The document discusses ways that marketers can better target online audiences and measure advertising effectiveness in the digital space. It provides examples of how refined targeting of existing customers for a TV provider increased engagement. It also discusses how utilizing real-time competitive ad occurrence data allowed an advertiser to target second screen ads during TV commercials. The document advocates measuring advertising across awareness, behavior, and sales outcomes to understand total ROI. It presents an example where measuring across these metrics found that $6.89 was returned for every $1 spent on advertising.

1. Insights from the
Cutting Edge of Digital
Stephen DiMarco
CEO, MB Digital,
Milward Brown
@sdimarco
George Pappachen
Executive Vice President
Global Strategy, WPP
@GPappachen

2. Digital Media Trends

3. (c) 2015 Millward Brown Digital. Source: Millward Brown Digital’s Getting DigitalRight study, 2015.
Many potential
touchpoints
No single path to
purchase
Difficult to quantify
impact
Marketing state of the union

4. Marketing execution – the right questions
What
questions
should I be
asking?
What are
the relevant
creative
messages?
Who is the
target
audience?
Where
did the ad
appear?
How much
was spent
to place it?
Who saw
the
message?
What did
they do
about it?
What is the
consumer’s
media
journey?
Advertising Intelligence
Audience
Intelligence
Earned Media
Intelligence
Consumer
Intelligence
Advertising Intelligence
Media
Intelligence

5. Targeting audiences online

6. Targeting audiences online
A TV provider was
looking to target existing
customers with an offer
promoting the ability to
watch different
channels, in different
rooms, on different
devices.
Create an audience of
existing subscribers who
watched TV across
multiple devices.
We refined the target by
including those who
definitely agreed that
‘PVR technology has
changed the way I watch
TV’ indicating an interest
in TV tech developments
Average video viewing time
across the target segment was
33% longer than the campaign
average.
The audience was more
engaged as a rich target
definition meant we were
hitting the right people, with the
message, efficiently.
Challenge What we did Result

7. Targeting audiences online
Utilize large scale
on/offline database
target respondents
are matched to
online cookies and
‘look-alike’
audiences are
modelled
Panelists are matched to
a provider’s database
using name, address,
email & more
seed
respondents Look-alike targets
made available to
ad-serving platforms

8. 2nd screen Ad Targeting
An advertiser was looking
to conquest by delivering
ads on the second screen
in direct competition with
the competition's TV ads.
The advertiser’s trading
platform used real-time ad
occurrence data feed to
optimize messaging during
the campaign.
This enabled the advertiser
to target online ads within
the same time period of
competitive ads running on
TV.
The real-time ad occurrence
feed provided a correlation for
more precise targeting on the
2nd screen.
This capability can be applied to
both competitive conquesting
and continued message.
Challenge What we did Result

9. 2nd screen Ad Targeting using real-time ad occurrences

10. Share-of-voice Ad Targeting
Challenge
An advertiser was looking
to combat against ‘brand
clutter’ and identify online
white-space opportunities
for uniqueness of
message.
What we did
Identify concentrations
of ads from the same
vertical as well as from
competitive brands.
The advertiser was then
able to target sites the
target was visiting where
there were fewer
competitive ads.
Result
Using ads data, the advertiser
gained an ability to employ a
more strategic approach.
With this information in-hand, the
advertiser identified and served
ads that commanded a higher
share-of-voice of message to the
target audience.

11. Share-of-voice Ad Targeting
Competitor Brands Websites Ad Activity
Opportunity Zones
Moderate
Clutter
High
Clutter
Zero
Clutter
Very High
Clutter
Low
Clutter
Ad Spend and Impressions Data

12. Reaching the Dynamic Consumer
in an Evolving Digital Landscape

13. (c) 2015 Millward Brown Digital. Source: Millward Brown Digital’s Demystifying the Consumer Journey study, 2015.
Understanding the consumer journey
DEMOGRAPHICS
GEOGRAPHICS
PSYCHOGRAPHICS
Relationship with
CATEGORY
BRAND
TOUCHPOINTS

14. (c) 2015 Millward Brown Digital. Source: Millward Brown Digital’s Demystifying the Consumer Journey study, 2015.
Category influences time investment
LENGTH OF PURCHASE JOURNEY
Number of days from start of journey to purchase for each category

15. (c) 2015 Millward Brown Digital. Source: Millward Brown Digital’s Getting Audiences Right study, 2015.
Laptop/PC usage goes up with task length
0%
20%
40%
60%
0-5 minutes 5-10 minutes 10-20 minutes 20-60 minutes More than one hour
%ofRespondents
Device Preference for Various Task Lengths
LAPTOP / PCSMARTPHONE TABLET

16. (c) 2015 Millward Brown Digital. Source: Millward Brown Digital’s Compete Clickstream panel; laptop/desktop unique visitors.
Higher Education drives high visitation
0
20,000,000
40,000,000
60,000,000
80,000,000
100,000,000
120,000,000
140,000,000
Higher Education Wireless Carriers Automotive Manufacturers Banking Consumer Electronics
Average Monthly UVs (laptop/PC)
4Q14 1Q15 2Q15

