $1,075 K 24
  • 25. TV YouTube + GDN delivered incremental reach to the lightest TV viewing Adult 30-39 at 74% less than the cost of TV Cost Per Incremental Reach $373.7 K $1,435 K 25
  • 26. TV YouTube + GDN delivered TRPs to the lightest TV viewing Adult 30-39 at 33% less than the Cost per Point of TV $38 K Cost Per Point 26 $57 K
  • 27. People 2-17 Persons 18-24 Persons 25-34 Persons 35-49 Persons 50-54 Persons 55+ Improve Efficiency Less reach spillover to older audiences on YouTube + GDN TV Online People 2-17 Persons 18-24 Persons 25-34 Persons 35-49 Persons 50-54 Persons 55+ Older Younger Persons 30-39 30-39 Target Note: Distribution of reach27 30-39 Target
  • 29. Reach A Complementary Audience Cost to reach to lightest TV viewers 30-39 is more efficient on YouTube/ GDN 100 29 27 TV Lightest TV Viewer Opportunity to reach light TV viewers more efficiently on YouTube + GDN… So how do you reach them?
  • 30. Better distribute TRPs across the quintiles HeavyHeavy-MedMed Less waste More balanced media delivery Similar or Increased reach to a valuable light TV viewing audience Light Shift budget out of heavy skewing TV networks Light-Med TV + YT Cross Media Video Planning 30
  • 31. Viewership Across TV Networks Is Diverse Some networks over-index for heaviest TV viewers and under-index to light TV viewers 125 175 225 275 325 5 10 15 20 Index to light TV viewers 25 30 IndextoheavyTVviewers HEAVY SKEW NETWORKS High disparity of reach between Heavy and Light Viewers LESS HEAVY SKEW NETWORKS 31 More even reach to Heavy and Light Viewers
  • 32. You could shift out of cable into broadcast, but that is expensive - broadcast CPM is ~3x the cable CPM Improve Efficiency Nick at Nite (heavy skew) vs ABC (less heavy skew) Entertainment 0 0 20 40 60 80 100 120 140 Index to Light Viewers Note: Bubble size represents % of total impressions Source: Nielsen Monitor Plus and Nielsen National People Meter Note: On the graph, the top 10 networks most skewed to heavy TV viewers and the top 10 networks least skewed to heavy networks are displayed. 32 500ESPNEWS Fox Business NewBsravAo&E 200VNeertsIwunsdoerkpendent Film WE: Women’s Nick at Nite USA Network Channel Discovery Channel VH1 TLC TNT Syfy CBS Speed HGTV ABC MTV BBC-America 100 300 400 Ex – Nick at Nite indexes 600 heavy/light viewers by ~20x Ex – ABC indexes heavy/light by ~2.6 x IndextoHeavyViewers
  • 33. 85% TV / 15% YouTube + GDN 33% Shift budget from heavy skewing TV networks to online 7% 14% 21% 26% Lightest Light Medium Medium Medium Heavy Cross Media Campaign TRPs Heavy A&E, Bravo, ESPNews, Fox Business Network, Independent Film Channel, Nick at Nite, TNT, USA, VS, WE 6% 12% 19% 26% 37% Lightest Light Medium Medium Medium Heavy Heavy Cross Media Campaign TRPs 33 16% in TRPs to heaviest TV viewers 10% in TRPs to the lightest TV viewer Scenario: TRP distribution shift Remember that TV impression distribution weighted to heavy viewers… while YouTube reaches a more balanced audience? 99% TV / 1% YouTube + GDN
  • 36. YouTube builds efficient incremental reach to TV YouTube helps build reach at higher efficiency (higher reach per TRP due to increasing saturation of the TV reach curve) Total Reach TV would have required 57.0 TRPs to realize the same total campaign reach + 0.32 %pts YouTube 86.4% TV + YouTube reach 86.0% TV reach 100 90 80 70 60 50 40 30 20 10 0 36 TRPs 0 50 100 150 200
  • 37. METHODOLOGY: Nielsen Data Fusion in a nutshell Fused Database using Common Demo Variables and Media Usage Fusion Using Common Person characteristics Variables and Media Usage Nielsen TV panel Step 2 – Online + TV fusion Nielsen Online Home Panel Nielsen Online Work Panel Step 1 – Home + Work online fusion 37
  • 38. METHODOLOGY: Nielsen Monitor Plus 38 Nielsen’s Monitor Plus’s system has electronic devices, which identify new copies (via an audio and digital signature). These advertisements are crossed against a database of known advertisements in the marketplace and matched up to the particular brand/campaign. For this analysis, Nielsen compares this known/tracked ad schedule against agency data to confirm that all advertisement buys are accounted for. Costs: Every network provides broad daypart valuation for their content. By isolating each individual campaign, Nielsen is able to cross this activity against the network costs to provide a topline average of costs. Usually, considering bulk purchasing and make-goods, these costs are over-estimating the costs of TV, but typically, these over-estimations are equal across all brands.