life is never random … how to make the most of your data strategy

#BRIDGE17

LIFE IS NEVER RANDOM … HOW TO MAKE THE MOST OF YOUR

DATA STRATEGY

DENIS MCSWEENEY: AARP- DIRECTOR, DIRECT MAIL CHANNEL

MARYANN BUONCRISTIANO: MERKLE- VP DATA SOLUTIONS

JENNIFER HONADEL: EPSILON- MANAGING DIRECTOR

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Elements of a data strategy

How to stay ahead of the changes

Key elements to success

Learning Objectives

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Elements of Data StrategySolid Strategy will be Aligned with Marketer’s Business Objectives and Budget

Long term valueNew

donors/members Average Gift/Spend

Channel

preferenceMailing

efficiencies

MessagingCreative/ Offer

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Key Components

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Optimizing Data StrategyThere are proven methodologies that we can employ to help organizations improve their data sourcing strategy to positively impact results:

• Utilizing data for multichannel people based marketing

• Leveraging analytics to drive data evaluations

• Enhancing data sourcing pre-campaign

• Improving data performance through predictive analytics

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All-Channel Planning, Activation & Measurement

Personally Identifiable Information (PII)

Direct Digital Broadcast

All-Channel Data for People-Based MarketingRead the blogpost about the conference at merkleinc.com

http://www2.merkleinc.com/l/47252/2017-09-18/4x6dl8

Data Evaluation Process to Drive Performance

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Coverage

Maximize unique reach and avoid

duplication across data providers

Descriptive power

Quantify descriptive power of data sets

based on granularity of segmentation

Predictive power

Benchmark predictive power

of data in live client models

Accuracy

Identify the most accurate data

based on consensus models

and distribution analysis

Cost

Optimize cost by minimizing

duplication across data providers

Read the blogpost about the conference at merkleinc.com


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Enhancing Data Sourcing Pre-CampaignLeverage Historic Information to:

• Reduce list sourcing costs (Typical Reduction Range = 20%-50% reduction in list costs per campaign)

• Maintain/Improve Campaign Performance• No impact to current campaign processing

7

AARP historical list sourcing AARP current list sourcing

ListList

List

List

List

ListList

List

List List

ListList

ListList

ListList

ListList

ListList List

List

List

List

List

List

List

List

ListList

List List

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Enhancing Data Sourcing Pre-Campaign

8

Response is assigned to each of the lists

on which the individual exists

Response is randomly assigned to a

single list, typically the list that got paid.

Remaining lists do not get the credit

hence resulting in incomplete attribution

Un-biased (appeared-on)

response attribution

Traditional response attribution

Response attribution analysis:

List

1

List

2

List

3

List

4

List

3

List

1

List

2

List

3

List

4

List

1

List

2

List

3

List

4

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• List Cost Per Piece -reduced the overall LCPP significantly over the last 5 years through removal of higher cost, high overlap rentals and ongoing price negotiations.

• Annual LCPP is over 60%+ lower than prior to this methodology.

$0.0256 $0.0238

$0.0161

$0.0135 $0.0120

$0.0093 $0.0098

$-

$0.0050

$0.0100

$0.0150

$0.0200

$0.0250

$0.0300

1/11-5/11 6/11-12/11 2012 2013 2014 2015 2016

LCPP

Success AARP has AchievedRead the blogpost about the conference at merkleinc.com


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AARP:Data Strategy Challenge• Nonprofit, nonpartisan, social welfare organization

• Mission: Enhance quality of life for all as we age –not just AARP members

• Membership: 38 million

• Target audience: age 50+

Gen X 1965-1984

(ages 50-52)#BRIDGE17

Boomers 1946 -1964

(ages 53-71)

Silent Gen 1925 -1945

(ages 72+)

Data Strategy Challenge: Part 1

54 years old

Different needs,

interests,

concerns

76 years old

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• Acquisition Mail’s response rate is highest among prospects turning 50: 'pent-up' demand’.

