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Recency: Web Retailing Example 
Drilling Down Newsletter # 30: February 2003


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

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

In This Issue:

# Topics Overview

# Best of the Best Customer Marketing Links

# Tracking the Customer LifeCycle: Recency

# Questions: ROI of CRM?

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

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

Hi again folks, Jim Novo here.  

We've got a good crop of must read customer marketing articles, IMIssAsia.com at the brink of a major discovery about customer behavior, and a fellow Driller who wants to predict - gasp - the ROI of CRM.  But do I sweat?  Do I shake in front of the question so many failed to answer?  Nah, I just tell 'em how to do it.

Let's do some Drillin'!

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

This section flags "must read" articles moving into the paid archives of trade magazines before the next newsletter is delivered.  If you don't read these articles by the date listed, you will have to pay the magazine to read them from the online archives.

Note to web site visitors: These links may have expired by the time you read this.  You can get these "must read" links e-mailed to you every 2 weeks before they expire by subscribing to the newsletter.

**Relearn the Rules of Direct Marketing
January 24, 2003 DM News
It really is amazing how some basic truths about direct marketing got so twisted up in the dot-com years and used to justify everything imaginable.  LifeTime Value comes to mind as one of the most tragic victims; everyone just skipped right over the Customer LifeCycle and ended up with a pot of fool's gold.  Likewise Relationship Marketing morphing into CRM.  Go back to the classics and relearn what you were taught during this period; you'll be much, much better off.

*** What to Do Once Your Loyalty Program Is Up and Running
January 28, 2003  DM News
If you are familiar with loyalty programs this list will come as no big shock, but loyalty programs are gaining steam right now, and this list may help with your planning if you are new to the loyalty game.  You can see the advice about control groups in action by downloading this loyalty case study.

**Advantages of Life-Stage Segmenting
February 7, 2003  DM News
Oh, so customer have life stages?  I wonder if that has anything to do with the Lifecycle?  Of course it does; Life Stage / Cycle marketing is at the core of Relationship Marketing, which is not about being buddies with customers, but understanding how needs change over time.


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 last month, the owner of IMissAsia.com completed the "Last Purchase Date" 30-60-90 bucket calculations and found the following percentages of customers in each bucket:

What Percentage of Customers Last
Purchased How Many Days Ago?

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


This was clearly not good news.  Almost one third of people who have ever purchased from the IMissAsia.com web site last purchased quite a long time ago - over half a year.  How could that be?  Sales have been flat to growing slightly each month.  If  such a huge percentage of customers had not purchased in six months, where were all the sales coming from?  Why are sales not falling?

Pondering this question, the owner went about the usual business tasks for the day.  Scanning the new newsletter subscriptions, the owner notes the different sources producing the majority of new subscribers, then moves on to process orders for the day.  Folks, recall that response to the newsletter has been falling, and the owner was pleased to see the latest newsletter generated decent order activity.

As usual, some orders stood out from the rest; the owner recognized repeat buyers and people who had just placed an order Recently.  "What makes them do that, I wonder?" thinks the owner.  They buy something then they buy something else only a week later.  Why don't they buy both at the same time?  They could save money on shipping, the owner thinks...

As the owner processed orders, thoughts returned to the 30-60-90 bucket analysis.  I have all these orders, day after day, the owner thinks, yet most customers have not bought from me in quite some time.  How is this possible?  It doesn't make any sense.

Then the owner has a brainstorm.  What would the 30-60-90 Last Purchase Date information look like just on people who responded and purchased from the recent newsletter?  I could match people who bought from the newsletter with their Last Purchase Date before I sent the newsletter, and then could find out how effective the newsletter is at getting  my "lost customers" - those who have not purchased in months - to buy again.

