Marketing Productivity Blog

After the lessons we learned in the Band 1 and 2 Optimizations (see Band diagram) for HSN, we were able to reallocate that budget to invest in Band 3 - Optimizing the Interface.  We realized during the previous Optimizations we were already getting a tremendous amount of traffic through channel surfer / clickers, but this traffic was not “converting”.  In other words, we really needed to Optimize the “Landing Page” for this existing audience - the TV show itself.

Don’t suppose the above scenario sounds at all familiar to the web analytics folks out there - you know, “more traffic, any traffic” is the answer?  Oops, maybe not, what about higher conversion?

I won’t bother providing the Band 3 example for the web; you all know what Optimizing Landing pages / web sites is about, or can certainly find that info elsewhere.  However, you might find the Optimization of a TV shopping channel interesting…

A little background first.

You probably don’t know how interactive HSN was, at least back then; the show just looks like somebody talking about products.  What you don’t know is there is a huge multi-screen war room setup steering the ship.  Every competitor monitored live in real time, along with all major TV networks.

Somebody is burning a flag on the steps of the Supreme Court, and every TV network is covering it?  Start selling American flags.  Folks on the Today Show say “blue is the new black”?  Put on blue clothing all day.  Competitor selling a product we have in inventory?  Put the same product up at a lower price.  The war room was a wild place - and especially so with 3 of these networks, all live, going full blast at the same time, 24 hours a day!

So first, HSN was interactive with the “environment”, followed trends rather than trying to Market against them.  Customer demand (sales per minute) declared what to put on a show; if they wanted to buy it, we wanted to sell it.  If they didn’t want to buy it, we tried to get rid of it by cutting price.

Sound familiar?  A bit like keyword phrase / Search analysis, perhaps?

HSN was also interactive with customers.  There are the callers you hear on TV, of course.  What you probably don’t know is all TV Shopping customers are absolutely chock full of comments about the products and presentations, and these are tracked and reported on the very next day.  Every day we had a sales meeting to review the prior day - how could we have done better - and as part of this meeting, we reviewed customer comments from the previous day, and tried to take action on these comments. 

To put some context around these daily sales meetings, the President of the company ran the show, and  the attendees were all VP or above.  It was the most important meeting anybody had.

Every day.

The kind of meeting a company might start having to really leverage the power of Interactivity and the output of Social Media, perhaps?  We’re talking about close to a billion dollar in sales company at this time, not a start up.  We sold management on the importance of an Analytical Business Culture.  You can too.

So, we have this pretty interactive system despite the one-way technology of TV, and Marketing now has budget to try and Optimize it.  What would you do, how would you improve this?

Here’s where we ended up, in some cases after years of working through the testing:

1.  Feed customer comments from the call center to the show host live.  We invented a system to send customer comments in real time to the host of the show.  They scrolled on a screen as the host was pitching the item, and could be tremendously effective in improving sales.  When I heard of people Twittering about speakers at conferences, that reminded me very much of this functionality.

2.  Capture successful interactions in the product database for review later.  After the show, the hosts would enter notes on which customer comments “worked” for specific products and allowed them to sell at a higher velocity.  These “best of” ideas could then be reviewed by any host who would be selling the product.

3.  Make real time testing actionable in the future.  There was a lot of testing in real time besides the host pitch - changing displays, lighting, formats, etc.  However, there was no “system” for capturing these ideas, it was all “gut” and learned by practice.  So we did the same as with the comments above - got these “tips and tricks” loaded into the product database so show prep folks and producers could get a leg up using the experience of others. 

Not exactly A / B testing, but there’s no A / B in live TV, you have to look at historical performance in the same Dayparts - and we did.  More on this in the next initiative…

4.  Program to the audience.  The very difficult thing with selling product on TV Shopping versus the web, of course, is that you are selling one product at a time.  How do you Optimize that? 

We studied the buying patterns - rowing machines sell best on Sunday mornings, Fashion on Tuesday nights, kitchen stuff at 3 PM weekday afternoons.  In other words, Dayparting. 

The audiences change throughout the day, and they have a different composition on Weekdays versus Weekends.  Optimize the product presentation to the audience.  Using Nielsen ratings for this Optimization would be a “Push” approach.  By using buying behavior, we were using a “Pull” approach - sell them what they have told us they want to buy using their actual behavior.  By the hour.

 5. Implement the best performance metrics and controls.  In the early days, Gross Sales per Minute  were everything.   Analysis proved that return rate and price had a very high correlation, which in this case was indeed causation - and we proved this with price testing. 

