Monthly Archives: May 2007

6033% ROI, Defining Churn

Jim answers questions from fellow Drillers
(More questions with answers here, Work Overview here, Index of concepts here)

6033% ROI

Q: We have exchanged email a few times, and I don’t recall if I ever said thank you for your book.¬† While I had been experimenting with many CRM programs in my little dry cleaning shop, your book gave my thoughts order and clarity to refine what I had started.¬† Today, I see the world differently.

A:† Well, thanks for the thanks!

Q: You may or may not remember me.† Just after I sold my dry cleaning shop, I had bought your Drilling Down book.† I was the dry cleaner who had been doing rudimentary data mining and CRM with a point of sale system I had developed in Regina, Saskatchewan.

A: I do remember.† Internally, I was thinking, “Wow, this is going to be a real test of the Drilling Down concept”.† I mean, I have seen it work in many small businesses, but dry clean (seems to me) is a very tough, tough business.† Too many players, a lot of competing on price, etc.† A great environment for underground customer marketing in terms of beating the other guy – they will never know what happened to them.† But still, tough for small owner / operator to have the “will” and time to really make it happen.† So yea, I remember…

Q: Well, I’ve continued working within the dry cleaning as a marketing consultant. The programs I had developed in my shop have now been transplanted into a few of my client’s shops, and are bearing fruit.

Tonight one of my clients reported a ROI of 6033% doing direct mail to certain customers in his market in California.† Another client of mine reported his fourth year of steady growth.† One of my first clients has been showing a 7 percent annual compound growth, and he is in a flat or declining market.† What began in my shop has been proven across North America, into Europe and Australia by my clients.

A: I can’t express how exciting that is.† Congratulations!

Q: Jim, data mining dry cleaner’s data is a blast.† You would be stunned at the quantity, and quality of data a dry cleaner gathers today.† Would you ever have thought data mining could be applied to suits and shirts?† Well yes, it can.

A:† I am stunned, and I bow to your most excellent Drilling!

Q:† Once again, thank you.

A: And thank you for sharing this, it’s very, very exciting to hear.† Like you said, no other word for it than “stunning”.† I remain most stunned!¬† Keep me informed.† Perhaps you should write a book?


Defining Churn

Q: I work for an economics consulting firm based in Washington DC.† I am researching customer churn and customer displacement statistics across a variety of industries to try to establish a benchmark of what is considered high and low customer displacement.

A:† Nice to meet you, and a noble task!

Q: Do you happen to have any such churn statistics, or know if a place you could recommend?  I found plenty of statistics regarding churn rates within the telecom industry, but am most interested in companies that are involved in business-to-business relationships with their customers (relationship between a customer and a supplier).

In addition, I would also like to find churn statistics for customers who use multiple suppliers.† For example, a customer may go to several grocery stores rather than sticking with one dedicated store.¬† I would be interested in learning more about the statistics companies in these types of industries use to track customer displacement.

A: The reason you find a lot of churn info in telco / cable is the end of the customer life is easily defined by the disconnect, and these numbers are reported publicly as part of annual reports and so forth.† In many other businesses like the ones you describe, typically the companies have failed to define customer defection and so in their minds, there is no churn because there is no defection.

A “customer”, even though they have not contacted the company for 3, 5 or 10 years, is always still a customer.† If the†company thinks like this there is no churn rate to be measured, by the definition the company has chosen for itself.

At the same time, defining defection is pretty easy to do by looking at the transactional data and defining the patterns of defection, for example “if a customer has not ordered from us in 3 years they are highly unlikely to order again”.† That’s defection defined; you just put a line in the sand and say “3 years no contact is a defection”.† The company then should declare customers in this status “defected” and then a churn rate could be found.† This is pretty easy to do, so if not executed, one of two situations exist: either the company does not have the data or they don’t have the “will” to discuss, internally or externally, the concept of customer defection.

A third possibility exists: the company in fact has the data and has defined defection, but would never, ever speak to churn or customer defection in any kind of public forum because this information is so critically important from a competitive and strategy perspective.† To discuss these numbers or the implications in public could have dramatic consequences for company positioning in the market or stock price.† So if they have the numbers, they’re locked in a safe.

As a result, I’m sorry to say, I do not have any broad-based “sources” for you, save one possibility: a book called The Loyalty Effect by Frederick F.† Reichheld (1996).† In this book, Reichheld goes through the business models of 25 different companies that excel at retaining customers in different industries , and proves out the financial model of customer retention using real data.† This is the book where the quote, “It costs 5x more to acquire a new customer than retain a current customer” (or the various bastardizations) came from.† So it might help you out.

The only other thing I can suggest is that “churn” is not always the word used to describe these stats but is most often used when the disconnect is easily defined, as in telco / cable; “displacement” is a rare use for this idea as far as I can tell..

“Customer Turnover” is a popular phrase in Europe and is used by some in the US; also “defection rate” is used quite a bit.† So if you’re pounding on Google to try to find these numbers, try those phrases and others you may find when doing these searches.† Banking / finance / insurance is another area where the “disconnect” is often easily defined, so you will find various defection rates in some of their case studies on the web.


Get the book at

Find Out Specifically What is in the Book

Learn Customer Marketing Concepts and Metrics (site article list)

Download the first 9 chapters of the Drilling Down book: PDF