Tag Archives: Customer Models

Optimizing for Customer Value

The following is from the February 2011 Drilling Down Newsletter.  Got a question about Customer Measurement, Management, Valuation, Retention, Loyalty, Defection?  Just ask your question.  Also, feel free to leave a comment and I’ll reply.

Want to see the answers to previous questions?  Here’s the blog archive; the pre-blog newsletter archives are here.

Q: Thank you for creating this useful website!

A: You’re welcome!

Q: When figuring out retention rate for an annual or a 8 months life time cycle period, how do I pick the starting period?  Do I look at their first orders on a date?  Or I pick a time frame such as one month?

A: It depends on:

1. What kind of “retention” you are talking about, the definition, which is probably impacted by the audience for the data

2.  What you will do with the retention data, what kind of decisions will be made and actions be taken because of the data

You should always ask these questions above  when someone requests “retention data” – or any other kind of analysis, for that matter!  For example, there probably is a huge difference in what you would provide to the Board of Directors for an annual benchmark and what you would provide to Marketing people for executing campaigns.

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When Does a Visitor Need a Coupon?

The following is from the November 2010 Drilling Down Newsletter.  Got a question about Customer Measurement, Management, Valuation, Retention, Loyalty, Defection?  Just ask your question.  Also, feel free to leave a comment and I’ll reply.

Want to see the answers to previous questions?  Here’s the blog archive; the pre-blog newsletter archives are here.

Q: First off, I very much appreciate you sharing all this wonderful content on your blog and conferences such as eMetrics.

A: Thanks for that!

Q: My question is a simple one, but I think the answer may be hard: When does a visitor “need” a coupon?  *Need* defined as: visitor would not have placed an order unless presented with the coupon.

A: Hmmm…methinks we’re going to have to define a few concepts and be clear on the goals to make sure we are nailing this down… visitor versus customer, sales versus profit, etc.  In other words, answer is not hard, but could be complex without defining context.

Q: It’s still a mystery to me why so many retailers seem more than willing to hand over all their margins to Groupon or give coupons to basically all visitors.  I am curious whether you would approach this question using  observational data (eg web analytics) or experiments (eg AB testing), or both.

A: Right – is a mystery to me too!

There are certain situations where this approach might be appropriate, but the problem with much web “marketing” (which often is really just advertising without much thought about marketing) is often there is success in a narrow or special situation.  Then the pundits jump on and say “if you’re not doing this you are stupid”, regardless of the business situation and / or without recognizing the special circumstances that are driving success.  This is all the real Marketing stuff people leave out; understanding why it works, under what circumstances, for which segments, involving which products.

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“X Month” Value

The basic concept of LifeTime Value (LTV) was ably outlined by Seth Godin in a great post here.  If you know the average net value of a customer is $2500 over their “Life”, why would you not spend  $50 (or $200, really) to acquire each one?  As long as you stuck to the model, your company would be insanely profitable over time.

Their are 2 primary challenges to implementing this idea.

1.  “Over time” is a concept many management folks have a hard time embracing; what matters are the profits this year, or this quarter, or this month.  Unless the whole company embraces an “over time” measurement approach it is difficult for Marketers and Analysts to drive towards programs and practices supporting the LTV outcome.

2.  The $2500 is an average figure.  Most customers are worth less; 10% or 20% are worth much more.

Most people I talk to embrace the general idea of LTV models intuitively.  It’s really a cash flow concept, isn’t it?

So Financial people get it right away, and if Marketers could align with it, there would be no conflicts and the Marketing budget becomes virtually unlimited.

In fact, many folks in the PPC world follow just this model – they have unlimited budget as long as each conversion costs no more than “X”.  Because the company knows if it spends no more than X on a conversion, it always makes money.   Marketers and Analysts involved with these “Cost < X” PPC programs love them, because Management loves them. 

And Management loves them, why?  Because the CFO loves these programs  Why?  Because they are based on Cash Flow analysis, which CFO’s understand very, very well.

So then, what will it take to get more acquisition budgets like these Cost < X  PPC programs?  We have to address the two challenges above:

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Visitor Retention Mapping

The following is from the January 2009 Drilling Down Newsletter.  Got a question about Customer Measurement, Management, Valuation, Retention, Loyalty, Defection?  Just ask your question.  Also, feel free to leave a comment. 

Want to see the answers to previous questions?  The pre-blog newsletter archives are here.

Q: The research folks in my company are trying to convince me that measuring sessions and Page Views per Session is more effective than using Recency and Sessions, as you advocate in your book, for a retention metric.

A: For a content site, the Page Views / Session measure can be used as a measure of visitor quality and appropriate marketing to the right audience – a customer acquisition idea – not retention.  And it really needs to be broken out by Source – the average has little actionable meaning.  You want to know the Visitor Sources, and then look at this metric by Source.  This is still Frequency though  – what about visitors who don’t come back?

Q: I am having some difficulty in making a decision regarding this. They want to give me a matrix with Page Views per Session on the Y axis and Total Sessions on the X axis as the “customer retention map”.

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Customer Modeling for Finance Folks

The following is from the May 2008 Drilling Down Newsletter.  Got a question about Customer Measurement, Management, Valuation, Retention, Loyalty, Defection?  Just ask your question.  Also, feel free to leave a comment. 

Want to see the answers to previous questions?  The pre-blog newsletter archives are here.

Customer Modeling for Finance Folks

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.

Good luck with the skunk works project and let me know if you have more questions!

===============

Any comments or questions on the above? 

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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