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Improved Data Will Produce Better Models
By Jim Wheaton
Principal, Wheaton Group
Original Version of an article that appeared in the
October 14, 1996 issue of "DM News"
How many angels can dance on the head of a pin? This is a
question that inspired a furious theological debate many centuries
We database marketers are fixated on our own pins and angels with
our constant wrangling about modeling techniques. A by-product
of this debate is the fantastic claims made by proponents of these
My favorite is a promotional piece that I received this summer from
a neural network software company. The brochure began by noting
that conventionally selected rental lists generate a 1% to 2% response,
and it ended with the case study of a client that pulled 63% via
the company's neural net product.
Unfortunately, such claims are pabulum for the gullible. I
am not questioning the veracity of the 63% response rate.
I am confident, however, that this extreme result was due to a unique
combination of list, product and offer — and not to the neural
net product itself. There is only so much variance in the
data, and the unfortunate truth is that new modeling techniques
are not going to drastically improve segmentation power.
While we focus on our pins and angels, however, a quiet revolution
is taking place that centers around improved data rather than modeling
techniques. Smart target marketers are realizing that the
real key to more powerful models is increased and more accurate
information — the input to the modeling process. In other
words, to fracture a quote from Bill Clinton, "It's
the data stupid!"
One important development is the co-op databases of catalog purchase
history. Abacus, the granddaddy of them all, has succeeded
in combining customer transaction history from over 600 catalogers
into one massive database. Other players, such as Smartbase
and Z-24, are formidable competitors.
A senior catalog executive recently relayed to me the success he
has had with one of these co-op databases. His co-op of choice
consistently has identified profitable groups of purchasers from
customer segments that his own models have classified as poor performing.
The reason for this success is improved data rather than revolutionary
modeling techniques. The co-op is able to identify individuals
who are buying from other catalogs — although not recently
from our senior executive's — and are therefore likely
to be responsive.
The power of co-op databases is that they contain what I call "money
where your mouth is" lifestyle information. Based on
actual catalog purchase behavior, individuals identify their life-stages
— parents of newborns, bicycling enthusiasts, and the like.
Such information is critical to targeted promotions.
A limitation of these co-op databases is that they only represent
the catalog-buying portion of U.S. households, and do not contain
all of the catalog purchases for even this minority. The challenge
is to extend the coverage in terms of both names and transactions
by finding additional sources of "money where your mouth
is" lifestyle information.
One candidate is retail databases. We have a client, for example,
that maintains detailed purchase information on eleven million customers.
This client tracks item-specific transactions, totaling several
billion dollars, on about 45 diverse merchandise groups such as
jewelry, sporting goods and electronics. Imagine the targeting
possibilities of a co-op database comprised of four or five large,
non-competing retailers, totaling — say — 70 million households.
Besides driving retail-specific promotions, this data would allow
the catalog co-ops to close their purchase gaps. The catalog
data, of course, would do the same for the retailers. Throw
in some clever marketing and creative, and the result would be innovative
combined offers; for example, purchase Product A from Retailer X
and get 50% off an order from complementary Catalog Y.
Another promising source is magazine subscriber files. The
hundreds of niche titles that populate newsstands throughout the
country are excellent vehicles for lifestyle information.
With complete lifestyle profiles gathered from multiple industries,
the targeting possibilities would be endless. The trick, of
course, is combining these disparate data sources in such a way
that it is advantageous to all participants. This is a challenging
yet not impossible task. After all, who would have thought
five or ten years ago that hundreds of catalogers would willingly
and profitably share data?
To summarize, the success of catalog co-op databases is evidence
that today's key to dramatically enhanced target marketing
lies more with improving the data — the input to the modeling
process — rather than with the modeling process itself.
"Money where your mouth is" lifestyle information, compiled
from multiple sources of purchase information, would result in astonishingly
Jim Wheaton is a Principal at Wheaton Group, and can be reached
at 919-969-8859 or email@example.com. The firm
specializes in direct marketing consulting and data mining, data
quality assessment and assurance, and the delivery of cost-effective
data warehouses and marts. Jim is also a Co-Founder of Data