Inefficiency

The best reason to dig into Online Marketing Simulations (buy the book, purchase via Kindle, or buy a digital download) is to find inefficiencies in your business.

Here's the deal. The vast majority of online marketing focuses on "easy conversions".

• SEO --- close to free.
• E-Mail via batch-based campaigns --- close to free.
• Promotions --- free shipping, % off, GWP, PWP.
• Paid Search --- expensive, but better when coupled with a promotion.

There are what I call "hard conversions". These are the conversions that happen the old fashioned way, when a customer finds your product so compelling that they cannot resist it. Hard conversions often lead to loyal customers.

So the goal is to find hard conversions that lead to long-term value. That's not easy. But that's what the OMS methodology enables you to do.

See, you'd rather get half of the clicks if it means that those customers are worth double or triple the value of easy conversions, right?

I'm here to tell you that Online Marketing is inherently inefficient. The entire ecosystem, and the Web Analytics solutions that measure the ecosystem, create a giant feedback loop based on easy conversions. It's easy to see how the conversion funnel worked via Google Analytics.

Now try to use Google Analytics to measure the five year simulated trajectory of your business, based on the customers who fall through the purchase funnel and eventually convert. Or Omniture. Or Coremetrics.

We use Online Marketing Simulations to find inefficiencies, seeking to optimize the long-term health of our business. Those who use Online Marketing Simulations have a clear competitive advantage over those optimizing the business based on conversion rates.

Optimizing Customer Acquisition

Buy the book on Amazon.com, or buy the Kindle version here. Finally, e-mail me for a copy of a free OMS spreadsheet so that you can follow along with our examples.

Ok folks, open up your spreadsheets. Take a look at the five year sales projection for this business.

• Year 1 = $75.9 million.
• Year 2 = $70.4 million.
• Year 3 = $66.7 million.
• Year 4 = $64.4 million.
• Year 5 = $62.9 million.

Now let's try something different. Go down to the customer acquisition portion of the spreadsheet, and do the following:

• Enter "0" into cell B452.
• Enter "10,142" into cell B441.
• Enter "11,463" into cell B443.

Look at the five year trajectory of this business:

• Year 1 = $75.8 million.
• Year 2 = $70.5 million.
• Year 3 = $67.1 million.
• Year 4 = $65.0 million.
• Year 5 = $63.9 million.

This doesn't look like much of a difference, does it? Of course, we're only looking at changes to three of 240 different customer acquisition segments.

Here's the point I want to make. Those of us in the Web Analytics and Online Marketing community do everything possible to improve conversions today. This creates inefficiencies in our business. Use the OMS framework to understand the customer acquisition strategies that improve the health of your business long-term.

Think about being in this business five years from now ... having an extra million in demand might mean an additional $400,000 in profit, enough money to save five jobs.

All of these little details add up over time. When we optimize our business for today, we potentially cost ourselves our job in the future.

A Laundry List Of Attributes

There's no reason that an Online Marketing Simulation (buy the book at Amazon.com or buy the Kindle version of the book) has to focus only on e-commerce purchase attributes.

For instance, here's a laundry list of attributes that are worth capturing:

• Customer subscribes to e-mail campaigns.
• Customer unsubscribes to e-mail campaigns.
• Most recent e-mail campaign click-through date.
• Customer only buys via free shipping.
• Customer prefers expedited shipping.
• Customer frequently abandons shopping cart.
• Customer never abandons shopping cart.
• Customer spends more than 15 minutes on your site.
• Customer spends less than 15 seconds on your site.
• Customer likes visiting clearance/sale pages/products.
• Customer actually read your privacy statement (hint, pay attention to this).
• Customer participated in live chat.
• Customer clicked on Facebook or Twitter icon.
• Customer generated a review of one of your products.
• Customer volunteers demographic information.
• Customer gave you contact information in an offline channel.
• Customer who clicked on "contact us" link.
• Customer watched one or more of your videos.
• Customer is a proprietary credit customer.
• Customer buys gift cards for others.
• Customer redeems gift cards.
• Customer clicked on your "careers" link.
• Customer clicks on your store locator link.
• Customer adds items to a "wish list".
• Customer clicks on your "Espanol" link.
• Customer returns merchandise.
• Customer returns more than 2/3 of merchandise purchased and has purchased 3+ times (hint, stop marketing to this customer).
• Customer purchased an extended warranty.
• Customer asks to have product automatically sent to her on a monthly basis.
• Customer utilizes rebates.
• Customer shops by brands.
• Customer shops by products.
• Customer enlarges images.
• Customer clicks on Top Sellers.
• Customer clicks on a toolbar to share products via social media.
• Customer clicks on "read reviews".
• Customer abandons items rated at two or fewer stars on a 1-5 scale.
• Customer uses site search function.

And on and on and on the list goes!

Take this information, and categorize the customer into one of forty segments, based on all of the information in the list. Combine the forty segments by five "grades" of productivity (A, B, C, D, F), and you have the perfect setup for an Online Marketing Simulation!

Subtle Differences

Buy the book on Amazon.com, or buy the Kindle version here!

Time to open up your spreadsheets! (e-mail if you would like a copy).

Ok, enter the value "0.00" into cells C6 - G6. Next, enter the value "0.00" into cells B101 - B340. Finally, enter "1,000" into cell B189.

Next year, we'll retain 38.4% of these customers (cell C11). These customers will order 1.49 times (cell C16), buying 2.47 items per order (cell C17), paying $48.02 per item (cell C18). Notice that as time goes by, these customers become more loyal, buying more expensive items. By the end of year five, these customers are purchasing $83.00 items.

Now, enter "0.00" into cell B189. Enter "1,000" into cell B190.

Next year, we'll retain 36.8% of these customers (cell C11). So basically, these customers are very similar to the customers outlined earlier. However, these customers will order 1.6 times next year, buying 3.0 items per order, paying $40.89 per item.

In other words, these customers are subtly different --- about the same repurchase rate, but buying more items per order, and buying cheaper items as well.

Over time, these customers also buy more expensive items, but only spend $71.89 per item by year five. But notice that these customers are worth more in year five than the customers in the first segment (spending $77,000 in year five, vs. $57,000 in the other segment).

There are such subtle differences between customers in the businesses we manage. Our dashboards and reports suggest similarities. Over time, similar customers with subtle differences in purchase behavior diverge, becoming fundamentally different customers. When we optimize our business for short-term results, we miss out on the things that cause us to have a healthy business in the long-term.

