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Drilling Down Newsletter # 14 -
November 2001 - Customer Surveys

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

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Prior Newsletters:
Drilling Down Newsletter # 14 - 
November 2001

In this issue:
#  Call for Case Studies
#  Best of the Best 
    Customer Marketing Articles
# Tracking the Customer LifeCycle:
    Longer Term Effects
# Questions from Fellow Drillers
Hi again folks, Jim Novo here.  This month we have a call for case studies from a new magazine, a few very interesting customer marketing article links (they could all be subtitled, "Hey, let's try to do it right this time"), and a fellow Driller with a question on survey bias.  We also come to a fork in the road in the series on Customer Latency, with you making the call on where we go next on our exploration of High ROI Customer Marketing techniques.  FYI: the last newsletter was longer than usual due to the ROI "proof" on the Latency promotion.  I've made this one 2/3 the usual length to try and "make it up" to you, as things tend to get busy this time of year for many. 

OK?  Let's do some Drillin'!

Call for Case Studies

There's a new magazine coming out in January called Optimize, from CMP.  The idea behind the mag is to present practical real world implementations of technology, and tell readers how it was done.  "Theories" have to be backed up with case studies from the people who did the work.  I've spoken to editor-in-chief Brian Gillooly about some articles, since I think the Drilling Down method is a classic example of what this magazine is about.  But I need some of you to come forward with actual implementation stories you are willing to have published.  Here's more on the magazine:


I have a ton of "soft" testimonials:


And a bunch of stuff I can't say anything about because folks just do not want anybody to know what they're doing.  But there has to be concrete implementation details in these articles for Optimize magazine.  Most of the above folks can't be bothered or don't want to reveal the outcome of their work for various reasons - like their boss will blow a gasket.  Too bad.  So...do I have any takers out there?  All you have to do is supply the raw data; I will write up the article for you, and you get final approval of the contents.  By the way, we can mask the actual results - but the material has to come from a real company where a real human is willing to go on record saying, "I did this, it works, and (required) here is how."  The case doesn't have to be complex, earth-shattering, or from a Fortune 500 company.  Just everyday people making it work. Great opportunity for a smaller business to put themselves on the map with the press.

Can you help me out?  E-mail any idea for a case study based on the techniques in the Drilling Down book here. Thanks for your help!

Best of the Best Customer Retention Articles

After a boatload of great DM News articles for the last article update, I find for this newsletter no "must read" articles they are about to lock away in the paid archives .  So here's a few other must read articles (which don't expire) you may have missed.  The first 2 URL's are too long for the newsletter, so the links take you to a page with more info on what is in the article and a direct link.  The last is a direct link to an article on my site.

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.

SAS chief: 'Analytics' an overused term October 17, 2001  searchCRM.com Oh man, is this guy a classic.  Kicked butt and took no prisoners.  And he's right.  Analytics should be about prediction, else they're just reports.  Too many of the current analytical apps are just reporting tools, and if you  don't know what to report on, are not much help. 

Next-Wave Business Analytics 
October 12, 2001  Information Week
And there it is, folks.  The next wave is here, and it's what I've been saying right here for a year now. "Change is the major concern in business... What's needed are business analytics tied to sensors and thresholds that can alert managers to the slightest nuance of change..."  In other words, not absolute measurement, but relative measurement.  Hmmm...

Should You Build A Data Warehouse?
October 29, 2001   Drilling Down Site
Article by a data architect friend of mine outlining the less expensive alternatives to a data warehouse  - what they are, what they can do - and a unique approach to proving the case for or against the selection of any alternative.  Definitely in the tradition of High ROI Customer Marketing - spend only when you have to, and when you do spend, do it at the point of maximum impact. 

Tracking the Customer LifeCycle: 
Longer Term Effects
If you are new to our group, you might want  to read the first four parts of this series.

