Transcript The Basics of Direct Mail Testing critical but simple

Patty Brehm
Mailmen, Inc.
June 21, 2010
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The plain pencil is symbolic of
both the attitude and the practice
of the true testing direct marketer:
1. You get up close to the numbers.
2. You must be prepared to make
a lot of changes.
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“If you're not failing
every now and again,
it's a sign you're not
doing anything
very innovative.”
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"It is common sense to take a method and try it.
If it fails, admit it frankly and try another.
But above all, try something.“
Franklin Delano Roosevelt
32nd U.S. president
…and if you want to stand out from
the crowd you have no choice
but to keep experimenting.
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What do the best direct mailers know
and how do they know it?
► They know how customer behavior differs at various
seasons of the year.
They keep complete records of what is mailed when.
► They know which sets of customers are their most
profitable, and which sets are a drag on their bottom line.
They assign each customer an RFM* score. (* to be explained)
► They know who tends to respond to what type of offers.
They integrate codes into each offer and each list.
► They know when to spend more money on a mailer and
when to save money and get the same results.
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A real-life example of the direct mail and email
test records kept by a major retailer:
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Product: Watches
Season: Graduation Time
15% Off, Free Engraving
Prestige Name Brands
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Aim Properly
When You Test:
Your goal is to gain
knowledge that will
translate to true
insight into your business.
Response rates and income are secondary
and will grow as your knowledge grows.
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What do you test first…
The package or the list?
► Create a basic direct mail piece and begin
with the basics.
► Keep it as simple as possible, without a lot of
“bells and whistles” in the package.
► Use examples of fairly well proven techniques
and avoid expensive and ultra-creative
formats.
► Then begin testing lists using this same piece.
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How many
different elements
can you test
at a time?
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► Don’t skimp on data kept
► If in doubt, record it
► # of pieces mailed, list used
► Weather, mailing circumstances, major
news events
► Number of responses, source of responses
► Average order size
► Conversion rate
► Response rate
► Cost per thousand for the piece
► Cost per order
► Percentage of no-pays, returns, etc
► ROMI
► Any differences in ordering trends
► Methods of payment
► Response methods chosen
What
do you
record
for
each
test?
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Q: What should you do with test numbers
after a test is complete?
A: After analysis, write a “verbatim” of your test. You
should have an official report for every mailing.
That report should contain:
► A description of the test
► The purpose of the test
► The components of the mailer
► Statistical data
► Complete results
► A numerical and a verbal analysis
► Action steps advised as a result of the test
Source: Dean Reick, CEO, Creative Direct LLC
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“Initial tests have a nasty tendency to be flaky.
So you should always retest, especially when you
get a positive result or a significant change in results.
It's tempting to instantly toss anything that fails
and adopt anything that wins. But it often
pays to be patient. Test it again and see
if you get similar results before making a decision.”
Dean Reick, CEO, Creative Direct LLC
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Your test results should be the most important determinant
of your list, offer, formats and creative strategies ongoing.
“Learn to observe and trust the data,
not your ‘gut instincts’.
Your gut doesn’t know squat.”
Steve Cuno, Chairman, The Response Agency, Inc.
Author:
Prove It Before You Promote It:
How to Take the Guesswork Out of Marketing.
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► Recency: When was the last customer
interaction?
► Frequency: How frequent has this customer
been in his or her interactions with the business?
► Monetary: What is the sum total of his her or her
purchases over the past cycle? (usually 1 year)
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► Score your customers.
► Rank or “decile” them.
► Overlay demographics.
► Overlay attitudes & lifestyles
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Record #
Scoring
Recency
Frequency
Monetary
RFM
A35976
1
3
3
7
C45022
5
3
1
9
R48232
3
1
5
9
A98301
3
5
5
13
B48937
0
1
3
4
J94837
1
5
3
9
Purchase in past 90 days…….5
Purchase in past 6 months…..3
Purchase in past 12 months…1
Purchased over 1 year ago…..0
Purchase 4 or more x annual……..5
Purchase 2 or more x annual……..3
Purchase annually………………….1
Purchased less than annually …..0
Spend over $2000 annually…..5
Spend over $1000 annually ….3
Spend over $500 annually……1
Less than…………………….…..0
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Deciling
A decile is any of the nine values that divide the
sorted data into ten equal parts, so that each
part represents 1/10 of the sample or population. Thus:
► The first decile consists of the top tier of customers.*
► The 5th decile is the top half, the 3rd decile is top quartile.
