Category Archives: Marketing thru Operations

Customer Segmentation: Tangible vs Intangible Cost, Let Data Define Segments

Analytics Education, DataBase Marketing, Driller Q & A, Marketing thru Operations, Measuring Engagement

Jim answers questions from fellow Drillers

Topic Overview

Hi again folks, Jim Novo here.

This month in the newsletter we answer questions on the nitty gritty of the actual discovery work by taking a very deep look into the whys and hows of segmenting customers. Straight-up and to the point, put on those data shoes and Let’s do some Drillin’!

Q:  Hi Jim, I’m a great fan of your work!

A:  Well, thanks for your kind words.

Q:  I have a basic question for you.  We are an online retailer and thus use email as the primary marketing communication channel (we do use Direct Mail to our best customers around holidays).

A:  Those are smart choices.  I’ve seen some stats on using direct mail to drive lapsed online customers either back online or into a store that are very encouraging, real money-makers for retail.  Definitely worth testing, though in both cases, the product mix averaged higher ticket than your category typically does.

Q:  However, we don’t have a set customer segmentation technique and thus no specific customer segments.  One outside consultant, a statistician, had suggested looking at a new customer’s activity in the first 30 days and then classifying them into High Spender, Frequent Transactor, etc. segments.  Not sure how well it works.

A:  That’s quite unusual, I think.  It would work in the first 30 days, but I think you would have to re-classify every 30 days using a scheme like that.  Considering web-only behavior, the typical retail lifecycle beyond 2nd purchase (many buy only one time) is a ramping to a peak and then a more gradual, but still steep, falloff in purchases.  The model above would not take this into account, and while the initial label might be accurate, it soon would not be.  That’s not to say these kinds of models don’t work, but it usually takes years of testing and study to perfect them.  “Data miners” often believe the numbers will simply tell them things like this, but they don’t take into account the human behavioral and other mitigating factors which may not be in the data.  

For example, Recency and Latency are really “meta-data” about customer behavior; they are data created from other data.  You can’t just look at the first 30 days of transactions and give a customer a label; customers have LifeCycles and you drive the highest ROI when you take advantage of knowing these cycles and acting on them to increase profits.

Q:  I feel that we target our customers primarily by their category purchases, and not by any kind of behavioral model.

Continue reading Customer Segmentation: Tangible vs Intangible Cost, Let Data Define Segments →

New RFM: Managing Customer Value Like an Investment Portfolio

Analytical Culture, Customer Experience, DataBase Marketing, Digital Analytics, Driller Q & A, Marketing / Tech Interface, Marketing Research, Marketing thru Operations, Measuring Engagement

Jim answers questions from fellow Drillers

Topic Overview

Hi again folks, Jim Novo here.

Do you manage your own investments in the stock market? If you do, you probably have used technical indicators like moving average of prices or up / down volume balances or similar to make investment decisions. And if so, guess what? This approach to investment portfolio management is very similar to the management of customer value, it’s really all about the metrics and the source of changes to those metrics. We can so some Drilling’ if you like …

Q:  I have been enjoying reading your tutorials.  I am interested in the financial planning market particularly and have developed an application for segmentation of market and clients by attitudinal factors.  Having provided my clients (advisers) with the tools to turn the qualitative data into quantitative measures and slice and dice their client base appropriately, the next question from them is “How do I use this and what to do with the information?.”

A:  You betcha, that’s the hard part.  A common question when people get into analysis; the “what do I do with this” should come first so the metrics produce an actionable outcome…

Q:  I would be interested in providing links on my web space to access your papers and content. Do you have any content or case study examples for marketing and client servicing for the financial planning industry?

A:  Well, I don’t think I have a page on my site specifically on this area, but let’s create one, OK?  I’ll include this example on my blog and it will go up on my site.

Characteristics and attitudes are interesting but frequently not particularly actionable because they are not “behaviors.”  When people speak of “doing something,” they are typically thinking of increasing or decreasing a behavior of the customer.  If you are trying to figure out what to do about a behavior, you really need to use behavioral metrics, which will tell you “who” to do something to and “when” you should do it for best results.

Continue reading New RFM: Managing Customer Value Like an Investment Portfolio →

New RFM: Customer Retention in “Subscription” Businesses

Analytical Culture, Analytics Education, Customer Experience, DataBase Marketing, Driller Q & A, Marketing thru Operations, Measuring Engagement, ,

Jim answers questions from fellow Drillers

Topic Overview

Hi again folks, Jim Novo here.

How do you measure likelihood of customer defection when purchase behavior is highly orchestrated or executed due to repetitive billings? Yea, it’s a bit more complicated because “orders” really can’t express any kind of behavioral change, can they? So, you have to find indicators other than sales to provide the triggers. The Drillin’ the Drillin’ …

Q:  Jim, first let me say that I am enjoying your book VERY MUCH!!  Nicely done, and a nice job of integrating it with the CRM paradigm, 1-to-1 etc… I’m reading very slowly and finished the Latency Metric Toolkit.

A:  Great!  Thanks for the kind words.

Q:  I had a couple of questions on the Latency toolkit and the Latency tripwire, especially as it applies to environments with built in cycles for repeat purchases.

I am in a business where our resources are quarterly based, i.e. customers purchase our resource use them for a quarter and re-purchase the next quarter’s resource.  That is, we have a built in pattern, where customers would purchase our resources each quarter.  I was wondering how well I can use Latency with this type of built in cycle or if I would have any problems applying your Latency concepts to it, maybe they apply that much more readily?   In our case we try to call most folks who haven’t purchased within 2 weeks of a new quarter beginning.

A:  Right, a subscription-type business.  This is also an issue with utilities and other like businesses who bill about the same amount each month or have contracts for service (like wireless).  The answer is if the revenue generation really doesn’t represent anything to do with the behavior, then you simply look for other parameters to profile.  For example, a friend of mine was responsible for analyzing the likelihood of subscription renewal in a business that provided the content online.   Increasing Latency of visit was a warning flag for pending defection, and they triggered their most profitable campaigns based on last visit Recency.  In wireless, the correlations are found in payment Latency and age of phone.

Continue reading New RFM: Customer Retention in “Subscription” Businesses →