Posts Tagged ‘Customer State’

LTV, RFM, LifeCycles – the Framework

Friday, June 18th, 2010

The following is from the May 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: I visited your website because I am trying to understand how to develop a customer LifeTime Value model for the company that I work at.  The reason is we are looking at LTV as a way to standardize the ROI measurement of different customer programs.

Not all of these programs are Marketing, some are Service, and some could be considered “Operations”.  But they all touch the customer, so we were thinking changes in customer value might be a common way to measure and compare the success of these programs.

A: Absolutely!  I just answered a question very much like this the other day, it’s great that people are becoming interested in customer value as the cross-enterprise common denominator for understanding success in any customer program!

If I am the CEO, I control dollars I can invest.  How do I decide where budget is best invested if every silo uses different metrics to prove success?  And even worse, different metrics for success within the same silo?

By establishing changes in customer value as the platform for all customer-related programs to be measured against, everyone is on an equal footing and can “fight” fairly for their share of the budget (or testing?) pie.  By using controlled testing, customers can be exposed to different treatments and lift in value can be compared on an apples to apples basis – even if you are comparing the effect of a Marketing Campaign to changes in the Service Center.

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Control Groups in Small Populations

Friday, February 5th, 2010

The following is from the January 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: Thank you for your recent article about Control Groups.  Our organization launched an online distance learning program this past August, and I’ve just completed some student behavior analysis for this past semester.

Using weekly RF-Scores based on Recently and Frequently they’ve logged in to courses within the previous three weeks, I’m able to assess their “Risk Level”– how likely they are to stop using the program.  We had a percentage who discontinued the program, but in retrospect, their login behavior and changes in their login behavior gave strong indication they were having trouble before they completely stopped using it.

A: Fantastic!  I have spoken with numerous online educators about this application of Recency – Frequency modeling, as well online research subscriptions, a similar behavioral model.  All reported great results predicting student / subscriber defection rates.

Q: I’m preparing to propose a program for the upcoming semester where we contact students by email and / or phone when their login behavior gives indication that they’re having trouble.  My hope is that by proactively contacting these students, we can resolve issues or provide assistance before things escalate to the point they defect completely.

A: Absolutely, the yield (% students / revenue retained) on a project like this should be excellent.  Plus, you will end up learning a lot about “why”, which will lead to better executions of the “potential dropout” program the more you test it.

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Acting on Buyer Engagement

Thursday, January 21st, 2010

Over the years I’ve argued that there is a single, easy to track metric for buyer engagement – Recency.  Though you can develop really complex models for purchase likelihood, just knowing “weeks since last purchase” gets you a long way to understanding how to optimize Marketing and Service programs for profit.

Which brings me to the latest Marketing Science article I have reviewed for the Web Analytics Association, Dynamic Customer Management and the Value of One-to-One Marketing, where the researchers find “customized promotions yield large increases in revenue and profits relative to uniform promotion policies”.  And what variable is most effective when customizing promotions?

The researchers took 56 weeks of purchase behavior from an online store, and used the first 50 weeks to construct a predictive model of purchase behavior.   Inputs to the model included Price, presence of Banner Ads, 3 types of promotions, order sizes, number of orders, merchandise category, demographics, and weeks since last purchase (Recency).

The last 6 weeks of data were used to test the predictive power of the model, and the answer to which variable is most predictive of purchase is displayed in the chart below, click to enlarge:

Weeks since last purchase dominated the predictive power of the model, controlling not only the Natural purchase rate (labeled Baseline in chart above, people who received no promotions) but the response to all three different types of promotion.

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Member Retention in Professional Orgs

Wednesday, November 4th, 2009

The following is from the October 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 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: I have recently purchased your book Drilling Down and going through the many interesting concepts.

A: Thanks for that!

Q:  I work for a membership Organization and we would like to conduct some analysis into who we may lose and approach them even before their membership lapses.  But the only problem here is that we carry data only on the purchases made (though many of our members do not purchase our products and stay a member) and web site visits.

A:  Are you *sure* that’s all the data you collect?  I once worked with a professional membership org that thought they only had one data source, but turns out they had 8 – from 8 different areas of the org – that nobody really knew about.

Q:  How do I know if a particular member is going to resign and lapse soon with this limited amount of behavioral data.  Recently it’s been a concern that we are losing members who have been with us for more than 10 years and who are in their mid career profession (aged between 30 to 45) and indicated no specific reason for resignation. 

This has been going on for the last few months and now we would like to strategically target these customers and approach them even before they react negative.  What concepts could help me to do this? Your guidance would be much appreciated.

