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In This Issue:

In This Issue:

# Topics Overview

# Best of the Best Customer Marketing Links

# Question - New RFM: Branding Metrics?

# Question - New RFM: RF versus RM

# New RFM Metrics: Take 10 on Retention

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Topics Overview
=============

Hi again folks, Jim Novo here.

We've got two hot customer marketing articles and two excellent questions on the next generation of web metrics.  RFM is a grand old offline predictive model that is simple to understand and use - and works even better online, with a few modifications.  

At some point, instead of reporting on the past, you are going to want to rank the future value of your customers so you can make more profitable decisions.  And the best news is this is now very simple to do.

Let's do some Drillin'!

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

This section usually flags "must read" articles about to move into the paid archives of major trade magazines before the next newsletter is delivered.  I highlight them here so you can catch them free before you would have to pay the fee.  This cycle there were no great articles from these particular magazines, but there were a couple of great articles from other magazines.  So check 'em out!

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.

**** Attitudinal Imperatives for Direct Marketing
August 12, 2003   Direct Magazine
Did you know the consumers using direct channels are smarter, happier, kinder, more physically fit, and have happier marriages?  This annual comparison of consumers buying direct with those that don't is a must read; implications for strategy and execution abound.  Seven attitudinal imperatives and the opportunities they create are identified.  Also:
They're Non-Responders, Not Non-Consumers

*** Supersizing Search
September 8, 2003  Internet Retailer
Search engine marketing has come quite a long way since I provided a roadmap to search success back in 2000.  It's the most logical path to profitability because it takes advantage of how people actually use the web.  The next frontier in search will be understanding how to optimize PPC and organic search together to maximize ROI.  And after that, people should begin to pay attention to customer retention, because what looks like a bad deal on the initial search conversion can be very profitable indeed over the longer term.  How to do this?  You will need to look at classic behavioral metrics like Recency and Latency by search engine and search term.  More info on this is here.

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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
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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:  Branding Metrics - Again

Q:  We constantly try to quantify the value of web sites as a branding vehicle.  The thing that keeps gnawing at me is we will often report the average time spent on site.  This intuitively seems like it should have a value we could wrap into our ROI, but as it is, it stands largely on its own.  

Are you aware of, or have any thoughts on, how we might put an actual value to this?  Is it enough to show lift without respect to time, and to talk about return visits in terms of frequency models, or is there some way to drill down to a fundamental value of what a person-second on your site could be worth (obviously the content of the site will impact how much of that value you actually got)? 

A:  I've done a bunch of work like this and personally, I think you measure branding with branding metrics and direct with direct metrics.  If the CPG people understand the value of advertising in terms of brand affinity, recall, intent to purchase, and so forth, then it seems to me that is what you measure.  They have already made the "final connection" between these metrics and ROI, so it's not really up to the marketer to make those connections.  They believe increasing intent to purchase = advertising worked.  And I'm not sure you really can make a connection, because the "units" you are measuring are different and the math ultimately fails.

Here's why.  Traditional advertising has never been judged by the "value of the customer", it is judged by the "value of the media".  The customer is "reach" and has no individual value; individual customers are totally
exchangeable as long as the reach is the same.  Any single person is irrelevant; it does not matter what they do or don't do.  If there is no "customer", I'm not sure how you would ever get to ROI.  It is assumed from reach comes sales, and this is proven using branding metrics, not ROI.

Q:  I've gone back and forth on this and approached it from a few different angles, like the fact that, on average, 1 second of TV advertising costs about $.0003 per person.  You could use this information to calculate how much it would have cost to communicate the total person-seconds you had on your site in a particular month, but this is fraught with problems as you might guess, and am looking for another point of view.

A:  You see, this is a media value, not a customer value.  It's all about how much it costs to communicate, not what the customer is worth.  Pegging the value relative to communication costs is a non-starter, my opinion, because to get to ROI, you need the value of the customer.

If I was going to try and "straddle" direct and brand metrics, I think I would migrate towards evidence of "loyalty".  You can use Frequency of visit, but it makes more sense when combined with Recency - not only have they visited often, but they are still visiting.  Since Recency predicts repeat action, you can imply this: someone who has visited in the past 7 days is more "loyal" than someone who last visited 60 days ago, because they are more likely to visit again.  You can look at the average Recency of the visitors created by different campaigns and measure which campaigns generate visitors with the highest average "loyalty" (Recency). 

This is in fact exactly how database marketing companies and people who know how to execute on CRM manage customer retention - falling Recency = defecting customer.  Falling Recency for a brand marketer's web site could = falling loyalty, and loyalty rising or falling is a metric branders have a good understanding of.

This makes some sense if you think of it in terms of demographics, something branders are intimately familiar with.  If you look at the Recency of visit by search engine, you usually see dramatic differences.  Visitors coming from one engine are more "loyal" than those coming from another engine, and this generally has to do with the distribution (and thus demos) of the engine.  Each search engine is really like a cable TV Channel, with it's own demos.  You can further see differences within a search engine by topic, which is similar in concept to the different demos of shows on a single cable TV channel. 

