Here’s your challenge:

Would anybody in your business recognize this as a problem?  Or would they just shrug and transfer the item to the picking racks?

In other words, finding this, would you or an employee:

1.  Ship to the customer as is, let the customer figure it out

2.  Cut the nozzle off so customer doesn’t have to even think about it, doesn’t have to send you e-mail or call asking about it

Your answer to this question depends on:

1.  How customer-centric you / your org really is

2.  How much you understand about the financials of your business

Me, I can see and feel what the customer experience opening the package is going to be, especially if the customer is New.  First, they will see our Welcome Kit, Free Gift, and Samples.  Surprise and Delight, generates incremental net profit of $36.68 per New Customer.

Then they come across this mis-matched sprayer set, and lose Emotional Momentum.  In case you can’t picture what is going to happen, our average customer (probably not someone like you) is:

1.  Not going to initially realize this is a problem
2.  Try to assemble the product
3.  Find that it’s difficult to assemble
4.  Spill the product trying to force assembly
5.  Get very frustrated

Then – and this is the ”Relationship” part – they will think, How could they ship a product to me like this?  What do I do with this?  Should I return it?  But I spilled it.  Can I fix this by trimming the tube?  Where are the scissors?  What if the sprayer doesn’t work after I cut it?  Why is ordering from these people a hassle?

This is Friction.  Friction gradually grinds the Relationship to a halt.

If a good experience can generate $36.68, does it follow a bad experience could wipe some or all of that profit out?  By decreasing the 2nd purchase conversion rate responsible for most of that profit?

I don’t want a single new customer to question their decision to buy from us; that’s planting the seed of dis-engagement, which leads to defection.  So I’m going to cut the nozzles off, because I can estimate the risk / reward.  But I have a lot of experience analyzing these kinds of issues, I can see the pro-forma in my mind’s eye.

What could you do?  For example, could you A / B test this hypothesis of mine before sticking your neck out and risking time or money to trim the nozzles?  Absolutely!  In fact, the classic split test is the fundamental tool in Relationship Marketing, and just about the only way to prove out the profitability of ”Customer Experience” issues.

And we’ve done that kind of thing before when the issue is important strategically (example).  In this case, ship 1/2 the bottles with the long nozzle, 1/2 the bottles with the trimmed nozzle, keep track of the customer ID’s (who got which), look at customer value and service costs 90 days out, compare profit of two groups.  All of these customer-centric ideas can be tested, just like you test landing pages or e-mail copy.  Let’s take a look at what the outcome might be.

I figure it will take me an hour to trim the whole lot.  That means my salary (or net profit, in the case of an Operational Test of this concept) for that hour, if  the trimming preserves the 2nd purchase rate of all these new customers, would be:

240 bottles x 40% to New Customers = 96 x $36.68 = $3,521

That’s a gigantic “found money” number for a company of our size.  What is $36.68 x number of new customers at your company?

If just one New Customer is impacted negatively by the nozzle, I make $36.68 for the hour.  Not gettin’ rich, but better than working fast food.

That’s just the New Customer impact.  Doesn’t include negative impact on current customer value / subsequent re-order likelihood, or savings from prevented e-mail and phone calls ($6 each?)

Downside?  I completely waste an hour in front of the TV clipping nozzles.  No brainer, at least for me.  What if you were paying somebody $15 an hour in the warehouse to do the trimming job, would the answer be any different?  How about at $20 an hour?  $25?

Would you risk $25 to preserve a Potential Value of $3,521?

I would.

In the above case, we have a classic value exchange between the company and the customer.  The company (me) does work for the customer to improve the experience.  In exchange, the customer responds by becoming more likely to make a 2nd purchase.  There is real work done for the customer and the company is rewarded by increased profits.  And you can prove it with an A / B test.

Relationship Marketing.  Dollar for dollar invested, often makes your company more money than Advertising because of the leverage you get from Optimizing customer-facing Business Processes.

If you want to gain credibility for Customer Experience ideas, if you want to actually do something about this area, you need to (as we used to say at HSN) “go down into the belly of the beast”.

Perhaps you could start by testing a New Customer Kit or On-Boarding program?  Form your hypothesis and test it.  Prove customer experience matters to people with the power to take action - Finance.

I’m pretty sure if you walk into Finance with proof that you can generate $48 in profit for every dollar they give you in 90 days on this New Customer program, you’ll get their attention.  I don’t know about you, but I have unlimited budget available for this kind of program!

Once Finance understands what you are doing and how profitable it is, you have a platform for any Customer Experience ideas you’d like to talk about, whether you call them Social or Service or Experience.

People listen to the sound of profits.

Have a question on Customer Valuation, Retention, Loyalty, or Defection? Go ahead and send it to me here. If on the topic above, you can leave a comment on the post:

Relationship Marketing Economics

Processed 10,172 orders, up 3% from last year, despite a logistical problem in the business model we did not have control over (breeding of animals).  Fixed that, so should not be an issue going forward.  Merchandise Return Rate of .3% on dollars, which is quite low.

