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Customer Retention in Durable Goods
Drilling Down Newsletter # 56: 5/2005

Drilling Down - Turning Customer
Data into Profits with a Spreadsheet
Customer Valuation, Retention, 
Loyalty, Defection

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Prior Newsletters:

In This Issue:
# Topics Overview
# Best Customer Retention Articles
# Customer Retention in Durable Goods
# Customer Retention in Mutual Funds

Topics Overview

Hi again folks, Jim Novo here.

This month, we're looking at Customer Retention in another couple of areas people don't expect active retention programs - durable goods and mutual funds.  Just because customer programs may be a little "out of the box" for these industries doesn't mean you can't use these techniques to increase profits.

Speaking of out of the box, we also have a couple of great customer marketing article links.  The first is about the amazing work some people are doing with analytics in - of all places - the restaurant industry.  Then we take a look into the future - a future I have already seen at the Home Shopping Network - where analytics are persuasive throughout all silos and at all levels of a company.

Let's do some Drillin'...

Best Customer Marketing Articles

The Brain Behind The Big, Bad Burger And Other Tales Of Business Intelligence
April 10, 2004  CIO Magazine
Instead of droning on and on about why analytics should be producing better returns, the restaurant industry (of all places!) is actually doing something with analytics.  Up next is Six Sigma Everything.

Pervasive Business Intelligence- 
Enhancing Key Performance Indicators
April 24, 2004  DM Review
What is it with people inventing acronyms?  The latest is PBI (Pervasive Business Intelligence) which is essentially "always on KPI monitoring and alerting for all levels of the company".  Sounds a lot like Six Sigma Everything to me.  The article mentions the need for a cultural shift under PBI (they are right) but doesn't get into the details.  If you want to understand how disruptive something like PBI can be and what to do about it, I'm speaking about this at the eMetrics Summit.

Questions from Fellow Drillers

Customer Retention in Durable Goods

Q:  Jim, we're a high end manufacturer of appliances, distributing offline only through dealers / the retail channel only.  We're trying to figure out how / if we should try to create relationships with the end buyers of our appliances, but we're stuck.  Would you answer a few questions we have?

A:  Sure!

Q:  1.  When does a deep market testing environment make sense for a large company like ours?  How do we know it will work?

A:  I'm not sure what you mean by "deep testing", but I assume you mean database- driven marketing / CRM or whatever they call it now.  It makes sense when you can get accurate data on the end target customers and there is a compelling reason to do it.  In your case, that compelling reason could be a customer LifeCycle starting with the low end or mid-tier brands that for some reason does not "pull" people up into the high end brands.  For example, people buy from you at the low end but do not consider you for the high end and defect to other high end brands.  

If this scenario is even a remote possibility, it would make sense for you to explore the idea with a "deep testing" program, since there is so much money being left on the table when the customer cycles out like this.  I suspect you probably don't know if it is happening and to what extent.  Perhaps you do, but if you
don't, that is where you start.  

If you really have no idea what goes on with the customer over time, then drop back to surveys using warranty card data or some other "in appliance" distribution.  For example, I have seen the "Fill out this survey and we will send you a free spice rack" type of thing work well for this.  The results will be a bit biased towards "freebie folks" but with your product I don't think this is a concern, and would be better than nothing at all!

Q:  2. Why is one2one marketing still difficult to achieve for many companies?

A:  It's not very difficult to achieve that I am aware of, it has been happening in many industries for decades.  It may be difficult for certain industries and distribution chains to do well because they lack good data or knowledge of the correct way to go about it. 

Here in the US, many high-end appliance brands engage their customers in these programs through the mail, and now using e-mail.  Offline newsletters are pretty standard
for the up-market brands, they provide recipes and "how to" as the "content" while pitching new or related products - "the ads".

Q:  3. Why can advanced analytics only take a company so far?

A:  I'm not sure you need "advanced analytics" of any kind to increase profitability.  You need a customer database and some kind of analytics, but it doesn't have to be advanced.  I think you are perhaps confusing
"advanced analytics" with "advanced marketing techniques", which really are
not very advanced unless you have never done them before.  But it's not "hard", really, and it's only cutting edge if no other companies in your industry are doing it.  You can build yourself a very simple "what if" model in a spreadsheet.  