As for time spent on the site, it's pretty difficult to comment on without understanding the objectives of the site.  In every case I have seen, longer visits = higher sales, leads, downloads, etc., because "tasks" take time to complete.  But unless you are "selling time", as with traditional media, I'm not sure "time" has an economic value to the marketer.  

It begins to sound like the PR valuation models, e.g. "it would have cost you $XX to get this coverage in an ad."  But guess what?  You don't control the content of PR like you do with an ad, so frequently it can be much less effective than an ad - so less valuable.

On the other hand, time sure has economic value to the consumer, in terms of opportunity costs - they could easily be doing something else rather than staring at your site.  So "person-seconds" could certainly be viewed as the sum of attention people are willing to give you instead of doing something else that has value to them.  You see this happening in search engine stats now - Yahoo has more visitors than Google, but the aggregate time Google's fewer visitors spend on the site is higher.  In other words, Google has higher "aggregate attention" than Yahoo.

This is being used to say Google users are more "loyal" than Yahoo users, or said another way,  Google users are of higher quality as advertising targets.  Makes some sense to me.

On the other hand, maybe Yahoo users are more responsive than Google users, and on the direct marketing side that would mean ... oh, never mind, I think I'm looping ...

Seems to me you can choose your metrics poison, branding or direct (ROI).  Every time I try to mix the two the math, or direct side, falls apart.  And the reality is you use whatever the client or culture believes in, unless they don't use metrics at all, and I'm not sure there is anybody still in business that sails the ship without navigational charts of some kind.

Jim

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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.
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New RFM:  RF versus RM

Q:  I've used your site a lot and found it to be very informative.

A:  Thanks for the kind words!

Q:  I have a question about the use of RFM analysis for a low margin, eCommerce business.  I read that for a relatively small customer list (<50k) using just the "RF" of the RFM analysis would be preferred since the "M" tends to hide shifts in behavior.

A:  Well, the M tends to smooth shifts regardless of the size of your list.  In addition, if you have a small list, 125 segments is too many to be really useful, so RF at 25 segments in more intuitive.  The real issue with M or Monetary Value is up and coming, accelerating customers.  If you use total spend (M), it will "punish" them with a lower rank.  But the fact is they have more future potential because Recency is low and Frequency is ramping.  Inversely, M tends to reward customers who have spent a lot in the past with a higher rank, though they may actually be declining or defected customers.  Predicting the future is more profitable than reporting on the past, so given a choice, I would drop "M".  This is especially true on the web, where communication costs are low and changes in behavior very rapid.

Q:  My question to you is, since I'm talking about a low margin business, wouldn't "M" actually be more valuable than "F" for the analysis?  For example, if 40% of my customers are driving 70% of my sales and 100% of my profits, that says that 60% of my customer base is losing me money.  I don't want them to be given a higher value rating because they're placing MORE unprofitable orders than someone placing fewer but profitable orders.  You see what I'm saying???

A:  Absolutely, and you have just proven to me you really understand the concept.  It's a tool.  The more you can customize it to your situation, the better.  There is actually some discussion of this situation in the book, the idea of "M" as a "check digit" on profitability rather than using F, if the business is low margin or certain very popular items are "loss leaders".  It's not common, but this model does exist, for sure.

A:  Does that then support my belief that an "RM" analysis would be more appropriate than RFM?

Q:  Well, I'm not sure I understand your situation completely, but if I'm getting it I would be more likely to use Recency-Gross Margin because if I'm hearing you correctly, you sell some (perhaps many) items at a negative profit.  However, some of those customers may go on to buy profitable items, and I would want to consider that.  So I wouldn't use sales, it could be deceiving; I would use cumulative Gross Margin.

In the end, there are 2 components to this model: Recency, which predicts likelihood to buy or visit again (future value), and the "Money" variable, which indicates how profitable the customer is to you now (current value).  You can plot the two variables on a two-dimensional space and literally "map" the current and future value of your customer base, and then use this knowledge to make marketing or service decisions.

You should design the money variable to be the one that makes the most sense for your business, according to your model and available data.  If total page views are your measure of a value of a customer (ad supported site), you use Frequency for current value.  If you are selling products with an evenly distributed price scale and roughly the same profit margin, you can use M.  Recency, or sometimes Latency, are used to measure the future value of the visitor or customer.

Frequency is actually a "tweener" variable, it has implications for both current and future value.  But the largest predictive power of Frequency is really in the distinction between one-time and multi-buyers.  

So, as I suggested here, if you have a small list you might want to score one-time and multi-buyers each by themselves.  This will buy you a lot of the power of the Frequency variable without having to mess with 3 variables and the 125 segments in the traditional RFM model.  The one-time buyers you can simply score on Recency and the rest you use RF, R-GM, or whatever financial metric makes sense for the biz.

If I have failed to explain this sufficiently, please let me know!

Jim

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 to make - ad design, media, 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

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