Returns cost money to process, imply negative Social feedback, and increase customer defection by creating poor experience.  We do everything we can up front to keep returns and other negative experiences from happening in the first place by screening products and actually taking action on customer feedback and analysis.  Often, we modify packaging, create our own instructions, or assemble products we know people will have trouble with.  More on this idea here: Marketing through Operations and Panic Pack!.

We retained between 75% – 87% of our best buyers depending on what time frame you use, and further improvement in these stats is pending test results.  More on this idea here: Frequent Buyer Analysis.

Ended with 12,218 (double opt-in, non-bouncing) newsletter subs acquired on our own site.  Many of these folks are “pipeline”, they are in learning mode.  The newsletter is strictly educational and does not include any discounts or promotions.  Articles we write often present ideas related to products we sell, and we do include product links, but no more than 2 per issue.  We don’t “force” people who buy from us to get the newsletter by automatically adding buyers to the list, though we do make them aware the newsletter exists in the e-mail order confirms and on packing slips if they want to sign up for it.

The primary idea driving the newsletter is conversion to 1st purchase, and the tone / approach sets up the next phase of customer management - 2nd purchase Marketing through Surprise and Delight.  AIDAS, baby.  More on this, see New Customer Kits.

Ended with 4317 units in stock, inventory turned 22.1 times this year – without ever stocking out.  More on this idea and why it’s important to the commerce business model here: Web Merchandising.

Our organic search coverage is quite good,  so we generally use PPC to “fill in” where our organic coverage is weak.  We don’t do “Brand” bidding because it doesn’t pay out; are people searching with your Brand because they don’t know it (um…?), or they just want to navigate to it?  More on these ideas here: Is Your PPC Incremental? 

Ad spend was 3.77% of sales, 96% of that on PPC, generating about 16% of orders.  Average cost per click 17 cents, average cost per new customer $15.87 versus an annual value (Gross Margin) of $184 on that same customer.  That’s printing money.  This cost is the AdWords number, we know it’s lower because some of the ads are driving offline conversions (telephone) that are not picked up by AdWords.

We could spend more on advertising, but we’re in the Productivity game, not the “bigger is better” game.  And the reality is, the Incremental Profits to be had with increased advertising over what we already get from Organic are small; 8 years of testing tell me that.  We’re not really interested in maximizing sales, we want to maximize Profit per Employee.  More on this Productivity idea and how it works here: Podcast Interview with Jim Novo (includes text version).

We do buy some highly targeted Display ads, mostly on topic-specific chatboards.  Spent $1100 for 126 orders, primarily new customers.  Much of that spend was during testing before the Display program was Optimized.  More on that here: AdSense Finally Works!

Close to half our orders on average shipped with our maintenance food product, a recurring sale.  This is up substantially from last year, meaning more folks are sticking with our diet.  How we discovered, analyzed, and implemented a super cheap repeat food buyer program is here: Managing Customer Experience.

Similar to our approach on advertising, we don’t actively “market ourselves” through Social Media; we understand the environment and facilitate best performance of the system.  We prefer to let the customers speak for themselves organically and for Search to do the rest.  In other words, we Optimize for Social internally not externally, with very high standards for Products and Service, and intervention as needed.  Basically, we try to prevent negative commentary from happening in the first place through superior operational monitoring and practices.  More on this idea here: Social for Business.

We do keep track of what’s going on in Social Media with Google Alerts, Addictomatic, and some other tools, and intervened on 2 board chats this year where people were spreading false information about us.  On the flip side, a competitor built several fake Social Review sites this year, with fake reviews of our business.  You can’t post to these sites, but people think they are real I guess, given what we’ve heard from customers.  We actually get converting traffic from the sites, even though our ratings suck compared to the competitor, who naturally has a (self-generated) ranking of 9.7 out of 10.

These same ”Social” issues and events have been taking place on the chat boards ever since we started the business back in 2000.  We have always been “listening” and taking action when appropriate, so the current Social Media movement has not changed anything for us.

For those of you thinking “this Relationship Marketing approach could only work in a small business”, think again.  I used the same model when I was VP Marketing & Programming at HSN, with over $1 billion in annual sales and 5,000 employees.  Many large catalog (now hybrid with online) operations follow the same model.  If you’re looking for employees who know how to drive this customer value-centric bus, recruit from the big catalogs.  More on how to work this model in large companies here: Optimizing the Interface.

The technology changes, but the ideas fundamental to success in interactive commerce really don’t.  If you have a good grip on the right Strategy, each new wave of technology is just more of the same – people are people.  If each new technology wave feels like it’s a “Brand New idea”, that probably means you’re letting the Tactics drive the business model.  Develop or Revise your Strategy. 

If your Strategy is to be customer-centric, the above is a pretty good roadmap.  This approach really shines with interactive environments, and now would be a good time to get on with it!

You see, Interactive is different.

Twitter: @jimnovo

Have a question on Customer Valuation, Retention, Loyalty, or Defection? Go ahead and send it to me here. If on the topic above, you can leave a comment on the post:

Lab Store: Year End Analysis

I often prefer to look at “worst case” data when doing customer analysis; this way you don’t over-estimate the Potential Value of the business going forward.  The beginning of the 4th Quarter is a good time to do this since “holiday” really hasn’t kicked in yet, so you don’t have those buying influences skewing the natural activity in the customer database.

