News
 3rd-Party
Data: Increasing Relevancy
By Austin Wright
Relevancy of communication is paramount in
developing relationships with customers. To do this,
you must properly identify, mine and apply
third-party data. It will facilitate more relevant,
meaningful communication streams and improve
consumer relationships.
To rely exclusively on house file data limits
marketers’ efforts to create meaningful dialogue
with their consumers. It is important to first
define your marketing goals and then identify the
data you need.
There are basically four types of data available for
appends: demographic, psychographic, life-stage and
transactional.
Type #1 Demographic Data
Demographic data will provide a customer’s age,
income, family size, education and employment
status.
Type #2 Psychographic Data
Psychographic data will enable better understanding
of consumer interests and general mindset.
Type #3 Life-Stage Data
Life-stage data identify key life-changing triggers
that can personalize a communication by sending the
right message to the right person at the right time.
With this type of data, it is important to
understand if the data identifies the life-stage at
the pre, during or post stage.
Type #4 Third-Party Transactional Data
Third-party transactional data is the most powerful
predictor of retail purchases. It will reveal where
people are actually spending their money.
Transactional data that are gathered across multiple
product categories from multiple retail sources give
marketers a multi-dimensional view of customers.
Frequency of industry purchases makes possible line
extension opportunities and insights into consumer
affinities, for marketing communications are
possible when third-party transactional data is
properly leveraged.
Research has shown that, on average, nearly 90
percent of the most meaningful variables used to
build high-performing direct response models are
transactional in nature, with demographic and
psychographic variables comprising the remainder.
In addition to knowing which data will best meet
your needs, it is important to identify the right
data vendor. Append bad data and you could do more
harm than good.
Source: Identify vendors who are original compilers
of data versus those that broker or allow the
hygiene and collection of the data to be handled by
outside parties. The further the data is from the
original source, the greater chance of error.
Definition: Make sure you understand the true
definitions of data you are getting. Some data may
be reported as 30 days fresh, but it may have taken
60 days for it to be gathered and processed, meaning
that the data is really three months old.
Definitions of variables can vary from source to
source.
Coverage: When data providers don’t have actual
data, they will infer or create model scores to
determine the likelihood of the information. Know
the percentage of actual data versus inferred data.
Not only does third-party data have a proven
history, but with costs ranging from 4 cents to 6
cents per record matched, the marketing investment
is more than justified. When properly sourced,
matched and used, analytic models perform better,
communications are more meaningful and relationships
can turn into loyalty and evangelism.
---Source:
Austin Wright is management supervisor at Rapp
Collins Retail. Reach him at wrighta@rappcollins.com;
DMNews March 26, 2007 issue.
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