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New RFM: LifeTime Value - Ad Budgets
Drilling Down Newsletter # 41: 1/2004

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
# Who we are, where we are going
# Question - New RFM: LTV & Budgeting?
# Question - New RFM: Modifying RFM?
# New RFM Metrics: Take 10 on Retention

Topics Overview

Hi again folks, Jim Novo here.

There is not usually a lot of "meaty" content in the December trade magazines, so for the January newsletter I replace the "links" section with a few comments.  Rather than make all kinds of inane forecasts on what will be hot and not in 2004, I instead like to update everyone on who you are and where this effort will be going this year.  We then have a couple very meaty questions from fellow drillers on using LTV for budgeting and creating modifiers to the basic RFM approach.

But first, a couple of job opportunities for those of you with web metrics skills:

Drs. Foster & Smith, Wisconsin

Karta, Los Angeles

If you have a job in web metrics / customer analysis you'd like to get in front of this newsletter audience, just send me a link.

Who we are, Where we're going

Globally, the majority of you are primarily interested in online customer marketing, which should be no surprise given the medium we're using.  The interesting thing that happened this year is the increasing interest in offline customer marketing, for example, "Can we take what we are learning online and use it offline to accomplish the same High ROI?"

This is a fascinating development (at least to me) because those of you who have been with me since 1999 - 2000 know the Drilling Down Project started as an effort to teach onliners how to "port over" the ideas offline direct / database / relationship marketing players are using to understand customers / business processes and reduce costs while increasing profits (CRM, if you want).  Now the onliners are going back across the wall and teaching the offline part of their company how to make it all happen - I love that!

You generally comprise 3 groups:

1.  People at the beginning of the learning curve, working to get a handle on customer source tracking and the cost to acquire a customer.  These folks are primarily interested in web analytics and conversion of visitors into buyers, leads, relationships, repeats, etc.

2.  People who have passed through this stage and are now looking at the more complex issue of visitor / customer value over time, for example, a customer I acquire for $10 may only be worth $5 in profits over the next 6 months, whereas a customer I acquire for $50 may be worth $3000 in profits over the next 6 months.  These folks are primarily interested in the simple customer models outlined on the web site and in my book.

3.  Advanced folks, who already had offline experience in customer value management and High ROI Customer Marketing before the whole online thing happened, and the rest of the world started caring about "CRM."  These folks were likely doing the same kinds of things CRM vendors now promise on a Unisys A Series the size of a restaurant refrigerator and remember a hardware company named Burroughs and disk packs (data storage) - hey buddy, can you spare a byte for a good cause?

By the way, I'm in the last group, circa 80's.

Yes, this general topic of using information on customer behavior to reduce costs while increasing profits has been chugging along for that long.  Did you think it was a new idea?  It actually started in the 50's, and back then, it was all done by hand.  No kidding.  You gotta start somewhere, right?

The content format I've been using this past year seems to be the most successful ever, that is, to not write a lot of long-winded articles but instead answer more questions, and try to group the questions in each issue by the 3 audience types above - web analytics, simple customer models, and more advanced ideas proposed / championed by readers.

Of course, without the long-winded articles there wouldn't be a library of content for me to link to and you to learn from, so that phase had a purpose.  But now, much of the core content is sent directly by e-mail to you when you subscribe to the newsletter.  So I intend to continue the Q & A format this year, with the occasional article when I think an issue needs to be addressed.  If you disagree with this approach, let me know by replying to this e-mail with your comments and preferences.  

Enough of the commentary, on to questions, which this month are targeted to Group #3.  Hopefully those of you in Groups 1 & 2 above  can benefit by seeing what's "down the road."

If you are in SEO and the client isn't converting the additional visitors you generate, you can help them make it happen - click here.

Questions from Fellow Drillers
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:  LTV and Budgeting

Q:  You'll be pleased to know that your book has been the catalyst for setting up a user forum on RFM which now has around 30 actively contributing members.  Not many, but not bad considering the only way the word was spread is by word of mouth!