At the end of September, we took a look at all customers, no matter when they became customers,  who have purchased from us at least 10 times - a best customer analysis.  Considering a “year” to be 9/30 to 9/29,  we bucketed them by when their last purchase was - past year, 2 years ago, 3 years ago, 4 or more years ago (the business started 5 years ago).

Here are the results:

Last purchase date was in               Percentage of all 10x or more Buyers

9/30/07 -  9/29/08                                 75%

9/30/06 -  9/29/07                                 12%

9/30/05 -  9/29/06                                   8%

9/30/04 -  9/29/05                                   5%

If this data is still confusing, the second line above would read, “Of all customers who have ever bought 10x or more, 12% last purchased in the period 9/30/06 -  9/29/07.

75%  of the best, most productive customers (all else equal, like margins, service costs, etc.) we have ever had since the busines started are still active buyers with us. 

Of course, this raises the question: What’s up with the rest of them?

When you segment like this, using the actual customer behavior, an analysis of each segment can be quite revealing.  What you are seeing is essentially a LifeCycle model, the attrition pattern of these best buyers.  No doubt some will come back, especially out of the “last year” 12% group, but here’s the thing – the longer they are inactive, the less likely they are to come back.

So if you’re going to “do something” with this 12% Recent best defector group, the time to do it is now, going into holiday season, because you have buying momentum running with you.  That’s another reason we do this analysis at the end of September ;)

To optimize this action plan, you should know something about who these defectors are.  And here is where people make a huge mistake: because they’re inactive buyers, or in the case of non-commerce sites, inactive visitors, they are not being surveyed by the usual survey pops. 

Let me say that again: arguably the most important segment of the customer base, dis-engaging  best customers, lacks voice under most approaches to VOC.  You have to reach out proactively to these people and find out what you did wrong; otherwise you will just keep doing it wrong and continue to churn off your best customers / visitors.

Got that?

A segmentation technique that is very helpful in this kind of analysis is to think in terms of controllable and uncontrollable customer defection.  Since the Lab Store is in the animal supplies business, the sale or death of the animal would create an uncontrollable defection – no amount of “Marketing” is going to get that customer back.  Other examples of uncontrollable defection would be when a cable or local newspaper customer moves out of the area serviced by the company, or a manufacturer ceases to produce a line and no longer needs parts.

We know from previous surveys of these defectors this uncontrollable population is about 4% a year.  So for each time span above, you can knock 4% off and get to the percent controllable defectors.  These are the people you really want to know about, because they are actionable.  So as far as the 12% “last year” group, it’s now about 8% of best buyers.

The first controllable defection trigger we would look for in the group would be Product.  Product drives everything in a commerce model; it’s why you exist as a commerce entity, and is fundamental to the Brand Promise.  If you have a product issue, no amount of Service or other drivers will fix the problem.  So Product is where you start.  Plus, you should have all the data you need, so it’s easier to get started on right away (no lag time).

Did these defecting best customers buy similar products which resulted in their defection?  In other words, something about the packaging, pricing, or performance of the product may be defective.  This type of analysis is how we discovered and cured the staple food problem.

The product analysis turned up an interesting trend, or non-trend, actually: while in general there were no hot spots among categories or products purchased by these folks, there was a surprising lack of purchases in the Toy category for the past year.  My first question upon seeing this: what toys have they bought from us in the past?

The answer: All of them.  About 70% of these defectors had purchased all the toys we carried at some point.

Now, there’s several reasons we don’t carry many toys.  The community we serve is extremely sensitive to the issue of materials used in products they expose their animals to, and most animal toys don’t make that cut.  Then there is our general philosopy on avoiding commodity products and keeping product selection trimmed to what people want to buy.

But clearly, this looked like a specific, nailed down opportunity to put some effort into this area.

To confirm this idea, we sat down and invented a couple of products, contacted a sample of these defected best customers, and showed them what we were thinking in terms of the new toys.  This action confirmed two things for us:

1.  Indeed, one of the reasons they stopped buying from us is they already owned most of our toys, and their animals were not on our staple diet, so there was no recurring purchase need.

2.  They thought the new toys were very cool ideas – ultra safe materials, fair pricing, unique, etc.

So there you have it – our holiday best customer reactivation plan is set.  The items are up and we’ll  be dropping a promotional e-mail to just these defected best customers with an “insider deal” on the new toys.  The sales generated should be almost completely incremental due to the research we did, but we’ll use a control group anyway, just to make sure we didn’t screw something up.

Now, I know a lot of people in this community would be running all kinds of statistical models and such against this defector data looking for the silver bullet, but what’s interesting about this case is:

1.  The segmentation was totally simple to do with a spreadsheet: Frequency cut with Recency dimension.  That’s it.  Anybody can do that, anybody.  No advanced stats needed.

2.  The “answer” was not something in the data, the answer was NOT in the data – lack of toy purchase. 

Sure, there are ways to set up the modeling to find this out, but you would have to come up with the idea of “missing category” before you constructed the model.  Then you would have to make a judgement call on whether the 70% ”purchased all toys” number was significant based on intimate knowledge of past customer analysis.