So we came up with the idea of an “average price per show” which would minimize return rates based on Daypart.  Literally, we found that the time of day a high priced product was sold influenced the return rate.  This was an improvement, but the system could be gamed by smart hosts looking to drive bonuses.

So, we converted from Gross Sales per Minute targets to Net Sales per Minute targets - net of returns, actual if available or forecast based on like item history, all in real time.  But in the case of some high volume categories with thin margins, this was not Optimal either.  So ultimately we made it to Net Gross Margin per Minute as the final sales metric.  Very similar to moving from ROAS to ROMI.

This series of “Business Rules” linking price, return rates, margins, and time of day basically ensured that even in a completely dynamic, real time environment, the whole system was Optimized for profit.

Do you wonder if a Dayparting approach could improve your commerce profits on the web?  Based on what I’ve seen, I’m pretty sure it would, as long as the costs of implementation are not prohibitive.

Question:

Look at these 5 ideas above.  Ask yourself if any of this is what you think of as “Marketing”.  These ideas are in reality a series of very intensive IT projects (on MainFrames!) involving telecommunications, core systems architecture, programming / code, and more.  Why was Marketing involved?  None of this is about ”Creating Ads”.

Marketing was involved because we insisted on being involved.  In an Interactive system, you can’t Optimize Marketing until you Optimize the systems delivering the Interactivity.   Those of you Optimizing web sites are quite familiar with this concept by now.

It’s about removing Friction.

Said another way, these ideas were all directly related to Voice of the Customer, Customer Experience, and long-term Customer Satisfaction.  The better HSN was on these issues, the more successful Marketing programs would be in terms of increasing Customer Value. 

Engineers are smart people, but if they knew everything, then why would web sites, VRU’s, or countless other machine-human interfaces have to be Optimized?  For best results, you really need both brains working together on these systems from the beginning.  iPod / iTunes / Mac is the most recent example - the Marketing Strategy is built into the product from the very beginning.

Failing this ideal world (and many companies are not there yet, for sure) analysts must get these Interactive systems Optimized before addressing the next challenge - Optimizing Customers - which begins in Band 4.  Otherwise, Marketing success will be undermined by Friction instead of driving incremental Customer Value.

For more on Measuring and Managing Friction, See Chapter 5 in the book sample PDF.

Any questions on the approaches / testing / decisions above?

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

Not sure if all the web analytics folks out there will appreciate this post, but I’m pretty sure at least some of you are interested in how all the things we talk about in the Web Analytics / Database Marketing world fit into the larger world of Marketing.  So following on a question from Judah on depth of segmentation, and a post you should read from Gary on joining behavioral and demo / psycho segments, I thought I would offer this example.

One of the challenges people seem to have with behavioral segmentation is finding a way to organize it in their mind.  It just seems too overwhelming to think of Marketing to individuals at the “right time” based on behavior as opposed to some “calendar” idea where you communicate to everybody at once. 

If you want to create a “structure” or “process” to hang behavioral communications on, try this one.

Below is a chart I created in 1993 to explain what Marketing looked like at HSN (you can click for a larger image in a new window):

The format for each level in the chart is:

Type of Marketing
Purpose of Marketing
Tools / Tactics

I’d like to point out a couple of things.

1.  Note that I used the word “Process” in the title.  This is reflective of a real step by step road the customer takes, as opposed to a “Marketing Blast” kind of idea.  Each step has a specific Goal and Outcome and is measured that way; some measurements are more precise than others.  For example, in this world, “Brand-ing” has a role but it’s a specific role, it’s not “everything”.  By the way, “Affiliates” in this case are cable systems carrying the HSN signal.

If you like, this is what the AIDAS Strategic model looks like when you fill it with Tactical Action programs.  It’s also representative of the “cascading metrics” methodology covered extensively in Akin’s book.

2.  I suppose no web analyst out there missed the fact this chart looks like a funnel.  It is.   The difference between this funnel and a “Scenario” funnel is you don’t really have knowledge of “who” in the top 3 layers, these targets are “audience” as opposed to individual visitors or customers. 

In terms of segmentation, these top 3 layers are the psycho / demo ideas; as soon as you pass Level 3 you are into the first purchase, where the segmentation becomes behavioral.  Since at this point we have real data on the customer, the behavioral segmentation is more actionable than demo / psycho in terms of increasing customer value. 

