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In This Issue:

# Topics Overview

# Best Customer Retention Articles

# Question - New RFM: Student Retention?

# Question - New RFM: Wireless Retention?

# New RFM Metrics: eMetrics Summit
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Topics Overview
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Hi again folks, Jim Novo here.

You've probably heard the hot new buzz phrase "behavioral targeting" thrown around a lot in the online display advertising space lately.  Are you happy folks are so excited about joining the party we've been throwing right here for the past 4 years now?  I'll have more to say on this topic in the future, including why I think a lot of what is being done is **not** behavioral targeting, but I'll leave that off the table for now.  

Instead, we've got two great article links, one an example of what **is** classic behavioral targeting in online display advertising, as behavior trumps demographics yet again.  The second great article delves a bit into why people have a hard time turning data mining results into actionable programs.  Plus, two great questions from fellow Drillers: a rare question on student retention programs (a personal favorite of mine because they are so darn challenging) and the most common question I get - retention in wireless services.  Rare or common, we try to take 'em when they have to do with customer retention programs.  

So let's do some Drillin'!

Best Customer Retention Articles
====================

Note to web site visitors: These links may have expired by the time you read this.  You can get these "must read" links e-mailed to you every 2 weeks before they expire by subscribing to the newsletter.

What a Woman Wants Shopping Online
April 16, 2004  Internet Retailer
The title is a bit deceptive, but the results remarkable.  People who clicked on women's clothes were more likely to buy them than people who identified themselves as women.  When you are looking to generate behavior, use behavior to target; it beats demographics every single time.  After all, do you really care who the buyer is, as long as they buy?

Beyond the Black Box
May 10, 2004  Target Marketing
This article addresses a very common issue.  People work very hard on capturing data and turning it into information, but then they don't know how to act on it.  This is particularly true with data mining, when you might not be sure why the segmentation is relevant.  Think about what your models means in terms of the customer and design actionable programs that make use of this knowledge.

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Questions from Fellow Drillers
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If you don't know what RFM is or how it can be used to drive customer profitability in just about any business, click here.

New RFM: Predicting Student Churn

Q:  It is clear that retention of students is a complex issue.  The students' satisfaction with the university will be partly determined by their experience during their first semester with the university.  I have identified that each service encounter will contribute to the overall impression that the student has of the university.  Some encounters are 'moments of truth' and will have a major impact on the student's perceptions of the university.

A:  Hmm....interesting.

You just got very lucky, I happen to have first-hand experience on this topic, which is very rare, as not many educational institutions are thinking this way.  You should be congratulated for making this connection, though it will be a difficult battle dealing with the university administration on making changes, in my experience...

Q:   I would much appreciate if you could advice me on the retention strategy and what approach the university should take to retention.  Also, any ideas on management of moments of truth, particularly what enhances and detracts from the customers' encounters with the university.

A:  Please consider this old business maxim: Only attempt to control what you can actually control; otherwise you will end up not having an affect on anything.  It very well may be that the various "touchpoints" exist and can be defined, but can you reasonably control any of them?  Which ones, and how will you control them?  This is where you need to focus your efforts.  

In my experience, a university is not the kind of place where you can undertake a "customer service education program" with employees and expect compliance at all the touchpoints.  So what you have to do is pick the major points of influence where you know you can exert some control and seek to prove your case with facts and testing.

The best way to do this is with (no surprise here) data.  What you need to do is take a population, e.g. "first semester students in January 2003" and then segment them into two groups - those who continued and those who did not.  Then compare - what is it about the "not enrolled" group that differs from the "still enrolled" group?

I can tell you from experience some likely differences between the segments.  Please be aware these are based on US experience and may not apply in your culture, but they provide good examples:

1.  The courses taken in first semester - this is very highly predictive of continuing enrollment.

2.  Within a single course, the professors teaching it.  For example, you may find students taking Calculus are very likely to drop out after first semester, and will think "Calculus" is the problem.  But when you look at Calculus by Professor, you find the drop out rate is concentrated around one or two professors, not the subject.

3.  Financial aid amounts and qualifications

4.  Involvement in non-academic pursuits - clubs, sports, student government, etc.

In the US, this last segment is also highly predictive of future donations to the institution, which is an important funding concern - in the language of CRM, the "Lifetime Value" of the student is positively correlated to participation in non-academic university activities.