These are the kinds of skills Marketing should be bringing to the party, because the Tech side is often so very stuck in binary thinking.  To optimize these Marketing systems, someone has to control for the problems caused by behavior chains like:

did not buy->
so did not get surveyed->
so did not uncover “lack of toys” problem

because the Tech side is always focused on what has happened, as opposed to what has not happened.

Might as well be Marketing who takes up this role, since solving “did not happen” problems almost always has a much higher ROI than looking at what did happen.  After all, a 4% conversion rate means 96% did not convert.

In solving this “did not happen” problem, we have both increased the potential for business with dis-engaged best customers and corrected a flaw in the system that would have continued to flush best buyers in the future.  One campaign, with both Current and Potential Value.

I’m guessing the response rate and ROI on this best defector holiday campaign will be huge.  What do you think?

Have a question on Customer Valuation, Retention, Loyalty, or Defection? Go ahead and send it to me here. If on the topic above, you can leave a comment on the post:

Lab Store: Frequent Buyer Analysis

AdSense, however, has always been a poor performer for the Lab Store (and many other commerce businesses).  AdSense is really a banner ad with lipstick on it, only marginally attached to the point of demand by context, and not by action.

We’ve tested it many times and always with the same result – unbelievable numbers of impressions and no sales.

In the last test cycle, we finally stuck pay dirt.  Behold, AdSense finally delivering value to the Lab Store:

(click to enlarge)

As you can see, we started out with a Cost / Conversion of about $155.  This ain’t going to work, because the net value of the customer generated from “context ads” is only about $65.  We’re literally losing money every time we make a sale.  But this time around, Google finally provided all the tools we needed to optimize this system, namely:

1.  More advanced control over site selection. 

In the earlier stages of this capability, we could not kill some sites without killing others, so it was not as flexible as we needed.  The most I could find out about this issue was it had something to do with the nature of the AdSense distribution agreements.  As of this summer, something had changed and we had finer levels of control.

The first thing we did was to kill any sites in Social Media land (primarily MySpace), which is where you get the first dogleg down in Cost per Conversion.  Then we continued to selectively prune more sites with the same profile as MySpace - tons of impressions, worthless traffic.

2.  Ability to change pricing models.  

Google allowed us to go from impression pricing (CPM) to click pricing (CPC).  Since we now had pruned the site list down to the most relevant, we were able to jam the price we would pay per click way above the equivalent CPM Google was getting from us before this change so we could own the real estate.

Look what happened – the next dogleg down in Cost / Conversion, finally stabilizing between $4 – $5 per new customer. 

This cost we can live with versus the net customer value of $65.

I know some folks may concern themselves with advertising higher up in the “funnel”.  Gee Jim, what about “awareness”?  How do you reach folks that don’t know about you, folks not searching for your products?

The answer is in the chart above.  I can’t afford to generate awareness, it costs too much.  Generating 400,000 impressions on MySpace basically creates awareness among people who are not interested.  I’m sorry, but I simply don’t see any value in that.

That’s what the mass media are for.

We have tons of high-ranking site content that generally addresses the awareness issue, if a person is casually interested enough in our category to do a simple search.  If they are not interested enough to even search, then why would I want to advertise to them?

I only want to advertise to people who are interested in our category.  Pull, not Push, if you know what I mean.  Relationship Marketing.

Just a beautiful business model I tell ya, this advertising at the point of demand.  As long as you only have to pay for the real demand, that is.

Thanks for making the changes, Google.  Some implications for display ads as a result of this test are discussed here.

How are your AdSense ads doing, have you been able to optimize them to profitability?  Or have you abandoned them completely?

The next post in this series is here.

Have a question on Customer Valuation, Retention, Loyalty, or Defection? Go ahead and send it to me here. If on the topic above, you can leave a comment on the post:

Lab Store: AdSense Finally Works!

We met in person for the first time doing a presentation together at the DMA show in Chicago this fall, and because he used to work at Crutchfield – a truly customer-driven remote retailer – we share some experiences and beliefs.

For those of you who might be wondering where a lot of the Marketing Productivity ideas I post here come from, this interview-podcast is probably a pretty good backgrounder.  We talk about a lot of stuff, including:

Monetizing customer experience

Importance of Control Groups / Source Attribution

Multichannel Marketing Strategy

LifeCycle Contact Strategy versus Calendar-based

Retail Business Models / Lab Store

Search box or not? / Serendipity

How to tell if online customers are really engaged – without web analytics

Here’s another link to the Interview-Podcast.  Enjoy! 

That was lots of fun, thanks Allen!

Have a question on Customer Valuation, Retention, Loyalty, or Defection? Go ahead and send it to me here. If on the topic above, you can leave a comment on the post:

Interview-Podcast w/ Jim Novo

For a variety of reasons we got a late start today packing the orders from over the weekend and New Year’s Eve / Day, and had to invoke a “Panic Pack” on these 131 orders.  A Panic Pack is a high speed affair where Barb picks all the orders but leaves some for me to pack (I suck at packing compared with her) while she packs the others.  We packed all 131 orders in 4 hours, just barely in time for UPS pickup.

