Marketing Productivity Blog

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?

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.

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!

Those of you interested in where web analytics is headed might check out the series of posts Jacques Warren in doing from TDWI (The Data Warehousing Institute) conference.  He’s in for a pound - an exhausting 6 days of high order brain-stuffing, much of it very technical in nature.

I believe most web analysts, if they didn’t come from DW / BI in the first place, would benefit tremendously from the kind of exposure Jacques is receiving at TDWI.  There is a larger scope sitting out there that WA fits into, and the DW / BI world has been around a lot longer.  Those folks have all the arrows in their backs already, and there is a lot to learn from them.

For example, the extent you believe what you see in web analytics reports actually happened, or whether you understand it is often an approximation of what happened, more like a model.  At least from a Marketing / Behavior standpoint.  A dose of reality like Jacques received can put this in perspective.

The very next question on the table is how do we get WA data into BI systems?  The answer, I believe, is Events.  There is really no point in stuffing page views and visits into a data warehouse; not enough value and won’t mean much to the broader Optimization picture. 

What the WA folks will have to do is decide what constitutes a significant Event (which could be a series of smaller actions) and then figure out how to mark that Event with a customer ID and get it into the warehouse. 

Some web analytics applications can already track Events (example), so that’s not the issue.  The question, as always, is what are you going to do with the Event?  Otherwise, it’s not worth tracking.  What’s needed is a Strategy for using high value Events first.

Otherwise, we’ll just end up with that many more junk reports.

At the same time, I think the more exciting prospect than what BI brings to WA is what web analysts can bring to BI, which continues to suffer from a focus on the technology instead of what they can do for the business.  While many WA folks understand the need to annotate and evangelize their work, many BI folks don’t see “being proactive” as part of their role.

I have to tell you, if you think WA and Optimizing web sites is exciting, wait until you get your hands on the entire business and start optimizing it.  Your first A/B test with a call center script, for example.  Fulfillment testing.  Packaging.  The list is endless.

That experience, my friends, is pure adrenaline.

I know some of you out there are already wearing both the WA and BI hats.  Got any killer Business Optimization stories (that you can tell?)

IN-line Marketing, that is.

Sitting here at the junction of Technology and Marketing as I do is frankly a weird place to be.  I often feel it’s a lonely place because it seems like neither side really understands what is at the center, how the Corpus Callosum works, if you know what I mean.  

And how to optimize this junction.

I have been writing about these topics in discussion groups since 1999 and on my web site since 2000, based on the (admittedly rare) experience of Optimizing an Interactive Television Network over a 10 year span.  Here’s what we learned, in a nutshell: Interactive means Behavior; without Behavior, there is no Interaction, by definition.

So it follows that the single most important thing you can do as a Marketer is understand Behavior - or often more importantly, the lack of Behavior.  Not demographics, not impressions, not any of the traditional Marketing stuff. 

Behavior.  It’s the key to everything Interactive.

Web analytics folks for the most part get this idea now, in terms of the straight-up applications of it: It’s about Reducing Friction.  How Usability affects the success of Interactive Marketing, for example.  Optimizing Landing pages,  Etc.  The importance of Customer Experience in reducing downstream Friction, which magnifies the natural ”Pull” of Interactive.

The challenge has been the Marketing side has stuck to many of the offline “Push” traditions, which don’t take into account the two-way nature of an Interactive Relationship.  The idea that people who are Interacting are trying to get something done.  The whole “Lean Forward versus Lean Back” argument, as we first talked about it back in the “old days”.

Relevance, which is forecast by Behavior.

Could it be the times are ‘a changing?  Could it be that the Marketers are coming around to the idea that the most important concept in Interactive Marketing is an “IN-line Experience” - an experience that facilitates or helps the visitor Accomplish Goals?  Like Search Marketing does, for example?

Check out these recent articles -  in an Advertising trade pub - to hear Marketers say this in their own words:

Form + Function (AdWeek)

Application Economics (AdWeek)

Want more?  Some related material:

What’s Next in Marketing + Advertising (slide show, a fast read)

The Great Leap Forward (blog)

Value Is the New Currency (ClickZ)

What do you think? 

Are we finally ready to move forward from the offline Push Marketing model into specialized approaches for Interactive?

As opposed to eMetrics 08 Toronto, don’t you know…

A really big shew, for sure. 

