Category Archives: Digital Analytics

Customer Perks Marketing

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

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: Using RFM to Improve Email Profit

Jim answers questions from fellow Drillers

Topic Overview

Hi again folks, Jim Novo here.

Traditional RFM execution is focused on giving a snapshot view of customer likelihood to respond / campaign profitability across large and varied customer databases. But is that all it can be used for? Heck no! If you understand the basics of how and why RFM works, and you understand your customer database, there’s a ton of different very valuable customer scoring operations you can accomplish. Interested? Get out the Drillin’ tools …

Q: I recently purchase your book “Drilling Down.” Really enjoying reading it!

A: Well, thanks for the kind words!

Q: I had a question about the implementation of the RFM model against email campaigns. Say we have a client that has done this:

  • Sent out 2 emails to entire database – in June and July
  • Sent out 3 targeted emails to a specific segment of database – in June, July and Aug

From my CTR and Open Rates I know that the targeted segment performance is better. For my scoring I am using the following:

  • Recency, last email responded to, and
  • Frequency, number of emails where an action (a click-thru) was taken

So the question is when trying to apply an Recency / Frequency RF score to the entire database, do you / can you use all 5 email programs? Would Recency include the email to the specific segment in August? Would frequency include the segment that received the email in August?

A:  The fact you are asking this question tells me you understand the methods better than you think you do.  The correct answer is yes, and no, depending on the objective of the scoring. As long as you **understand** that there is the potential for the marketing to the target segment to skew the scoring of the overall group, then you are thinking about the problem correctly.  Whether you decide to do the scoring as “everybody” or you score the targeted segment and then score “everybody else” separately really depends on what you are trying to accomplish / the objective of the effort.

Continue reading New RFM: Using RFM to Improve Email Profit