Drilling Down Newsletter # 19 -
Drilling Down - Turning Customer
Data into Profits with a Spreadsheet
Customer Valuation, Retention,
Get the Drilling Down Book!
Now also available online through
Amazon and Barnes & Noble
In This Issue:
# Topics Overview
# New Goodies for Download
# Best of the Best Customer Marketing Links
# Tracking the Customer LifeCycle: Salon #4
# Measuring Insurance Agent Loyalty
Hi again folks, Jim Novo here.
We've got an absolute bucketful of new free downloads for your customer value Measuring, Managing, and Maximizing pleasure.
Then some "best of" Customer Marketing links, the final chapter of the Hair Salon Example, and a fellow Driller
looking to compare the "loyalty" of sales agents and use
this information to manage them more effectively.
Let's do some Drillin'!
New Goodies for Download
At long last, one of the best examples of High ROI Customer Marketing I have ever worked on is available
as a case study. Folks are generally reluctant to allow my release of this information because of the severe
competitive implications. Fortunately, due to the spate of mergers in telco land, I have been given permission
to release this one on cellular loyalty, since the company it was done for has been merged into
In a tightly controlled, "under the radar" 2 year test, this program generated an average 252% ROI, with the average customer increasing their spend by 35%.
The churn rate decreased a jaw-dropping 15% during this 2 year time frame.
This case will become a classic in the loyalty area, and shows the power of well though out, targeted
The case study 8 page case study is in PDF format, and is free to download for newsletter subscribers,
customers, and for a short time on the site. Click
here to download.
The free Web Analytics calculator has been revised and updated, with new fields to handle more types of
customer data. This modification simplifies analysis and tightens up the definitions of the "action-oriented"
customer metrics you need to know to track and improve your web business.
The free Excel spreadsheet calculator is available for download here.
If you want the whole web metrics story, including a 13 week tracking version of the calculator and detailed
info on how the metrics are derived, click
A new version of the Drilling Down customer scoring application for MS Access / Excel is now available for customers who have purchased the Drilling Down book.
The application ranks customers for likelihood to respond to promotions and potential profitability to the company, enabling the creation of very High ROI Customer Marketing.
The application has been upgraded to accept virtually all characters in the Customer ID field.
We did not test every character, but all the characters on a standard keyboard are allowed.
This change makes it possible to use e-mail addresses or even URL's as customer ID's - a feature long sought after by users.
We're happy to provide this functionality for the Access 2000 user; Access 97 users are limited to numerical information only in the customer ID field.
To get the new version of the application, simply follow the directions in the Drilling Down book for downloading the software.
These directions are at the top of the Appendix at the end of the book.
In the 90 page version of the book, the download instructions are also in the 6th paragraph of Chapter 5, above the paragraph titled "Process Overview".
More details on the application are here.
Finally, though not new, they're worth mentioning. If you have ever tried to explain LifeTime Value measurement to an accounting type, or think you may have to, you should read Lifetime Value, I'd Like to Introduce You to the
CFO, available here.
Also, you can download the first 9 chapters of the Drilling Down book - the guide to Do It Yourself Customer Modeling -
Best Customer Retention Articles
This section flags "must read" articles moving into the paid DM News archives before the next newsletter is delivered. If you don't read these articles by the date listed, you will have to pay $25 to DM News to read them from the archives. The URL's are too long for the newsletter, so these links take you to a page with more info on what is in the article and a direct link to the article.
Note to web
site visitors: These links may have expired by the time you read
can get these "must read" links e-mailed to
every 2 weeks before they expire by subscribing to the newsletter.
Open Rates Deserve Far More Respect Than They Get
Expires April 13, 2002 DM News
OK, this is a shameless plug for a partner. But it's worth reading, too,
because it contains solids thinking on how you should track and measure open
rates. That idea about discarding absolute measurement in favor of
measuring relative change, that one sounds real
familiar somehow. If you like this kind of thinking, make sure you
check out the whole story in The
Guide to Web Analytics.
The Challenge in a Tech-Savvy World
Expires April 13, 2002 DM News
Some good stats on multi-channel retailing, accompanied by some horrendous stats
on what marketing people know about their businesses and customers. Wasn't
CRM supposed to solve all this? At HSN, we had the proverbial "360
degree view of the customer" across 12 to 15 different businesses - in 1992. We could measure cross-channel cannibalization, subsidy
costs, halo effects, the whole thing. What is taking so long for the rest
of the world to catch up?
** CRM and Its Arguments Are Failing
Expires April 22, 2002 DM News
One of the greats, Mr. Hughes sharpens his pencil for the final kill in this
first piece on the topic. After all, CRM is
simply database marketing with better software, isn't it?
Tracking the Customer LifeCycle:
Real World Examples
Note: If you are new to our group and want to know more about the following ongoing discussion, the background theory is
And the "Beauty Salon Example" (4 parts total) starts here.
A Tale of Two Hair Salons
Part 4: Maximize in Action
Recall the owner of Salon B conducted a very successful customer retention promotion which paid for itself many times over, but was puzzled by some of the results.
You know Customer Retention is about
Action - Reaction -
FeedBack - Repeat.
The owner of Salon B has taken an action, and there has been a Reaction.
How should the owner go about Analyzing the Feedback? There were two
puzzling situations - customers who said "Thanks for the coupon, I was coming in anyway" and the 75% of Salon B's targeted best customers who never responded to the mailing.
