Jed Dederick and Sean D'Arcy from The Trade Desk's presentation from the Digiday Programmatic Summit in Nashville - November 15, 2015.

1. Accelerated
Onramps:
Leaving
Learning
Budgets
Behind

2. Who
We
Are
2

3. Planning
Process
Today
3

4. Optimizing
a
Hypothetical
Audience
4
Males
18-­‐35

5. 5
5
Learn
Budget
Training

6. Move
the
Learn
Phase
into
the
Planning
Cycle
6

7.
Patterns
of
Historical
Openings
Account
openings
Account
Openings
by
Date

8. Explain
the
Outliers
8

9. Plan
Budget
Where
it
Makes
an
Impact
9
0
50
100
150
200
250
300
350
400
450
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2
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4
5
6
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9
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12
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14
15
16
17
18
19
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21
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23
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4
5
6
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10
11
12
13
14
15
16
17
18
19
20
21
22
23
Account
Openings
Hour
Est
Account
Openings
per
Hour:
Sell-­‐off
Week
vs.
Typical
Monday
-­‐
Wednesday
Sell
Off
Average

10. Examine
Trends
10
0.00%
0.20%
0.40%
0.60%
0.80%
1.00%
1.20%
1.40%
1.60%
0
2
4
6
8
10
12
14
16
18
20
22
0
2
4
6
8
10
12
14
16
18
20
22
0
2
4
6
8
10
12
14
16
18
20
22
0
2
4
6
8
10
12
14
16
18
20
22
0
2
4
6
8
10
12
14
16
18
20
22
0
2
4
6
8
10
12
14
16
18
20
22
0
2
4
6
8
10
12
14
16
18
20
22
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
Sunday
Account
Openings
Hour
Est
Account
Openings
by
Hour
of
Week

11. Investigate
the
Path
to
Conversion
6am
8am
10am
12pm
2pm
4pm
6pm
8pm

12. Where
are
additional
opportunities
to
target?
12
Additional
opportunities
exist
in
France,
Canada,
Philippines,
Indonesia,
Malaysia
and
Singapore.
Europe:
France
is
another
European
country
with
pixel
fires
greater
a
thousand.
North
America:
Canada
has
significant
amount
of
pixel
fires
compared
to
rest
of
the
world.
SE
Asia:
Philippines
had
comparable
pixel
fires
to
Japan.
Indonesia,
Malaysia
and
Singapore
collectively
had
more
pixel
fires
than
Japan.

13. Identify
the
Brand’s
Geographical
Footprint
13
Where
will
DR
campaigns
be
successful?
Where
is
awareness
needed?

14. What
are
the
general
US
geographical
trends?
14
Drill
Down
to
the
City
Level
to
Create
Custom
Geo
White
and
Black
Lists