Firing Customers

E-mail me if you want a copy of the OMS spreadsheet to follow along with on our examples. Click here to buy the book on Amazon, or click here to purchase the book for your Kindle.

The concept of firing customers is a popular one. We read a lot of content that tells us to focus on the 20% of our customer base, the part of the customer base that generates most of the demand.

I'm not here to tell you that the strategy is right or wrong. I'm here to give you the tools to understand what it means to fire customers.

In our OMS spreadsheet, we grade customers with a grade of "A", "B", "C", "D", and "F". So today, we're going to attempt an experiment.

Open your spreadsheet. Notice the five year sales trajectory of this business.

• Year 1 = $75.9 million.
• Year 2 = $70.4 million.
• Year 3 = $66.7 million.
• Year 4 = $64.4 million.
• Year 5 = $62.9 million.

Clearly, this business is in free fall. So, let's do something odd. Let's fire every customer with a grade of "D" or "F". These customers cannot purchase again, ever. We'll literally block them from buying from us. Any customer that falls into a grade of "D" or "F", during the next five years, is prevented from buying again in our simulation.

Enter the value "0.00" into cells C245 - C340. This means that customers with a grade of "D" or "F" cannot buy again. We'll keep acquiring new customers. Take a look at the results.

• Year 1 = $73.4 million.
• Year 2 = $66.1 million.
• Year 3 = $60.4 million.
• Year 4 = $56.1 million.
• Year 5 = $52.9 million.

In the first year, firing customers has almost no impact on sales ... sales decrease from $75.9 million to $73.4 million.

In the fifth year of the simulation, firing customers has a significant impact on sales ... sales decrease from $62.9 million to $52.9 million.

Your job is to determine if this type of decision increases profit, or decreases profit. My job is to show you that there is a cumulative impact that results from the decisions we make today. So many of us in the Web Analytics community and Online Marketing community look to optimize conversion rate, seeking to optimize the performance of the business today.

Hint: The Online Marketing world is "inefficient". When everybody is trying to optimize short-term results, you gain a competitive advantage by optimizing long-term performance. Use the OMS framework to do this!!

Digital Download Now Available: Online Marketing Simulations

Oh sure, I can offer merchandise across multiple channels!

You can buy the book on Amazon.com, $19.95 --- click here.

You can buy the Kindle version via Amazon, $4.99 --- click here.

And now, you can purchase a digital download of the new book for $4.99 via Lulu.com --- click here.

If you are a "best customer", you'll purchase this book in multiple channels, right? I mean, multichannel customers are the best customers, so that means you'll probably purchase multiple copies in multiple channels!

Different Customers, Different Behaviors

Online Marketing Simulations (buy the book on Amazon.com) routinely show us that different customers exhibit different behaviors.

Go to the sample spreadsheet (e-mail me for a copy), and do the following:

• Enter 0.00 in C6 - G6.
• Zero-out cells B149 - B340.

Here, we're running a simulation, evaluating only how customers with a Grade = A (the very best customers) perform over time. Play close attention to cells J5 - N7, these cells represent the sales trajectory of best customers across three advertising channels.

Don't save these results. Close the spreadsheet, then open it again, and do the following.

• Enter 0.00 in C6 - G6.
• Zero-out cells B101 - B292

Here, we're running a simulation, evaluating only how customers with a Grade = F (the most marginal customers in your database) perform over time. Look at cells J5 - N7. What do you observe? Well, Channel 2 gets disproportionately more sales, while Channel 3 gets disproportionately less sales.

This happens in your business too, folks. You will see that your best customers have purchase preferences that are different than are the preferences of marginal customers.

Use this information to your advantage. Know which marketing channels appeal to best customers, and to marginal customers!

Paid Search: Low Long-Term Value?

Get your copy of Online Marketing Simulations via Amazon.com.

Paid Search is an absolute enigma, folks.

Talk to online marketing experts, and it is truly a big deal, the primary way many online brands acquire new customers.

Talk to offline marketing experts, and you hear a common theme ... "paid search customers have poor long-term value."

Long-term value is a relative term, comprised of two components ... "involuntary expense", and "voluntary expense".

Voluntary Expense includes all outbound direct marketing expenses that work for/against long-term value. Catalog marketers often begin to send paid search customers a veritable plethora of catalogs. If the paid search customer has no interest in catalog marketing, long-term value is going to decline, rapidly. The marketer is making a voluntary choice to speak with the customer, impacting long-term value.

Involuntary Expense happens after the customer is acquired. If a paid search customer elects to use paid search in the future, the brand experiences "involuntary expense". Sure, the brand could choose to not participate in paid search, but if the brand does participate, expenses are rung up in an involuntary manner, essentially controlled by the customer.

Marketing Executives use Online Marketing Simulations to understand how the customer is likely to migrate and change in the future. Simply isolate the paid search customer, and then see which channels the customer is likely to purchase from over the next five years. You can literally tally-up the offline advertising expense you'll incur, and the paid search expense you'll incur.

If you find that paid search customers are unprofitable, eliminate voluntary expense (i.e. offline direct marketing that you control). You may find that paid search customers have low long-term value only because they don't want to be marketed to with offline direct marketing activities. You may also find that paid search customers who purchase specific items have lower long-term value, or that non-branded terms have lower long-term value, as an FYI.

For those of us managing businesses where we do a lot of outbound marketing (post cards, catalogs, e-mail), long-term value is controllable. It is perfectly acceptable to acquire a paid search buyer that generates $5 of long-term value, and it is perfectly acceptable to acquire a customer via postcard marketing that generates $50 of long-term value. It is how we manage the long-term value that matters! Heck, let's go find ten of the paid search buyers and just deal with the subsequent value difference.

Most important, use Online Marketing Simulations to understand the long-term value of all customers from all advertising micro-channels!

Kindle Version of Online Marketing Simulations is Available

Good news for those of you who are into reading books on your Kindle ... Online Marketing Simulations is now available in Kindle format!

Click Here For Paperback Version ... $19.95.

Click Here For Kindle Version ... $4.99.

By the way, loyal blog readers, the Twitter audience is drubbing you in sales totals ... by a factor of nearly 4 to 1. Are you going to stand for this? Are you going to let the Twitterati run circles around you? Or are you going make the technological leap and be competitive and buy this book? I mean, I've been brazen in my claims that you cannot sell anything on Twitter, and yet this book is selling so much better among the analytical types following on Twitter than among this audience. Oh boy!