The widest “Reach” is at the top layer, but it’s the least targeted.  The finest segmentation is at the bottom layer, where the Marketing is absolutely hyper-targeted and very specific to the individual customer.

3.  You can see on the far right two continuums (continnua?) - Mass to Targeted Marketing and Push to Pull Marketing.  The transition area between the two is the 3rd to 4th layers (dark bar in the Push / Pull continuum), where you get into Retention and Continuity Tactics; now that you have customer data you can engage in these activities.

Generally, these shifts happen pretty much together, so Mass Marketing = Demo / Psycho Segmentation = Push Marketing, and Targeted Marketing = Behavioral Segmentation = Pull Marketing.

4.  Another way to view this chart is as the Customer LifeCycle, which starts with general Awareness and ends with Customer Defection and a final tally of LifeTime Value and ROMI.  At HSN, the Catalog business generated the most incremental value as a Retention Device, so it kicks in on Levels 6 and 7, first as a general merchandise idea, then as a very targeted category idea. 

For those of you wondering where the web is on this chart, we bought the first web property in 1994, after this chart was created.  But on the web, the core idea is much the same.  Different tactics have different primary purposes and they should be treated and measured that way, not just “Blasted” out in one continuous Marketing puke.  

The impact of these tactics should be measured at the customer level (not campaign level) whenever possible to really understand the net value added.  That’s how you optimize the system.

Now, I have two questions for you:

1.  Did this chart help explain at all what the heck I’m talking about on this blog, or some other Marketing / Analysis issues?

2.  Do you have any questions?

I could go on and on about this chart in my language, but I would rather have you (especially the tech-oriented folks) ask questions in your own language, since:

* It seems like we get better knowledge transfer that way!

*  I don’t know what you don’t know; stuff that’s obvious to me after 25 years of Marketing is probably completely opaque to you.

So, any questions?

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

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

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

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

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

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

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

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

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

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

That experience, my friends, is pure adrenaline.

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

IN-line Marketing, that is.

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

And how to optimize this junction.

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

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

Behavior.  It’s the key to everything Interactive.

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

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

Relevance, which is forecast by Behavior.

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

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

Form + Function (AdWeek)

Application Economics (AdWeek)

Want more?  Some related material:

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

The Great Leap Forward (blog)

Value Is the New Currency (ClickZ)

What do you think? 

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

Friend and fellow blogger Alan Rimm-Kaufman spent some of his valuable time asking my opinion on various online marketing issues in a far-ranging interview and podcast.

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!

The average ecommerce / catalog packer can pack about 22 - 25 boxes an hour, depending on the level of automation.  Of course, we don’t have anything like traditional mail order automation in the Lab Store; just a computer, a printer and my wife Barb as Chief Packer & Chief Customer Officer.  I pitch in by assembling products and generally keeping the “warehouse” shelves stocked so the Chief can do her thing with the packages and customers.

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.

Information Week gives us this article: Step Up - or Step Back.  Before the Marketers in the audience click Back, I think you should read this article. 

Lead Data: From the annual meeting last month of the Society for Information Management, the percentage of CIOs and other top IT executives reporting directly to CEOs had fallen dramatically from the year-earlier survey, SIM revealed.

The premise is basically this: the “Command and Control” CIO is on the way out; these are the folks that are dropping in rank and no longer reporting to the CEO.  At the same time, we find CIO’s that are business oriented and advocates for process improvement are moving up and more of them are reporting to the CEO.

Makes sense to me.

There seems to be a lot parallels between what is going on with CIO’s and CMO’s; both are looking for a seat at the strategic table.  And both need to become more business-oriented to do it.  I think “business oriented” here is probably just a code word for “more accountable for what you contribute”.  In the case of CMO’s, this includes reaching out into the operational side of the business and finding out how operations affects the success of Marketing.

To go a step further, wanna-be CIO’s and CMO’s not afraid of an accountable orientation would do themselves a huge favor by reaching out to each other; otherwise both or either may be “absorbed into the Network“. 

This pattern playing out over in CIO-land has some lessons for those (mostly analytical) Marketers who aspire to the CMO seat.  If you do aspire to be CMO, read about the CIO’s who do report to the CEO and the business attitude that got them there - the same attitude you need.

Here’s that article link again: Step Up - or Step Back

Or Behavioral Messaging, as we used to call it. 

Much has been written about Measuring Engagement, but once you measure it, then what do you do with this information?  Most folks know the idea driving the Engagement Movement is to make your messaging more Relevant, but how do you implement?  Perhaps you can find the triggers with a behavioral measurement, but then what do you say?