17. (c) 2015 Millward Brown Digital. Source: Millward Brown Digital’s Compete Clickstream panel; top sites for Higher Education behavioral segment
(includes Colleges & Universities, Financial Aid, Online Courses, Student Resources.
Higher Education receives higher engagement
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
Aug-14 Sep-14 Oct-14 Nov-14 Dec-14 Jan-15 Feb-15 Mar-15 Apr-15 May-15 Jun-15 Jul-15 Aug-15
Time Spent per UV (min)
Higher Education Wireless Carriers Automotive Banking Consumer Electronics

18. (c) 2015 Millward Brown Digital. Source: Millward Brown Digital’s Compete Clickstream panel; top sites for Higher Education behavioral segment
(includes Colleges & Universities, Financial Aid, Online Courses, Student Resources.
Top 10 Sites Higher Education sites
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
Aug
2015

19. Optimize through better measurement

20. The ABC’S help marketers uncover insights
Maximize reach,
frequency, & viewable
brand impact to targets
Audience Insights
Impact of campaigns
on attitudes and brand
lift measures
Brand Lift
Demonstrate how
marketing
contributes to
sales/application
Sales Outcomes
Analyze actual online
behavior and the impact
of exposure
Consumer Behavior Impact

21. Total U.S. Adults 25-54 Site A Campaign Delivery Adults 25-54
Targeting Efficiency
Audience Effect – Target Consumers Reached
The campaign reached 2MM target consumers at a cost per target of $0.05. This translates into roughly 19 target
consumers gained per dollar spent. The campaign successfully delivered significant targeting and audience scale.
Percent Difference: +5.0%
Incremental Target Consumers:
(Incremental Efficiency*Reach)
0.025 * 3,823,480= + 95,587
Total Target Consumers:
(Efficiency*Reach)
0.53 * 3,823,480= +2,026,444
Return Objective
Target
Consumers
Cost per
Consumer*
A-Effect **
Audience 2,026,444
$0.05 spent
per target consumer
19 target consumers
per $ spent
+2.5%

22. Brand Effect – Aided Brand Awareness
The campaign drove a 7.4% point increase in Aided Awareness. This translates to an incremental 283K consumers
that became aware of Brand X. This cost $0.37 per consumer, meaning about 3 consumers gained per dollar spent.
Percent Difference: +10.1%
Significance Level: 83%
Incremental Aware Consumers:
(Incremental Awareness*Reach)
0.07 * 3,823,480 = +282,938
Return Objective
Campaign
Impact
Cost per
Consumer*
B-Effect **
Brand 282,938
$0.37 spent
per target consumer
2.7 target consumers
per $ spent
+7.4%
Non-Exposed Exposed
Aided Brand Awareness
(consumers aware of Brand X when prompted)

23. Consumer Behavior Effect – Brand Visits
With a +13% increase in brand visits observed over the campaign +4 week period, an incremental 459K consumers
went on to the brand site.
5.13%
17.94%
Control Exposed
+13%
Percent Difference: +13%
Significance Level: 90%
Incremental Visitation:
(Incremental Visitation*Reach)
0.13 * 3,823,480 = +458,818
Return Objective
Campaign
Impact
Cost per
Consumer*
C-Effect **
Consumer
Behavior
458,818
$0.23 spent
per target consumer
4.3 consumers
per $ spent
Branded Visitation Activity
(Rate of brand visit lift for exposed vs. control)

24. 8.3%
8.7%
Non-Exposed Exposed
Penetration
Sales Effect - Penetration
The campaign drove a 0.4% point increase in Penetration for Brand X. This translates to an incremental 15K
consumers that became purchasers. Given the campaign investment of $105,503, this cost $6.90 per consumer.
Percent Difference: +.4%
Significance Level: 73%
Total Incremental Penetration:
(Incremental Pen*Reach)
0.004* 3,823,480= +15,294
Return Objective
Campaign
Impact
Cost per
Consumer*
S-Effect **
Sales
+15,294
consumers
$6.90 spent
per consumer
0.14 consumers
per $ spent
+0.4%

25. Measurable returns at every funnel level
Holistic programs not only explore the individual measurement elements, but combine them to tell a complete story
and achieve maximum results.
Total ROI Objective KPI’s
Campaign
Impact
Cost Per
Consumer*
Consumers per
Dollar Spent
Targeting
Efficiency
+2,026,444
consumers
$0.05 19.2
Aided Brand
Awareness
+282,938
consumers
$0.37 2.7
Brand Visits
+ 458,818
consumers
$0.23 4.3
Penetration
+15,294
consumers
$6.90 0.14
Incremental Sales $726,461
= $6.89
per $ spent on advertising **Advertising Spend ($105,503)

26. What does this mean for Marketers?

27. george.pappachen@kantarmedia.com
George Pappachen
Stephen DiMarco
stephen.dimarco@millwardbrown.com