Also interesting is the fact that the book, in the very early stages, is being embraced by the online vendor community, in fact, it's a bit of a surprise to me. I strongly feel that the methodology should be part of online marketing software tools.

Thanks to all of you who made the debut of the book the 9,500th best selling book on Amazon last Wednesday, I appreciate it! That's quite a feat for a self-published book with no marketing behind it whatsoever.

Dear E-Mail Marketers: E-Mail Is Dead, Huh?

Dear E-Mail Marketers:

You represent a fun niche. The leading pundits have declared your medium "dead", less than two decades after being formally launched. You now join catalog marketers in the direct marketing graveyard.

Sure, your niche is still highly profitable. Pundits, however, don't care about profitability. They care about "what's next".

Companies, however, care an awful lot about profitability. It turns out that companies cannot stay in business unless they generate a lot of profit.

Maybe it is time for e-mail marketers to finally prove that e-mail marketing generates long-term profit.

Carefully review your Online Marketing Simulations (buy the book here on Amazon.com, the 9,500th best selling book on Amazon yesterday!), paying specific attention to what customers who purchase from the e-mail advertising micro-channel "do next".

Often, you'll find that e-mail drives future sales increases in other channels. You'll notice that e-mail customers become paid search buyers, or respond to offline ads, or become so loyal that they no longer require advertising to purchase in the future. Heck, in a lot of my projects, I can prove that Google absolutely loves e-mail marketing --- e-mail causes a purchase to happen, and then customer behavior changes, resulting in future paid searches. In other words, your e-mail marketing activities fuel future success for Google.

Use your simulations to analyze the long-term value of the social media shopper, and compare it with the simulated long-term value of the e-mail customer. Seriously. Do it! Tell the world what you find!

E-Mail marketers, once you have the data to defend your channel, defend it!!! It's not going to be good enough to say that e-mail is a relationship builder, or is the glue that holds marketing together, or is the tactic that feeds social media activities. Prove the value of your channel, demonstrating the value via long-term sales and profit. Show what happens to a business if e-mail marketing doesn't exist. This is one of the best applications of an Online Marketing Simulation.

Dear e-mail marketers. Buy the book. Apply the techniques outlined in the book. And then prove to people the profit your discipline contributes to your business.

Amazon.com Is Now Offering Online Marketing Simulations!!

Well, that happened 10 days faster than it was supposed to happen.

You can now purchase Online Marketing Simulations at Amazon.com --- click here for more details.

Click here to search inside the book, to see the table of contents and a few tidbits.

And if you're waiting for the Kindle version of the book, it will be ready shortly, available for $4.99.

Read the book. Create your own spreadsheet. Apply the concepts to your business. Be a sage, be one of the only people in your company who knows whether your business is forecast to grow indefinitely, or is heading toward a problem.

If you are particularly "geeky", you'll enjoy the 50-ish pages of computer code at the back of the book.

If you're a CEO, you must have this information. Every CEO must know where business is heading, and must be ready to mitigate negative outcomes.

If you are a Marketing Executive, you will be light years ahead of your competition by having the outcome of an Online Marketing Simulation.

These are the projects that CEOs are hiring me to perform these days, so buy the book, and get busy on your own OMS project!!

The Pre-Release of Online Marketing Simulations!!!

I am so excited!!

Click here to purchase my new book, Online Marketing Simulations. The book is being pre-released via my publishing platform --- so if you are dying to have the book, you can buy it today via Createspace for the same $19.95 fee that you'll be able to purchase it for on Amazon.com in two weeks, plus a shipping/handling fee.

Because you are a loyal blog reader, you get access to the content two weeks before the general public!

About fifteen years of intense customer research have gone into the creation of this industry-leading methodology.

This handbook walks you through an e-commerce online marketing simulation. You'll get to explore the ways that customers of different levels of quality, merchandise preference, and online advertising micro-channels (Affiliates, Offline Ads, E-Mail, Social Media, Print Ads, Search, No Attributed Source) all interact with each other. You will clearly see the "MVP", or "Most Valuable Path" that a customer takes as the customer migrates from first purchase to loyal shopper.

Most important, you will learn how to optimize your online business for long-term success. Current web analytics software applications fail to provide you with a five year sales forecast by advertising micro-channel / merchandise division. The Online Marketing Simulation allows you to play "what-if" games, identifying the optimal strategy for long-term success.

And if you don't think you'll be in your job 24 months from now, then Online Marketing Simulations allow you to optimize your business for the next twelve months, so that you can earn a nice bonus!

Here's what you get when you purchase this book. There are plenty of geeky details, and plenty of high-level strategy appropriate for a CEO, CMO, or CFO.

• 106 pages of examples that illustrate how to execute Online Marketing Simulations.
• A companion spreadsheet to work through examples and use in your projects.
• 51 examples and accompanying tables.
• More than 50 pages of programming code, so that you can populate your own spreadsheet.
• 162 pages, total.

Who should buy this book?

• CEOs looking to predict where e-commerce sales are headed over the next five years.
• CMOs trying to allocate marketing dollars across advertising channels.
• Vendors looking to add important functionality to their software suite.
• Online Marketing Executives trying to demonstrate the value of each advertising channel.
• Web Analytics Experts, especially those looking to obtain skills necessary to analyze the entire business, not just the online channel.
• Business Intelligence mavens with an interest in simulating future activity.

I'm so excited that it is finally available!!!!!!! Help spread the word!

OMS: Compound Interest

Please send me an e-mail message if you'd like a copy of the spreadsheet to follow along with.

Old-school direct marketers like to explore the concept of Lifetime Value.

In online marketing, however, the focus is generally on conversion rate, on getting customers to purchase something today, now!

So go ahead and obtain every single conversion you can. You can't argue that it generates sales today!

Now that you have a bunch of new customers, let's try something. Enter "0.00" in cells D6 - G6. Then enter "0.00" in cells B101 - B340. In this situation, you are acquiring new customers in year one, and then you're following them (and only them) for the next four years.

What did you learn?

Well, these customers generated $13.3 million in the year you acquired the customer.

But now take a look at the compound interest you earned ... $6.7 million in year two, $5.9 million in year three, $4.8 million in year four, and $3.9 million in year five.

You could roll this out into infinity if you wanted to.

In the subsequent four years, these customers generated $21.3 million.

Customers acquired in one year don't act like compound interest. But when you keep acquiring new customers, year after year after year, the result is like compound interest.

You think about your conversion activities differently when you realize that the customers you acquire today will spend 1.6 times as much over the next four years. By balancing short-term and long-term profit, you optimize your online business for long-term success.

