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Data Driven Strategies. Integrating Quantitative & Qualitative. Objectives. Share some new marketing strategies that have been successful within the Financial Services arena in 2007. Get you thinking about breaking down traditional barriers that have existed within our space.

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data driven strategies

Data Driven Strategies

Integrating Quantitative & Qualitative

objectives
Objectives
  • Share some new marketing strategies that have been successful within the Financial Services arena in 2007.
  • Get you thinking about breaking down traditional barriers that have existed within our space.
  • Explore three examples from 2007:
      • Advancements in ITA marketing
      • Segmentation Development and Execution
      • Qualitative and Quantitative Integration
  • Take learnings and apply to your business.
why merkle
Why Merkle?
  • Merkle works with over 50 different financial services clients around driving a better marketing result
  • Our passion is to continue to push the DBM envelope and find new areas that can change the marketing landscape
    • Merkle spends over a $1 MM in R&D around DBM best practices and thought leadership
  • We will share with you two emerging opportunities that we believe can drive big gains in your marketing results!
slide4

Breaking through Barriers to Growth

  • Mature organizations face barriers to sustained revenue growth.
  • They key is to understand how to respond to these challenges.
  • Innovation:
  • New Audiences
  • New Channels
  • New Offers.

Revenue

Doing “more of the same” and playing with incremental wins to maintain.

biggest opportunities in dbm
Biggest Opportunities in DBM
  • Marketing Measurement
  • Media Mix Optimization
  • Enterprise Segmentation
  • Brand Engagement Measurement
  • Data Sourcing, Evaluation and Integration
  • “Whole Brain” Marketing
  • Integrating Quantitative Planning with Creative Execution
whole brain marketing
“Whole Brain” Marketing
  • Lots of press and emphasis around “Left Brain” Marketing
    • Forrester, “What Sticks”, “Competing on Analytics”, etc.
  • Less talk about the power of research and consumer insights - the “why”
  • Our belief is that it is not one or the other…it is both working together - “Whole Brain” Marketing!
  • Traditionally, marketers have approached, managed and hired these two competencies separate from one another
  • This has led to under-optimized marketing performance
current landscape
Current Landscape

In general, we have observed four different levels integrating the right and left brain capabilities.

Level 4

“One Agency”

Both capabilities exist

in one team

The team works daily

with each other

Neither capability

Dominates

Marketing strategy is

in a unified fashion

Accountability and the

Big Idea working together!

Level 3

“Virtual Agency”

Both capabilities exist

through separate groups

Groups come together

periodically to share info

Strategies are debated

and decided upon in this

virtual agency forum

“Turf war” tends to exist

  • Level 2
  • “Agency and DBM”
  • Both capabilities exist
  • through separate groups
  • Groups work independent
  • from one another
  • Both offer up strategies
  • with marketer left to
  • determine best approach
  • Level 1
  • “Right Brain Only”
  • Creative and Big Idea
  • people lead marketing
  • Little quantitative skills
  • Experience and intuition
  • are key drivers
research and analytics
Research and Analytics
  • Data Analytics (often called Quantitative) and Primary Research (often called Qualitative) are typically disjointed from each other.
    • Example – DBM company and Market Research Company. Very rarely do you go to one company to get these.
    • Yet both are dependent on each other, both tell a story and both are data driven.
    • Separating them can and will cause a loss of knowledge and create inferior results
research analytics
Research & Analytics

DESCRIPTIVE Research

Focuses on the “why” and the “how” of audience behavior –

identifying and interpreting the meaning behind consumer

actions, decisions, beliefs and values; and understanding

their decision making process

Qualitative

Insights

PREDICTIVE Analytics

Focuses on the “who’ and “what” components of direct

marketing – utilizing data, facts, information and

knowledge to identify and create statistically valid

measures that drive business decisions

Quantitative

Approach

the combined benefits
The Combined Benefits
  • Accurately identifying customer and prospect universes and segments
  • Understanding purchase influencers
  • Gauging reaction to new concepts/products
  • Identifying key loyalty and attrition factors
  • Optimizing channel expenditures
  • Increasing the ability to predict campaign performance
  • Moving beyond “Beat the Control” in creative
  • Tangible and actionable insights to improve your value proposition.
  • Ultimately...improved ROI

Qualitative

Insights

Quantitative

Approach

process overview
Process Overview

Creative &

Production

Analytics

&

Test

Design

Behavioral

&

Attitudinal

Data

Applicable Data

Quantitative

Models

Objectives

& Strategy

Qualitative

Insights

Content

Solutions

Why?

