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
(More questions with answers here, Work Overview here, Index of concepts here)

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 →

Customer Perks Marketing

Analytical Culture, Customer Experience, DataBase Marketing, Digital Analytics, Driller Q & A

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

Topic Overview

Hi again folks, Jim Novo here.

What’s the best way to handle customized marketing programs, particularly if you are using customer value as the key segmentation approach? Surprise and delight, perhaps slightly influenced by making more money. Sound good? Let’s Drill it … 

Q:  Jim, do you have an opinion on overt versus covert customer benefits?  What I meant by overt vs. covert… have you seen clients do programs where they TOLD their customers they are a valued (Gold, Platinum) customer and provided tangible benefits, vs. others who have just covertly treated these customers specially in some way (i.e. priority routing, better reps, thank you calls, etc.)

A:  Well, a program won’t be very effective if everything is completely covert.  I mean, it’s nice to get great service and that certainly contributes to customer retention, but recognition is much more powerful.  The customer needs to know they are being treated specially at some level to maximize program effectiveness. Why?

Something like call routing is a good example.  If a customer is getting priority call routing and they don’t know it, they may think the service is good.  If you tell them they are going to get it and then they get it, it’s an entitlement they earned.  More powerful, and more effective in keeping the customer.  Let’s say they are thinking of defecting.  If they don’t know they are getting priority routing, they could suspect the service might be as good at the competition.  If they know they are getting priority routing, the question becomes “Does the other guy do this to?  And if so, will he give it to me?”  See what I mean?  It’s much more powerful for the customer to know they are getting special treatment than not to know.

Continue reading Customer Perks Marketing →

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
(More questions with answers here, Work Overview here, Index of concepts here)

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 →