The New OMS Book: One Week Away!

We're closing in on the release of my new book on OMS, aptly titled 'Online Marketing Simulations'!

This book is written for CEOs, CMOs, Online Marketing Directors, Online Marketing Managers, and Web Analytics Experts looking to understand how to optimize the long-term health of a business.

This book is paired with a companion spreadsheet (the url for the spreadsheet is listed in the book). The spreadsheet outlines an online business with the following advertising micro-channels:

• Affiliates.
• Offline Advertisements.
• E-Mail Campaigns.
• Social Media.
• Print Ads.
• Search.
• No Attributed Source.

The spreadsheet also contains five merchandise divisions. Think of these as being similar to the tabs running across the top of an e-commerce website. In total, there are five customer grades (A, B, C, D, and F) with eight online advertising micro-channels (all channels + multiple channels) and six merchandising divisions (five + multiple merchandise divisions) yielding 240 segment combinations.

Most important, you will get to see how you can identify a "MVP", or "Most Valuable Path", the route that customers take from acquisition to loyalty. It is my opinion that identification of the "MVP" is more important to the long-term health of your business than is optimization of conversion rate.

The book walks you through an analysis of a business, helping you understand what steps you can take to make sure that, in five years, your business is growing at the rate you want for it to grow. If you are a CEO or CMO, you need to know how your actions impact the future of your business.

If you are an SPSS/SAS programmer, or you use another programming language, then you'll appreciate the 50+ pages of programming code in the appendix. With this information and the spreadsheet, you will be able to create your own Online Marketing Simulation.

I am self-publishing this book via Amazon, and am offering the book at a reasonable $19.95 price point. The book is clean and simple, no fancy colors or fonts or graphics, it simply offers a soup-to-nuts approach to conducting an Online Marketing Simulation.

I sincerely believe that Online Marketing Simulations should be part of any web analytics software package. After you purchase the book (or read the posts on this blog), if you feel the same way, let our web analytics software provider know that you want to see Online Marketing Simulations incorporated in their software offering.

OMS projects and Multichannel Forensics work will be the focus of my consulting work over the course of the next year --- these are things that CEOs are asking me to do for them. So give the book a chance when it becomes available next week!

OMS: You Shape The Direction Of Your Brand

Please send me an e-mail message if you'd like for me to send you a copy of the OMS spreadsheet to follow along with our posts.

Do you ever feel like you don't make a difference?

Maybe you are the humble paid search analyst at your company, and your CEO wonders what you're doing with all of those confusing keywords.

Maybe you just had a breakthrough --- you've found one set of keywords that, coupled with outstanding merchandise, cause a breakthrough in conversion rate.

Can you prove your worth to your CEO?

Go to the OMS spreadsheet. Take a look at cells N15 - N27. These are the annual demand totals for each merchandise division five years from now.

Now try this. Go to cell B39, and instead of the value 3,599 that is in that cell, change the cell to "6,599". In other words, you are adding 3,000 new customers, over each of the next five years, to the business, because you did such a great job of finding a set of keywords that, coupled with outstanding merchandise, cause a breakthrough in conversion rate.

Now look at cells N15 - N27. How did the cells differ?

Well, you've increased the value of your business over time, haven't you? Look at merchandise divisions 14 and 21.

• Division 14 Old Value = $8.9 million. New Value = $9.3 million.
• Division 21 Old Value = $1.17 million. New Value = $1.23 million.

Each division experienced increases of more than 4%, just from a subtle change in keyword strategy across a few merchandise divisions. Also notice that all merchandise divisions generated some benefit, as customers spilled-over, during the course of five years, from divisions 14 and 21 into other divisions. In year five, the business is $800,000 bigger because of the efforts of one individual, making one or two subtle changes today.

Every online marketing professional is making small improvements, improvements that have long-term consequences. As an industry, we do a terrible job of demonstrating our value, on a long-term basis.

The CEO uses the Online Marketing Simulation environment to understand the value all employees bring to the table. Once we get to see that value, illustrated over time, we make different decisions in the short-term to capitalize on it. Online marketing is taken in a new direction, a more productive direction.

OMS: Cross-Selling and Up-Selling

Please send me an e-mail message if you'd like to follow along with your own copy of a sample OMS spreadsheet, or if you're looking to work with me on an OMS project.

We read a lot about cross-selling and up-selling merchandise, and for good reason. There's nothing more fun, from the standpoint of a merchant, than adding another item to an order, generating an additional $20 of profit for almost no additional work.

Now, let me ask you a question: Does customer value increase if a customer adds a cross-sell or up-sell item to their order?

Go into the OMS spreadsheet, and type the value "1.05" into cell C7. Look at the demand values for the next five years:

• Year 1 = $79.7 million.
• Year 2 = $70.5 million.
• Year 3 = $66.7 million.
• Year 4 = $64.4 million.
• Year 5 = $62.9 million.

Next, type "1.00" into cell C7. Next, type the number "1.05" into cells C5 and C6. Look at the demand values for the next five years:

• Year 1 = $79.7 million.
• Year 2 = $72.3 million.
• Year 3 = $68.1 million.
• Year 4 = $65.3 million.
• Year 5 = $63.6 million.

Do you notice the difference?

Getting customers to spend 5% more in one year has the potential to benefit one year.

Increasing customer response by 5% pays us downstream benefits ... in this case, an additional $4.8 million over the next four years.

Carefully analyze the customers who purchase cross-sell and up-sell items, comparing them against customers who have identical characteristics but have not been swayed by cross-sell and up-sell items. Measure the long-term benefit your programs deliver ... are you fundamentally changing customer behavior, or are you enjoying the benefits of short-term profit generation?

Breaking News: A New Book!!!!

In just a few weeks, you will be among the first to have the opportunity to purchase a new book:

Online Marketing Simulations: The Definitive Methodology For Predicting The Future Of Your Online Business

The book walks you through an example of an e-commerce business with the following characteristics:

• Seven Advertising Micro-Channels, including Affiliates, E-Mail, Offline Advertising, Print Ads, Paid Search, Social Media, No Defined Source.
• Five Merchandise Divisions.
• 240 Analysis Segments.
• Free Spreadsheet, downloadable from http://minethatdata.com/, to use as you walk through the exercises in the book.
• SPSS Computer Code required to build the spreadsheet from scratch --- more than 4,000 lines of programming code will be available. If you're an enterprising coder, you'll be able to recognize what I'm doing, allowing you to code the entire simulation in the programming language of your choice.

