Category Archives: Marketing / Tech Interface

Modeling Defections – When is a Customer No Longer a Customer?

DataBase Marketing, Driller Q & A, Marketing / Tech Interface, 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.

Metrics are not usually also Models; the metrics have to be fine-tuned / combined and built up into models. And executing this process usually depends alot on what type of business is being analyzed, and what kind of problem is targeted for a solution. So while it’s pretty simple to define a metric, creating a version of the metric that specifically addresses the challenge at hand can be a bit more difficult. Not hard, mind you; it mostly just takes a decent understanding of how the business works. Want some examples? Read on, O Fellow Driller …

Q:  Is Latency, as a metric, out of the question when the spread of the number of days in a latency period is so wide that to average them out and call the resultant figure “Acceptable days to date of predicted purchase” would seem meaningless?  I am thinking about the disparity in latency between customers who are Heavy, Moderate and Low users.

A:  I’m not sure I have enough context to understand the question (what are you trying to accomplish by using the metric?) but Latency is what it is.  In other words, you take your clue from the existing behavior itself.  If the average Latency for a certain segment is 2 years, well, it is, and that’s not too long or too short, it just is.  Whether you can act on that information is another story; it depends on what you are trying to accomplish.

For example, average Latency on major home appliances, depending on brand, is anywhere from 5 to 10 years.  Is that too long of a “spread” to make the metric useful?  No.  It just is what it is, and you deal with it. Typically these ideas are used to reallocate marketing spend away from waste on unresponsive segments towards segments that will generate incremental profits.

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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
(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 →

Predicting CRM Payback

Analytical Culture, Analytics Education, Customer Experience, DataBase Marketing, Driller Q & A, Marketing / Tech Interface

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.

Yea, I know. Boss wants to do smart customer marketing, but also wants to know what the payback will be for the “CRM investment”. Geesh, can’t we just figure cost out later? Sure you can, but might be better to make sure you understand what the “CRM success levers” are before you go spend a ton of money. You mean Drillin’, Jim? Sure, on to The Drillin’ …

Q:  Hi Jim,

Our industry is facility management services where a headquarters with chain locations contracts with us to manage their facilities in all their markets.  The President is interested in a “CRM Solution” but is concerned about the ROI he might expect from implementation.  Do you know of any number that I can pass along to him that would placate his insistence on knowing in advance what the ROI will be?

A:  Bad news: No, not really.

Good news: You can figure it out, which is something often not done.  You might not even need any new software to “do CRM,” though it depends on what you have now and what the objective of the CRM program is (you do have an objective, correct?).  But the software required is likely not millions of dollars and if you only have 100’s of clients you could probably do it with some combination of contact software, MS Access / Excel. 

The key question to ask: do you really know how your customers behave?  In this kind of contract business, I imagine the central issue is this: Can you predict which customers are likely to re-up a contract, and which ones are not?  And then can you use this information to focus on the ones less likely to re-up, and take steps to make them more likely to re-up?

Sometimes it is just a matter of better customer service.  In this case, what you need is better service practices, not “CRM.”  From a distance, it is very difficult to know what the issues might be in your company.

Here’s a test you can do to find out where you might be on the road to answering the CRM question.  If you cannot accomplish one or more parts of the following, you are not ready to even talk about “CRM,” and need to do some more internal research.  These steps, by the way, are the ones everybody skipped on the early rounds of CRM that created so many bad outcomes. Research / Implement / Discuss the following ideas to pave the way for a successful implementation if you decide to go with a CRM approach:

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