What?

Who?

How?

Combined approach answers the root questions

ita marketing
ITA Marketing
  • Over the years, ITA marketing (especially within the credit card space) has struggled to find a firm spot within the marketing plan
  • Major advances in technology, data and analytics have the ability to boost the performance of ITA programs
  • We are observing that many credit cards companies are not capitalizing on this and are running sub-optimal ITA programs
the credit crutch
The Credit “Crutch”
  • Many companies have become too reliant on credit data!
    • Past ITA performance poor
    • Data, technology, analytics, creative and campaigns are built around pre-approved programs
    • Difficult to change
    • Assumed to minimized risk and loss
    • Hard to get commitment from Sr. Management
disadvantages of credit data
Disadvantages of Credit Data
  • Many disadvantages exist around utilizing credit data in 2007
    • Increasing Legislation and privacy
    • Expensive
    • Limited audience
    • Diluting offers and messaging to be conservative
ita yesteryear today
ITA - Yesteryear & Today

ITA

Today

Many Major Advancements:

Better Data - Predictive

Advanced Analytics

Segmentation

Data Lab vs. Vertical Lists

New Channels

ITA

Yesteryear

Faster Learning Cycles

making ita work approach
Making ITA Work - Approach
  • Create an integrated ITA Marketing Team
  • Get access to External Data
  • Make use of powerful Internal Data
  • Segment the Audience
  • Powerful analytics
  • Insight
  • Offer, messaging and creative testing
  • Measure, Learn and Improve
integrated ita team
Integrated ITA Team
  • Optimizing your ITA program requires a team of highly skilled people working together on a daily basis
  • Requires both right and left brain marketers
    • Marketing ITA leader
    • Analytics lead
    • Data Expert
    • Insight specialist
    • Creative Lead
    • Program manager
    • Campaign manager
external ita data
External ITA Data
  • Data is extremely important in building a high performing ITA program!
  • In the last several years, the availability of external third party data has increased dramatically:
    • Summarized Credit Data
    • Auto Data
    • Mortgage, Homeowner Data
    • Transactional Co-op Data
    • Demographic Data
    • Wealth Data and Models
    • Lifestyle Data
    • Life Event Data, Etc.
slide20

ITA Data Matrix

Summarized Credit Statistics

High

Auto Data

Mortgage Data

Universe

Demographic Data

Real Estate Data

Wealth Indicators

ITA Impact

low

high

Econometrics

Transactional

Lifestyle Data

Segmentation Data

Life Event Data

Low

Vertical Data

internal ita data
Internal ITA Data
  • This is data that is available within your existing infrastructure
  • Some of the most descriptive and predictive data come from your “internal” data:
    • Promotional history
    • Summarized cardholder data
    • Response history
    • Derived Data
    • Etc.
derived variable spending velocity
Derived Variable – SPENDING VELOCITY

A modeled field estimating how frequently a household is likely to spend over a period of time. Higher values indicate high spending velocity.

Value and Ranges:1 to 20

  • TOP VARIABLES
  • Avg loan amount & all open revolving trades
  • Avg Spending Velocity Index (CR level)
  • HOH age & Household size & Car owner
  • LM Finance Card Index
  • Avg outstanding balance on all open bank card trades
  • Avg number of revolving trades 30 or more days delinquent or derogatory
  • Length of residence
  • Percent of profile consisting of open retail accounts

ITA Impact Score

HIGH

LOW

derived variable inferred cardholder
Derived Variable – INFERRED CARDHOLDER

A modeled field that estimates the probability of the household having bank and/or credit cards. The higher the ranking, the more likely it is that the household has a credit card.