Within this framework, you will explore all of the ways that Online Marketing Simulations can be used to learn which customers have the best long-term value, allowing you to optimize your marketing campaigns in the short-term for better results. You will also get to see how a business can be calibrated for long-term growth.

The book will be available on Amazon.com. And I listened to you, I heard your concerns about how much a business book should cost. So this time, the price is tentatively set for $19.90. You will be hard-pressed to find content of this nature available anywhere else, much less at that price. Management Consultants might charge a hundred thousand dollars or more for this kind of information. Research organizations would charge $1,495. Seriously. Ask both audiences.

Online Marketing Simulations will be one of my two key consulting project focuses over the next twelve months (the other project focus, of course, is Multichannel Forensics). This topic isn't going away. I'll be happy when I have plenty of consulting projects and the leading web analytics vendors incorporate this methodology into their software offering, so that all of us can easily access this information. I would like to politely ask you to help make that happen, that you ask your software providers to help arm you with the tools necessary to make good long-term decisions. Our industry simply lacks tools that allow really talented analysts to optimize conversion rates in a way that guarantees long-term success.

OMS: Price Points

It's trendy in online marketing to entice customers to purchase with low price points, discounts, and promotions.

But is it healthy for you business, in the long-term?

Let's look at an example from the OMS Spreadsheet (e-mail me if you wish to follow along, I'll send you a copy).

Zero out cells D6 - G6.

Zero out cells B101 - B580.

Now we're going to compare the evolution of two segments of new customers.

Go to cell B419, and enter the number "1,000". Now go up to the top of the spreadsheet, and look at cells C17 - G18. In the future, these customers like to purchase 3-4 items per order, spending $30 to $40 per item. In the year the customers were acquired, they spent $159,000. These customers basically stay stuck in department 11.

Next, zero out cell B419, and instead enter "1,000 into cell B421. Now go up to the top of the spreadsheet, and look at cells C17 - G18. In the future, these customers like to purchase much more expensive items. In the year the customers were acquired, they spent $147,000 ... but these customers are likely to migrate to expensive items in department 15. These customers hold much more potential than do other customers.

Online Marketers have the opportunity to carefully link the micro-channel the customer purchases from with the merchandise the customer purchases and the price point of the merchandise purchased. The combination of micro-channel, merchandise, and price point yield a customer that has outstanding potential, or limited potential.

This is an important area for online marketers to provide attention to!!

OMS: Merchandise Mix

If you'd like to follow along, please send me a message via e-mail, and I'll send you a copy of the spreadsheet.

Today we're going to talk a little bit about the role that merchandise mix plays in a business. Our online businesses are often managed by campaigns and landing pages. We execute offline campaigns (catalogs or direct mail or whatever works for you), and we execute a ton of online campaigns.

On average, we don't care what sells nearly as much as we care about the campaigns that work. We optimize our business based on the campaigns that deliver an acceptable return on investment.

But what happens when we cause customers to buy a different set of merchandise? In other words, does the future of the business change if I influence the merchandise that a customer purchases?

Give this a try. Zero out cells C5 - G5. Zero out cells B101 - B340. Enter "1,000" into cell B130.

Notice that these customers love Merchandise Department 11. After five years, they still spend more than half of their money in this department. After five years, the customers who stay active purchase 2.6 times a year, purchasing 2.9 items per order at $80 per item.

Now zero out cell B130, and type "1,000" into cell B136. These customers love Merchandise Department 14, but these customers are at least a little bit more willing to shift their money across other departments. After five years, the customers who keep active purchase 2.6 times a year, purchasing 2.6 items per order at $105 per item.

This is a tame example, one where the customer is fundamentally different, but the outcome after five years is not dramatically different.

That being said, it's a good thing for you to pay attention to this trend. Are your keywords causing you to acquire customers who have a preference for only a specific item or set of items, causing you to not achieve the long-term potential you'd like to achieve? Do your e-mail campaigns influence the merchandise preferences of your customers?

OMS: Constant Decay And Reactivation

If you want a copy of the OMS (Online Marketing Spreadsheet) to follow along with, please e-mail me, and I will send you a copy.

Ok, let's look at another issue with your online business, the issue of "decay".

For the past fifteen years, we've lived in an environment of unfettered e-commerce growth. Everything was easy. Lick you finger, point it to the sky, and guess that next year's growth will be 35%. And then it would come in at 45%. You'd look like a genius. Those were good times!

Well, growth was happening because new customers were trying e-commerce. Most customers have tried e-commerce now. Growth is harder to come by.

It is important to understand how a segment of customers experiences "constant decay". Here's what I want for you to do:

• Zero out cells C6 - G6.
• Zero out cells B101 - B340.

Now, enter the number "1,000" into cell B117. We're going to see how 1,000 really good customers (in my model, they are graded as "A") will evolve over time.

Take a look at the results.

• Grade = "A": Year 1 = 596, Year 2 = 380, Year 3 = 254, Year 4 = 177, Year 5 = 128.
• Grade = "B": Year 1 = 217, Year 2 = 220, Year 3 = 198, Year 4 = 172, Year 5 = 148.
• Grade = "C": Year 1 = 186, Year 2 = 293, Year 3 = 289, Year 4 = 255, Year 5 = 217.
• Grade = "D": Year 1 = 0, Year 2 = 106, Year 3 = 209, Year 4 = 251, Year 5 = 251.
• Grade = "F": Year 1 = 0, Year 2 = 0, Year 3 = 50, Year 4 = 145, Year 5 = 257.

Sales keep declining, too, from $400,000 in Year 1 to $89,000 in Year 5.

E-commerce is in a state of "constant decay". Without a steady diet of new customers, the whole ecosystem simply essentially falls apart. This is happening to your business, every single day ... you just mask it by finding new customers. Strip out the new customers, and you're on your way to being laid off.

You'll hear catalog marketers obsess about "customer reactivation". This is why. They know, from a hundred years of catalog marketing experience, that their customer file is in a state of constant decay, so they obsess about every possible strategy to get customers who haven't purchased in a long time to come back and buy again.

Reactivation is hard work, and the rewards aren't dramatic. Go ahead and plug "1,000" customers into cell B261. These customers have a grade of "D". Notice that very few of these customers ever move up into "A" or "B" status (see cells C21 - G25).

Now do something unique. Change the value of "1.00" in cell C5 to a value of "1.20". In other words, for one year, we're going to do something, whatever that is, that improves the ability to reactivate these customers by twenty percent. What do you see?

