MAKING OFFLINE DATA PERFORM

SUBU DESARAJU

VP/Group Director, Strategy

‘DATAPHORIA’

The driver behind the Publicis-

Omnicom merger: Marketers

increasingly rely on data 

Old-School Ad Execs

Sweat as Data Geeks Flex

Muscle

New Ways Marketers Are

Manipulating Data to

Influence You

Ogilvy Chief Data Officer

Role May Be Sign of Things

to Come

CONSUMER DECISION JOURNEY

ACTIVE

EVALUATION

INITIAL

CONSIDERATION

POST-PURCHASE

EXPERIENCE

CLOSURE/

PURCHASE

Intent

Touch Points

Location

Channels Sources of Influence

THE PROMISE OF

DATA

JET FUEL FOR

PROGRAMMATIC MEDIA

01ACTIONABLE

02FREE

03EFFICIENT

FIRST PARTY DATA

Actionable01 Free02 Efficient03

MYTH VS. REALITY

FIRST PARTY DATA

Offline data

?

?

?

Online data

TO USING OFFLINE DATA IN PROGRAMMATIC

3 STEPS

AGGREGATE

Cleanse

Connect

ACTIVATE

Match

Select

SERVE

Bid

Find

AGGREGATION

AUDIENCE ACTIVATION

SERVE

150-200% highereC

PM

OFFLINE DATA ONLINE DATA

OFFLINE DATA EFFICIENCY LEAKS

Offline data yield needs to be significantly higher to compensate for higher costs

• Mine Data

• Model Audiences

• Maximize Find Rate

• Persist Data

• Project Offline Attributes

• Attribute, Eliminate

& Iterate

OFFLINE DATA EFFICIENCY LEVERS

YIELD

COSTS

Share of Market

Conquest/Penetrate

Retain

MA

RK

ET/B

RA

ND

STR

EN

GTH

Maintain

Color = Market, Size of Bubble = Size of Market

MINE DATA

MODEL AUDIENCESLifetime

Value

Propensity

Reachability

V ά 1/PV ά 1/R

R ά P

V

R P

DSP/s

Test DSPs

DMP

Ramp Cookie Pool

Match Providers

Cascade/Utilize Cookie Match Vendors

20-25%

MAXIMIZE MATCH & FIND RATES

Prospect

CRM

PERSIST & REUSE DATA

DATA MANAGEMENT PLATFORM

CPG

A

Cooki

es

(MM

)

18-M

ar

22-M

ar

26-M

ar

30-M

ar

3-Apr

7-Apr

11-A

pr

15-A

pr

19-A

pr

23-A

pr

27-A

pr

1-May

5-May

9-May

13-M

ay

17-M

ay

21-M

ay

25-M

ay0

2

4

6

8

10

12

$-

$500

$1,000

$1,500

$2,000

$2,500

$3,000 Cookie Pool Growth (Mn)CPA By Week

ONLINE ATTRIBUTES

• Behavioral

• Sites visited

• Interests

• Purchase Intent

• Shopping categories

• Location

PROJECT OFFLINE ATTRIBUTES

OFFLINE ATTRIBUTES

• Transactional

• Recency

• Frequency

• Lifetime Value

• Demographic

• Income

• Psychographic

• Lifestyle

Audience Universe

Offline Audienc

e

Attribute both online and offline conversions

Understand the full picture – Over 5 X offline/retail conversions attributable to digital campaigns

Analyze responder/converter segments

Eliminate underperforming audiences

ATTRIBUTE, ELIMINATE &

ITERATE

RESULTS

Realized a 150% improvement in yield;

Reduced CPA by 60%

200 M Offline Prospect

& Customer Records

Modeled records for

conversion propensity

Matched high propensity

prospects to 15M ONLINE

COOKIES

Optimized reach, frequency and

overlap across 100’s of media partners

MATCHED BACK TO RETAIL SALES

Created, extended custom

audience segments

through First Party and

Third Party Data

Served 200 MM

Impressions over 3 months

across Display, Social

media

INTEGRATED OFFLINE AND

ONLINEMARKETING

Q&A

355 Park Avenue SouthNew York, NY 10010 USA