Value and Ranges: 1-10

  • TOP VARIABLES
  • Marital status – married
  • Number of sources
  • Merkle Donor Rating
  • Avg Auto1 open date
  • Percent population inside urbanized area
  • Polk flag
  • Merkle Wealth Rating
  • Age range in HH
  • Responders (Group Variables)
  • Avg student high credit

ITA Impact Score

HIGH

LOW

prospect segmentation
Prospect Segmentation

Experian

I

III

II

ITA Universe

Credit Universe

Equifax

TU

Segmented Targeting Opportunities

Segment I – Universe Expansion

Segment II – Leverage non-credit data to optimize the performance

Segment III – Maximize the Pre-screen Program

slide25

“Audience to Offer” Expands Universe

Climbers

Urban Singles

Gen Y

Difficult

Underserved

“Seekers”

Market Penetration Index

Poor Credit

Easy

Low $

High $

Affluent Families

behavioral segmentation
Behavioral Segmentation

Descriptive Profiling Characteristics

ITA Segments

Spending Habits

Lifestyle

Travel

• Cash transactions

• Credit transactions

• Lifetime Average Spend

• Lifetime Transactions

• Lifetime Quantity per

Transaction

• Trailing 12 mo Spend

• Trailing 12 mo

Transactions

• Cars

• Electronics

• Home & Garden

• Babies & Kids

• Apparel & Jewelry

• Health

• Sports & Outdoors

• Entertainment

• Foreign Travel

• Domestic Travel

• Premier Foreign

Travel

• Premier Domestic

Travel

Gen Y

Climbers

Seekers

Urban Singles

Affluent Families

Poor Credit

slide27

AUDIENCE

OFFER

20 to 1

10 to 1

ITA Success = “Audience to Offer” vs. traditional “Offer to Audience”

“Whole Brain” Marketing Profit Drivers

CREATIVE

CONTACT

MEDIA

CHANNEL

MESSAGE

Database Marketing Profit Drivers

6 to 1

5 to 1

3 to 1

3 to 1

2 to 1

Marketing Focus Changes from YOU to THEM (Audience)

Expands Prospect Universe

Maximizes and Optimizes Revenue

Establishes More Relevancy

slide28

CREATIVE

CONTACT

MEDIA

CHANNEL

MESSAGE

6 to 1

5 to 1

3 to 1

3 to 1

2 to 1

Building & Executing the Plan

“Whole Brain” Marketing Profit Drivers

AUDIENCE

OFFER

Database Marketing Profit Drivers

20 to 1

10 to 1

  • Need to build communication strategic roadmap that optimizes the:
  • Media (Channel) preference,
  • Frequency,
  • Channel of interaction,
  • Messaging (value proposition) and finally……
  • The creative that brings all of the above to life!
slide29

Strategy vs. Creative

  • Marketing campaigns conceived by blue-sky ‘creative’ thinking are 4Xmore likely to fail than succeed.
  • Campaigns based on insights are 15Xmore likely to succeed than fail.”

A statistic quoted by Michael Moon at a DMA Symposium in Amsterdam

the proof
The Proof:

Background

  • Client was 100% Credit Data
  • Losing share and needed universe expansion
  • Tired creative with “vanilla” offerings

Result

  • Increased marketable universe by over 25% via new data,
  • Lower Cost, Greater Response, Same Risk via segmentation scheme, modeling
  • New Segment-specific Offers & Messaging with comprehensive communications plan
  • Through aggressive testing strategies, developed optimal communication plan for select segments
  • Program deemed roll-out in 3 Months
enterprise segmentation
Enterprise Segmentation
  • That market is cluttered with segmentation schemes and solutions
  • Some are robust and effective but most are vaporware with little impact
  • Merkle believes that, at the highest levels, segmentation can and should be a strategic asset for a company
segmentation
Segmentation

Why Segmentation Disappoints*

  • Excessive interest in consumer identities rather than focusing on product features that matter most to consumers
  • Too little emphasis on actual consumer behavior, which reveal attitudes and predict business outcomes
  • Undue absorption in the technical details of devising the segmentation
  • Creation of a solution that focuses on insights but fails to address actionability
  • Lack of vision regarding methods and tactics enabling maximization of the segmentation solution