Well, you see very, VERY modest improvements in the number of customers achieving "A" and "B" status over time. Clearly, it is very hard to reactivate customers. But if you can do it, on a grand scale, year after year after year, it will pay dividends.

Now update C5 - G5 from a value of 1.00 to a value of 1.20. All of a sudden, we have 122 "A" customers after five years, vs. just 91 if we improve reactivation for one year, and vs. just 89 if we do nothing but let customers migrate organically.

In other words, customer reactivation is a 24/7/365 activity that must be managed with discipline. Constant improvement and strategy is required, every day, every year, to move the needle. If the attention isn't given, then the e-commerce business is in a state of constant decay.

If you're an Executive or Analyst looking to understand what the future trajectory of your business looks like, give me a holler about working on an OMS project!

OMS: MVP = Most Valuable Path

When you take a few moments to read articles about online marketing, you quickly learn that the goal is to get a conversion ... NOW!

What happens if the customers you acquire aren't very good long-term prospects?

Time to pull out the OMS and see if that happens! If you want to follow along, send me an e-mail message, and I'll send you the free spreadsheet with 80% of the content I use when working with my clients.

Here's what I want for you to do:

• Zero out cells D6 - G6, we only want to acquire customers in the first year.
• Zero out cells B101 - B340, the cells that have the number of customers by segment to start the simulation with.
• Now, zero out cells B341 - B580. These are the cells that tell us how many people we're going to acquire. I have 240 segments, I add "300" to the segment label on each of these ... so segment 412 is really segment 112.

Ok, now let's try something. Plug the value "1,000" into cell B452. We're going to track what happens when we acquire 1,000 customers into what is Segment 112, a cell graded as a "C". What do you observe:

• Almost all of these customers purchased from online marketing channel number two (see cell J6).
• Almost all of these customers purchased merchandise from department number 11 (see cell J15).
• After the first year, almost none of these customers purchased again, generating about $35,000 over the next four years.
• When acquired, these customers typically bought 1.8 items at $17.49 per item.

Now let's try something different. Zero out cell B452, and instead, plug the value "1,000" into cell B477. Look at these customers.

• Almost all of these customers purchase from online marketing channel number one (see cell J5).
• Almost all of these customers purchased merchandise from either department numbers 15 and 19 (see cells J19 and J23).
• After the first year, some of these customers purchased again, generating about $121,000 over the next four years.
• When acquired, these customers typically bought 1.4 items at $30.28 per item.

There's a fundamental difference in the subsequent behavior of these customers, right? Which customer would you want to acquire?

This is part of the art of online marketing that is missing these days. We look at conversion metrics, and determine if we did well or not. By folding in the merchandise a customer purchased (and the price point the merchandise is offered at), and simulating what is likely to happen in the future, we see a different story --- we can identify the marketing channels (offline, e-mail, search, affiliates, etc.) that yield high-value customers, and we can identify the merchandise that we should advertise, merchandise that yields high-value customers.

This is part of something I call the "MVP", or "Most Valuable Path". What we want to do is understand how customers progress through our ecosystem, identify that path (micro-channel + merchandise + geography + price point) that yields a high value customer, and then acquire customers who take the Most Valuable Path.

Make sense?

Homework assignment: Describe the dynamics that happen when you acquire 1,000 customers from segments 349, 350, 355, 357, and 364. Which segment yields customers with the most future value? What do you see happening that is driving this?

OMS: A KPI For You, Customer Asset Value

Let's do something nuts with our spreadsheet (e-mail me here to obtain your free copy of the OMS 240 Segment Simulation Spreadsheet).

Go to cells C6 - G6, and type in the number 0.00 in each cell.

This means that there will be no customer acquisition in each of the next five years.

Now look at the sales numbers in C13 - G13:

• Year 1 = $62.6 million.
• Year 2 = $50.5 million.
• Year 3 = $40.9 million.
• Year 4 = $33.7 million.
• Year 5 = $28.4 million.

Looks like customer acquisition is pretty important, huh? How many times have you been told that if you just fix your loyalty program, everything will be fine?

But maybe more important is this interesting metric.

• This business generated $80.0 million last year.
• Over the next five years, this business will generate $216.1 million from the existing customer base.

Your customer base is an asset, in this case, one worth $216.1 million in the next five years.

Some companies calculate this metric (five year sales value of current customer base, what I call the "Customer Asset Value", or "CAV") on a weekly/daily basis, allowing them to see how marketers and merchants positively/negatively impact a business --- in ways that go way beyond conversion rates.

This is a KPI every company can calculate. Ask your Web Analyst to calculate this metric for you. Ask your Business Intelligence Manager to calculate this metric for you. Ask me to calculate this metrics for you!

OMS: Customer Acquisition

If you haven't received your copy of a sample Online Marketing Simulation worksheet and wish to follow along on these examples, go ahead and send me an e-mail message and I'll forward you a copy.

In our example, we estimated that this business needs a 17% increase in customer retention, in order for the business to improve.

What about customer acquisition?

In the spreadsheet, change cells C6 - G6 from a value of 1.00 to a value of 1.70.

Notice that the business stabilizes when customer acquisition activities drive a 70% increase in new customers.

This doesn't even seem feasible, does it? I mean, how the heck would you improve customer acquisition activities by 70%?

In upcoming posts, we'll explore how to investigate which customer acquisition segments can contribute high-value customers. We'll introduce the concept of the "MVP", the "Most Valuable Path" that a customer follows from new customer to great customer. We'll better understand what drives this business, and what holds back this business. You'll be able to take the concepts and apply them to your business.

OMS: Retention Via The Sample Worksheet

Thanks to the many of you who asked for a sample copy of a watered-down Online Marketing Simulation worksheet!

Over the next few weeks, we'll be going over numerous examples, based on the contents of the spreadsheet. If you would like a copy so that you can follow along, send me an e-mail message, and I will send you a copy.

Remember, I've removed some of the really important elements of the spreadsheet, those that factor in what happens when marketing is increased or decreased, the good stuff that CEOs ask me to estimate for them.

Take a look at the spreadsheet. This example illustrates how a business is likely to evolve over the next five years. Notice that this business, if things continue "as-is", will be in steady decline, dropping from $76 million next year to $63 million after five years.

When this happens, you've got problems!

So let's try something, as a way of easing into the simulation. Look at cells C5 - G5. Here you can make changes to the annual retention rate. Let's assume that the economy magically bounces back, so annual retention rates improve, by, say, 17%. Plug the scalar 1.17 into cells C5 - G5. Now look at what happens to annual sales.