With the tons of WAA EdCom stuff going on, and the tremendous opportunities to just run into people in the halls and have hour long spontaneous “shootouts” (thanks for your help with “The Cluelessness of Crowds), it can be difficult to get to all the sessions I want to see.  

Still, I always try to catch sessions outside of the mainstream that look interesting.  Often nobody comments on these overlooked sessions, so I like to bring them to the surface.

The presentation by Egan van Doorn of the Dutch Automobile Association (ANWB) called Connecting Web Analytics with Decades of Marketing Metrics was such a session. 

Here, the beauty was in the simplicity and purity of the approach.  Classic Database Marketing - the targeting, the pacing.  No breathless monthly or weekly blasting of the same message to every customer.  No, to each customer the right message at the right time.

ANWB works with the understanding the calendar doesn’t matter nearly as much as the customer’s individual behavior.  When the customer is ready, they say so.  It’s all about Pull - gently bringing them to you, not beating them over the head.  Context, relevance; what they want, when they want it, while they are interested in it.  Like Search, right?

Web analytics folks often view multi-channel ideas as too complicated, and they’re really not - if you are using the right methodology and if you have some discipline.  Apparently, ANWB has both.

From a Marketing perspective, ANWB pays close attention primarily to high value online events.  Forget page views, visits, etc.  What they want to know is this: what action was taken for which we have a related product?  They store these events in the customer record, and then play out the online / offline Marketing stream accordingly.  If they can reach them online, that’s obviously cheaper.  If they decide to go offline (in the mail) they have their timing issues down and they make it happen. 

Very efficient, highly productive.  Huge increases in response rates, even offline when using online behavior to trigger the Marketing event.  Classic Database Marketing.  And there’s a reason they are so good at this - they’ve been doing the same thing offline forever.

If you can make money doing this offline, you can make an absolute pile of money doing it online because the Marketing is so much cheaper.  The problem is, most online folks don’t have access to that Database Marketing background, the understanding of how to optimize remote relationships.  So instead of playing it as Database Marketing, they play it like Media (Push) Marketing.  And they get unremarkable results.

How simple is it to do multi-channel right? 

Here’s an example, courtesy of ANWB.  Customer comes to the web site.  Customer searches for and finds info for “bike and hike” trails.  When this happens, customer is shown banners offering a “Bike and Hike Trails of the Netherlands” book during the rest of the visit.  Customer maybe buys the book.

Or not.  If they don’t, and waiting a reasonable amount of time for the sale to occur online, ANWB goes in the mail with an offer on the book, and then later on, a modified offer in the mail if there is no response.  Customers buy scads of these books.  Enormous ROI, both online and offline. 

Then repeat this scenario with every product line - what is the trigger event, what is the timing?  Man, that’s a beautiful business they’ve got going there.  Just printing money.

They do have one advantage - as a membership org, each customer has a unique ID, offline and online.  This was raised as an “unfair advantage” in terms of their success.  Disagree. 

Megan Burns of Forrester said as much in the 2nd half of the presentation.  The reason people don’t usually factorize to do this kind of stuff is they can’t project the ROI, they don’t know what they would do with a unified view of the customer to generate incremental profit.  So they can’t justify spending the money to make it happen.

This is really the same Push versus Pull issue I mentioned before - as long as you batch and blast, as long as you keep using the offline Push model, there’s no point in understanding any of this multi-channel stuff.  When you get ready to accept that the behavior of the customer is your key to relevance, and test through a couple of scenarios (as all offline DB Marketers have done), the ROI of the offline / online join becomes self-evident and justifies the spend to set up for it.

Wait a minute, you say - there’s no reason anyone would want to log into our web site.  Oh.  But now you are into Marketing Strategy.  Not the same issue.

Why won’t they log in?  Let’s say you don’t think you can get people to “log in” so you can create a database match.  Here’s the real question - have you conceived an experience for your web site that is worth a log in?  If the experience is worth it, people will log in, and you will have a database match.

That’s Marketing, my friends.  It’s not just about the “Push” MarCom stuff.  It’s the Strategy, the whole picture that creates the Pull that is so incredibly powerful. 

This is what makes interactive different.

Let’s assume you think I am wrong, that what I’m saying couldn’t possibly be true.  After all, how could so many people get interactive wrong?  Wisdom of Crowds, right?  After all, look at all the folks who got it so right in 2000 (not).  THAT was a Crowd.  This Jim Novo, he’s just pushing the ideas in his book.