* Source: First three (3) reasons for disappointment provided by the following article: Rediscovering Market Segmentation, by Daniel Yankelovich & David Meer, Harvard Business Review, February 2006

segmentation our view
Segmentation - Our View
  • There is no single best approach to segmentation
  • The right approach is one that will satisfy the overall objectives and leverage the right information
  • Merkle believes that leveraging research-based, customer and marketable universe data is a best practice
  • The solution must be both relevant to the marketing executive and actionable to the marketing manager
3 major types of information
3 Major Types of Information

Research

Customer

  • Primary Research
  • Secondary Research
  • Syndicated Panels
  • Behavioral
  • Product Mix
  • Transactions
  • Usage
  • Revenue / Value

?

  • Most directly tiedto customer value
  • Strongest predictor of future purchase activity
  • Product mix provides overall depth of relationship
  • Provides insightsinto consumer needs and intentions
  • Overall market share and total behaviors (not just with your brand)
  • Self reported information, typically very simple to understand
  • Get media consumption and awareness / consideration metrics

?

?

Universe

  • Compiled
  • Credit
  • Verticals
  • Co-ops
  • Only source available on total marketable universe
  • Other two buckets are a subset of this universe
  • Bureau and co-op sources can provide some behavioral insight
option 1 start with attitudes
Option 1: Start with Attitudes
  • Benefit: Directly gets to customer intentions, needs and attitudes
  • Approach:
    • Drive the initial survey and segmentation – guide it to leverage more widely available data and steer the initial segmentation to potentially be more predictable
    • Build a unique methodology to map to DB and then re-profile and define the segments based on the post mapping procedure

Customers

Sample

InitialResearch

AdditionalResearch

Map segments to Universe

Marketable

Universe

Prospects

Segmentation using Market Research

Sample

Panel

Seg #1

Seg #2

Seg #3

Seg #n

Seg #1

Seg #2

Seg #3

Seg #n

Build Initial Profiles on Segments

Re-Profile and Re-Define Final Segments based on Prospect, Customer and 2nd Research Stage

Initial Segments(Sample Only)

Final Segments(Marketable Universe)

option 2 start with customer behaviors
Option 2: Start with Customer Behaviors
  • Benefit: Assume that in mature markets, companies with decent market share have some penetration into all underlying (unobserved) market segments
    • Given that, this approach can identify and describe the differences within these segments, especially between prospects and customers
  • Approach:
    • Leverage market research, conduct research specific to each segment and drive the descriptions and profiles with that insight information for the presentation layer
    • Starting with customer behaviors gives us a solid foundation on which to build a mapping process to the marketable universe

Marketable

Universe

Customers

Segmentation using Customer Behavioral Data

Map Segments from Customers to Universe

Seg #1

Seg #2

Seg #3

Seg #n

Seg #1

Seg #2

Seg #3

Seg #n

Build Profiles on Customer Behaviors

Build Profiles on Customer & Prospect Data

Customer Segments

Final Segments

Finalize Market Segments based on Learnings from Research – Use this information to “color” segments

ConductResearch by Segment

choosing the approach
Choosing the Approach

Determining the right approach to strategic depends on the client and the situation

  • Consider the company’s business model and competitive landscape
  • The maturity of the company and the product play a factor – immature markets/company lack data and market share
  • Determine the primary and overall objectives – if there is a specific objective, perhaps a tactical approach would be better
  • Consider modifications or customizations to the two solutions presented to best fit the situation (hybrid approaches)
choosing the approach1
Choosing the Approach

Mature / MarketLeader

Option II

Option I

Industry / Company

Option II

Option II

Immature/ New

Non-Direct

Direct toConsumer

BusinessModel

making the segments actionable
Making the Segments Actionable

2

3

4

5

1

6

Coming of Age

Conservatives

Savings Hunters

Growing Families

Upscale Singles

Cosmopolitans

Prospects

% of all US Households

13.3%

14.3%

11.2%

27.7%

15.6%

17.8%

% of Client Inquiries (funnel Index)

