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Recency: Web Retailing Example 
Drilling Down Newsletter # 29: January 2003


Drilling Down - Turning Customer
Data into Profits with a Spreadsheet
*************************
Customer Valuation, Retention, 
Loyalty, Defection

Get the Drilling Down Book!
http://www.booklocker.com/jimnovo
Now also available online through
Amazon and Barnes & Noble

Check out:

The Marketer's Common Sense Guide to E-Metrics - 22 benchmarks to understand the major trends, key opportunities, and hidden hazards your web logs uncover.  I wrote this manual with Bryan Eisenberg of Future Now, the visitor conversion specialists.  Download a free white paper on the topic:
Marketer's Common Sense Guide to E-Metrics

Prior Newsletters:
http://www.drilling-down.com/newsletters.htm
-------------------------------

In This Issue:

# Topics Overview

# New Case Study

# Free E-Mail Class, Simple Customer Models

# Best of the Best Customer Marketing Links

# Tracking the Customer LifeCycle: Recency

# Questions: Affinity or Loyalty?

-------------------------------

Topics Overview
=============

Hi again folks, Jim Novo here. 

We've got a couple of new items - a case study and a free e-mail class on using simple customer models.  For regular features, we have the annual explanation of how the free "Expiring Articles" service works, the first segmentation of the IMissAsia customer base by Recency, and a fellow Driller who wants to know the difference between a loyalty program and
an affinity program.

So, let's do some Drillin'!

New Case Study

I am constantly asked for new case studies. They are difficult to get published because the issues I work on for companies are often highly confidential, competitive issues.

Jason Weaver was one of the first people to buy my book, and over the years we have become "friends" even though we have never met - funny how the web works, isn't it?  Jason steers the list management of a non-profit childcare organization that relies on direct response for fund raising.  

Using one of the customer scoring techniques in the book, Jason predicted which 10% of all donors would be most likely to contribute.   And then a mailing to this group generated total donations 192% higher than the same mailing to a control group.  Sweet!

You can check out the case study here.  And if you are of a mind and the means to, please consider donating to Jason's organization.


Free Tutorial by E-mail: Simple Customer Models

As you might know, I released a new version of the Drilling Down book late last year, adding 9 Chapters covering even simpler High ROI Customer Models than in the original book.  These 9 Chapters were taken from the over 320,000 words now up on this web site, and really read like a "how to" class on using simple customer models to create High ROI Customer Marketing.  For this tutorial, the 9 Chapters are delivered in 10 e-mails over a 30-day period, one e-mail every 3 days.  Free.

If you would like to read the "best of the best" on this web site, edited into a logical, serial, "book-like" format, send any e-mail (blank OK) to the address below after removing the red capital letters NOSPAM from the address:

drillingdown@list.inboxfictionNOSPAM.com


Best Customer Retention Articles
====================

As happens every year, publishers go to sleep during December and don't publish much of the "good stuff" because they know people are not paying attention.  There are no "Expiring Articles" to point out to you in this newsletter.  So let me just take a minute here in the first newsletter of the year to describe what this section is usually about.  There are offline database and direct marketing trade mags like DM News, Catalog Success, Target Marketing, etc. that publish a ton of case studies with lots of metrics and "how to" articles.

When they put these articles on the web, they set them up so they "expire" and move into a paid archive after 30 days.  This section of the newsletter, and the very short "Article Links Update" that goes out between the monthly newsletters, serves as a reminder that certain "must read" articles are about to expire and move into the paid archives.  This gives you one last chance to read them and copy out any stuff you need at no cost.

All is not lost for this issue, however.  A slew of great stuff on other sites has come out the past couple of weeks.  You will find these links on my "Fresh Articles" page with quality rankings and a brief (frequently sarcastic, sometimes joyous) overview of each.  I sift out the best stuff (case studies, metrics) from all over the web and post links to it on this page two or three times a week.  So on this round, just check out the Fresh Articles page.

I don't think you will be disappointed.  We'll start up the "Expiring Articles" thing on the next cycle - if the trades come up with anything worth reading.


Tracking the Customer LifeCycle: Real World Examples
=====================
If you are new to our group and want to review the previous LifeCycle metric - Latency - that discussion is here, along with the Real World examples
Hair Salon and B2B Software.  The previous piece on Recency is here; this series on Recency starts here.

Recency: The Web Retailing Example

Recall from last month the owner of IMissAsia.com was pondering a falling response rate to the newsletter. But who is not responding to the newsletter? Or who is responding?  Is it new customers?  Is it repeat customers?  Is it "best customers"?  The owner realized there was no definition of the different kinds of customers, so the question of "who", from a "types of customer" perspective, could not be answered.

If different types of customers were defined, the owner might be able to understand what is happening.  What the owner needs to do is not only define the customers, but also to define them relative to the newsletter.  What percent of new customers respond?  What percent of "old customers" respond?  What percent of "best customers" respond?

When thinking about defining new customers, customers, best customers and so on, one concept keeps coming up, and that is "how long".  How long has it been since the customer last made a purchase?  Surely this concept must have a direct bearing on defining customers; at some point a customer who has not purchased in a long time is no longer really a customer, the owner thinks.

Also, at some point a customer who made a first purchase is no longer a "new customer" - they're just a customer.  A "best customer" would also need some kind of definition involving last purchase date.  