A:  That's great!

Q:  We operate a retail stores, a catalog, and web site.  I want to make sure I understand how LTV tables help in drawing up your budget and marketing plan.  Obviously in the context of my assignment I make a few assumptions, because hardly any data is given.  My take on the process is as follows:

- Work out rough average customer spend

- Work out how much I want to increase my sales in FY 2004

- Work out how many customers I need to get me to sales budget

- Now split the overall number of customers by distribution channel (distribute customer spend through each as I think appropriate)

- Work out an LTV table for Shop, Print Catalogue, and web site

- Take a percentage of the 'LTV at Net Present Value' figure for 2004 (say 20%) which will give me the amount of money I can afford to spend on my marketing budget.

- Create a budget and campaign for shop, catalogue and website for 2004 only

- Write analysis

Is this process correct?

A:  Well, it's hard to define "correct" not knowing the specific requirements of the task,
but I think you are generally on track.  A couple of comments:

** "How much I want to increase my sales by in 2004" is a retail concept you may find difficult to crunch into direct methodology.   Remember, direct is much more focused on profits than sales.  In retail, you follow a standard "percentage of sales" model and as long as sales go up, profits are expected
to go up.  Not so with direct.  For one thing, in direct actions you take today have value in the future.  If you want, you could say, "OK, I know a direct customer will spend $100 first year, $80 second year, and so forth, and crush direct into a retail model, but to me this defeats the beauty of direct, because now you are using a "periodic financial accounting" system rather than a "customer accounting" system.  More on this idea here.

** In fact, I'm not sure what the value is of including "the stores" is in the process, other than to determine what gross revenue needs are.  The stores involve a completely different model than catalog and web, and I think down the line you are going to get to a place where it is hard to "force" the stores into the direct model.  Now, if you are assuming that these stores possess some way to behave like a direct operation - that is, they always have customer-level knowledge of all customer transactions - then maybe it works.  

But in the stores, if you have walk-in traffic that transacts anonymously, then you bust the direct model, you can't track LTV and so on.  So retail is much more like a "snapshot" idea (activity today has value today) than a "movie" idea (activity today has value over time).  Offline retailing is generally managed in the aggregate, not at the customer level.  Direct is managed at the customer level.  These two models will "collide."

For example, you do newspaper ads for the store and you see a boost in traffic.  You have sales - product costs - ad cost = profit, in the aggregate.  There is no measurement at the customer level, no LTV involved in this, no future stream.  In direct, you know who you attracted and can measure future profits.  A campaign that looks like a loser today can be a winner in 2 months.  From a management perspective, to try and "force" the retail store manager to operate under the direct model would result in sub-optimal performance.

Q:  My second question draws on your experience of the catalogue market.  I need to make an assumption on costs versus profit.  So, what I intend to do (presuming this is correct) is to take a percentage of the 'LTV at Net Present Value' figure for 2004 (say 20%) which will give me the amount of money I can afford to spend on my marketing budget.

Question is, what should this percentage cost be for the shop, catalogue (print) and website distribution, bearing in mind that they have relatively little experience of catalogue/web marketing and already own three shops.

A:  Yes, and do you see where this is leading?  20% NPV (Net Present Value) of LTV (LifeTime Value) is OK for direct, 3% of retail sales is what is typically spent in retail.  How do you reconcile this?  You can't.  This is what I mean by the models colliding.  If you went to a retail store manager and told him he could spend 20% of the NPV of the LTV of the average customer on ads, he would at least be a bit confused, at most think you're totally bonkers.

Put another way, retail operates on a single transaction basis (snapshot), direct takes into account transactions over time (movie).  Retail cannot afford to pay more than 3% of sales because they cannot target and cannot track.  In direct, you generally lose money on the first purchase from the customer.  Retail management could not tolerate that approach, they try to make money on every sale.  It's simply a different operating model, and this difference is driven by the difference in cost components.  Retail is a high fixed, low variable cost model; direct is low fixed, high variable cost model.  The seeds of "model collision" are planted in this fundamental difference
between the two cost structures.

