Category Archives: Customer Experience

Customer Perks Marketing

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

Jim answers questions from fellow Drillers

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.

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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.

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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.

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