For example, customer #1 who purchased $500 in the past month must be more valuable than customer #2 who purchased $500 2 years ago and has not purchased since.  It seems to the owner customer #1 is much more likely to buy again than customer #2; if this is true, customer #1 has a higher value to the business, because customer #1 has a higher likelihood to buy even more.  This "future value" makes customer #1 more valuable than #2.

The owner's brain was starting to hurt thinking about all these possibilities, and it seemed like time to quit thinking and "do something" about it.  Since last purchase date seemed like the most critical element, the owner decided to classify the IMissAsia.com customers by last purchase date, and then take it from there. Perhaps the data would spark some ideas on how to think about and define customers.

The owner decided the easiest way to do this would be to put customers in monthly "buckets" of 30 days each - last purchase date 0 - 30 days ago, last purchase 31 - 60 days ago, last purchase 61 - 90 days ago, and so forth.  By creating a standard classification like this, the owner could compare the number and percentage of customers in each bucket month to month, and see what was happening to the customer base.  The owner was not quite sure what to do with this information, but knew one thing - if the percentage of customers purchasing Recently was low and the percentage not purchasing in a while was high, that could not be a good thing.

The owner completed the calculations and found the following percentages of customers in each "Last Purchase Date" bucket:

What Percentage of Customers Last
Purchased How Many Days Ago?

Days Percentage
0-30 3%
31-60 6%
61-90 10%
91-120 14%
121-150 16%
151-180 20%
181+ 31%
100%

The owner of IMissAsia.com was devastated. 

Things looked bad, the owner thought, but what did this information really mean, and what could be done with it?  It appeared as if the customer base was "sliding downhill" or aging; the largest group are customers who have not purchased for a very long time, almost like people would buy, then give up, and fall down to the bottom of the "purchased recently" barrel.  

The owner used to think of all customers as pretty much equal, they were just "customers", and all equally likely to buy at any time.  But to see this, the customer base kind of looks like a pyramid in time, with very few people at the top and a huge number at the bottom.  What did it mean?

Fellow Drillers, I encourage YOU to do a "30-60-90", as I call it, on your own customer base.  You will find it looks very similar in form to the one from IMiss Asia.com.  Pick any activity - purchases, visits, board postings, game plays - and rank all your customers, not just a group you choose, by how long it has been since they engaged in that activity.

 You will find your very own activity "pyramid" in your customer database.  Compared with IMissAsia.com, it may be "flatter" or it may be "taller", but you will generally see a much smaller percentage of customers in the most Recent group than you will see in the least Recent group, very often by a factor of 10. 

Of course, the real question is, what can you do with this information, how can you change this state of affairs, and how much money can you make doing it?  We'll get to that issue next month, when the owner of IMissAsia.com uncovers the dirty little secret of Recency for you.  

Will you be ready for it?

If you would like to read the next installment of 
Recency: The Web Retailing Example, click here.

-----------------------------------------
If you are a consultant, agency, or software developer with clients needing action-oriented customer modeling or High ROI Customer Marketing program designs, click here.  If you are in SEO and the client isn't converting the additional visitors you generate, click here.
-----------------------------------------


Questions from Fellow Drillers
=====================
Jim's note: If you still don't know what RFM is and how it can be used to drive increased profitability in almost any business, read this.

Q:  Jim - interesting site.

A:  Thanks for the kind words!

Q:  How would you define the difference between an affinity program and a loyalty program.

A:  Well, I'm not sure they are all that different from a customer perspective, but one could think of the difference in this way:

In a loyalty program, you are going directly to the customer and want them to be directly loyal to you.  In an affinity program, you are typically going to an *organization* the customer is already loyal to and hoping some of that loyalty rubs off on you.  This often involves cutting a special deal for the organization's members, and giving the organization a piece of the profits.

Affinity deals tend to work if there is a strong relationship between your products and the mission or make-up of the organization.  If I can imply the underlying business we are talking about from your e-mail address, that would mean knowing that tech types make great cell customers and going to a software association and making a deal.  Here is an example of that kind of thing, scroll down the page to see the "Preferred Vendors":

http://www.csa.org/memship.html

If you think pet owners make great cell phone customers, you go to the ASPCA and do a deal.  When a non-profit is involved, affinity is usually called cause-related marketing.

I'll say again, for affinity to work, you have to know of a logical bond between your best customers and the group.  For a product like wireless, something that universal, affinity may be more expensive to execute than loyalty and not provide the same bottom line benefits.

Finally, for an interesting blend of affinity and loyalty, check out the case study on my site, which in fact in on wireless; click here.

It's a classic loyalty program, with an affinity twist: many of the rewards were locally based.   In this case, the affinity was to the Philadelphia / NJ area, and we used local rewards to fulfill and reinforce this affinity.

Hope that helps!

Jim

-----------------------------------------
I can teach you and your staff the basics of high ROI customer marketing using your business model and customer data, and without using a lot of fancy software.  Not ready for the expense and resource drain of CRM?  Get CRM benefits using existing resources by scheduling a workshop
-----------------------------------------

That's it for this month's edition of the Drilling Down Newsletter. If you like the newsletter, please forward it to a friend - why don't you do this now while you are thinking of it? Subscription instructions are at the top and bottom of the newsletter for their convenience when subscribing.

Any comments on the newsletter (it's too long, too short, topic suggestions, etc.) please send them right along to me, along with any other questions on customer Valuation, Retention, Loyalty, and Defection right here.

'Til next time, keep Drilling Down!

- Jim Novo

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