That might not sound like a big deal versus the 25 boxes an hour, but remember we are also picking the orders and dealing with all the customer service – can you add this to my order, can you change my shipping method, etc.  Most packers simply pack an order that has already been picked for them, and don’t do any customer service.

My point with this post is not that we know how to pack like banshees, but the enabling technology behind this capability.

It would have been impossible to pack and manage the service with this many orders in such a short time without a proper backend order management system – something I see many ecommerce folks go without.  Most web-based cart back-ends are incredibly difficult to deal with, especially on order changes. 

In many web-based order processing systems, it can take multiple steps to make simple changes rather than just a few clicks – add another product to an order, run another credit card charge, reprint the packing slips, etc.  This is because once an order is processed, it’s not meant to be changed; order changes were not taken into account when these systems were designed.  Nobody talked to customer service to get specs, I guess…  

“You mean customers might want to change an order they already placed?  Why?”  ‘Cause most of them are not geeks.  They make mistakes.  They forget stuff. 

Often, when you call companies using these systems to add products to your order, they tell you “we can’t” and to go online and place another order.  Nice.  Great service. 

We actually don’t mind if customers want to add to orders they have already placed with us - silly, huh?  Gee, you want to spend more money with us?  Sure, bring it on!  By the way, Flat Rate shipping encourages this behavior.

If you have a good backend system, you can just add the product and the software does the rest, because the order has not been “processed” yet as it has with web-based systems – you process the order right before you print the packing slips, including the credit card capture.  And, you can do all kinds of customization on the packing slip, like messaging for new customers, repeat customers, and so forth, and automatically interface with the shipping manifest system.

The labor cost savings alone when using these order management systems is huge.  When we moved from web-based “copy & paste” order management to local software, our time spent per order on customer service dropped by 50%.  This kind of gain in productivity is common, as you can see here.

And when you have more time to service each customer, you  can provide better, more customized service.  Simple as that.

Plus, our backend system creates one heck of a customer database, automatically consolidating orders at the customer level and providing one-click access to customer service history, cumulative sales, and so forth.  Whenever we are faced with a complex service issue, the first thing we do is look at the cumulative sales of the customer, and then we act accordingly.  In other words, for proven good customers, we bend the rules.  That’s how you build loyalty.

So you need a customer database to provide great service.  As far as Marketing goes, you need a customer database to measure the success of customer-centric programs like this one and this one.

If you don’t have a flexible and marketing friendly order management system, you really should consider getting one.  We use Stone Edge.

Have a question on Customer Valuation, Retention, Loyalty, or Defection? Go ahead and send it to me here. If on the topic above, you can leave a comment on the post:

Lab Store: Panic Pack!

To be clear, I don’t have anything against the poor robots or testing – it’s the people using them.

All the way back in 2000, Bryan Eisenberg and I wrote the Marketer’s Guide to E-Metrics – 22 Benchmarks because nobody was measuring or testing anything, and that was silly, especially when it was so easy to do.   Now, it seems web analytics has taken that mantra and run all the way to the other side with it – testing is Strategy, and Marketing is whatever the robots say it should be after the tests are done.

Yes, web marketing seems to be going IT-centric again.  Worked out well last time, didn’t it?

Here’s the bottom line: I have no doubt you can improve a faulty execution with a lot of multivariate testing, but the real question is this: if the execution is Strategically flawed, will you ever get where it is you want to go? 

I think not.

I’m sure you are convinced your Strategy is on target, based on conventional web commerce wisdom.  The following is a bit of unconventional web commerce wisdom for you to consider when you sit down around the table with your robots.

——–

The Lab Store – my wife’s pure online commerce business where I am Chief Product Assembler and also do a lot of marketing testing on the customer base - services the exotic pet customer.

It’s a very odd experience going to the pet trade shows for this biz to review merchandise and make purchases, on many levels.  The root of this odd-ness can be summed up this way: we buy narrow and deep, and most everybody else in the pet business – which means retail stores, and many online stores - buy broad and shallow.

We work with one of the largest pet supplies distributors on the East Coast.  At their show, we get a bit of a discount if we place orders directly with the vendors, which are then managed by the distributor.

As we place our order with this one vendor, he asks, “Did you know this order is nearly 40% of the entire annual volume we do on these SKU’s with the distributor?”  We chuckle, hearing this all the time.  “Yea, well we do sell a lot of them” is basically the only thing we can say.

Another common conversation goes something like this: “Are you sure you want that many of this SKU?  No offense, but this is one of our slowest moving products, and I just wanted to be sure the quantity was correct.”  And our response is always something like, “Really?  That’s one of our best sellers, it’s a great product.”

Narrow and deep.  We only sell what the customer buys – a little trick I learned at HSN (not sure how they do it now).

Kind of makes sense though, doesn’t it?  “Customer-centric”, as they say.  And we are not afraid to completely re-build / re-brand any product we think has potential but has simply not been marketed correctly.  Or to take a “poor selling” product and change the intended use of it, turning it into a best seller. 