OK, fair enough.  Here’s another voice that has been added to mine.  More on Akin’s book in the future - I’m only 1/2 through!

On the heels of the Desirability Series we have two related articles:

1.  This first piece is by Lester Wunderman, one of the “fathers” of Direct Marketing (so many fathers, so little time).  To me, it’s significant Mr. Wunderman would feel the need to come out and provide us with his definition of Engagement, at least as it relates to Advertising.  If he didn’t see Engagement as an important idea thrashing around looking for clarity, why bother?

His statements are necessarily broad I think, because he’s coming at it from the top level, the Strategic Layer, and in doing so has to cover a very wide range of industries and media.  Nonetheless, if you take the time to really read what he’s saying and think about it, he’s setting up a new kind of approach to Advertising similar to what I defined here.

Here’s the article link:
Engagement — A New Information-Based Form of Advertising

2.  In contrast, I’m not sure whether Roy Young is the “father” of anything but he is the President of MarketingProfs.com and coauthor of Marketing Champions: Practical Strategies for Improving Marketing’s Power, Influence and Business Impact - something I talk about a lot.

His topic?  Silo Busting, which is so critical to really driving a customer-centric Strategy.  Roy provides 5 solid tips on how to get started if you want to Take Action on Desirability.

Here’s the article link:
Five Tactics for Busting Silos in Your Company

Now that we know how to Measure Desirability, we need to act on what we learn.

Many web Analysts and Marketers are pretty hip to Optimizing for Actions.  What they have a hard time thinking about is Optimizing Against in-Action.  It’s the mirror image of what people usually pay attention to.  If you’re having a hard time wrapping your head around this idea, try this analogy:

In the early days of web site funnel analysis, most people focused on the Active traffic, that is, the traffic making it to the next step, ”step conversion”.  The focus was always on optimizing “for Action”, on getting people who made it to Step 2 to Step 3, etc.

One problem with this mindset, of course, is that the percentage of traffic making it through the funnel steps is often quite small.  So by optimizing “for Action” you are dealing with a small, probably biased group and the potential impact versus total traffic is going to be relatively small.

At some point, people began to realize the tremendous value of the mirror-image question - this traffic that is falling out of the funnel, where did it go?  Because if you could optimize against in-Action you would hit a much larger cross-section of the population and have a larger total impact.

In other words, the most important question to ask is not “Why is this small group of visitors converting”, it’s “Why is this huge group of visitors not converting?”  Further, if you knew what non-converting traffic did just before the in-Action, you could infer from this “Previous Action” why they were not converting.

This thought process is what convinced the web analytics vendors to start creating the “leak diagram” version of the Funnel, where you can see exit paths by funnel step.  This functionality allows you to target efforts not based on what people were doing, but what they were not doing, and infer why they were not doing it by looking at the Previous Action (funnel Exit path).

I challenge anyone to argue it’s easier or more effective to optimize a funnel by Action rather than by in-Action with Previous Action.  Previous Action shouts “why”.  Knowing that 80% of the Funnel Abandonment at Step 2 goes to the “Shipping Policies” page is like all those visitors screaming at you “I need more info on Shipping!” 

It just makes too much sense.

Likewise, when we see dis-Engagement we should read un-Desirability.  And we should look to the Previous Action for clues on what is un-Desirable.  Previous Action Clues such as:

a.  They bought the same product or products
b.  Products bought were from the same vendor or category
c.  Responded to same campaign / traffic from same source
d.  They talked to the same salesperson or service agent
e.  They were formally Engaged with the same kind of content

and on and on.  Find the dis-Engaging visitors or customers, then cross-tab by Previous Action.   Just like a Funnel Analysis with Exit Paths.  Attack the high volume ones first.  If you need help starting, perhaps you should ask Customer Service for a whole list of un-Desirability opportunities.

Here’s what needs to be understood.  Interactivity demands that these issues are somebody’s problem.  For as great as Interactivity is as attracting customers, it tends to be quite weak at holding them.  There is a tremendous ramp in Engagement early on in the cycle, which drops off just as fast on the other side for most participants except the very hard core.  Why?  Interactivity drives very high expectations on the visitor / customer side, and it doesn’t take much to screw up that relationship.