This is the part Marketing folks typically get wrong on the execution side.  They might have a nice behavioral segmentation, but then crush the value of that hard analytical work by sending a demographically-oriented message, often because that is really all they know how to do.  So as an analyst, how to you raise this issue or effect change?

Marketing messaging can be a complex topic, but there are some baseline ideas you can use.  Start here, then do what you do best - analyze the results, test, repeat.

You want to think of customers as being in different “states” or “stages” along an engagement continuum.  For example:

• Engaged - highly positive on company, very willing to interact - Highest Potential Value
• Apathetic - don’t really care one way or the other, will interact when prompted - Medium Potential Value
• Detached - not really interested, don’t think they need product or service anymore - Lowest Potential Value

Please note that none of these states have anything to do with demographics - they are about emotions.  The messaging should relate to visitor / customer experience as expressed through behavior, not age and income.

These states are in flux and you can affect state by using the appropriate message based on the behavioral analysis.  Customers generally all start out being Engaged (which is why a New Customer Kit works so well), then drop down through the stages.  The rate of this drop generally depends on the product / service experience - the Customer LifeCycle.

Generically, this approach sets up what is known as “right message, to the right person, at the right time” or trigger-based messaging.  Just think about your own experience interacting with different companies; for each company, you could probably select the state you are in right now!

OK, so for each state there is an appropriate message approach:

Engaged - Kiss Messaging: We think you are the best.  Really.  We’d like to do something special for you - give you higher levels of service, create a special club for you, thank you profusely with free gifts.  Marketing Note: be creative, and avoid discounting to this group.  Save the discounts for the next two stages.

Apathetic - Date Messaging: We’re not real clear where we stand with you, so we’re going to be exploratory, test different ideas and see where the relationship stands.  Perhaps we can get you to be Engaged again?  In terms of ROI, this group has the highest incremental potential.  Example: this is where loyalty programs derive the most payback.

Detached - Bribe Messaging: You’re not really into this relationship, and we know that.  So we are simply going to make very strong offers to you and try to get you to respond.  A few of you might even become Engaged again.

Can you see how sending a generic message to all of these groups is sub-optimal?  Can you see how sending an Engaged message to the Detached group would probably generate a belly laugh as opposed to a response?  You’ve received this mis-messaged before stuff, right?  You basically hate the company for screwing you and then they send you a lovey-dovey Kiss message.  Makes you want to scream, you think, “Man, they are clueless!” and now you dislike the company even more.

Combine this messaging approach with a classic behavioral analysis, and you now have a strategy and tactic map.  For example, you know the longer it has been since someone purchased, clicked, opened, visited etc, the less likely they are to engage in that activity again.  Here’s the behavioral analysis with the messaging overlay:

Click image to enlarge…

Please note “Months Since Last Contact” means the customer taking action and contacting you in some way (purchase, click) not the fact that you have tried to contact them! 

So does this make sense?  Those most likely to respond are messaged as Engaged - as is proper in terms of the relationship (left side of chart).  As they become less likely to respond, you should change the tone of your communication to fit the relationship up to a point, where quite frankly you should take a clue from the eMetrics Summit and not message them any more at all (right side of chart).

Example Campaign for the Engaged: At HSN, I came up with the idea of creating some kind of “Holiday Ornament” we could send to Engaged customers.  If the idea worked (meaning it generated incremental profit), we could do it as an annual thing; we could put the year on the ornament and create a ”collectible” feel, which is the right idea for this audience.  No discount - just a “Thank You” message “for one of our best customers” and “Here’s a gift for you”.

These snowflake ornaments were about $1.20 in the mail (laser cut card stock) and generated about $5 in 90-day incremental profit per household with the Engaged, test versus control.  Why?  Good ‘ol Surprise and Delight, I would bet.

We had some test cells running to see how far we could take this, and as expected, the profitability dropped off dramatically based on how Engaged the customer was.  If the customer was even minimally dis-engaged - no purchase for over 120 days - there was very little effect. 

Interactivity cuts both ways; it’s great when customers are Engaged, but once the relationship starts to degrade, folks can move on very quickly emotionally.  That’s why it is so important to track this stuff - so you can predict when your audience is dis-engaging and do something about it.

Seems like every day I hear about a new way to stick ads in front of people online or through a mobile device.

