Monthly Archives: January 2007

Lab Store: The Next Inspector

This is a great B2B example of a Marketing / Customer Service program operating in Fulfillment from a vendor of ours.  It drives profitability on the vendor side as well as increased satisfaction on the customer side.  Simple as a rock, effective on a number of levels, and measurable.

When we open a carton (usually 6 or 12 items in a carton) from this vendor, the first thing we see printed on the inside lid of the box is this message:

Our Customer is the
Next Inspector

Think about that message.  If you are packing the vendor boxes, you see this message every time you start to seal the box.  Every time.  How much “training” would it take to have the same effect?  In addition to the more direct message it sends to a packer about quality control at the carton level, it also sends a broader message to employees concerning customer experience and care.  After all, the employees know customers see the same message.

Simple, direct, impactful.

As a customer, when we opened these cartons for the first time, we thought, “Wow, that is pretty neat.  These guys really give a crap about what they do.”  Whether they really do care or not, of course, is up for speculation, but that is not the point, is it?  We think they care.  In fact, my wife’s response to this message was to cut off the carton flap with the message on it and put it over the packing station.  Not sure they planned for something like that, but a nice “halo effect”.

And, unlike most of the vendors we deal with, we have never received a mis-packed box from these folks in 6 years.

I talked with the vendor about this and he filled me in.  The idea came out of Marketing as a potential solution to a packing error problem that was causing nasty-gram traffic in Customer Service and the hard loss of customers.  An Operational defect that had a direct and trackable negative effect on both Customer Service and Marketing – as these process problems almost always do.  He doesn’t know what the ROI is because it’s silly to even calculate it – the incremental profit generated by decreased packing errors (cost reduction in “make good” shipments and returns processing) since program implementation is so large relative to the cost of printing the message on the box that the ROMI would have 8 or 9 figures to the left of the decimal point.

That’s not including any customer metrics like slowing of customer defection rate and halo effects, because those are obvious to them.  Customers simply stopped defecting due to mispacked packages.

Period.  Do you need to run a lot of math on a result like that to figure out if it’s profitable?

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Proactive versus Reactive Customer Experience Management

The data-based business model was customer-centric long before this idea became a buzz phrase.  When you have detailed data on your customers and your operations, you understand a lot more about how the customer experience directly affects profits.  This means you can quantify the value of reducing process defects before they impact the customer.

For example, in catalog (and a few great web retailers) you know what it costs to process a return on both the business side and the customer side (customer value / LifeCycle issues) and you do everything you can to prevent that return from happening – up front.  This means before you launch a new product:

* Fulfillment reviews it to make sure it is shippable and the packaging is going to protect the product in transit

* Customer service reviews the product to make sure the packaging and any instructions are clear to the customer and won’t generate costly calls to customer service or usability problems.  If the packing is incomplete, it is either rejected, modified with an insert, or at the very least, discovering this defect generates a training class for the reps who are going to take the calls.

* Marketing reviews it to make sure that the item and usage fits the brand image of the company, and that the purchase history of customers purchasing similar items / categories does not raise red flags (defection rate, LifeCycle).

This is what I would call a Proactive stance on customer service and experience management.  The Proactive stance understands “value” is a two-sided equation and that to maximize customer value to the company, you must maximize company value to the customer – including the removal of process errors that whack people off (you don’t want to make people Cranky).  It strikes me that most offline retailers and many online retailers are Reactive; they wait for crap to hit the fan and then they do something.  That doesn’t mean that some or even many don’t provide great service when stuff hits the fan.

But it seems to me many of these folks don’t work nearly as hard to prevent it from hitting the fan in the first place as the folks who really know the costs / customer value destruction surrounding defective product selection.  Or for that matter, any defective operational process directly affecting the customer.  Responding to complaints is much more expensive than preventing them, and the folks who feed on customer data know this.  The data enables a proactive analytical culture that can support the additional care / expense required up front before a product is even available for sale, because the downstream negative affects are quantifiable.

Top flight customer service / experience management would mean that there is significant effort to prevent problems from happening in the first place, not responding to them after they happen, no matter how good the response is.  How much effort would it take to make sure packaging, instructions, fulfillment, web site copy, and so forth don’t create problems that would have to be solved later?  That’s a base requirement, in my opinion.  Better, how about taking the same touchpoints and actually making them work harder to deliver a positive experience?

I suspect most so-called “empathy” for the customer / experience takes place on a generic level; it’s a “standards” kind of thing for treating customers.  Listen to the complaint.  Empathize with the customer.  Respond in a calm voice.  Etc.  This is reactive empathy and in today’s world, the baseline expectation of the customer.  If you really want to make it to “surprise and delight“, you need to engage in Proactive Empathy.