15.8% (119)

9.3% (65)

Inquiries

20.8 (133)

12.4% (111)

29.8% (108)

11.9% (67)

Population

% of Client

Customers

(funnel Index)

Customers

11.6% (125)

10.3% (83)

31.0% (104)

15.7% (75)

15.6% (99)

15.5% (133)

% of Client Cancels (funnel Index)

15.7% (100)

9.2% (79)

Cancels

21.5% (137)

13.0% (126)

30.2% (97)

10.3% (66)

  • 27%<30 yrs; 14%>60yrs
  • 24% with Bachelors or higher
  • 5.5
  • 39%
  • 39% married
  • 21%
  • 2.9 Years
  • 17%<30 yrs; 21%>60yrs
  • 19% with Bachelors or higher
  • 6.7
  • 38%
  • 50% married
  • 33%
  • 4.7 Years
  • 17%<30 yrs; 15%>60yrs
  • 29% with Bachelors or higher
  • 7.7
  • 48%
  • 60% married
  • 47%
  • 5.6 Years
  • 15%<30 yrs; 18%>60yrs
  • 37% with Bachelors or higher
  • 7.6
  • 38%
  • 58% married
  • 41%
  • 5.0 Years
  • 6%<30 yrs; 45%>60yrs
  • 44% with Bachelors or higher
  • 8.9
  • 18%
  • 62% married
  • 56%
  • 7.0 Years
  • 7%<30 yrs; 40%>60yrs
  • 37% with Bachelors or higher
  • 8.4
  • 22%
  • 62% married
  • 44%
  • 6.0 Years

Age

Education

Wealth Rating

Children in Household

Married

Homeowner

Length of Residence

Demographics

  • Quoted Premium
  • Premium per Driver
  • Premium per vehicle
  • Stated Previous Insurer:
  • Competitor 1
  • Competitor 2
  • Competitor 3
  • Competitor 4
  • Competitor 5
  • Competitor 6

Inquiry Profile

Premium

Premium per Driver

Premium per vehicle

% New Customers

Tenure

% Internet Sale

% With a new car

% with claim

Gender

Customer Profile

the funnel framework

Segment 3

The Funnel Framework

27.7%

Segment 4

Segment 1

Segment 6

Segment 5

Segment 2

17.8%

Entire Marketplace

15.6%

14.3%

13.3%

11.2%

  • Primary Framework for Clients
  • The two permanent segments: attitudinal segments (across the funnel & lifecycle (down the funnel)
  • The Funnel data can be selected based on time (most recent 1, 3, 6, 12 months) and geography (national, state, DMA)
  • Many different metrics can be displayed within the boxes (population % and indices shown to the left)

Aware

Engaged

108

133

Inquirer

119

111

67

65

26.1%

26.4%

25.3%

27.8%

25.2%

22.9%

104

Customers

133

75

99

125

83

97

Cancels

137

100

126

66

79

identifying with your segments
Identifying with Your Segments

Some basic rules:

  • Telling them you know things about them with the copy or images does not win you their appreciation or drive results.
  • Remember creative should always keep an aspirational (younger, wealthier, action packed) vibe.
  • Listen to your segments and define them based on their needs, attitudes and behaviors.
  • Tailor your offers (if you can) and/or your value propositions within those offers as your primary means of executing segment specific creative approaches.
implementation focus
Implementation Focus

75%

The

Offer

50%

Impact

Value

Prop/

Offer

Message

25%

Creative

Design

& Copy

Focus

recent segment specific creatives
Recent Segment Specific Creatives

Based on the new segmentation, Merkle recommended expanded testing to increase messaging strategies and “personalize” the marketing approach

Client selected two segments of inquirers to start the testing process:

Cosmopolitans

Savings Seekers

Merkle and Client’s internal creative team would each develop new kits to drive inquirer conversion and beat the longstanding 3 year+ control.