Last month, we looked at how to execute a Latency-based promotion and use the two core rules of High ROI Customer Marketing:

1.  Don't spend until you have to

2.  When you spend, spend at the point of
     maximum impact

By focusing your resources squarely on the problem, each dollar you spend works much harder.  By waiting for the trip wire you narrowed the population you were promoting to, weeding out people you would normally waste money on.  And by acting when the wire was tripped, you spent at the point of maximum impact. This approach led to a 114% return on the promotion, as result of the "found profits" you generate when you surgically prevent customer defections with ultra-targeted promotions.

We were left with a question, though.  This promotion was not designed to extend the customer LifeCycle, but to add value to the LifeCycle.  Did we actually extend the LifeCycle, and how would you measure this effect?

That's the topic for this month.

Recall you made $8000 in 90 days after paying back an investment of $7000 with this promotion.  You generated a bottom line profit of $1.60 per customer - without even looking at what happens to the customer after the 90 day promotional period is over. But it is very likely you did something else with your promotion - you extended the LifeCycle of the customer - and this is how you track these "LifeCycle extension" effects. 

All the customers in both the test (received promotion) and control (did not receive promotion) groups were 3x buyers who failed to make a 4th purchase by 180 days after their first purchase.  This was the Latency "trip wire" selected to trigger the sending of the promotion.  So let's look at tracking these two groups for another 90 days, and look at continuing purchase activity using what I call the Hurdle Rate method.

A Hurdle Rate is simply the percentage of customers in a group who have "at least" a certain amount of activity.  You define the behavior hurdle they have to reach, and measure the percentage of customers who have achieved this "threshold" (rate).  If you track these percentages over time, you can use them to compare the actual and potential value of customer groups as a whole. 

At the point of the promotion, 0% of both groups had made a 4th purchase.  Recall we measured the profitability of the promotion over a 90-day period after we sent it to customers.  To track the Hurdle Rates for each group, we ask, "What percent had made at least 1 more purchase at 30 days, at 60 days, and at 90 days after the 90-day promotion was over, in both the test and control groups?"

We know some percentage of both groups made a purchase during the promotion, because there were revenues generated in both groups.  We made a profit in the first 90 days because the revenues were much higher for the test than control group.  So at the beginning of this "post promotion" tracking, we see 1% of test and 3% of control have made 4 or more purchases.  For the following 90 days, the data might look like this: 

% 4 or more purchases.........Control......Test

End of 90-day Promotion........1%............3%
30 Days After Promotion End..1%...........5%
60 Days After Promotion End...2%...........8%
90 Days After Promotion End...2%.........10%

Realize this: we have already made money on this promotion, a 114% ROI.  We have already added value to the LifeCycle, increasing LifeTime Value - no matter how long a "LifeTime" is (does it really matter, as long as you are making profits?) 

But as you can see from the chart above, we also extended the LifeCycle itself, because the percentage of customers exceeding the "4 or greater Hurdle" in the test group is far higher than the percentage of customers over the same Hurdle in control, and it appears to be growing over time. 

There is a group of customers in the test group who just keep on keeping on - and this percentage (10% at 90 days after Promotion End) is much higher than both the initial group who responded to the promotion and made a 4th purchase (3%) and the test group.  What's going on with that? 

It's called the Halo Effect.  It represents customer activity stimulated by the promotion which did not occur within the promotional period.  Now we don't know exactly where it's coming from, and we can't show any measure of profit from it (we defined our promotion period as 90 days) , but it is clearly there, plain as the nose on your face.  

Recall when describing the original promotion, I stated, "Response doesn't matter; what matters is actual buying behavior. When you use control groups, you pick up buying behavior you never could have measured by just looking at response rates." 

This "buying behavior you never could have measured" is the Halo Effect, working magic during the promotion.  People you have no way to track will respond to the promotion.  They want to make a purchase but forget the coupon, for example. So they go ahead and make the purchase anyway - because the promotion "woke them up" to a need.