Interactivity is relentless like that.

So somebody has to do this job: finding the root cause of dis-Engagement and fixing it.  Why?  Because even more than with the typical web site optimization, very small changes can produce enormous increases in Profits.  Why?  Because you are dealing with much larger populations - those who did not Act, as opposed to those that tool Action of some kind.

What does this all mean on the ground level?

For Web Analysts: There is an exciting and challenging world waiting for you in this dis-Engagement data.  You may or may not be able to access this data through your web analytics tool.  If you can’t, find out where it is - in the customer service systems, help desk systems, commerce systems - and start exploring.  If you have a BI unit, find somebody in BI who wants to work on these ideas with you.

For any given free cycle, you should resist the natural tendency to “Go Deep” in your own world, spending your precious time probing the inaccurate.  Instead, “Go Broad”, and try to start connecting some of these un-Desirability ideas.  This can be hard work, but I know you’ll enjoy it, and the payoffs in terms of profitability are huge.

For Strategic Marketers:  Somebody has to do this job.  Will it be you or the “Chief Customer Officer?  Given Marketing causes a lot of these un-Desirability problems in the first place, it seems to me the Root Cause folks should be in charge of this effort, rather than those catching the flack.

Now I know what you’re thinking - this Desirability thing ain’t my job.  I Push.  I generate Sales, Awareness, etc.  “Desirability” is not on the List.  Poor service?  Not on the list.  Faulty products? 

Please, not my area.

OK.  Let me ask you something.  When you lose a customer, what needs to happen on your side?  You have to replace that customer just to stay even, right?   So, to grow sales - which I think you are in charge of - you have to not only replace the lost customer but also add another customer.  That means, for a fixed budget, that you’re not going to be able to grow sales as fast as you could if you were better at keeping customers, if you were attacking un-Desirability.

Do you think your sales goals for this year are “cake”?  That you have “easy” targets?  That you are absolutely confident you’re going to hit the numbers?  If you answered Yes, then fine, you don’t need to care about Desirability.  Just churn ‘em and burn ‘em, my friend.  I guess you’re not the kind of person who would like to absolutely smash your sales targets to bits.

For Both Analysts and Strategic Marketers:  If you are going to talk the customer experience talk, please start walking the walk.

A couple of suggestions:

1.  Yes, this un-Desirability work often requires (demands?) cross-functional teams, because un-Desirability problems often start in one silo (Sales, Marketing, Product) and end in another (Service).  Is that an impossible barrier to overcome?  Start looking for partners.  Better yet, start formalizing the idea of a Business SWAT team.  More real world examples here, here, and here.

 2.  Wikipedia defines Experience as “observation of some thing or some event gained through involvement in or exposure to that thing or event”.  Event.  Behavior.  Stop with the demographic segmentation already, it’s just obscuring everything that’s important to customer experience.  Save the demographics for the Push end of the funnel where they mean something.  Once you get to Action and move over into Pull mode, you’re now into Behavior. 

Desirability is about Behavior, not Age and Income.

So that’s the whole model, front-end to back-end.  This model incorporates many of the ideas floating around out there right now - Customer Centricity and Experience, Engagement, Reputation Management - into a single Data-Driven, Optimization-friendly, Customer-Aware, Accountable Marketing process.

In short, Measure Customers, not Campaigns.  That’s the secret to unlocking the power of Interactivity and making it work for you.  Otherwise, Interactivity can work against you.

Your Comments and Questions are appreciated.  Your challenges as well - why can’t you do this?  What will it take to change that?

Example: At HSN, I started by forming the Business Swat Team at the Director Level - IT, TeleCom, Customer Service, Marketing (me), Merchandising / Presentation, Fulfillment, Finance, and (of course) BI

Our first mission was this one.

Why do we want to do a 2-Step acquisition?  Because the conversion rate is going to be higher per dollar of media spend.  It’s the equivalent in Online of the difference between buying single words and buying phrases in PPC.  The former generates a lot of traffic, but the latter gets higher conversion and is much more Productive.

In other words, a 2-step customer comes into the Relationship with higher Potential Value and higher Momentum.  And that’s important, because it means you spend less in Marketing over the longer term as the customer will, on average, keep interacting for a longer time.