► The 8th decile represents the least responsive, least valuable,
and least profitable customers.
Market Deciles can be ranked highest to lowest or vice versa
* Some statisticians do it the opposite way, with the 1st decile lowest
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Overlays
By overlaying geographic, demographic and
psychographic (attitude & lifestyle) data, you
can build a PROFILE VIEW of your various
deciles and take your testing to an even higher
level.
A basic model built by a database consultant will cost
from between $2500 - $7500 for basic profile/models.
For huge databases, etc., the cost goes up from there.
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Customer Profiling is a relatively
static process that builds a
“profile view” of your deciles.
Customer Modeling is an active
process that builds a model of
the prime target for a particular
product, offer, or initiative.
Both methods have their place for the ongoing
testing and databased mailer.
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Once you begin keeping and tracking data, you can go deeper
and deeper in your applications. Here is an example of a
RETURNS ANALYSIS – THOSE WHO RETURN SALES TO A RETAILER.
This is a national retailer whose average
transaction is under $90.
They had over 400,000 customers shopping
in Spring, 2009, of which 354,000 had only sales,
i.e., no returns.
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Source: Claude Johnson Associates
Perhaps an emphasis on
making customers happy
and comfortable about
► They retained 34.5% of customers from Spring to Fall ’09.
merchandise,
as stayed
well at
► The best ofreturning
the best spent
over $1000 and
as making it easier to do so….
a rate of 81.5%.
► 47% of purchase-returners came back, 12% higher than
the mean percentage
retained
customers.
MIGHTofBE
A GOOD
IDEA?
► And the average spend for the returners is $200 compared
to $127 for those who did not return items!
► If the non-returners had come back and spent like those
returners, the company would have realized another
$7.7 million in revenue!!!
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Thought for the day:
Every business is a big bathtub
that has cracks and leaks.
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Your acquisition programs are the faucets that
fill the tub with water (new customers).
Some water
leaks out because
customers move to
new phases in
their lives.
Some just
don’t need
your services
very often.
Some feel like they
were mistreated.
Some like
other tubs
better.
Some water
leaks out because
customers can’t afford
to stay in the tub anymore.
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Basics of Building a Predictive Modeling System
Segmentation is a way of grouping people or organizations
with similar demographic profiles, attitudes, purchasing patterns,
buying behaviors or other attributes to help understand customers
more thoroughly and thus market to them more effectively.
The problem is many businesses use segmentation to only
recognize that every customer has some unique characteristics,
providing a somewhat superficial view for each….then all
you have is “one-to-some,” which is not much better than
“one-to-all.”
Source: David Vergera, Director of Product Marketing, SPSS Analytics, Chicago IL
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► Create customer segments to enable differential
marketing programs.
► Use past purchase data and demographics to
construct customer subgroups.
► Isolate key performance factors linked to long-term
customer value as major data drivers for the
segmentation.
► Link product line or category affinity to each subgroup.
►Example:
Develop marketing
plans
incorporating
value-based
You may
have
to offer less
expensive
budgeting
and category
affinity
to make programs
value-added
specials
to certain
sub-groups
to keep them
more relevant and efficient.
from deserting you altogether.
Source: David Vergera, Director of Product Marketing, SPSS Analytics, Chicago IL
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Summary and Take-Aways
► Aim Properly: Your goal is knowledge and you
search for specific bits of knowledge with each test.
► Start with a basic direct mail piece, and test it
against lists.
► Then test offers. Lists and offers are 80% of the
power of mail.
► Score by RFM, then build segmentation clusters.
► Make marketing decisions that are relevant to each
group.
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The LI PCC would like to thank
today’s session sponsor
Thank you
Bi-County Mailing
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