The business is now at $86 million, each year.

This gives you an idea of how the business will change, over time, if the economy improves. And we know that there is basically no chance of the economy improving by 17% anytime soon.

So this business has a problem.

In upcoming weeks, we will use this Online Marketing Simulation spreadsheet to better understand how a business might decompose what is happening, and then find a path to a brighter future. This is a logical extension of the Web Analytics tools we've been trained to use.

Call For Data, And Do You Want To See A Simple OMS Spreadsheet?

Two things for you, the loyal reader.

First, I have a 10mb Online Marketing Spreadsheet I'd be willing to share with you. Everything has been dummied in the spreadsheet (channels, merchandise divisions, segments, sales performance, rebuy rates). The spreadsheet is purposely messy and undocumented, and I chose not to include any of the advertising effectiveness components of the spreadsheet (i.e. increase pay-per-click budget by 20%, increase total sales by 8%). If you'd like to see the spreadsheet, send me an e-mail message. Your e-mail client will need to be able to accept a large, Microsoft Office 2007 Excel format file (.xlsl).

Second, I am looking for a volunteer dataset. For obvious reasons, I cannot share client data with you, so I'm looking for one of two potential datasets that I could share the results of with you.

I'm looking for an e-commerce brand willing to send me summarized clickstream/visit data and purchase data for a multi-year period of time, a brand wanting to demonstrate the long-term value of actions that happened yesterday (shopping cart abandonment, visit certain pages but do not put items in a shopping cart, click-through an e-mail campaign but do not purchase, that kind of thing).

I'd also consider a social media dataset, one where we could demonstrate how short-term actions change the long-term trajectory/value of a user.

I would never give away your trade secrets, share proprietary information, or in any other way harm your business. I would, however, publish how customers interact with your business via the Online Marketing Simulation, similar to the way I've shared OMS concepts over the past few months. In return, you get free OMS project work. I'm asking about data because many of you are suggesting that you want to see the Online Marketing Simulation "come to life". You want to see concrete examples. This is one way to accomplish this.

If you have an interest in this type of project, please send me an e-mail message describing your business and the data you'd be willing to share.

OMS vs. Multichannel Forensics

One of our loyal readers says ... "I don't understand how OMS represents the logical evolution of Multichannel Forensics."

We've been talking about Multichannel Forensics for almost four years. The metrics (MPT) and the modes (Retention Mode, Hybrid Mode, Acquisition Mode, Isolation Mode, Equilibrium Mode, Transfer Mode, Oscillation Mode) are unique to Multichannel Forensics. We use the metrics and modes to describe how customers migrate through our channels, we learn the role that each of our channels play in our total business.

It has been my experience that Analysts/Managers are very interested in this aspect of Multichannel Forensics.

It has been my experience that CEOs/CFOs/CMOs are very interested in having me predict what sales will look like, by marketing channel (catalog, e-mail, pay-per-click, affiliates, natural search, organic demand), for each of the next five years. They want to understand how e-mail marketing will be impacted by paid search, how affiliates influence future off-price purchase activity. They want to know if they should invest more/less in e-commerce. They want to know what impact their website has on retail sales. They want to know why certain merchandise divisions aren't growing online anymore. They want to be able to understand if shopping cart abandonment truly impacts long-term customer behavior, or if it is a psuedo-metric that isn't truly correlated with long-term customer value, sales, and profit.

In other words, the needs of business leaders changed in the past two years. The focus dramatically shifted ... reduce offline marketing expense, find ways to understand online customers beyond segmentation and conversion rates and optimization.

CEOs/CFOs/CMOs were increasingly asking me to fold online activity into the Multichannel Forecasts I was running. This really picked up after the economy crumbled last fall. E-commerce no longer represented an unfettered growth channel. Boards and Owners are now challenging CEOs to present an accurate picture of long-term e-commerce growth, in order to make long-term investment decisions.

After receiving several similar requests from Management teams across a diverse set of companies, requests that shifted focus from high-level channels (retail, online, catalog) to online channels (e-mail, pay-per-click, affiliates) and their impact on the total business, it became obvious that we needed to evolve the forecasting component of Multichannel Forensics projects.

This is why you now see the intense focus on the Online Marketing Simulation on this blog. This is what business leaders are now asking me to do for them.

And this is why I am imploring you, the Web Analytics expert, to read this content carefully, and to adopt this information in your daily activities. Your business leaders are looking for you to do this type of work for them.

OMS: Optimizing Paid Search And Customer Acquisition

Let's tackle a question that we all eventually have to deal with. Somebody is requiring us to cut back on an advertising channel. Maybe the CFO did an analysis, and thinks that the ad-to-sales ratio in paid search is too high. She demands that we cut our paid search program by 50%.

The online marketer and web analyst work together to cobble conversion rate reporting, and if available, profitability reporting, attempting to make a case to continue to spend money. And this is a good thing. Your web analytics reporting helps you see what happened in the past. Your reporting shows you that you're losing a lot of money at the margin in your paid search program. It sounds like your CFO is right.

Your CEO, however, will want to know what will happen in the future if the CFO gets her way and cuts your paid search program in half. Your job is to make a case to the CEO to keep spending the money. You have to prove that there is a long-term return-on-investment that must be protected.

This is a perfect application of the Online Marketing Simulation, the "OMS" as I call it. Why not simulate what happens over the next five years if your paid search budget is cut by 50%?

First up, the current plan.

• Year 1 Demand = $19.1 million, Profit = $0.6 million.
• Year 2 Demand = $19.3 million, Profit = $0.7 million.
• Year 3 Demand = $19.5 million, Profit = $0.7 million.
• Year 4 Demand = $19.6 million, Profit = $0.8 million.
• Year 5 Demand = $19.6 million, Profit = $0.8 million.

This information alone would be good for your CFO and CEO to see. When is the last time you showed your Sr. Management team where your online business is heading, from a sales and profit standpoint, over the next five years? In the old days, you'd put your finger in the air and guess that a 35% sales increase would happen, and then you'd be praised when you had a 45% sales increase. Unfortunately, for most of us, those days are gone.

Ok, now we plug the 50% reduction in the paid search budget into the OMS.

• Year 1 Demand = $18.2 million, Profit = $1.0 million.
• Year 2 Demand = $17.5 million, Profit = $0.8 million.
• Year 3 Demand = $16.8 million, Profit = $0.6 million.
• Year 4 Demand = $16.1 million, Profit = $0.4 million.
• Year 5 Demand = $15.4 million, Profit = $0.1 million.