If you’re not sure what that all means, perhaps it will become clearer as we dissect Desirability (Satisfaction), the last component of the AIDAS model.  Here’s the core issue:

Offline, we know people come back to Brands or Businesses “by themselves” because they like the Product or Experience.  We also do Advertising to these same people, as well as those less likely to come back or not likely to come back at all.

So how do we know what percent of the resulting activity is due to people just coming back because they enjoy the business, and how much is due to the Advertising?  How do you calculate ROI? 

A Very difficult task.  Even if you could identify the “likelies”, you generally can’t exclude them from offline media.  So this whole issue of “likelihood to come back” offline has been completely ignored, because there’s no way to act on it.

Online, and in much of Offline Database Marketing, we don’t have this problem.  It’s a pretty straightforward and common analytical task.

We can measure quite accurately how much of “coming back” is from Advertising and how much is from “Experience” or the more global concept of what Forrester calls Desirability - the fact the customer simply enjoys interacting with the business, and wants to interact again.   And, online we can target specific individuals with specific messages based on their likelihood to come back.

But, most people in Online marketing are not acting on this intelligence or targeting capability; they’re ignoring the idea largely because it didn’t matter offline.  Are these the same people that keep saying “Interactivity is Different”? 

I hope not, because they’re certainly not acting like it is!

Why should this concept of “likelihood to come back” really matter to Online Marketers?  Because it is much, much more powerful than you think it is.  Orders of magnitude larger.  However, once you screw up, the downside is also quite powerful - “not likely to come back”.  This brings up two important and powerful areas to consider:

1.  Over-spending to get people to come back who would have come back anyway
2.  Under-spending to get people to come back who are less likely or unlikely to come back

In most cases, you will find the budget mis-allocated in this way.  To optimize, you will want to reallocate budget from #1 into #2.

Online, there is a powerful ”Pull” that brings people back, over and over - without needing to provide incentives or begging them.  This Pull is the very fabric of Interactivity. 

What’s more, you can measure this Pull quite precisely and take action where appropriate.  Here is how:

1.  If you don’t try anything else new this year, do a controlled test with your e-mail program.  This is the simplest, most direct way to prove to people you’re not (I’m not?) crazy about how powerful this Pull idea is.  Please do not use whatever demo / product segmentation you normally use with e-mail for this test.  If you want to analyze this Pull behavior, you have to segment using behavior.  

Most of the big e-mail vendors can do this for you, tell them you want to do a “Recency Test with 30-day segments and a Control Group for each segment”.  The most universal “last interaction” (the base for Recency) for many folks will be “last open”.  You could also use “last click-through”, but of course you will have smaller active base.  If you’re in commerce, use “last purchase date” if you can, since that is what really matters.   Just send whatever your default creative is so you keep a baseline with prior campaigns.  You will probably end up with results that look like this.

If you want to know more about these ideas or set the test up yourself, there are detailed explanations  in this series and this series.  Questions?  Just comment below.

2.  Perhaps more importantly, you can measure the decline of Pull, the absence of Pull, and take action on that as well.  Pull is your measurement of Desirability.  Where you find lack of Pull, you will find un-Desirable experiences you can take action on. 

Now, a lot of people talk about being “customer-centric” and customer experience and all that.  Makes perfect sense, and has made sense since probably the first barter transactions, right? 

What you don’t hear people talk about is how to measure the profitability of a customer experience or Desirability effort.  How to identify Desirability problems - even if the customer doesn’t say a word about them.  How to isolate and fix these Desirability problems.  And how to measure the increased profitability directly attributable to fixing these Desirability problems.  Wouldn’t you like to identify these un-Desirability problems before they go Social on you?  Why be reactive when you can be proactive?

That would be a pretty neat trick, don’t you think? 

Here’s how you do it.

Once you have proven how powerful this Pull (come back by themselves) concept is with your own data - and it is especially powerful among your best, most Engaged customers (is that a surprise to you?), start asking why, for other groups, Pull is declining or absent.  What is the commonality among visitors or customers with the lowest “”likelihood to come back”, where Pull is declining or absent?

Here’s what you will find:

a.  They bought the same product or products
b.  Products bought were from the same vendor or category
c.  Responded to same campaign / traffic from same source
d.  They talked to the same salesperson or service agent
e.  They were formally Engaged with the same kind of content

and on and on.  Behavioral segments. 

Visitors or customers who “did the same thing”.