In fact, we routinely rip off all the packaging a product comes with and create our own packaging and new name for the product.  Any online retailer who has done a great job marketing a product only to find it appearing in a competitor’s store at a lower price should understand exactly why we do this.  We absolutely love this kind of product.

In many cases, multi-variate testing can improve the sales of any product, but can it turn a dog into a best-seller by completely rethinking it?  Nope, sorry.  Are there any “best practices” a human can follow to repackage a product successfully?

What, are you kidding?

Most pet stores stock a broad range of SKU’s and buy only a few units deep on each.  We buy only a few SKU’s and buy them as deep as makes economic sense – based on volume discounts, weight to value ratio (freight cost from distributor), storage considerations (is the product large relative to value) and so forth.

In other words, everything we do in the Lab Store is really based not on Sales, but on Productivity – how can we generate the greatest amount of profit for the least amount of time, money, and effort?  I realize this approach does not square with conventional wisdom, but the Objective of the store was to replace 1 income (my wife’s) with the least amount of effort possible.  If that is the Objective, then the Strategy is Productivity, not a focus on Sales.

For example, we turn our entire inventory 21.8 times a year.  I’m pretty sure most small (micro?) online retailers in our category ($1 – $5 million in annual sales) don’t care about that stat, but I’m also sure a few of the offliners out there are feeling their jaws hit the desk.  Most of them turn at 5 – 6 times with the really good ones at 10 – 12.  This stat is one of the most important in retail, it’s an “inventory productivity” thing.  And it also points out the economic difference between a narrow-deep and broad-shallow merchandising strategy. 

I know this is going to sound insane to a lot of small online retailers, but in our online store, you do not find a lot of variety, and this is intentional.  What you find is the single very best product for each need a customer has.  And most all except commodity products are priced that way – as the super-premium product in the category.  We carry the commodity stuff not because we want to, but because customers want access to it when they order from us.  It’s a Service decision, not a Product decision.

When customers ask, “Why don’t you have more variety?” we simply tell them we don’t see a need to offer anything but the best product for each need they have. “But don’t you have any cheaper ones?”

Notice, ”variety” here is a code word for price.

“No, we don’t have cheaper ones.  You can find cheaper versions on eBay.  Or try a shopping search engine, if you are shopping only on price.  If you want products we have personally tested, are vet-certified for the particular exotic pet you are dealing with, and are absolutely guaranteed to satisfy your needs, we welcome your purchase.”

As a result, we clearly narrow the ability to attract a wide audience.  But we don’t want a wide audience.  We want an audience and a business we can easily defend against the constant price wars that are a reality of the web.  We knew that would be the evolution, and designed the business that way.  We want a Productive audience, one with high demand for the best, and a low Sales to Service ratio. 

Do you know your Sales to Service ratio (orders / service inquiries) and how to optimize it?  Do your robots?

If we did an on-site survey, I’m sure a lot of casual visitors would complain the store “lacks variety” and is “over-priced”.  That we’re not being customer-centric, don’t you know.  But we are, for the customer we want - she wants a high degree of quality, professional one-to-one advice, extremely fast and accurate execution, all with no hassles.  The rest of these high maintenance, high variable cost ”customers” who are buying single items on price and suck the life out of the business if you let them can go to hell.  Really.  Those shoppers looking for value, which we deliver through aggressive product bundling and flat rate shipping, find it in our store.  And those are the customers we want.

It takes nearly as much effort to process, pick, pack, ship, and service a $40 order as it does a $140 order.  Given that, we prefer to drive higher value orders, and all our marketing is set up to do just that.  We actively discourage low value orders by using flat-rate shipping.  It’s that Productivity thing again; it’s the Strategy, and the store was built from the beginning with that idea in mind. 

Please sir, can you multivariate test that idea for me?

For example, we don’t have a search engine on the site, because we want to force (sorry, I mean “encourage”) customers to look at all our products, and not to cherry-pick the product they originally came to buy.  We specifically and intentionally designed the navigation that way.  And since we have less than 80 products by design, it’s easy for customers to review every product we have very quickly. 

The end idea is ease of use by the customer.  We do it by having fewer products and really smart navigation, not by substituting technology to fix a broken execution.

I know this also sounds insane given “best practices“, but you have to realize that a lot of these “best practices” tests related to on-site search were done on sites with terrible navigation, screwed up product assortments, and lousy merchandising.  In that case, I’m pretty sure a search engine increases conversion.  In our case, a search engine did not increase conversion, but it surely did lower Average Order Value. 

C’mon, do you think I didn’t test it?  Productivity again.

Can we get a multivariate test to confirm search improves conversion on poorly merchandised web sites?  Or can we just look at the site and know it will be true because the nav sucks?

One of things we do very aggressively is cross-merchandise, bundle, and package.  We do it precisely and intentionally within the navigation, which is why a search engine doesn’t help us.  Our approach is not an automated system, it’s a carefully considered marketing decision based on known behaviors.  People who buy this will be interested in this.  We don’t need a computer to do that for us, all we need is intimate knowledge of the customer and some merchandising savvy.  This bundling and packaging doesn’t change, it uses the same format over and over (so the customer gets used to it) and the bundles don’t change dynamically, they are the same for every customer.