There is a great deal of difference between a culture of reactive customer empathy and a culture of proactive customer empathy; and there is a big financial difference between “I’m sorry” and no complaint in the first place.

Marketers interested in direct contribution to profitability and increasing Marketing Productivity will seek out their peers in the operational silos and start creating and managing proactive empathy for the customer through each process of the business.  And the smartest of them will be able to actually prove how much incremental profit embracing a proactive empathy for the customer culture generates for the company.

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The Deconstruction of Marketing

Seems to me these days “Marketing” is being deconstructed into a bunch of pieces.  When I was coming up through the ranks, Marketing included Customer Service plus all the stuff now called CRM, Customer Experience, and all the related ideas.  The person in charge of Marketing was in charge of all these things.  It made so much sense to manage a business this way, because to control your fate as a Marketer, you had to control or at least influence all the customer touchpoints.  So why are these responsibilities being split off into little sub-cultures today?

The answer is they’re not really; that’s just the way it looks to me, because every industry I worked in for 25 years was rich with customer data and we used that data to prove why it made so much sense for Marketing to be in charge of all these aspects of the company interface with the customer.  We proved time and time again that by exerting cross-silo influence where the customer was involved, Marketing could generate much improved profitability.  Every Marketing program worked even harder towards generating profits when Marketing got all the silos aligned.

So I guess it just looks to me (and some other data-driven Marketing folks) like these functions are being split out of Marketing.  The reality is that many companies never had any of these data-driven functions before, and when they start getting access to customer data, they created these areas as new entities.  The question: why not create them under Marketing?  This approach sure would have saved a lot of trouble in CRM, for example. 

And I suspect the answer is the Marketing folks took one look at this new data-driven world with the associated need to have a basic understanding of technology issues, and said, “No thanks, I’ll stick to Advertising and PR”.  And as Marketers let go of / failed to capture control of these key operational touchpoints with the customer, they essentially devolved Marketing from a strategic C-Level force into “MarCom”.

And that’s a real shame.  This splintering of Marketing Management by technological issues is a waste of time at best and a long term problem at worst.  Ultimately, after we go through all this CRM and Chief Experience Officer stuff and whatever else you want to call it (seems like a new name every day), people will realize that all of this belongs in Marketing.  And then we’ll just need some brave Marketing folks who think they can handle it to step up to the plate and really make it work.  If you’re a mid-level MarCom person and want to start preparing for this transition, start making some friends in Finance, Technology, and Customer Service.  Find out what it is that keeps them awake at night, and think about how Marketing could help solve their problems.

And to jump-start your brain towards making Marketing decisions based on customer data rather than using nameless, faceless GRP’s, try taking a look at the business side of web analytics.  You’ll be amazed at how much of it transfers directly to Data-based / CRM / Customer Experience Marketing.  Why?  Because the web analytics community has decided best practices require a cross-functional team approach with a focus on Customer Experience and a requirement to examine the Financial implications of actions taken.  Web analytics teams are a functioning microcosm of what Marketing used to be, and what it should be in the future.

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Lab Store: Managing Customer Experience

When Ron wrote this great post on Marketing’s responsibility for managing customer experience (more on process improvement from me here), I thought I would relate this simple example from the Lab Store.

We sell some exotic pet food that is meant to be a continuity item – the customer buys it every 3 months or so.  This product offering is, of course, designed to extend the Customer LifeCycle.  The food is a “staple” meaning it is generally kept in the cage at all times to supplement the fresh foods fed to the animal.  This food is not as appealing to the anlmal as say, fresh fruit, but it’s an important part of a well rounded diet for the animal.  The feeding instructions on the web site are extensive – portion size relative to fresh food, when to feed, amount to feed, etc.

So we start analyzing the repurchase rate of this staple food that is supposed to be our “back end” and it is dismal relative to expectations.  Why?  Have the customers switched to a different, cheaper source?  Are they not feeding the diet plan we suggest?  Is this even a “marketing problem”?  Well, in the Lab Store, anything related to customer behavior is a marketing problem.

So we grab a sample of the customers who passed the re-order point Tripwire of 3 months without ordering again and ask them, Why aren’t you ordering the staple food?  And the answer is “The critters don’t like it”.  Really?  That’s a surprise; we know the animals generally eat the food.  So we ask about portion size, are they following the diet plan?  And they say, “Not really, when they didn’t eat the staple food, we thought they would be hungry and so we gave them more fresh food.  They never ate any of the staple food”.