Basically, you will find out where Desirability is lacking, literally, what you are doing every day in Sales, Marketing / Product, Service, or Operations to drive away customers and prospects.

And then you can decide what you are going to do about it.  That’s a whole other challenge I will address in the next post.

Your feedback and questions are appreciated.

Before we move into the Tactical stuff, I would like you to think about something, and if you could, give it more than a passing thought.  Here goes:

If you stopped all Advertising to customers today, what would happen to customer activity in the next 90 days?

In some businesses, Sales / Visits from customers would slow down a lot.  These are typically offline, low-Engagement businesses, the kinds of businesses that require a ton of advertising to drive Sales.  People don’t really care much about the products one way or the other - they’re not Engaged with the business.  Many packaged goods products are in this camp, for example.  They need Advertising.

In other businesses, and in particular many web businesses, Sales / Visits from customers would slow only a little.  This is because the customers are Engaged with the product, the site, the community, and so forth.  They come back anyway - regardless of whether you Advertise to them or not.

This is Engagement, folks, from a Marketing perspective.  The emotional bond, the Desirability, the Delight.

This is why Interactivity is different, and why Interactive Marketing should be treated differently.  The customer has always-on, 24 hour a day access to the business, and they are Delighted by that access, stimulated by that access, enjoy that Interactivity.  Many customers will come back even if you don’t Advertise to them.

That is, if you have Engaged them.  Engagement is more powerful than Advertising, in many ways Engagement replaces Advertising, Engagement IS Advertising.

Is that so hard to understand in a Web 2.0 world?

Personally, when measuring web site activity, I don’t think it’s really appropriate to create a box of Actions called “Engagement” and declare ”if a visitor does this, they are Engaged”.  What I care about is they came back at all.  People have all kinds of reasons to visit an Engaging web site / business; they are in different modes and do different kinds of things.  As far as I’m concerned, they can take whatever action they wanted to take, as long as they came back.  To me, that’s Engagement.

And the idea of them deciding not to come back, well, that’s dis-Engagement.  As a Marketer in an Interactive business, that’s what you have to pay the most attention to.   Follow the dis-Engagement cycle, and for highest ROMI, use the right messages at the right times.

Because when folks are Engaged, well, they come back all by themselves, and I don’t need to do any Advertising to them.  That’s not to say I shouldn’t do any Marketing with them.  For those Engaged folks, what I am doing on the site as far as Products, Usability, Features, Service, unique / special Messaging, etc. - that’s what keeps people Engaged, that’s what I should focus Marketing skills on.  Spend some time in Customer Service, for example, and figure out what Marketing can do to help.

I only need to put the Advertising hat on when they start to dis-Engage, and then it’s all about knowing why.  Which segments are dis-Engaging?  Do they have a Service problem in common?  A Product problem in common?  A Content problem in common? 

What’s the Root Cause?

As an Interactive Marketer, I now have to try to fix that problem - even if it’s not in my silo.  Why?  Because it’s causing people not to come back, and that’s a Marketing problem, because it impacts Sales / Visits, and I’m responsible for generating Sales / Visits.

Now, I realize many web analytics folks want to specifically define Engagement for their sites and that is fine.  Define it any way you want, whatever way makes the most sense for the site.

But then, pay most attention not to the achievement of Engagement, but to dis-Engagement - when the previously Engaged, using whatever definition you like, no longer qualify as Engaged.  That’s the secret sauce of Interactive Marketing, that’s what makes Interactivity different from all other types of customer relationships.

Tip: dis-Engagement is a process.  It’s a movie, not a snapshot.  The question is not “What percent were Engaged last month?”  The question is “Of those Engaged in month X, what percent are still Engaged?”  Reason this difference is important: Newly Engaged customers / visitors will mask dis-Engagement by current customers / visitors in a % Engaged snapshot view

You can answer the question I first asked above about shutting off Advertising to customers.  Without creating a lot of disruption.

Test it like this.  I’m sure you will be surprised by what you find.

And then you can start spending more of your time and budget on fixing dis-Engagement rather than trying to create Engagement that in many cases is already there. 

Unless, of course, your site / product / service delivers a lousy customer experience, fails the Desirability test.  Then you’re going to need all the Advertising you can get your hands on.  Just keep pounding ‘em with e-mail, that should fix the problem, right?

Does that approach really make any sense to you?