Are any of the above "controllable"?  In the US, if you value your job, you don't even bring up any of the results of #2.  This is a losing battle, the politics are thick and the issues not always clear.  #3 is likewise surrounded (in the US) with a lot of uncontrollable and often legal and marketing issues.

But on #1 and #4, you may be able to actually "do something".  You can change marketing materials and "first semester required courses"  to promote specific courses which tend to generate long-term students.  

Once students are enrolled, you can boost the promotion of non-academic pursuits by having educational and recruitment events.  A further refinement of this strategy would be to single out students enrolled in courses showing a high "first semester defection rate" and put extra effort into getting them into non-academic pursuits.

The amount of effort required to address #2 & #3 is enormous because there are huge institutional barriers to changes in these areas.  Addressing #1 & #4 can be a more "under the radar" effort and not nearly as costly, either personally or monetarily.  

Once you know the most critical "touchpoints" that you also **can have some control over**, make your changes and measure your results.  When you can prove first semester retention rate increases, you will get a seat at the table for going further and asking for control of other important touchpoints.

Jim

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New RFM: Wireless Segmentation

Q:  I have taken up a new assignment in this new financial year in my company in India (Cellular / Mobile connections).  I would like some direction from you; also I have suggested your book to my management.

A:  Well, thanks for the plug on the book and I'll give the "direction" a try...

Q:  Objective: To create loyal customers who become brand evangelists

Areas covered:

1. To drive customer loyalty to ensure 80% of the customers recommend brand to others.

2. Customer Behaviour Profiling: Create an action oriented customer profile, use profiles to create marketing & service programs to retain & increase value of customers.

3. Predictive Marketing / Promotions: To predict the likelihood of future events based on customer models & to predict the profitability of a promotion to encourage customers to do what we want them to do & achieve the highest ROI (Return on investment).  Predict when a customer is about to defect / leave us.

4. Life Time Value: To find what a customer is worth in the future and based on this, find how much you can spend on retaining them & still make a profit.

Please reply on how to start this activity?

A:  Yikes!  That's a pretty long list of "areas to be covered", you are going to be very busy!  Some of it sounds pretty familiar too, like I've read it on my web site...you might want to get that book after all...

The creation of retention programs always starts with customer segmentation, you have to understand the behavior you have before you can create programs to modify behavior.

That probably means starting with #4, LTV.  You want to look at LTV by segment.  Get records of defected customers, put them in a spreadsheet or database, and determine:

* Average length of time as subscriber
* Average spending over that time
* % of this spend that is considered "profit", used as a proxy for LTV.

In the beginning, you can use a company "profit" average for LTV until you get more sophisticated.  In communications, the number often used is EBITDA Margin; ask your finance people what you should use to determine % of spending that is LTV.

Once finding the average, it is time to segment by different dimensions and determine the same 3 variables above for all the different customer segments.  For example:

Spending quintiles - highest 20%, high 20%, middle 20%, low 20%, lowest 20% of defected customers; what is the average length of subscription, average spend, LTV?

Product / service bundling - identify different levels of service / tiers / add on services of defected customers; what is the average length of subscription, average spend, LTV?

Source of customer - which ads / offers / selling methods originally attracted the defected customer; what is average length of subscription, spend, LTV?

Geography - using transmitter locations or other natural boundaries dividing the defected customers; what is the average length of subscription, average spend, LTV?

Hardware - group defectors by type of phone or terminal or other hardware; what is average length of subscription, spend, LTV?

Contract details -  if contracts vary widely as to their basic nature and terms, group defectors by contract type; what is the average length of subscription, average spend, LTV?

After running these studies you should have enough data to logically and critically construct your other 3 initiatives in profitable ways.

New RFM Metrics: eMetrics Summit
====================

Jim Sterne's eMetrics Summit is in Santa Barbara June 2 - 4 and I'll
be there speaking on (guess) customer retention metrics and
management.  Or, translated into the language of the newly reborn
online display advertising market, the hot new discipline called
"behavioral targeting".  Join the party!

The official title of the piece is "LifeTime Value Without Waiting a
LifeTime" and explores how to predict which customers will be more
valuable than others in the future.  Why would you want to know this?

Because future value should drive all you customer investment
decisions, from how much you can afford to acquire a customer to when
to stop wasting money marketing to a customer.  If you attend the
conference, be sure to grab me and say "Hi."  More info on the
eMetrics Summit 2004 Santa Barbara:

eMetrics Summit 2004 Santa Barbara

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