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

New RFM:  Modifying RFM

Q:  I've been through your site and have found it immensely useful, thanks a lot for the wonderful resource!

A:  Well, thank you for the kind words, glad you found it useful!

Q:  As head of Data analytics at a leading direct and loyalty marketing agency in India, I've seen a fair bit of action on the RFM front as well, and thought I should share a couple of 'additions' to RFM we use frequently.  You might, at this moment, be rolling your eyes in despair because there's a million guys who've mailed you with this same suggestion, but I guess that's a chance I'll take.

A:  Trust me - there isn't a million guys (or gals) who are doing any of this stuff yet, the focus is still on getting customers and not keeping them.  Your odds just improved!

Q:  Here's one - RFM(C):

We've found addition of 'Consistency' very useful.  Two customers with the same Recency and frequency score can have widely different behaviours.  One bought ten times in Jan and once in November, the other bought once every month from Jan-Nov. Introducing Consistency differentiates between these two species of customers.  Consistency measures could be Variance (monthly value / frequency), or simple ratios.

A:  Yes, this is what I refer to as "rate of change" or "acceleration / deceleration" and I have actually had a few e-mail discussions on this one.  It can be seen as a "dx / dy" derivative idea if you take it further down the road.  This is an underlying theme in my book and referred to several times though I don't go into it explicitly because the book was not intended for an expert audience.

For example, if you track the RFM scores of an individual over time, the more dramatic the change in score (a "rate" of sorts), the more highly predictive it is of an acceleration (becoming a better customer) or defection (ceasing the relationship).  You can also get to some of this by including a Latency screen, e.g. in your example, these customers would have different Latency profiles.

Q:  And this one - RFM(CS):

In retail situations where different product groups may have to be treated differently, Saliency could become relevant.  It's a measure of the importance of that product group in the customers basket.  For instance, a customer with high RFM in Menswear where Menswear constitutes only 2% of his / her sales, should be treated differently from a customer with a lower 'M', but where Menswear constitutes 60% of the sales.

A:  Absolutely.  As a matter of fact, there is a specific discussion of this in the book.  One of the great untapped areas for direct retail is category migration, where customers who start buying one kind of product need to be "migrated" to another category or they defect and stop buying completely.  Some customers make the migration themselves, and become long term, very profitable customers.  Many do not migrate.  If you can "push" them to migrate with the right kind of promotions delivered at the right time in the LifeCycle, you get customers who stick around longer and achieve much higher value.  This kind of promotion strategy has the highest ROI of any customer marketing I have ever seen because it addresses fundamental LifeCycle issues.  To work well, it has to be tightly linked with good merchandising, something not very many companies are good at (at least on the web).  So it's not easy, but very profitable.

As a matter of fact, this second issue ties to the first.  Essentially, you want to hit the customer with the migration offer when you see deceleration in the initial or primary category.  For example, customer buys once a month like clockwork for 4 months in a single category, then skips a month.  This triggers the migration offer.  But you first have to understand the "category pairs" to make this work - e.g. long-term customers who end up buying fashion started in jewelry, long-term customers who end up buying kitchen started in home fashion, etc.  You can "reverse lookup" these pairs by analyzing high value customers over time.

Q:  If at any point you want to know more about the sort of work we're doing related to analytics for relationship / loyalty programs here in India, mail me!

A:  Consider yourself mailed!


New RFM Metrics: Take 10 on Retention

If you would like to know more about how to use the new RFM metrics to improve your profitability on the web, check out the free "Take 10 on Retention" package I wrote.  It includes a 10 minute presentation on the strategy and reporting behind increasing web customer ROI using simple predictive models.

Here's the idea in a nutshell: when you make investments, you expect the value of them to rise in the future.  You have web investment choices - media buys, ad designs, building out content, etc.  Retention metrics tell you which of these investments are the most likely to generate increased profits in the future.

Click here for the Take 10 on Retention


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 2004, 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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