Let's say only 50% of your low end customers who end up buying high end buy it from someone else.  Further, let's say these people will make 2 high end purchases in their lifetime.  Well, how much in sales and profits is
this?  That is how much money you are leaving on the table by not having some kind of relationship program.  Use whatever numbers you have.  If you don't have any numbers and no data, a survey is the way to start so you can determine "where you are".  And if you don't have any end-customer records at all, try the "freebie for a survey" tool.

Hope that helps!

If you are a consultant, agency, or software developer with clients needing action-oriented customer intelligence or High ROI Customer
Marketing program designs, click here.

Customer Retention in Mutual Funds

Q:  I just found the "Drilling Down Project" and it sounds perfect for my company (a mutual fund company).  We were about to start trying to profile shareholders by testing hypotheses, but from your book excerpt it appears we should be creating action-based customer models first.

A:  Sure, it depends on what you're trying to get at.  If you create your behavioral segments first, and then look at the demographics / other features of those segments, you will have predictive power because you can target people behaving in a certain way.  It doesn't work in reverse; demographic segments by themselves rarely predict behavior because they give no "signals", they are fairly static.

Q:  I'm about to order the book but had a software question -- Does the Access template address negative units?  Mutual fund transactions can be inflows (positive) or outflows (negative).  It's great if someone is
making a lot of recent transactions, but if all of them involve taking out their money, that's not good from a business perspective.

A:  Strictly speaking, the software will "handle" negative transactions because it simply sums the value of the transactions, in your case providing a "net" number.  I'm not sure this will be useful to you and could considerably cloud the results, depending on what you are trying to accomplish.  For example, a high "turnover" customer (frequent deposits and withdrawals of similar value) will seem to have a low Monetary value yet will be very Recent and Frequent.  Assuming there are fees associated with the transaction activity, this type of customer might well be a "profitable" or "best" customer but might have a low rank.

So it really depends what you are trying to shoot for; and to be honest, I'm not sure RFM is the right model for your industry anyway.  For example, a lack of transactions at all might be good - a stable, long-term investor - and RFM is not a particularly good tool for that kind of low transaction volume environment.

It strikes me that Latency - the time between transactions, also covered extensively in the book - might be a more useful tool, but I don't know what makes a "profitable" customer in your business so it's hard to say.  Of course, if you don't really have any idea what you are looking for (very common!), it's best to work "backwards" - isolate the behavior and then look for commonality.

Let's say you are trying to predict complete defection - a customer withdrawing all their funds.  It seems to me a customer who is devoted to a "theme" in investing would try to stay with the fund family if they could, and if they were disappointed with the returns, would try different funds in the family before completely defecting.

So find customers who have defected already and then look at their behavior prior to the defection.  Was there, for example, a period where the customer was actively "switching" between funds in your family before pulling out all their money?  If this behavior occurs in many of the defected customers, then this switching behavior becomes the "red flag" that tells you execute a "save the customer" program against all "switchers" when the behavior is detected.

Then, you want to try and go back further.  Where did these "switchers" come from, did you in fact "create" them?  Many times, specific marketing programs are in fact responsible for creating best and worst customers.  If you see the "source" of many of these switchers is ultimately a specific acquisition campaign, then you can make a judgment as to whether this campaign is a good idea to run or not.

If you care to provide some more info on the behavior / outcomes you are reaching for perhaps I could be of more help...



That's it for this month's edition of the Drilling Down newsletter.  If you like the newsletter, please forward it to a friend!  Subscription instructions are top and bottom of this page.

Any comments on the newsletter (it's too long, too short, topic suggestions, etc.) please send them right along to me, along with any other questions on customer Valuation, Retention, Loyalty, and Defection here.

'Til next time, keep Drilling Down!

- Jim Novo

Copyright 2005, The Drilling Down Project by Jim Novo.  All rights reserved.  You are free to use material from this newsletter in whole or in part as long as you include complete credits, including live web site link and e-mail link.  Please tell me where the material will appear. 


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