15. IP
RangeTargeting

16. Actual
IP
Model
Results

17. High-­‐Value
User
fullpath
relevance
Type
Audience
Profiles
>
B2B
Data
-­‐
Func9onal
Area
>
Finance
>
Investment
Banking
88.72
Occupa9on
Travel
>
Interest
>
Flights
>
First
Class
81.99
Past
Purchase
In-­‐Market
>
Retail
>
Business
&
Office
>
Healthcare,
Lab
&
Life
Science
70.21
Occupa9on
Audience
Profiles
>
B2B
Data
-­‐
Industry
>
Finance
>
Investment
Banking
67.73
Occupa9on
Lotame_OCR
Op9mized
>
Age
>
21-­‐29_M
49.35
Demographic
Audience
Profiles
>
Automo9ve
>
Land
Rover
New
Car
Shopper
43.18
Past
Purchase
Branded
Data
>
Experian
>
Past
Purchase
>
High
Price
Jewelry/Accessories
>
Number
of
Purchases:
5-­‐999
34.82
Past
Purchase
Demographics
>
Occupa9on
>
Business
Services
34.00
Occupa9on
Branded
Data
>
Acxiom
>
Basic
Rate
>
ACXM
Demographic
>
Job
Role
>
Re9red
31.29
Occupa9on
Demographics
>
Career
>
Engineering
28.44
Occupa9on
interests
>
educa9on
>
graduate
school
>
extreme
27.50
Demographic
Branded
Data
>
Forbes
>
Forbes.com
>
Entrepreneurs
26.82
Occupa9on
Branded
Data
>
Acxiom
>
Basic
Rate
>
ACXM
Demographic
>
Children
Age
and
Gender
>
Age
>
16-­‐17
>
Male
child
16
-­‐
17
26.65
Demographic
US
>
TRB_US_ITRS_Personal_Finance~Financial_News
22.54
Finance
Branded
Data
>
Webbula
>
Demographic
>
Employment
>
Occupa9on
>
Mid-­‐Level-­‐Management
>
Manager
22.11
Occupa9on
Branded
Data
>
Dataline
>
Purchasing
Interest
>
Golf
Products
Purchasing
Interest
21.92
Past
Purchase
MasterCard
>
Top
Tier
Spender
>
Restaurant
-­‐
Mid-­‐Range
and
Non-­‐Chain
Restaurants
21.77
Past
Purchase
B2B
Predic9ve
Signals
>
Technology
>
Virtualiza9on
21.48
Interest
purchase
intent
>
travel
>
vaca9on
rentals
>
strong
affinity
21.27
Past
Purchase
Interest
>
Finance
>
Markets
>
Finance
-­‐
Markets
-­‐
Mutual
Funds
17.46
Finance
Global
>
B2B
Demo
>
Industry
>
Real
Estate
>
Residen9al
17.34
Occupa9on
In-­‐Market
>
Retail
>
Electronics
17.33
Past
Purchase
Nielsen
TV
>
Genre
>
News
-­‐
Light
Viewers
17.00
Interest
Branded
Data
>
Financial
Audiences
>
Ac9ve
Traders
>
ETFs
16.74
Finance
Global
>
B2B
Demo
>
Industry
>
Real
Estate
16.56
Occupa9on
Branded
Data
>
Analy9cs
IQ
>
Finance
>
Annual
Discre9onary
Spending
on
Reading
16.26
Past
Purchase
Interest
>
Politcs
>
Poli9cs
-­‐
Poli9cal
Views
-­‐
Leans
right
15.44
Demographic
17

18. Low-­‐Value
User
Data Segment
Relevance
Type
Interest > Sports > Cricket
0.0148716
Interest
Interest > Entertainment > Books
0.01521
Interest
Interest > Food Enthusiasts > Vegetarians and Vegans
0.0152249
Demographic
Interest > Auto Enthusiasts
0.0197282
Interest
Demographic > Lifestyle > With Children
0.0206471
Demographic
Branded Data > Lotame > Technology > Android Users
0.0375812
Past Purchase
Interest > Entertainment > Music > Music -­‐ Interviews
0.041369
Interest
Interest > Entertainment > Music > Music -­‐ Songwriters
0.041369
Interest
Interest > Entertainment > Music
0.0414357
Interest
purchase intent > music > extreme
0.0417575
Interest
SEA > Interest > Arts & Entertainment
0.043351
Interest
Interest > Shopping > Impulse Buyers
0.0483746
Interest
Nielsen > Scarborough > Retail Shopping -­‐ Shops at > Sams Club
0.0582562
Past Purchase
Branded Data > Lotame > Ages > 18-­‐24
0.0584328
Demographic
Interest > EducaYon > College
0.0613546
Demographic
CPG > Deli Food Buyers > Deli Bulk Meat
0.0694407
Past Purchase
Branded Data > TARGUSinfo AdAdvisor > Household Products > Disposable Diapers
0.0704916
Past Purchase
In-­‐Market > Retail > Shopping Predictors > TransacYon Predictors > Retail > Cell Phones, PDAs & Smartphones
0.0709293
Past Purchase
Branded Data > Alliant > Women's Interests > CosmeYcs/Beauty
0.0735624
Interest
Interest > Home & Garden > Home Furnishings & DecoraYng
0.0745872
Interest
US > Premium > Social > Social Influencers > Food
0.0769075
Past Purchase
US > Premium > Food > Social > Food Influencers
0.0769541
Past Purchase
US > Reach > Food > Cooking
0.0788016
Interest
Interest > Home & Garden
0.0798161
Interest
Interest > Entertainment
0.0830019
Interest
Branded Data > Experian > Lifestyle and Interests > Pets > Cat Owners -­‐ Precision
0.0834827
Interest
Smart Segments > Shopping Moms
0.085028
Demographic
Nielsen > Scarborough > Retail Shopping -­‐ Shops at > Victorias Secret
0.0885594
Past Purchase
18

19. Better
Targeting
Leads
to
Better
Performance
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Total
Account
Openings
vs.
A9ributed
Conversions
by
Date
Openings
Conversions
Linear
(Conversions)

20. 20