New RFM: Managing Customer Value Like an Investment Portfolio

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.

These are the hardest parts of “doing” because “who” and “when” get to value of the customer, time management, resource allocation, and ultimately ROI.  The attitudinal stuff comes into play after you identify behavioral metrics and provides more insight into “how” you should approach the customer.

For example, from the prospective of a financial planner, let’s say it is desirable to have customers buy and sell securities, and it is undesirable when they stop or slow down this activity.  First, you must come up with a measure of this behavior.  Then, you can connect this behavioral measure to certain attitudinal types.  If you find certain attitudinal types consistently behave in certain ways, then you can predict the behavior (buying and selling securities) based on attitudinal profiles.

And certainly, this is part of what planners and  brokers have always done intuitively.  They know which clients are prone to trade and so on.  The challenge occurs when the number of clients is too large to remember what these behaviors are, and also in the fact this intuitive system is backward looking – it does not “predict” anything, and a customer could one day defect to another planner without advance warning – even though the warning signs were there all along.  But the planner has no “system” to recognize these warning signs and act on them – the “who” and “when.”

What kind of system?  Well, let’s take the analogy fully into the world of securities trading.  There are dozens of different technical indicators that are commonly used in trading – 50-day moving average, MACD, On Balance Volume, Relative Strength (RSI), etc.  Now, think of customers as securities.

You can apply these technical indicators to whatever customer metrics you are looking at – volume of trades, balances on accounts, and so forth.  Customers can have “Relative Strength” against each other.  They can be engaged in a number of trades that are above or below their 50-day moving average, and above or below the 50-day moving average of the “index” – the entire customer portfolio.  Do you see where this is going?

With securities trading systems, you can set stops or trigger alarms based on changes in the behavior of the security that violate or penetrate certain indicators like the 50-day moving average.  You could also do this with the customer portfolio.  Much like in securities trading, if a customer’s trade volume or balance drops below the 50-day average, there could be cause for concern.  

And what happens, for example, when a stock owned by a lot of mutual funds drops to the 50-day?  It is often “supported” by mutual fund buying at that level – as long as there isn’t something “wrong” with the stock, in which case they just sell and abandon the stock.

If a customer drops to the 50-day in trading volume, they too should be supported, in the form of a phone call or other contact, to try and “lift” them off the 50-day.  To allow them to “plunge” below the 50-day without “doing something” is to accept the fact the customer is defecting and just abandon the customer.  If the customer has low value, you might want to let them go – especially if you also have high value customers dropping to the 50-day who need attention and this requires resources.  This kind of resource allocation increases revenues while at the same time reducing expenses.  The trigger is the behavior, the “how” or approach taken can be influenced by known attitudinal factors.

Is this making any sense to you?

So, let’s say a large group of customers fall to the 50-day moving average in their trading volume (or commissions, or whatever).  This is unusual behavior versus the rest of the customers.   As a financial planner, you don’t want this happening because it means you are losing out on income. 

You could then look at the attitudinal measures on this group and see if there are any similarities.  If there are, you can draw conclusions and do something about it.  Exactly what would depend on the metrics and attitudes used, but it is probably at least a contact of some kind.  But you now have the most critical part of the equation – “who”  needs attention and “when.”

You can use a drop to the 50-day – or an On Balance Volume break through zero, or whatever is relevant.  And then you analyze the results of your contacts and see what worked the best with this behavior on customers with specific attitudes.  Further, you now know something about predicting the future behavior of customers with this particular attitudinal set.  When you see customers with this set begin to fall towards the 50-day, you can be proactive and anticipate the move, using best practices learned from the past.

Finally, since you are familiar with my work, the Recency and Latency metrics are just two more ideas which happen to be particularly good at enhancing the power of other measures of human behavior.  For example, a customer who has dropped to the 50-day AND the last trade was less Recent than the average of all customers is somebody who is in a heightened state of probable defection.   Likewise with someone who trades on average every two days and both drops to the 50-day AND their trade Latency expands to a trade every 7 days.  If either of these customers is valuable, action should be taken immediately to try and save the customer. 

Hope I didn’t go to far out of the world on this for you.  Customers can really be looked at as a portfolio of assets with differing future potential for returns, and as such, can actually be “managed” in the same way as a securities portfolio.  “Managing a portfolio of customer assets” is often talked about in CRM circles but rarely implemented in any meaningful way.  I find portfolio management one of the best “templates” for managing customer value out there.

Let me know if you have any questions!

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