Could we have a more sophisticated system?  Sure, but at what cost?  Given we already know what drives buying behavior, we understand pricing theory, we attract a specific audience, and we know what they want, why do we need a machine?  What would the incremental benefit be relative to the cost?

The store itself was built with a $70 copy of FrontPage.  Our monthly costs for hosting and the MIVA Merchant shopping cart (which is all but hidden from the customer except for checkout) is $40 a month.  When the package volume got to 15 boxes a day, we bought a back-end inventory / pack / ship label processing package for $500.  That’s it, that is all the infrastructure there is.  No employees.

Does the store look “slick”?  No.  Doesn’t need to.  Instead, it oozes personality from every pore – the product copy, the newsletter e-mails (which have no offers in them, we never discount or have a sale), the customer service communications – they all speak with one voice.  People adore the site, they think it’s the easiest to use site in the entire category.  People anticipate the newsletter and actually complain when they perceive it to be “late”.

Had any complaints recently from customers about not getting the newsletter?  How about the opposite?

The average product description on our site has over 500 words – even for the most mundane products.  We tell you absolutely everything there is to know about a product.  I noted that the big thing on e-commerce retailers “to do” list for 2008 is improve product descriptions.  Did they need a multivariate test to tell them that?

We have a no questions asked returns policy without a restocking fee.  We can do this because we anticipate product problems by extensively reviewing every product..  If a product is difficult to assemble, we assemble it before we ship.  If the assembly instructions suck, we re-write them and include them with the product.  Sounds like a lot of effort, until you find out we have a return rate of 3% on units and 1% on dollars.  Yea, it’s that Productivity thing again…

What is missing in web analytics today, with all due respect to both sides, is people who understand both the Marketing and the Technology aspects of web Behavior and Analytics.  Optimization is in the middle, not at the extremes.

Following “Best Practices” leads to commodity positioning, as everybody plays Monkey-See Monkey-Do (MSMD).  The constant benchmarking that is part of the IT culture is simply wrong-headed for Marketing; why does it matter what the other guys do, especially if they do a crappy job?  Do you take pride in the fact you benchmark better than some of the crappiest folks on the planet?  That your site / performance sucks less than theirs, but still sucks?

Do you have a Marketing Strategy, and do you execute in line with it, down through every fiber of the company?  Substituting brute force robotics or worship of MSMD best practices will never replace a great Strategy.  If you are at the point where all you can do is test things to death, perhaps you need to rethink your Strategy instead.

Please understand, I am not saying you should run your commerce operation like we do.  I’m just saying there are other, highly successful ways to do it and blindly following Best Practices and robotic testing – for any web operation, commerce or not - should be reconsidered.

Have a question on Customer Valuation, Retention, Loyalty, or Defection? Go ahead and send it to me here. If on the topic above, you can leave a comment on the post:

Lab Store: Web Merchandising

Back in the old days (meaning the 80’s), what I guess is now called WOW was referred to as “surprise and delight”.  Essentially, this 2-step idea works like this: when you surprise the customer, you really get their attention.  If you can get their attention by surprise and delight them at the same time (instead of pissing them off with your surprise), then you are going to have a more loyal customer.  The trick, of course, is to somehow make more money doing it…

New Customer Kits are a very simple way to do this, and in my remote retailing experience, it works every time.  First impressions, in case you didn’t know, are really important – and especially so in remote retailing, where there is no way for the customer to get any tangible “feeling” for the company.  Sure, you have copy on the web site that paints a picture.  But how many times have people read all this wonderful copy only to be screwed when delivered the tangible experience?

The challenge is to design a kit that is relatively inexpensive yet packs an emotional delight.  Lots of people toss extra stuff for the customer in the first order, but that stuff is usually company-centric, for example, “Here is a magnet with our URL on it” or “Here is a catalog of our other products”.  That’s fine, but it’s neither surprising nor delightful.

Here is what makes up a good New Customer Kit, based on years of testing:

1.  A letter or other message from the company that Welcomes the customer, talks about the people and philosophy behind the company, and reinforces any guarantees or promises that are part of the Brand.  This piece must be written carefully, and from a customer-centric point of view.  No “we we” stuff.

2.  A free gift.  This gift must be related to the merchandise or general category being purchased, and must not be discards, seconds, or defective merch.  Giving a new customer something that is dented or discolored is not a gift, it’s an insult.  Giving a new customer something that is promotional (magnet) may be a gift, but it is expected and not particularly delightful.  Giving a new customer a “gift” because they made a first purchase (Buy today and we’ll include a…) might be delightful but sure is not surprising.  Ignore the above cautions at your own peril.

