Monthly Archives: May 2008

Customer Modeling for Finance Folks

Jim answers more questions from fellow Drillers

Want to see additional questions & answers from fellow Drillers?

Here’s the blog archive; the pre-blog email newsletter archives are here.

Q:  My boss (VP of Phone Sales) is really looking to try out some new ideas and RFM is one he has latched onto.  He actually has explored this concept for a few years but never acted upon it.  Anyway, he just purchased your book and after finding that he did not have time to read it he gave it to me.  My job was to read and understand at a high level and to lead a discussion with the marketing group to get them excited about the concept.  I am a finance guy by trade so this concept was very interesting.

A:  That’s funny, the people who really “get it” the most are Finance people and IT people, because my approach is very numbers driven.  Stuff either works or it doesn’t – did you make money or not?  Many marketing people seem to dislike the idea of accountability…..hmmm…

Q:  Obviously I either did not do a good enough job explaining RFM, Latency Tripwires, etc. or they just are unwilling to have someone from their team tackle the concept.  My feeling is they felt this is a sales tool.  The question they always wanted answered was “Why did the customer behave the way they did?  We find that out and make a sales call, not engage in ‘marketing air cover’ tactics.”

A:  Not sure what you mean by this…in fact, depending on the value of the customer, a sales call might be exactly what is needed.  If you have a formal “wall” between sales and marketing, usually the issue can be decided by “degree of pain” e.g. how painful will it be to lose the customer?  Generally, a personal call is more effective than Marketing but more costly, so you use those guns sparingly.

If you have a small number of very high value customers who look to be defecting then a sales call is triggered.  If you have lots of medium to low value customers who look to be defecting, then a direct mail campaign is probably what you need, which is probably Marketing.  Match the value of the effort to the value of the customer; this is how you get gigantic ROI’s (or since you are a finance guy, more accurately something like ROME’s – Return On Marketing Expense).  The scoring approach to customer value is about allocating scarce resources to the highest and best use.

I think what Sales is saying is this: if you know a specific thing about a customer, we handle that “one to one” thing; Marketing does the “all customers” messaging.  And this is precisely the point of customer models – they allow Marketing to do the “one to one” thing, as opposed to the “air cover” thing.

Q:  So it has fallen upon me to develop a project plan and come up with some ideas to implement.  If we can not get marketing support we will run with it ourselves.

A:  Good for you!  A good old fashioned skunk works operation, I love that!  And led by a Finance guy on top of that.  Bravo!

Q:  I am now reading the book for a second time and I have a slight problem with how to best implement with our business. I can see how this concept could be used to radically change our sales channel, but I do not think I have that much pull.

A:  Well, let’s take a look at it.  Typically, and particularly since you are in Finance, what you do is look to prove out a high value concept, then share financial success up the chain.  This builds momentum for the approach and gets people really interested in knowing more, which leads to taking concrete action.

So for example, find your very highest value potential defectors using either Recency or Latency.  Then split them into two equal groups – test and control.  Have sales call the people in the test group and find out what is causing the defection behavior, try to save the customer.

Then 90 or 180 days later, look at the number of test and control that stuck with the service.  Subtract the control number from the test number, this is the “net” retained due to your calls. Multiply by value of the contracts, and you have sales due to your program.

Q:  We are a subscription service in which customers pre-pay for the service they expect to use.  Our sales (and I guess marketing to some extent) are responsible for driving customers to use their service throughout the year.  Usually if a customer uses more than they committed to then they raise the commitment the following year.  For us sales leads to higher revenues leads to higher sales, etc, one big circle.  So I guess my question is this: Can RF scores be used for a pre-paid subscription service?

A:  Sure, but perhaps not in the “classic” sense of transactional revenue.  For many service biz, particularly subscription ones, you profile activity other than billing, since the billing tends to be static.  Sounds to me like what you want to profile is **usage** – the more Recently and Frequently a customer has used the service, the more likely they are to continue using it.  I assume you are authenticating subscribers to the service on your web site, so this shouldn’t be a big deal.  Then your scores would rank customers by likelihood to “continue using the service” and their value. 

High value customers with falling or low likelihood (falling RF score) to continue using  the service get a sales call, mid to low value customers with low likelihood to continue get a direct mail piece from marketing.  Dramatic changes in score require the most urgent attention, in terms of allocating resources.

Q:  As an FYI,  we have customers who pay as they go and customers that sign a yearly commitment.  Would it be best to segment the two groups individually for the RF model and Latency tripwires?

A:  Yes.  Annual subscriptions and Pay As You Go are two fundamentally different behaviors and mindsets, so mixing them will confuse the scoring.  You have a Long cycle (annual) and a Short cycle (PAYG) decision being made; both the models and the actions would be different.  For example, PAYG will be a more sensitive model with action required more immediately.  Also, these are probably low value customers so you’re talking about e-mail or direct mail.