In other words, what percentage of people in each 30 day bucket purchased through the last newsletter I sent out?  Perhaps this would provide the insight needed to demonstrate what this Recency data means, and provide some insight into the kind of action that needs to be taken to keep people buying for a longer time.  The owner sorted responders to the newsletter according to the Last Purchase Date before the newsletter was mailed out, with the following results:

Last Purchase Date Before Newsletter Drop

30-Day Buckets
(Days Ago)

All Customers All Newsletter Responders
0-30    3% 31%
31-60    6% 18%
61-90 10% 18%
91-120 14% 14%
121-150 16% 10%
151-180 20%   6%
181+ 31%   3%
Total        100%           100%

The owner was slack-jawed.  How could this be?  Is it possible that (top row) almost 1/3 of the responses came from 3% of customers?  That (top two rows together) nearly 50% of the responses came from 9% of customers?  The owner's head was swimming!  What was the implication here?  Is it possible - and just this simple - that the response rate of a customer to the newsletter could be predicted based on how many days ago they last made a purchase?  The implications were stunning.  One simple calculation.  Incredible ability to predict purchase behavior.

Of course, my fellow Drillers, the question really is what can the owner of IMIssAsia do with this new information to make the business more profitable?   We'll get to that issue next month, when the owner discovers an even more stunning connection between the newsletter and the purchase behavior of subscribers - and figures out how to increase profits by taking advantage of 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: Hi Jim,

Our industry is facility management services where a headquarters with chain locations contracts with us to manage their facilities in all their markets.  The President is interested in a "CRM Solution" but is concerned about the ROI he might expect from implementation.  Do you know of any number that I can pass along to him that would placate his insistence on knowing in advance what the ROI will be?

A:  Bad news: No, not really.

Good news: You can figure it out, which is something nobody did in the past and is why so many "failed" at CRM.  You might not even need any new software to "do CRM", though it depends on what you have now and what the objective of the CRM program is (you do have one, correct?).  But the software required is certainly not millions of dollars and if you only have 1000's of clients you can probably do it with some combination of ACT! or GoldMine, MS Access, and MS Excel. 

The key question to ask: do you really know how your customers behave?  In this kind of contract business, I imagine the central issue is this: Can you predict which customers are likely to re-up a contract, and which ones are not?  And then can you use this information to focus on the ones less likely to re-up, and take steps to make them more likely to re-up?

Sometimes it is just a matter of better customer service.  In this case, what you need is better service practices, not "CRM".  From a distance, it is very difficult to know what the issues might be in your company.

Here's a test you can do to find out where you might be on the road to answering the CRM question.  If you cannot accomplish one or more parts of the following, you are not ready to even talk about "CRM", and need to do some more internal research.  These steps, by the way, are the ones everybody skipped on the first round of CRM and will pave the way for a successful implementation if you decide to go with a CRM approach:

1.  Define a "best customer".  It's not just sales, you have to take into account margins, service costs, etc.  Don't worry about finding exact financial numbers.  Think about best in relative terms - these customers are better than those customers, and you are pretty sure it is true.  If you can't get to this point, you probably need better data collection before you think about a CRM project.

2.  Once defined, how many of these customers left you in the past year or 2 years or whatever the right time frame is for your business?  If you typically sign 3 year contracts, then it might be "in the past 4 years".  Also identify best customers who stayed with you and renewed.  If you can't get to this point, you probably need better data organization before you think about a CRM project.

3.  Group best customers who left and best customers who stayed and compare the two groups.  Look for similarities and differences.  Is it the kind of business they are in, geography, number of "trouble calls", billing disputes?  You will almost always see patterns that will lead you to conclusions on what circumstances create a best customer who stays and one who leaves.  If you can't get to this point, you probably need better data analysis before you think about CRM.

4.  Now that you know what causes customer defection and retention, figure how much more money you could make if you could keep a certain percentage of these best customers that would otherwise leave.  If you can't do this, you probably need better customer reporting before you think about a CRM project.

5.  Figure out what it would cost to keep this certain percentage of best customers that would otherwise leave.  Is it better targeting in sales upfront, better customer service, better billing practices?  If you can't do this, you probably need better financial reporting before you think about CRM.

6.  Calculate your ROI and either decide to do it or not.  If you can't do this, don't invest in CRM, because it is going to cost you more than you will make by implementing it!

Sorry I don't have "a number" for you, it simply does not work like that.  But you can find that number, a number that is right for your business, with a little detective work.  If you get hung up with any of the above steps, perhaps I can help.  Many businesses can get great results following the above plan.  If you are a larger organization with a lot of complex issues, you might need the industrial strength version of the above, described here.

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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