3.  Free Samples, if relevant to the business.  Anything that is consumable and generates repeat purchase is ideal.

Anyway, I suppose you’re expecting some kind of numbers to go along with all the fuzzy-wuzzy “Oh, if we just make their experience better, they will be more loyal” drivel you hear all the time online.  This is the Marketing Productivity Blog, after all, right?  OK, here are the stats on this technique from the Lab Store.  As usual, this promotion was tested versus control (new customers who did not receive a New Customer Kit are control) and we compare sales activity of both test and control over the next 90 days.  Why 90 days?  Well, if it makes money at 90 days, it sure makes money at 120…

Average cost of New Member Kit (there are several versions) – $.74

Increase in 90-day second purchase rate, test versus control – over 30%

90-day ROMI – 4,891%  ($36.68 in net profit for every $.75 spent)

Surprised and Delighted Customers – Priceless

Now that the bottom line has been presented, the black box folks simply interested in the “what happens” can skip the next part.  If you want to know why it works and maybe learn something useful you can port elsewhere, read on.

New Customer Kits are a great way to shape Theatre of the Mind. 

What you have with a remote retailing customer is a ”theatre of the mind” scenario, much like you have in radio advertising.  Customers can’t see or touch you, so “Cues” become extremely important; if you don’t populate the theatre of the mind for the customer, the customer will go ahead and populate it themselves.  If you want some control over the image of your company people create in their head, you need to be proactive.  Theatre of the mind, folks.  Very powerful stuff. 

Our New Customer Kit generates absolutely tons of “Thank You” e-mails from new customers who want to tell us all about how great the experience was purchasing from the Lab Store.  Now, I think you’d agree that purchasing from a web site isn’t a particularly thrilling experience in any way, but if you really listen (and understand a bit of Consumer Psychology) these customers are not really talking about the web site, or even our company.  

What they really are saying is they are very happy with themselves for making a first purchase from us; our actions have confirmed they made a good decision.  Remember, this is remote retailing.  There is risk to the customer, especially on that first purchase; they have no idea if their expectations based on the web site copy are going to match the reality of delivery.  They are concerned about what might happen – will they be proven smart or dumb for taking this risk?

When we deliver the products they ordered in a timely way we meet expectations.  When we deliver these products carefully packed in a pristine new box packed with fresh blank newspaper, we probably exceed expectations by a bit.  But when these new customers get to the Welcome letter, the free gift, and the samples, we blow out their expectations. 

The picture these new customers had in their mind of our company based on the web site experience is then permanently altered; we’re doing brain surgery for 74 cents a head.

Now, I have a question for you – is this program Marketing or Customer Experience Management?

Have a question on Customer Valuation, Retention, Loyalty, or Defection? Go ahead and send it to me here. If on the topic above, you can leave a comment on the post:

Measuring Customer Experience ROMI #2: Lab Store – New Customer Kits

Here is a real world example from the Lab Store.  I am constantly fighting the Google AdWords A/B split testing algorithm for rotating ads.  Google almost always picks the wrong ad to run more frequently so I have to force it to run 50 / 50 in order to get accurate results.  How do I know Google is picking the wrong ad?  Because I have seen thousands of such tests, online and off, and I have a “feel’ for these things based on my background in Database Marketing, Consumer Behavior and Psychology.  In each case where Google has picked one ad over another, and where I have forced it to then run the ads 50 / 50, it ends up I was right – Google picked the ad that generated the least profit per dollar of PPC spend as “best” and demoted the more profitable ad until it was not running at all.

Why does this happen?  Because Google isn’t smart enough to understand the complexity of the customer behavior in the Lab Store - and it can’t be, given the number of clients it has.  If you have done a lot of this kind of testing, you know that often the campaign with the highest response rate generates the lowest quality customers.  While these campaigns were running, I could see that the visitors generated by the campaigns Google picked as “best” were actually inferior to the visitors generated by the campaigns Google demoted, using a variety of metrics other than conversion (primarily Recency).  In other words, I was able to predict Google was doing the wrong thing by looking at the Customer LifeCycle.  When I forced Google to run the ads 50 / 50 to give the demoted ads a chance, I was proven right – the campaigns Google demoted had a 90-day ROMI averaging 2.1 times higher than the campaigns Google promoted.

Look, I know these are software companies and their sole purpose in life is to create the next big thing and sell their software into it.  That’s fine, and frankly, I hope they are successful in doing it, because it will create a tremendous amount of business down the road for database marketing consultants as “machine optimization” hits the wall and companies need to be rescued from the results of it.  Just like they had to be rescued from demographic clustering in the 80’s and data mining in the 90’s. 

People are always looking for the easy way out, and it ends up costing them more in the long run because they don’t really understand what the tool does and does not do.  Perhaps that is simply the state of Marketing today.  So be it…

If you are an analyst and you see a black-box test result that simply does not make any sense based on your past experience, I encourage you to question the result, find a way to test it outside the system.  Learn why, because this kind of incident usually will lead to a shattering of some myth or bias you will be most happy to fully understand.

Have a question on Customer Valuation, Retention, Loyalty, or Defection? Go ahead and send it to me here. If on the topic above, you can leave a comment on the post:

Lab Store: Automating Worst Practices

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:

Remember
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?

Have a question on Customer Valuation, Retention, Loyalty, or Defection? Go ahead and send it to me here. If on the topic above, you can leave a comment on the post:

Lab Store: The Next Inspector