• The 50-59 age group is strategically important (and large), but does not view AARP as relevant to their lives.

188

81

110117

94

3.4%

41.6%

34.5%

13.0%

7.5%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%

40.0%

45.0%

0

20

40

60

80

100

120

140

160

180

200

49 50-59 60-69 70-79 80+

AARP Response Rate Index by Age Share of Mail Quantity by Age



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How can AARP be more relevant to the 50-59 age group?

• Special messaging for prospects turning ‘the big five-0’.

• Provide the option to respond online via a coupon code.

• Different copy (skip Medicare supplemental insurance).

• Premiums (for joining) that skew younger… like a Bluetooth speaker.



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Coupon code audience:

• Ages 50-69 with $40k+ HH income.

• Tested among a broad age range, and then used analytics to identify the ‘optimal’ segment.

• Optimal = Maximizing online’s share of responses without lowering overall response.



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Data Strategy Challenge: Part 2The quest for the ‘holy grail’:

• Goal: Segment the prospect universe based on propensity to respond (transact) online

• Step 1: Test the use of an Epsilon TotalSource Plus variable, Channel Preference Ratio – Online • Postcards vs. letter packages

• Higher vs. lower online channel preference

• Step 2: To be decided…

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Data Strategy Challenge: Part 3Multicultural:

• Hispanic and AA/B segments are an important part of each Acquisition Mail campaign.

• Prospects are classified as Hispanic or AA/B based on an internal model (data variables, Census, zip/last name) and/or list owner classification.

Key questions:

Are there sub-segments

that will respond better to

differentiated messaging?

Can these segments

be modeled using

variables on the

prospect database?

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Utilize analytics to

determine the optimal

list mix for each

campaign. (List rental

can get out of control:

AARP was paying

more than 2x what it

should have been!)

Utilize modeling to

rank and select names

for mailing. Update the

model annually.

Mail random samples

of names in each

campaign to enable

update of the model

and measurement of

model performance.

Target special offers

based on promotion

history and data

variables (e.g., month

of birth for

a birthday offer).

Data Strategy: Best Practices

1 2 3 4

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Data Strategy as Growth Engine

Data Assets

Matched to AARP

Analytics

Isolate target audience

Insights - Strategy

Understand wants, needs concerns

Creative & Messaging

Align to audience

Technology

Ensure accuracy and consistency

Delivery

Data-driven inputs Multi-channel decision Reach

Activation & Performance

Reach audience in all channels

Data and Insights Drive the Organization



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Isolate and Profile the Target Audience

Gift Size/MembershipTerm

1

Lifetime Value

2

Season4

5

New Donors/Members

Channel

3

Match & profile

Survey

Machine learning



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Know Them BetterPredictive modeling/segmentation

Attitudinal Data

Why you join• Relationship to cause/org

• Engagement

Demographic Data

Who you are• Demographics and Financials

• Lifestyles and hobbies

• Digital activity

• Media consumption

Purchase Data

What you buy• Consumer transaction data

across brands / categories

• All channels

• Charitable categories

• Size of gift

• Frequency of giving

• Ratio giving to spending

Donation/Member Data

What you give

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Reach in All Channels

• Direct Mail

• Email

• Online

• Social

• Mobile

• Television



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Its Smart to Use the Same Data Across All Channels

Suppose you need income information for online targeting

Multi-sourced profile data

“12 different offline sources

agree Household Income is $100-120k. User has

checking account and a value score of

A2”

Online behavioral data

“Visited Forbes.com,

where average visitor has

income of $180k”

IP/ Geographic data

“Uses an IP address that

corresponds to a DMA where

average income is $70k”



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Read about the conference at merkleinc.com!

Thank You Mary Ann Buoncristiano – [email protected]

Denis McSweeney – [email protected]

Jennifer Honadel – [email protected]


mailto:[email protected]



life is never random … how to make the most of your data strategy

Government & Nonprofit