And, your measurement cycle would be different.  Taking the test example above, you would check for “net results” on PAYG probably at 60 days; annuals you would wait for renewal date unless the offer affected this date in some way.

Q:  We also have different size customers some spending more than $10K / year and  some $1K, should we segment based upon dollar values as well since the more they committed to the higher their FM scores (you would expect)?

A:  You can make anything really complicated with segmentation if you want to!  Just starting out, my answer is Segment in terms of message yes, but Segment in terms of scoring and triggering action, no.

Keep in mind the Current Value / Potential Value model; don’t confuse the two behavioral vectors and their meaning.  Current Value – what they have paid so far – is about how valuable the customer is to the company and determines what action is taken.  This is the “personal call” versus “send e-mail” part of the equation; the cost component.

The Potential Value (Recency, Latency) is about predicting the likelihood for future business, it’s about “when” to act.  This is the risk of losing the business in the future.

So I would not segment by value in terms of predicting defection, because the likelihood of losing the business is really unrelated to the Current Value of the customer. You can have High Value and Low Value customers with the same defection likelihood, whether “value” is measured as Sales, Page Views, Engagement, whatever.  Value is largely independent of likelihood to defect.  But once defection is predicted, you then segment between High Value and Low Value and take action based on the value of the customer or visitor segment.

The two primary rules of High ROI Customer Marketing are:

1.  Don’t spend until you have to
2.  When you spend, spend at the point of maximum impact

Current Value = What to do
Potential Value = When to do it

That’s why this approach is so much more profitable then dropping Marketing on a “batch and blast” calendar schedule (you called it “marketing air cover”).  Right message, to the right person, at the right time. And it works especially well online because Relevancy (right message, right time) is so important and switching costs are low. 

Q:  What kind of Marketing should we do?  Is there any other segmentation we should try?

A:  Well, that’s a little tough without knowing more about the business, but there’s a good way for you to find out!

With a service, you hopefully know why people stop using it.  To prepare for these campaigns from a Marketing perspective, find defected best customers (high value cancels) and look at why they stopped using it (or interview them if you don’t know, offer a free month or whatever to get them to talk to you).  Create Sales / Marketing – pitches / materials / offers to address their issues. 

Then when you see a client engaging in a defection pattern on usage (drop in RF score, Latency Tripwire), engage the appropriate response (Sales or Marketing) based on the value of the customer.

And sure, the more you segment your customer base, the better it works.  You should start at the bottom, however.  Don’t “out-think” the segmentation; let the data speak to you.  Try something at a very basic level and look for the hands to be raised; this will tell you what works and put you on the right track for more complexity.

For example, let’s say (and I imagine it would be true) that SIC codes play a role in your sales and retention.  Certain types of businesses are simply going to be more likely to realize value from the services.  So you do a campaign (sales, marketing, or both) to *all* customers in a particular defection state and let the SIC data speak.

Let’s say for simplicity that you find if a PAYG  subscriber doesn’t use the service for 10 days that’s a warning flag for defection.  You prepare and drop the retention campaigns to any accounts that “trip” this trigger – right message, at the right time.

What you see when the data comes back is certain SIC codes had a very high response and “activation” and start using your database again, and others do not.  The data has now spoken, told you which SIC’s it is worth spending time / money on.

Then you look at bit deeper, and find that within an SIC code that looks to be a “bad idea” overall, the results are pretty good as long as the offer is made by direct mail in the South.  So you keep this particular segment of the “direct mail” campaign and kill the rest of the marketing activity for that SIC code.

You can look for other segments by value, by region, by services subscribed to, by type of data they look up, whatever.  As you subdivide segments, you will find new pockets of profitability.  You could spend a LifeTime chasing down all the segments – I have never, ever finished this task on any particular engagement.  In fact, clients call me years after they have stopped using my services to tell me they have discovered unique new segments that are extremely profitable.

I’m not saying you should abandon traditional customer communications, the batch and blast that you do.  What I am saying is there is a deeper, more Strategic Objective you can drive through either customization of current programs or by adding an additional layer – maybe cut back on a little of the blasting at the same time?

The basic idea is really no different than optimizing Campaigns – except you’re optimizing Customers by recognizing problems with individuals and offering solutions, instead of always being in their face asking for something – especially when the customer is already demonstrating to you there is a problem of some kind. A little “Is there something we’ve done wrong”? or “Can we help you use our product more efficiently?” or “Would you take a survey?” to specific customers could not hurt.

Sound like a good idea?


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But which Book?

I got e-mail on the review I did of Akin’s new book.

“How is this book different from your book or Kevin’s books?”