By recording who these customers were and comparing them with each other, the owner came to a Eureka conclusion.
Most of the customers who "would have come in anyway" all had long hair cuts, and the most of the customers who did not respond had short hair cuts.
Conclusion? Even though the average customer comes in every 40 days,
there are very few "real world" customers with this trip cycle.
The true cycle is longer or shorter depending on hair length, which causes the retention mailing to be either early or late for many customers.
If it's early, the owner gets "would have come in anyway". if it's too late, the owner gets weak response rates.
The owner resolves to divide the customer base in two - by length of cut, and finds the average time between trips of long cut customers is actually 75 days, and for short cut customers is actually 20 days.
Rethinking the retention campaign, the owner resolves to track each group individually, and
to do two types of mailings each week - one to long cut customers over 75 days since last visit, and one to short cut customers over 20 days since
the last visit.
Using the advanced CRM system (a spreadsheet program with one customer per row), the owner creates a
column for acceptable number of days since last visit - 75 days for long cut customers and 20 days for or short cut customers.
Using the date of last appointment, the owner creates a simple equation that uses today's date and last appointment date to calculate days since last visit, and to subtract this number from the number in the "acceptable" column. The salon owner thinks:
When the number in this column approaches zero or goes negative for a customer, it is time to mail the discount "where have you been" postcard.
Since each customer has an acceptable number of days since last visit based on hair cut length, the timing of the mailings should more closely reflect
whether or not the customer has actually defected.
The salon owner tests the new campaign - and it works. Not only does the owner get many fewer customers saying "thanks for the discount, would have been in anyway", the response rate among targeted best customers increases by 30%.
The program now is maximized for this level of detail - it makes even more money than it did before, and retains more customers while decreasing the cost of discounts given away.
A beautiful thing, the owner thinks. But then another Eureka moment
comes to the owner of Salon B:
If I use this system there is another benefit - I should be able to actually
forecast what my volume should be months in advance based on customers likely to schedule an appointment.
If I see a week coming up where visit volume looks to be low, I can promote to some customers and fill up empty slots, maybe give them a discount for scheduling on a specific day when my traffic is light.
That way the customer is happy because they get a special one-time discount, and I am happy because I am maximizing my revenue per day by reducing light traffic days!
Just then, the owner of Salon B hears someone walk in the door. A voice calls out, "Can we schedule appointments?"
The owner recognizes the voice - it belongs to lost best customer
Angela, the one who started this whole project by being tardy in scheduling an appointment.
Angela is the reason the owner of Salon B first asked the question, "How many tardy best customers do I have?"
But what does she mean "we"?
As the owner of Salon B comes around the corner, Angela smiles and says, "This is my friend
Mary Lou. She was going to Salon A, but is dissatisfied with the results she is getting.
She would like to try Salon B. And I need a cut too! I tried growing my hair out long, but
I decided I like it better short".
The owner of Salon B thinks: I can't predict everything, but my new
system is sure better than not predicting anything at all!
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
Questions from Fellow Drillers
Q: Hi Jim,
I happened upon your site and found the information there very valuable - so much so that I ordered your
book (customer is referring to Drilling
A: Well, thank you very much for that!
Q: I'm a marketing manager with an insurance company that distributes its life, auto, home, and business insurance products
through independent insurance agents. These agents represent our company as well as others.
I'm interested in techniques for measuring agent loyalty - which I think would be demonstrated by
the agents choosing to place business with our
company instead of another company they represent for policies.
A: I'm not sure in this case anything is too terribly different from the scenarios used in the book. Essentially, agents or consumers demonstrate loyalty though their actions, and if you can track their actions, you can spot increasing or decreasing loyalty.
Your business is more complex in many ways than retail, but to the consumer (in your case agent), there are always choices to be made between alternatives, and changes in the purchase patterns agents or consumers generate often precede customer defection.
In a very simple case, let's say the average agent writes a policy every
week with you. Some will write more, some less. But what you are
interested in for estimating loyalty (increasing or decreasing?) is not the
rate at which they write policies, but any change in rate. If you have an
agent writing 3 policies a week and they drop to 1 a week, this is a
significant change in behavior, and this behavior should be flagged and investigated as a prelude to agent defection.
If this agent is a "best agent", then the need to find out if there is a problem is even more urgent.
The more policies the agent writes, the more imperative it is to find out if something is wrong.
In the book, the Recency (how many days since last policy was written) and Frequency (how many policies have been written in total) of writing
policies is used to rank all agents against each other for "likelihood to
keep writing policies". Any changes in this likelihood show up as a change in rank - called RF Score, or Recency-Frequency Score - and will alert you to high value agents who may be defecting and dropping your lines.
There are several different versions of this approach; you can read about one of them in some detail
right here on the
Depending on the data you have access to, another approach is to use
Latency, in which simpler average behavior patterns rather than agent scoring are used.
The example here would be the average agent writes one policy a week, and those who slide below this rate are likely future defectors.
You can run these Latency numbers by line by area of the country for example, because the average Latency of writing a Life policy in New England may be different than for a home policy in the Southeast or auto policy in California.
For more information, see this
If I am way off base in understanding how your business works, please let me know (Jim's note: she didn't, so I guess I wasn't!)
I hope I answered your question!
If you are a consultant, agency, or software developer with clients needing action-oriented customer modeling or High ROI Customer Marketing program designs,
If you are in SEO and the client isn't converting the additional
visitors you generate, click here.
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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