A:  OK, my answer will be in two sections: if you (hopefully) find you have more data than you think, and if you really don’t have any other data to fall back on.

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Lead Scoring and Nurturing

Friday, July 3rd, 2009

The following Q & A is from the June 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?  Here’s the blog archive; the pre-blog newsletter archives are here.

Q: I received this article (Norms of Reciprocity, measuring value of Social Marketing) via a friend’s Twitter account.  Very interesting.

A:  Glad you enjoyed it!

Q:  It has made open up my ACT! database, and my Outlook databases and add the metric of Growing / Strong / Weakening / Failed to my normal Sales and Business progress metrics.  If I group those categories and correlate to traditional metrics, it’s impressive how they reflect each other.

A:  Yes, most people are surprised.  It’s a very, very simple idea that seems to work across just about any human activity including crime, attendance, and so forth.  

The more Recently someone has done something, the more likely they are to do it again.  Conversely, the longer since an activity last took place, the less likely the person will do it again.  Often called Recency in Psychology and studied quite a bit.

Q:  Now I have to think about how I really use and apply this. : )

A:  Well, if I can guess you are in Sales from your title, typically one of the best applications is in what Strategic Marketing folks might call “allocation of resources”, which probably translates into “lead nurturing” for you.

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Norms of Reciprocity

Friday, June 26th, 2009

Social Marketing Doesn’t Rely on Social Media

Do you believe human beings share certain fundamental traits that define “being human”?

If so, do you believe that human beings tend to behave in certain ways under certain circumstances?

If so, do you then believe since human behavior has these tendencies, it can often be predicted?

If so, then do you think perhaps the study of Psychology and Sociology might provide you some clues to creating successful businesses, campaigns, products, and services?  While your friends and competitors are all iterating their way into oblivion?

On the web, time and time again, we see the same themes repeating.  Yet with each introduction of a new technology, these themes tend to be treated like a new discovery, even though the theme has been well established in the past.

Norms of Reciprocity is a constant human theme.  You may know the expression of these norms as ”Sharing”.  Web old timers will probably recognize this idea as “Give, then Take” from the I-Sales discussion list as early as 1995.  In various forms, this theme goes back to the beginning of human history, all the way back to the handshake and other greeting gestures.  This same theme is embedded in countless Religions all over the world: “Do onto others as you would wish them do onto you”.  At least a couple centuries old, this idea.

Norms of Reciprocity simply means this: When you do something nice for a human being, help them in some way, this human tends to feel Gratitude towards ”the doer” and tends to do something nice back.  Gratitude drives the desire to Reciprocate, because it’s just what humans do, it’s normal, a “norm”.

Norms of Reciprocity.

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Offline Engagement Modeling

Wednesday, November 26th, 2008

The following is from the November 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.

Offline Engagement Modeling

Q:  In our business (airline) – particularly on the loyalty side – we’ve been using both RFM as well as lifetime and current cumulative totals.  For instance in our mileage program, we look at both lifetime miles earned and used as well as current balance. 

Does that seem appropriate?

A:  Well, I guess the question is appropriate for what purpose, what action are you driving to?

For example, if you were to divide metrics into “strategic” and “tactical”, meaning “for management / long-term planning” and “for campaigns / taking short-term action” then you get different answers.

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Marketing Bands: the Numbers

Sunday, June 29th, 2008

(A post by post index of this Marketing Bands Series is here.)

Just wanted to add a quick piece about the results of Optimizing the Bands (see Band Model) - this is the Marketing Productivity Blog after all!  Thanks Moe for the reminder

As we Optimized, there were changes in budget allocation by Band, and as a result there was an increase in Net Customer Value – the goal of the Optimization program in the first place.  For those of you not following the whole story, the budget remained constant, we simply allocated it to the highest and best use through testing.

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Online Marketing Bands

Friday, June 6th, 2008

So, we had some good ”translation” discussions on the HSN Marketing process document, and the idea that there are a couple of ways to look at “Segments”. 

It’s my belief that if you start with Communication Segments (an idea we finally arrived at with the HSN Optimization in 1993) and then move to Visitor or Customer Segments, you will end up with a clearer, more actionable picture in the end. 

If each Band has a single Objective, and you Optimize to this single Objective, you will end up Optimizing the entire system because Visitors / Customers naturally flow down through the Bands as they pass through the LifeCycle.

There’s really no concrete benefit, on either side, to send the same message to all the folks in these different Bands.  That approach is inefficient at the least and irritating to the customer at the most!

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Customer Modeling for Finance Folks

Thursday, May 29th, 2008

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!

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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?