And there you have it.  We don’t need to ask any other questions.  The animal is not going to eat the boring staple food when they are being overfed the fresh food.  This is like asking a kid if they would rather have spinach or candy; one is good for them, the other tastes better.  And the customer isn’t going to buy staple food the animal will not eat.

The problem is, this “fresh food only” diet is unhealthy for the animal; they are not going to get critical nutrients they need from the staple food.  But, this exact feeding scenario is covered on the web site; we’re already communicating this issue to the customer.  So it’s not a marketing problem, right?

Wrong.  That is the marketing problem – the information is on the web site.  We started including a package insert with the staple food containing the very same info as on the web site, except now, of course, it was “contextual”; delivered in exactly the right place and at exactly the right time – when the customer opened the staple food package.  And magically, the repeat purchase rate on the staple food increased 32%.

The point is, if we had been off “marketing” and not paying attention to the Potential Value of the customer by setting up the Tripwire, we’d have never found this flaw in the process.  And by fixing it, we increase the return on all the acquisition marketing we do, because the LifeCycle of the customer has been extended.

Marketing Productivity, indeed.  More Lab Store tales to come.

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Lab Store: Background & ROMI Formula

Many of you in the blog audience might not know I have been writing about both offline and online Marketing Productivity since late 2000 on my web site through articles, an e-mail newsletter with about 7,500 double opt-in subscribers, and a blog-like database marketing article review section.  Anyway, back in 2000 it was pretty hard to get people to listen to Marketing Productivity ideas because there was just too much money sloshing around.  Who cares about Productivity when you have unlimited budgets? 

So to prove out some of the concepts I was talking about, I started my own online store for under $1,000, all costs in.  Those of you who have seen me speak at Search Engine Strategies or the eMetrics Summit on customer retention know this web site as the “Lab Store”, which has turned into a large enough business on that same $1,000 infrastructure my wife now runs it as her full time job.  The Lab Store is a great resource for online marketing research and testing because I control everything (unlike most client situations) and perhaps more importantly, I don’t have to ask permission to release results.  So from time to time, I pull analysis out of the store operation I think will be interesting to other people and provide it for your review. 

That said, I’m not linking to the Lab Store site because I’m not fond of the idea that our competitors might use this blog to improve their business.  Lab Store Analysis Examples will link back to this post to provide context for new subscribers.

ROMI – Return on Marketing Investment

When we execute different tactics designed to increase customer value in the Lab Store, we measure the results using an incremental flow-through model I call ROMI (to differentiate from the extremely lightweight ROAS).  We define ROMI in online retail this way:

Sales – Cost of Product = Gross Margin
Gross Margin – Variable Overhead Cost = Gross Profit
(Gross Profit – Marketing Cost) / Marketing Cost = ROMI

where Variable Overhead Cost is basically the cost to process, pick, pack, ship, and service the incremental orders generated by the marketing, service, or operational initiatives.  ROMI answers the question, “For every $1 I spend on a marketing, service, or operational effort, how much cash flows through to cover fixed costs?  What do I get back, after all variable costs, including the cost of the effort?

Examples of how this works with efforts other than Advertising:

New Customer Kits
Managing Customer Experience

Overview of Lab Store stats and metrics can be found here.  Pics here.


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**** Market Share Goal versus Profitability Goal

Some interesting studies from The Wharton School on the negative correlation between “Competitor-oriented objectives” such as market share goals and ROI.  I can’t tell you how many times I have had this conversation with people, including those that base online advertising spend on some theory of “share”.  “We have to be in the top paid search position to accomplish our brand objectives” etc.  Even though being in the top position can result in negative ROMI.  “But that’s just the cost of being #1, advertising costs money”.  And that’s where I lose them, because even if you are a big fan of brand-oriented  / share-oriented marketing strategy, do you walk into those ad buys knowing you are going to “lose money” on them?  I don’t think so; there has to be a least some perceived positive benefit.

According to the article, lab experiments with MBA students indicated they tended to choose strategies that maximized competitor-oriented objectives rather than profitability.  Is there really a whole generation of folks out there that think marketing is basically a “sunk cost” so it doesn’t matter if it is profitable?  That’s insane.

So let me get this straight.  We’re starting to turn the corner on the marketing accountability issue; we now try to measure the profitability of marketing.  But when faced with an unprofitable campaign, there’s still a giant “fear of failure” safety hatch called “market share”?  Please tell me how you explain that to the CFO.  No wonder customer retention and LifeCycle Marketing ideas can’t get any traction if this is how people think.

If you’re more interested in profits than market share with PPC marketing, see these excellent guidelines.