The Result: ALL TESTS BEAT THE CONTROL

valuable messaging insights
Valuable Messaging Insights

Cosmopolitans

Demographics:

  • Oldest Population (66% over 50yrs old)
  • High income group
  • Most educated (44% with Bachelors or higher)

Media Consumption:

  • Very likely to read newspapers
  • Radio formats likely to listen to: news/talk, sports
  • Radio formats not likely to listen to: urban, CHR
  • Likely to watch: Documentary, evening news, golf, horse racing, skating, tennis
  • Not likely to watch: daytime comedies, primetime comedies, daytime drama, game shows, reality shows

Insurance and Automotive:

  • Highest levels of auto insurance coverage

Attitudes and Perceptions:

  • Buy based on quality not price
  • Loyal to brands they like
  • Low consumer confidence: feel they will be financially worse off within 12 months
  • Focused on eating healthy
  • Feel TV advertising is too loud and repeated too often
  • Most likely to trust newspaper, Least likely to trust TV
  • Likely to purchase items by phone
  • Much more likely to engage in foreign travel
valuable messaging insights1
Valuable Messaging Insights

Savings Hunters

Insurance and Automotive:

  • Want the cheap/easy to maintain vehicle

Attitudes and Perceptions:

  • Tend to make impulse purchases
  • Will switch brands for small discount
  • Only save money for specific purposes
  • Like humorous TV advertising
  • Get least amount of sleep at night compared to other segments
  • Most likely to say holding true to religious faith and beliefs is important
  • Most likely to trust TV, least likely to trust internet

Demographics:

  • Typically 30 – 55
  • Low income group
  • Lowest education level (19% with Bachelors or higher)

Media Consumption:

  • Likely to watch: Auto racing, daytime dramas, reality shows, primetime comedies, early morning news, game shows, primetime films
  • Not likely to watch: Golf, horse racing, tennis, news specials
  • Radio formats likely to listen to: country, urban, rock
  • Radio formats not likely to listen to: news, talk, oldies
quick story
Quick Story

CFM Direct Had Great Results

  • AOR of College Savings Product in the 529 Family.
  • Handled all aspects: Planning, Media, Creative, Production, Analytics
  • “Knew the product” - had the insights, control and skills.
  • Identified good stable of Vertical and some Compiled Lists
  • Had great lead volume from multiple channels: Schools, Pubs, Web & Mail
  • But…the product was not performing the way they had planned - it was “grow or die”
quick story1
Quick Story

CFM Direct Purchased by Merkle

  • Analytic horsepower and data options expanded exponentially
  • Knew we needed a more precision based marketing approach - a way to SHOW the client hot to drive results
  • Assembled a new Client team complete with Research, Creative, Analytics, Data and Search SMEs.
the process and approach
The Process and Approach

Quantitative

Qualitative

Analyzed Past Performance of all Variables:

Lists, Creative, Channel, Value Propositions, Seasonality, etc.

Delivered full year “Precision” marketing plan with detailed learning agenda

  • Analytic Approach:
  • Lower CPA via “Look Alike Models”
  • Grow Universe via New Data & Resp Models
  • Identify Segments for Messaging
  • Creative Approach:
  • Reviewed Secondary Research
  • Created 3 New Key value propositions.
  • Conducted Primary Research

Coordinated design of testing with execution to accelerate learning agenda.

Out of the gate…results beat our existing controls by 48%

slide52

Qualitative & Quantitative: Why it’s Working

Sharing a Vision & Strategic Roadmap

Understanding what the Business,

Product and Client Requires

Face to Face Meetings

Analysts, Creative, Strategy, Production

Key Points of Integration

Analytic Brief, Analysis Review,

Data Brief, Data Review

Creative Brief, Creative Review

Integrated Communications

Schedules, Status Reports, Invoicing, Approvals,

Presentations, Performance Review

summary
Summary

“Whole Brain” Marketing – Bring the two competencies of left and right brain closer together

Client

Client

DM

Agency

DBM

Company

DBM Agency

DBM Agency

Best

“Virtual” Agency

Good

summary1
Summary

Capitalize on the synergy and power of integrating research and analytics

Traditional Scenario

New Scenario

Market Research

Market

Research

Quantitative

Analytics

Quantitative Analytics