After the promotion is over, the same thing continues.  It's the Halo Effect again, working after the promotion.  For example, people think about participating in the promotion but wait too long.  They've missed it.  But they're now in a new state of awareness about your company because of the promotion, and so are more likely to make a purchase given any random positive stimulus.  Perhaps some product appears on a TV show.  Maybe a competitor promoted a product to them, the customer remembers you sell it also, and prefers your store.  

It doesn't really matter.  Fact is fact, and because of your promotion, you extended the customer LifeCycle.  You created a situation where people became more likely to purchase from your company in the future, as demonstrated by the chart above. 

Not bad for a beginner.  In the first 90 days, your promotion created present value - real bottom line, measurable ROI - which adds Value to the customer LifeCycle (LifeTime  Value).  In the 2nd 90 days, your promotion created future value - accelerated repeat purchase rates - by extending the length of the LifeCycle of the customer.  

CFO sings your praises!  At last, somebody who can prove they are making more money than they are spending with marketing! 

Well folks, I think I've fulfilled the objective of this series.  In the first article, I stated: 

"I'm going to back up a second and explain in a more general sense how metrics like Latency are used, and in particular, address some of the misconceptions people have regarding customer value-based and relationship marketing techniques.  Much of CRM is based on these fundamental ideas.  You do not need to live on the bleeding edge of technology to take advantage of a customer-based management philosophy." 

That's how we started down this current path.  Now that you know where we end up (for now), you might want to skim the whole series again when you have time.  I'm sure it will make more sense to you as "one article" as opposed to five articles over five months.  Here's where you start

So I think I've accomplished the goal from the first article stated above.  But I could go on.  And on.  So, you tell me. You just read Part Five in the series.  Do you want a Part Six?  If so, send me any e-mail (blank OK) here.  If you think we're starting to beat a dead horse here, and want me to go in a different direction, send an email here and tell me what you would like to read about in the world of Customer Valuation, Retention, Defection, or Loyalty.  Helpful: Also tell me if this series was too easy, just right, or too difficult for your needs.  I'll take the feedback and we'll push ahead next month with the business of Drilling Down into customer data.

I can teach you and your staff the basics of high ROI customer marketing using your business model and customer data, and without using a lot of fancy software.  Not ready for the expense and resource drain of CRM?  Get CRM benefits using existing resources by scheduling a roundtable or workshop.  Details here.

Questions from Fellow Drillers

Q: I have really enjoyed reading your newsletters.  Keep up the outstanding work!! 

A: Well, thank you for the kind words. 

Q:  Typically, most marketers offer an incentive for their customers' valuable feedback on a survey .  I am interested in knowing if studies have proven or disproven that this offering skews the results of the survey.  Any insight you can provide on this topic would be greatly appreciated.

A: I don't know of any "tight" studies on this I can link to.  In general, rewards of any kind skew results, so I'm not sure anybody would bother studying it.  How much skew occurs  depends on the objective of the survey, the product, and the offer, so any study would have limited application in different situations.

The whole question of bias in surveys keeps the academic community alive with perpetual white papers.  The key is to be consistent with your approach and look at trends.  The first survey doesn't mean much as a stand-alone effort; the real question is, are things getting better or worse?  The important number to look at is not the "absolute" level of any parameter, but the relative change in a parameter - the change over time.

With or without reward, you will introduce bias - it' the nature of this work.  Some types of people answer, others don't; you always get bias!  What you want to do is *control* the bias, and one of easiest ways to do this is to use the same survey method (and incentive, if you use one) each time you survey.  The real issue is to set up something your company feels comfortable being consistent with, and look at the trends.  If you ask if people are "satisfied" and 20% are, this is meaningless. What matters is the next time you ask, is it 25% or 15%? 

Hope this answers your question.


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.

If you're in a tight spot on a customer marketing program or CRM initiative (it just doesn't pay out / can't prove it makes money) and need some help making it profitable, check out my project-oriented services

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 2001, 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 attribution, including live web site link and/or e-mail link. Please tell me where & when the material will appear. 


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