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I’m not clear on the Chief Customer Officer concept…

I don’t have any problem with the direction Jeanne Bliss provides regarding how to become the “customer champion” in your company, especially the idea of aligning with the CFO and CIO.

What I’m trying to figure out is why this is not Marketing’s job; seems to me the CMO should be the Chief Customer Officer, complete with the ultimate responsibility for Customer Service.  Otherwise, it seems like this CCO position is just an excuse for people keeping their heads in their own silos and letting somebody else worry about cross-functional processes, customer experience, and defects.

In other words, do we really need a unique exec to be able to create / enforce / enable cross-silo functionality on the “soft” side (marketing, service, some fulfillment) of the business?  After all, the CIO and CFO operate across all the silos, why can’t the CMO?  As Ron said in his excellent piece What Marketers Should Learn From IT, the CMO now needs to get involved in the whole business and act cross-functionally to be successful, as the folks in IT have learned.

I guess the answer is probably that “Marketing” has been redefined over the years and has somehow lost the strategic seat at the table, morphing downward into “MarCom”.  This has not happened at all companies – I can tell you at most truly data-driven companies, the CMO is the Chief Customer Officer, because these folks / the company understand how the totality of the customer experience affects Marketing Productivity.

Perhaps the answer to Kevin’s question on what happens to the Marketing folks in the catalog business as the web takes over is this: they become Chief Customer Officers or consultants to them like Jeanne Bliss, formerly of Lands’ End.  After all, they already know how to do the Chief Customer Officer job.

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Is Your PPC Incremental?

Something that analytical folks talk a lot about is “the incremental”.  In customer marketing, it’s not enough to get response, what we want to know is how much of the response was above and beyond what we could be expected had the test or promotion not been done.  Typically incrementality is measured using control groups – people just like the people you are sending the campaign to who do not receive the campaign.  Then you compare the profitability of the people who received the campaign versus the profitability of those who didn’t.  The difference is the true, incremental profitability of the campaign.

Kevin over at the MineThatData blog relates that Blue Nile has decided to lower prices as opposed to chasing rising ad costs.  I don’t know enough about their business model to really comment on that action, but I do know one thing – they (and many, many other companies) are wasting Pay-Per-Click spend on non-incremental clicks.

Check out this shot.  Search for Blue Nile in Google, you get a Pay-Per-Click ad for Blue Nile, and Blue Nile has the fiirst natural listing:

Search: Blue Nile







Now someone, somewhere, back in the beginning of PPC probably had a conference speech that told everybody to buy the search for your company’s brand name, maybe for “branding” or “exposure” purposes.  But almost every web site ranks first in the natural rankings for their own brand name.  So I ask you, is there any incremental here?  What are the chances, if the PPC ad was not there, that the visitor searching “Blue Nile” would not click on the first natural listing?

What do you suppose the volume of this search is, and how much money is being wasted by people clicking on the paid ad who would have clicked on the natural link anyway?  I asked the same question back in 2003, and though the structure of the test wasn’t as pure as most hard core test & control folks would like to see, the results were so dramatic that you can’t really argue much with the methodology.  A few percentage points here or there and you still get to the same place.

In this particular test, on a high volume PPC phrase for a site that also had a top 3 natural ranking, 77% of PPC sales were non-incremental – stolen from the natural side – and would have happened anyway without the PPC link.

I will be the first to say that results are going to vary a lot by the type of site, the phrase, the target audience, the search engine, and so on.  But Golly Gee folks, has anybody else ever questioned the wisdom of “railroading” a top natural listing with a paid listing – and especially for your own brand name?  I bet a lot of analytical folks have, they just couldn’t convince the marketing folks to test it.  After all, addressing / fixing this by taking down the PPC ad means:

1.  There will probably be a few lost sales, perhaps from people who for whatever reason, always click on paid ads (newbies?)  However, profits will increase.  Some folks will not believe in this idea, it’s that whole analytical culture problem.  You have to trust the numbers, not fear them.  Unless, of course, you have been specifically told to grow sales and not profits.  Rare, but it does happen.

2.  Then there is the whole “How could you not know this was a bad thing and continue doing it for so long?” problem.   That’s more analytical culture stuff.  Failure is a learning experience in the analytical culture, not a cause for whippings and firings and demotions.  The question is not how much money was lost, the question is how much will be saved going forward.  Right?

3.  Potentially, some PPC budget will be reallocated to other, more profitable marketing activities.  This could be a problem if there is “ego spend” involved in the management of PPC.  I wouldn’t move the money out of PPC, I would just find better ways to use the existing budget.  But the potential exists for losing it for a higher and better purpose that is proven out by the numbers.  Just optimizing the system, no hard feelings, right?