Every new business model is advertising-based and is going to attract billions of dollars.  Companies are out there buying other companies that are basically worth nothing for billions of dollars based on the promise of ad revenue.  This despite the fact (for example) social media advertising has really sucked - and is getting worse.  Plus, there’s the fact nobody will pay for social media services.

Further, ask yourself this question: what if social media advertising does suck and will always suck because it is simply always out of context?  To be clear, by context I mean not the content surrounding the ad, but from the end user perspective.  If people hate seeing your ads while they are trying to do personal stuff, won’t the advertising always be ineffective?  That fundamentally, the advertising model for this kind of content is flawed and will not get better? 

Can you say GeoCities?

This situation reminds me of the dot-com “ads on your car” thing, which got so ridiculous that companies were actually giving away FREE CARS to people as long as they drove them around with ads on them.  How do you ever pay that back?  And how are those ads effective?  I guess there are a ton of marketing rubes out there who will buy any ad just to get the “exposure” - regardless of how out of context the exposure is.  Do they still sell ads on matchbooks?

But let’s not stop there.  For some reason I can’t get the economics of supply and demand out of my head.  If every single display surface online becomes a display ad, doesn’t that mean there will be an unlimited supply of online display advertising and so the value of online display ads will drop close to zero?  Perhaps a lot closer to the economic value most of these ads provide?

You tell me.

At least with eyeblack advertising, there is a limited supply - teams on televised sporting events (TV is actually the media, not the eyeblack).  That is, until somebody comes up with the idea of paying people to wear eyeblack ads - which can’t be too far away, can it?

Hey, I have an idea…want to make a billion dollars?  Know any marketing people just dying to buy this kind of “walking around” media?  Fortunately, I think the buy side has pushed back and is a lot smarter as a whole.

The above is not to say that specific exotic media will not work for certain very targeted applications.  The problem is in thinking any of this media is “mass” in nature, that it will be able to move the needle.  If the applications for this advertising are very narrow, then only certain narrow portions of the inventory have value, meaning the value of the companies is a lot lower than what is perceived.

Personally, I think the same thing will happen in mobile.  The killer advertising app for mobile is search, not display or audio, whether geo-intelligent or not.  Search fits the context of the user, just as search does online.  Free mobile services if you listen to an ad first?  C’mon folks, that model has been played and played online and it never works.  The combination of audience quality and the notion of being “forced” to pay attention do not equal great advertising results.

Your Ad Everywhere, as a whole, is an economically broken business model that delivers little value to either the advertiser or the audience.  Let’s just stop creating business models based solely on delivering display ads to people.

I suggest to you the test for the viability of an “network effect” display ad business model is very simple: ask the audience, would you pay for this service / application / access?  If the answer is no, the audience is not a viable advertising audience.  If the answer is yes, then you can look for ways to reduce billing by introducing the right kind of advertising.  This means, of course, that these networks will be much smaller, but have a high quality audience worth advertising to.

If you start with free, you have already poisoned the audience for any ad model relying on “impressions”.

Yes, I know for many marketing folks this seems to be an oxymoron, but the fact is that Marketers - especially those with some understanding of business process and the IT world - can influence the direction of IT and generate genuine customer-centric wins.  This in turn makes all your marketing efforts more productive. 

Web analysts, this is the kind of work you will be supporting with analysis in 5 years…it’s just a much larger version of optimizing a web site, isn’t it?  And in many ways, a lot more fun…

Requires a different mindset?  Sure, it’s not buying media or developing creative or analyzing response.  But these are the kinds of projects Marketing folks (especially data-driven ones) should be championing by providing the customer models for IT to base a plan on and forge ahead.

Here are 3 great examples, case studies from CIO Magazine:

Washington Mutual  - a classic example of cross-functional teams looking at “how we sell” versus “how they buy” barriers; reminds me a lot of the Check Shredding Example.  I wonder how many online Marketing folks at banks have asked “why do we need signature cards?” in the past 5 years - what is the Root Cause?  Ron, make sure you check this one out, especially given your post - what do you think?

Best Buy - the offline retail version of “people who bought this also bought that”.  I’m sure this one will sound simple to many folks - all except those working in offline retail analysis and store logistics, that is.  A tough, messy business to optimize and even small wins are remarkable.

Hilton Hotels - another seeming no brainer, just let people order online.  But not just any people, we’re talking about event / conference planners ordering meeting rooms, food and beverage, A / V etc. not to mention guest rooms for thousands of people.  This is not a small deal on the infrastucture side, with plenty of politics to go around.

Check the cases out here, and let me know what you think.