Optimizing Mail Drops for Consumables
# 77: 3 / 2007
Drilling Down - Turning Customer
Data into Profits with a Spreadsheet
Customer Valuation, Retention, Loyalty, Defection
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Hi again folks, Jim Novo here.
How do you figure out the optimum (offline) mailing cycle for a
continuity product? Very carefully - especially if you are
looking at messing around with an existing program. We'll take a
look at a few ways to go about tackling this challenge.
We also have a couple of great customer marketing article links and
a blog post you might be interested in. I highly recommend you
read or get a copy of the "7 Deadly Sins" piece to review
later - this topic may not be relevant to you today, but it will be
someday, and then you'll want a copy, trust me!
Let's get on with the Drillin'...
Best Customer Marketing Articles
7 Deadly Sins of Performance
Management and How to Avoid Them
Must read discussion of the seven types of
"sins" companies commit that mess up their use of analytics
in a productive way. This is really the heart of the analytical
culture problem; if you are having difficulty advancing analytics in
your company you really should read this and perhaps send links
around...also, feel free to leave comments about this article on
Care to share any examples of The 7 Deadly Sins at your
This article from CRM Magazine both makes fun of the current “Customer Experience” bandwagon and provides a solid suggestion (I think) about how to properly use an online
community - know who you are talking to.
To access all article reviews, click
Sample Marketing Productivity Blog Post
the Blog" as a Post
March 14th, 2007
I had a request to publish my “About the Blog” page as a post so people could comment on it.
If you are interested in the challenges of "acceptance" and
"culture" surrounding the use of analytics in your company,
it's probably worth a read (and a comment too!)
on About the Blog as a Post...
You can subscribe to the Blog by e-mail if you want to, just go to
the Blog home page.
Questions from Fellow Drillers
Optimizing Mail Drops for Consumables
Please note: The business discussed below is a "continuity
business", where customers consume the product and need to either
reorder from the company every few months or seek alternatives sources
for the product. In this scenario, the behavior of customers is
generally governed by the Latency
Metric in terms of reorder patterns.
Q: Currently we mail our current customers direct mail every 6.5 weeks.
We have a new VP and he is asking if that is the optimal spacing of mailings.
I'm wondering if there are any best practices for setting up frequency tests?
If you can shed any light on how to set up such a test I would greatly appreciate it.
A: Well, do you know how you got to the 6.5 weeks number in
the first place? Somebody must have thought it was a good idea based on
some kind of data (I hope)!
Obviously, there is some significant financial risk in simply
"moving the drop around" and testing results that way.
You can do it, often by slivering off parts of the drop and dropping
then at different times, but there could be a substantial financial
penalty for approaching the problem this way - both on the cost and
sales sides. This is especially true when you have a current
schedule that seems to be working.
The first thing I would do, if possible, before taking on the risk of
messing with the mailing is to see if you can find any segmentation /
frequency that makes more sense from the customer data itself. Since you also have a web site, there probably is evidence of "natural purchase cycles" the customer engages in that operate outside the mail drop - customers ordering "when
and how they want to".
Can you find
evidence that the average purchase cycle is more like 5 weeks or 7 weeks?
How does this differ by product line, or packaging of the product?
Both segmentation by actual customer behavior and segmentation by
product line will generally provide increased profits, provided the
cost of dropping different mail streams does not overpower the
For example, if someone can buy a "90-day supply", well, 6.5 weeks is a bit
early for the mailing, I'd think. If they can only buy a 30-day supply,
well, it seems to me that 6.5 weeks could be a bit late. Look to actual
purchase cycles by product line / supply length and see if you can find any
patterns in the purchase behavior.
The key to this kind of analysis is to line up all the customers so that the
purchase cycles match. In other words, you need to enforce the same start
date. One way to do this, for example, is look at all new customers who
started in January 2007; of the ones that bought again, when did they
purchase - 5 weeks, 6 weeks, 7 weeks out? What percentage of new starts in
January (or any other month) purchased in each of the subsequent weeks?
Be aware choosing a single month may create results that have a seasonal bias,
but I'm not sure that is relevant in a product line like yours.
A more complex but possibly more accurate way to do this is to "normalize"
the start date of all new customers in 2006 and then look at the subsequent
purchase patterns - given the same start date, what percent bought again 5 weeks out, 6 weeks
out, 7 weeks out? You can achieve virtually the same thing by taking each month of
2006 and running it through the same drill as the one described above for
January 2007, though it won't be as accurate.
Once you have nailed the cycle for new customers, you can move on to see if
there is any change in optimal cycle date as customers age. My guess is the
cycle probably gradually lengthens until the customer defects. If this is
true, it might be worth it to do two mailings with different cycles - one
cycle for customers who became new customers in the past (say) 6 months and
all other customers. It's likely in this business there could be an
important behavioral difference between new and current customers that would
allow you to deliver a more optimized mailing cycle.
Failing access to any analytical means to drill down into the data first,
because either you lack the resources or simply don't have the time, set up
your next drop with flagged segments based on "weeks since last purchase"
and look at profit per customer. You could also back into this if you have
good promotional history on your customers.
In other words, if you are going to drop "everybody" at the same time, there
must be a segment where for this single drop, the time since last purchase
based on arrival of the mail is 5 weeks ago, 6 weeks ago, 7 weeks ago, and
so forth. If you flag these segments before the drop in the database, you
should be able to go back and determine sales per customer mailed for each
segment. This will tell you if your timing should be adjusted.
Further, you might divide these time-based segments, if there are enough members in the
segment, along various product lines.
Then, once you have a handle on the general cyclicality of
different segments, you can get to profit per segment by using control
groups to measure the lift and profit by segment.
A careful analysis of the next drop (or as I said, a previous drop if you
have good history) should tell you which drop cycle for each product line is
optimal. From there, you have to look at economies of scale and decide if
you can afford that kind of segmentation. You may find that due to the
economies of scale in the mailing, you simply cannot drop 50% of your
mail one week and the other 50% the next, for example. But you might find
enough support in your analysis to either justify the current 6.5 week drop
as the most efficient, or to move it up or back somewhat.
Another way to approach the "timing problem" relative to economies of scale
would be to try "reminder to re-order postcards" instead of
mail or catalogs to some members of the group that require special timing considerations.
For example, new customers might not really need a catalog on their first drop, a postcard driving them
to the phone or web site to reorder might be enough.
No silver bullets, I'm afraid. Just good 'ol fashioned sloggin' through the
data ought to get you to where you want to go!
If you are a consultant, agency, or software developer with clients
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Marketing program designs, click
That's it for this month's edition of the Drilling Down newsletter.
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'Til next time, keep Drilling Down!
- Jim Novo
Copyright 2007, The Drilling Down Project by Jim Novo. All
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