PPC Marketers, if you’d like to free up budget for something else, ask your web analytics folks if they can track this test for you.  Locate a high volume search phrase that you buy PPC for ads for where your web site naturally ranks as #1 or #2 for the same phrase.  Try shutting the PPC for that phrase off.  How much click volume do you lose versus the cost of the clicks when PPC is tuned on, and what does that translate into in terms of increased profit?

And I am really not picking on Blue Nile here – search any brand name, online or off.  Go ahead.  What do you see?

Would you fail to click on the organic link if the paid link was not there?  Really?  If you think you’d miss the organic link if the PPC link wasn’t there, send me a pic of the example.

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*** Selling Generators on the Web – Using Radio?

It can’t be very easy to sell $5,000 electric generators on the web, but it sure is a lot easier if you’re a clever marketer.  You see, weather is local, so is radio, and guess which media source most people pay attention to when the power goes out?  Right.  Check out this very slick idea brought to us by Internet Retailer.  That’s one productive marketer.

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LifeCycle Marketing

Lisa Bradner from Forrester Research called to discuss LifeCycle Marketing, which is kind of a coincidence given the Sense and Respond post below.  Apparently folks are having some difficulty with implementing the concept…

The Customer LifeCycle is really just a process that you can map, just like any other business process.  At each stage of the LifeCycle you have an expected result based on the behavior of other customers as a whole or in the customer segment.  You measure the behavior of individual customers against the process benchmarks, and when the customer is behaving as expected, you do nothing, taking no action.  If the customer behavior is “out of bounds” with the expected result, you take action.  This method generally allocates marketing spend to the highest and best use.  If this sounds a bit like Six Sigma for Marketing, well, you’re right, it does.  You have a problem with that?

Another way to look at it is this: there is a “tolerance” band for behavior and the ability of marketing to affect behavior depends on where the customer is within that band.  If the customer moves too far outside the band, it becomes impossible for marketing to really do anything at all to affect behavior.  So as long as the customer remains in that band, it conserves marketing resources to take no action.  As the customer begins moving towards the band, significant marketing action is triggered and needs to be taken before the customer moves too far outside the band.  So you have a reallocation of marketing resources towards highest and best use, always pushing marketing spend to where it will be most effective.  It’s a marketing resource allocation model of sorts.

Let’s take a simple retail example of how this works.  Let’s say you look at new customer purchase behavior, and you see for new customers who make a second purchase, they usually make the 2nd within 45 days of the first purchase.  So, you can look at new customers and divide them into 2 groups; those that are doing the “expected” and those that are not, based on the 45 day rule.  Applying the LifeCycle concept, any new customer that makes a second purchase within 45 days of the first, marketing does nothing (inside the band).  This conserves marketing resources and margin dollars that would have been lost to discounting.  That money is then reallocated and spent on the customers crossing over the 45 day tripwire without a second purchase (outside the band), and since you have more to spend (courtesy of the reallocation), the programs can be more effective.

Further, let’s say that you analyze this 45-day idea looking at the marketing campaign that generated the new customer.  You have only 2 campaigns and the days between 1st and second purchase is 60 days for one and 30 days for the other (average 45 days).  So, the first thing you ask yourself is why is the behavior different – media, copy, offer?  The second thing you ask is should we reallocate spend from the campaign with a 60 day window to the campaign with the 30 day window, which would generally increase cash flow?  And the last thing you do is adjust the original 45 day trip wire to 2 distinct tripwires, one for the 30 day campaign and one for the 60 day campaign (if you keep the 60 day campaign).  You are optimizing the marketing system based on the unique LifeCycle profiles of these new customers, generally lowering costs and increasing margins as you optimize.

The thing is, this is really fundamentally the same as optimizing a web site.  It’s the same idea, only with different variables and more detailed data.  I think that’s why many of the web analytics folks seem to “get it” and are now working on systems to automate it.  I saw a shopping cart demo last week with this kind of LifeCycle profiling built right into it.  You could run the profiles and execute the LifeCycle-targeted e-mails right within the same interface.

Behavior predicts behavior.  If you use behavioral metrics like Latency and Recency, you can discover these LifeCycle patterns and use them to your advantage.  Every marketing system, B2C or B2B, has LifeCycle processes in it.  By understanding these processes you can focus resources and increase the overall profitability of all your marketing efforts.

Why are companies having troubles implementing such a relatively simple concept?  I dunno, guess we will have to see what Lisa has to say in her report…but why do companies have trouble implementing just about every data-driven Marketing or Service effort?  More often than not, the root cause is lack of a proper analytical culture to support the effort.

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