Choosing the Right Data Model Infographic

ARE YOU CHOOSING THE RIGHT
DATA MODEL?
Amidst an increasingly complex landscape of mobile and other digitally
generated customer data, marketers are turning to a wide-range of data
solutions in order to aggregate, manage, and leverage these valuable
high-volume and high-velocity data sources with valuable offline data.
VS.
Response Models
Cloning Models
What Does the Model Do?
Identify inﬂuential
attributes of responders
& non-responders
Identify key
demographic attributes
of existing customers
Rank prospect ﬁles
based on the likelihood
to respond to an offer
Rank prospect files
base on their similarity
(or strength of match)
to current customers
How is the Model Built?
Using...
Using...
OR
Historical
Marketing Data
Current Customer
Data
Direct Marketing
Test Data
Demographic attributes for
responders & non-responders
are identified through
Exploratory Data Analysis
& refined through Multivariate
Logistic Regression Modeling
Key demographies are
identified via a Multivariate
Logistic Regression Model
Demographic attributes
are then “matched”
to a prospect ﬁle
These attributes are then
used to score a target
geographic list
What is the Model’s Output?
A Response Gains Chart
ranks customers into
10 groups (“deciles”) based
on the likelihood of
response (response rate)
A Power Ranking Table
identifies influential
demographies associated
with likely responders
A Prospect List
is then scored based
on the most influential
attributes
A “Match Rate” Gains Chart
ranks populations of customers
and corresponding prospects
into 10 groups ("deciles")
based on strength of
match to customers
A Power Ranking Table that
includes key demographies
associated with the sample
customer group
A Prospect List is then
scored based on the most
influential attributes
Which Model is Right for You?
A Response Model if...
A Cloning Model if...
You want a predictive tool
you can use to project response,
revenue, profit or ROI scenarios,
on a continuous basis
You are primarily interested in
identifying prospects similar
to your current customers
You are changing aspects of
your marketing strategy, i.e.
target audience, product/service,
promotional strategy or media
You are maintaining your
offer & other key aspects of
your marketing strategy
You have historical response data
or have adequate time, budget
and data to conduct a test
campaign/Responder Analysis
You lack historical response
data or have limited time,
budget for a test campaign/
Responder Analysis
* Predictive Models can be developed to measure and predict
many other behaviors, including: spending, cart size, lifetime
value and attrition
Your Success. Data Driven.

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