Archive for the ‘Measuring Engagement’ Category

Optimizing End of LifeCycle (Bands 6 – 8)

Wednesday, June 25th, 2008

In the Band 5 Optimization for HSN, we looked for high ROMI special situations in the database.  This is really classic database marketing stuff, you’re looking for segments, and you’re looking for ways to Optimize those segments.  You could spend the rest of a career doing this kind of thing; there are always new segments like FIPS being revealed if you have an active analytical staff.

There were other programs in Band 5 based primarily on product-related transition phases in the LifeCycle; I won’t go into these here.  If you are interested in these ideas, I wrote one detailed example, which combines Customer Experience Management / Band 3 – Customer Comment Analysis / Math / Product / Marketing right here.

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Peak Engagement (Band 5)

Sunday, June 22nd, 2008

Optimizing Individual Communications

Where the Band 4 Optimization optimizes general communications like newsletters, the Band 5 Optimization is all about hyper-targeted communications to individuals.  We’re talking mostly about special circumstance stuff here, more exotic ideas that may actually fall outside what you might traditionally think of as “Marketing”. 

If Band 4 is the “Air Cover“, Band 5 is Special Ops (see Band Model).

In Band 5, you basically have algorithms of various kinds that are ”sniffing” the databases looking for special situations that have exceedingly high ROMI.  Often, these ideas deal in one way or another with high value customers that appear to be dis-Engaging; many of these scenarios related to Marketing, Service, or Product in one way or another.

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Optimizing General Communication (Band 4)

Wednesday, June 18th, 2008

In the Band 3 Optimization, we’re concerned about the Interface, the moment of truth when people who have Awareness, Interest, and Desire generated in Bands 1 and 2 are ready to take Action.  If we are successful at Optimizing the Interface, people take Action and become Customers, entering Band 4 of the model.

At HSN, we looked at customer communication this way: as soon as a customer makes their first purchase, they begin the defection (dis-Engagement) process.  I’ve referred to this idea before as “customers naturally fall down through the bands“.  The approach assumes every customer interaction we have after the first purchase directly affects how long this new customer will remain a customer.

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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?

Acting on Desirability

Tuesday, April 29th, 2008

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 herehere, 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.

Measuring Desirability

Saturday, April 26th, 2008

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.

Engagement Defined (for Marketing)

Sunday, April 20th, 2008

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?

Desirability, Satisfaction

Thursday, April 17th, 2008

I didn’t talk about Satisfaction, the 5th component of the AIDAS model, in the last post on Desirability.  That’s because it’s the most difficult for folks to get a grip on and I wanted to treat it separately.   There’s a reason for this difficulty: Most Marketers (and many analysts) think they’re “done” when they get through the Action part of AIDAS. 

They achieved Engagement, don’t you know.

So even though Interactivity is different, these folks are still using the old offline models to run their Marketing programs.  “Satisfaction” isn’t their problem, Action is.  Satisfaction is somebody else’s problem, a longer-term issue.  Marketers have no control over it.

Now, I’m pretty sure most folks reading this know Marketing plays a big role in Satisfaction and have seen live examples of it.  Everything from over-promising in the Sales pitch to Products with known faults that are still sold to Service Policies that don’t make any sense. 

And most Marketers say, “That’s not my problem, my job is selling.”

This attitude is so old school, offline thinking again.  Interactivity is about the Exchange, it’s not a one-way, always Outbound kind of thing.  Interactivity, by definition, says there is a Relationship.  So if you are going to be an Interactive Marketer, you have to be in the Relationship business.

And this means Satisfaction is part of your job. 

You’re not only responsible for creating Engagement, you are responsible for managing / correcting Dis-Engagement as well.  Because that’s how you have a Relationship, that’s Interactivity - you analyze, and react.  If you don’t, this is what can happen.

You wanted Interactivity, right?  What part of the Interactive premise says you can walk away from the Customer Relationships you have created?  That you’re “finished” after the Relationship is created?  That attitude is so old-school Marketing.

For many Marketing folks, what this all means they need to change from understanding “who the customer is” (demographics) to “what the customer does” (behavior) as being the primary segmentation concern.   Understanding Desirability means understanding how people use or consume products over time.  It’s about the behavior of consumers, regardless of how old or young, rich or poor, or what their zip code is.  

What’s happening at a higher level is this:  There are business models that are truly customer-centric, and there are those that are not.  People prefer dealing with a model that is customer centric – and they always have.  But over the past several decades, they have not had much choice in this matter.

Insert your favorite “Corner Grocery Store” tale here.

Then came the web.  The web represents interactivity on a mass scale.  People like interactivity.  But it’s a different kind of relationship, and demands a customer-centric business model to be really successful.  You can’t just put a topping of interactivity on the old mass Marketing model most folks are using online and expect it to work for you.

That’s called a Meatball Sundae

In the past, the number of companies in the “not centric” category dwarfed those in the “centric” category.  Then the web happened, and companies that never had contact with the end customer before, and were insulated from interactivity, now all of a sudden had to open contact centers.  Interactivity was forced on them.

It’s not that customers did not want direct relationships, and the web somehow gave them “power” or put them “in control”.  It’s just now people have experienced these kind of relationships with more companies than they ever could before, and they want this kind of relationship with every company they deal with.  So the environment at companies not used to the customer-centric idea feels like customers are taking control.

The customer is only in control if you are using the wrong Marketing model in an interactive world.  If you are using the right model, there should be no reason customers would want to take control in the first place. 

This is what customer-centricity really means.

Ladies and Gentlemen, Choose Your Marketing / Business Model.

Update:  See this post from Alan on why Marketing might need to Analyze and take Action on dis-Engagement.

———

Now that we’ve powered through the Strategic landscape, on to the Tactical “OK, so what do we do now?” part of the program in the next couple of posts.

Comments on these ideas?  Or are you all waiting for the Tactical stuff to jump in?

Want Engagement? Get Desirability

Thursday, April 10th, 2008

Forrester’s Marketing Forum this year covered Engagement, but not the kind of Engagement so often discussed in web analytics. 

Nope, Engagement from a Marketing perspective, you know, surprise and delight leads to better customer experiences leads to better customer retention and higher profits.

The presentation came complete with some nifty offline Engagement examples, e.g. the more a patient is Engaged in their healthcare the better the result.  The improved results came from, get this, “improving doctor usability”.  And yes, there was a test on this business optimization effort with tangible results generated.

You can get a good feel for where this conversation is headed from Jeremiah Owyang’s blog by listening to the 2 Forrester keynotes, each about an hour long.  For those short on time, pick one, depending on your interest:

Strategic Level: platforms, frameworks, etc. from Brian Haven

Tactical Level: examples, “how to” etc. from Kerry Bodine

No time for a video? 

For a bulleted list of the key points you need to understand in order to optimize your Marketing model, see the “Five Fundamentals of Integrated Marketing” ClickZ article here.

I’ll have more to say on why these ideas are so important in the next couple of days.  For now, I will leave you with this:

If the customer is taking control, it’s only because you’re using the wrong Marketing model, maybe one like this one.  No customer wants to have to “take control” in the first place. 

The more Engaging you are, the less old-school “pray and spray” Marketing  – online or offline - you should have to do. 

That’s the whole point of Engagement.

Comments on the videos or article?  Anything ring a bell for you?