Fair question.  Both Akin and Kevin read this blog and are free to add their voices and describe their books here in their own words.  I don’t presume for a second to be a “judge” of other people’s work – at least in this case.

Fundamentally, I think the difference between the books is the writer. 

I’m a Marketing guy, Kevin is an Analyst, Akin (I believe) was / is a Software Engineer.  So even through we talk about a lot of similar things, we approach these topics differently.

The intent of my book is to explain how very simple customer models can be used to drive tremendous increases in profitability, in virtually any business.  The book is about Marketing, it talks about how to create and measure Marketing Programs that maximize customer value while lowering costs.

Kevin’s books focus on multichannel retailing specifically, bringing varied and deep, often complex analytical insights to bear on this business model.  His books are about Analysis, models you can use to bring strategic insight to the business.

Akin’s book defines and explains a way to think about, measure, and execute Marketing in a complex multi-channel communications environment.  His book describes a System or “RoadMap”, a step-by-step way to break down this challenge and understand it.

There are similarities and differences between all these approaches.

The really interesting thing to me is this: across all three books, there isn’t any directly conflicting information or guidance, yet there isn’t a lot of redundancy either.  There are preferences for certain ways to approach Marketing issues, to be sure. 

But like I said, I think that’s simply based on where the writer comes from, what their background and experience is.

While we’re talking about Database Marketing books, any further suggestions on good books?  Please give a brief recap of the book.

Multichannel Marketing by Akin Arikan

Metrics and Methods for On and Offline Success, so goes the subtitle of this book.  This is a fantastic piece of work by Akin, who I have known for quite some time - since the early days of eMetrics.

What’s so good about this book?  Well, this is a tough space to write for, this seam where Marketing and Technology meet.  There’s an audience on either side and you’re writing down the middle.  Akin has done a great job producing a work that should have both sides paying attention and hopefully will provide a platform for better communication with each other.

The framework he chose for the book is a brilliant approach.

First, a dissection of Online, Direct, and Brand Marketing.  What are the metrics and methods that drive each of them?  How is each of these Marketing disciplines handling the multichannel challenge within their own silos, and what are they probably missing because of silos?

This first part of the book I think will be widely appreciated, especially on the Technology side, for laying out in a logical way what the various Marketing factions are up to, why they do what they do, and how they look at measurement.  I find in the web space particularly lots of people have 1999-era notions of what “Measuring Marketing” is.  Akin provides really great background here, lots of detail on where the various measurement approaches come from and how they are used. 

This Online, Direct, and Brand Marketing structure becomes the backbone of the book, it continues throughout the entire work and provides the reference point, the base for understanding.  Very smart idea, it brings everybody to the party.

In Part 2, Akin looks at why the various factions should be sharing their metrics and methods, how fusing the various multichannel measurement approaches developed by Online, Direct, and Brand Marketers results in a whole better than the sum of parts.  This section really digs into which metrics and measurement approaches are best for different situations and levels of available data.  I really like this “cascading” approach to data.  Got a little data?  Look at measurement this way.  Got more data?  Think about measurement this way.  Got a ton of data?  Here’s the best way to look at measurement.

This section really gets into the whole control group issue, and why, if you can, you should Measure Customers, not Campaigns, to determine your success.  Response is one thing, lift can be quite another.  Once this idea becomes fully embraced by the web analytics community, it’s going to be very disruptive.  But using controls is standard procedure in the BI world, so trust me, it’s coming to web analytics.

In Part 3, Akin flows it all together, providing sequential examples using the Attract & Acquire, Engage & Covert, Grow LifeTime Value metaphor.  What does truly integrated (no silos) multichannel Marketing look like in practice?  What do you do and how do you measure the results?  Now we’re cutting waste and improving Marketing Productivity throughout the entire Customer LifeCycle.

This section is notable for the use of case studies and detailed examples of what it looks like when you are actually maximizing value in an integrated way across all the touchpoints.  What Marketing looks like as it morphs from the ancient offline calendar-based Campaign model into the “right person, at the right time, with the right message”, Measure Customers not Campaigns approach.

This book is a significant addition to the knowledge base, particularly in the area of integrating Brand Measurement into the overall customer management picture.  He also provides a fabulous aggregation of Brand Measurement research sources I found very useful. 

Notable brand new ideas that I’m not aware of seeing anywhere else are the Maturity of Multi-channel Profiles idea and the Cross-Channel Funnel Report.  There are numerous other concepts that may not be brand new to the reader but are expressed in new or unique ways that are better than what has come before.

Fantastic job, really.  I’d call the book a must read, the kind of book I absolutely would not hesitate to hand to Senior Marketing folks and say, “Read this, it’s about where we are going”.

Probably wouldn’t use those exact words, but you get the idea…

As for the relevance of the picture below, see page 144 in Akin’s book!

Reduce Friction, Maintain Momentum