Which business would you rather be part of?

So often, our customer acquisition activities are unprofitable, and are the first area that the CFO wants to cut. If you're using your standard web analytics platform, you're going to look at conversion rates and average order values and you'll end up agreeing with your CFO.

If you run your customers through the OMS, simulating the long-term migration of your customer base, you'll arrive at a different answer. The example I illustrate above repeats itself across the data I analyze.

Short-term optimization frequently results in a long-term drain on the business. It is here that the web analytics community are sometimes sold the wrong message. We're told about these glorious optimization tests, we even read about how offline data is integrated into the multivariate tests that result in an optimized outcome. It all sounds really good.

Until we do a better job of simulating the long-term impact of our decisions, we won't know if we're actually optimizing our business, or if we're hurting the future of our business. It is time for the online marketing and web analytics community to take the next step!

OMS: Optimizing Landing Pages

In old-school catalog marketing, it was hard to isolate the impact of any spread in a catalog. But in e-commerce, we have better metrics, metrics that help us understand the best ways to merchandise our website. We're grateful that we have talented web analytics experts and great software to guide us through the decision-making process.

Now we have the Online Marketing Simulation, the "OMS". And for many of us, we finally have a tool to understand the long-term impact of a shift in merchandising strategy.

In one dataset, I looked at thirteen merchandise divisions. Two of the merchandise divisions underwent significant online changes, one was featured prominently due to conversion rate improvements, one was de-emphasized because conversion was poor.

Given the results, I can simulate the five-year impact of this short-term decision.

In terms of annual sales, there was no difference between the old strategy and the newly optimized strategy, over a five year period of time. In essence, we emphasize one division, shifting business to that division. But long-term, customer spending habits are unchanged.

What did change was the distribution of sales by merchandise division, over time. After five years, here's how merchandise sales were altered:

• Merchandise Division #1 = +4.2% (this division was emphasized due to optimization results).
• Merchandise Division #2 = +2.4%.
• Merchandise Division #3 = +0.9%.
• Merchandise Division #4 = -2.6%.
• Merchandise Division #5 = -6.0% (this division was de-emphasized due to optimization results).
• Merchandise Division #6 = +1.2%.
• Merchandise Division #7 = -0.3%.
• Merchandise Division #8 = -1.5%.
• Merchandise Division #9 = -2.4%.
• Merchandise Division #10 = -1.8%.
• Merchandise Division #11 = -3.1%.
• Merchandise Division #12 = -2.1%.
• Merchandise Division #13 = -2.7%.

By making simple changes to the merchandising of your landing pages, you unwittingly impact the long-term sales trajectory of many of your merchandising divisions. You subtly shift customer behavior.

The Web Analytics practitioner and Online Marketing expert can both benefit from the OMS environment. Imagine being able to sit with your Executive leadership team, helping them understand how decisions being made today impact the future of your business? We move beyond simple conversions and KPIs, instead gaining insight into what our business looks like in the future. Who wouldn't want to know what the future of our business looks like? Who wouldn't want to know how his/her own personal actions are influencing the future trajectory of the business?

And if you don't think this information would help your organization, why not use the comments section to describe the reasons why? There's nothing wrong with a dissenting point of view, it may make for a good discussion!

OMS: PPC And Retail

You've probably been paying attention to the stuff that George Michie has been writing about on the Rimm-Kaufman blog.

• Geographic and Demographic Impact on PPC, Part 1.
• Geographic Impact of PPC, Part 2.

Pay attention to his work, folks. It's always fun when the results don't match up with conventional thinking, that's the only way we learn!

The fun part about his research is that it helps you optimize and improve your business. This is great stuff for the online marketer and web analytics expert.

Over here in Online Marketing Simulation (OMS) land, we like web analytics and we like online marketing. But we don't compete with web analytics and online marketing, do we? No, we complement web analytics and online marketing by helping CEOs answer one important question ... "what happens next?"

In other words, you are a retailer, and you just acquired a customer via search. Will this customer shop in your store in the future?

Let's go to the OMS to find out.

A typical outcome looks like this, for a segment of newly acquired search customers:

• Year 1 Search = $70,000. Year 1 Retail = $130,000.
• Year 2 Search = $60,000. Year 2 Retail = $170,000.
• Year 5 Search = $40,000. Year 5 Retail = $140,000.

Notice that most of the future value happens in a retail store.

Your mileage will vary. At Nordstrom, we used Multichannel Forensics, the precursor to the OMS, to learn several years ago that every dollar we saw in search today was paired with another future dollar in retail stores.

This meant that we could dramatically increase the search budget. If you're an online marketer, you like it when your budget is increased because somebody proved that you are adding value not captured in your web analytics software package.

Use online marketing and web analytics to understand what is happening today.

Use the OMS, the Online Marketing Simulation (my version, or the one you create), to understand what is going to happen tomorrow. Once you know what is going to happen tomorrow, you can significantly change your budget levels today!

OMS: Frequently Asked Questions (FAQ)

After more than a thousand downloads of the original Online Marketing Simulation (OMS) presentation, there are questions!


Question: I've been practicing web analytics for a decade. I'm perfectly happy analyzing conversion rates and executing multivariate tests, and my boss has never once asked me for something like this. Why would I ever need to execute an Online Marketing Simulation?

Answer: Your business leaders are telling me they want you to do this type of work for them. Your CMOs, CFOs, and CEOs communicate to me that they want to know what will happen to their business in the future. Your leaders are being pressured to understand if their business is capable of significant growth in the future. They want to know which micro-channel is best positioned to provide future growth (e-mail, affiliates, search, social media). They want to know if e-mail marketing performance improves if they increase spend in paid search. They want to know if making radical adjustments to offline advertising will impact sales online. They want to know what happens to the rest of the business if they decide to end all affiliate marketing programs. They want to know what total online sales will look like in 2014. They want you to give them the answers to these questions. I think your company is best served when you can provide "the C-Suite" with these answers.


Question: All of the Web Analytics bloggers and experts seem to be ignoring this topic. Is it possible that they know what's best for us and that you are talking about something that just isn't part of the typical web analytics tool kit?

Answer: Of course it is possible that they are right! But let's be honest. The Web Analytics community needs to integrate all offline and online data, and then become proficient not only at measuring what is happening, but forecasting what it means to the future health of a business. The vast majority of Web Analytics bloggers and consultant experts haven't had a need to solve a problem like this, especially when e-commerce was growing organically at 20% or 30% a year. Those days are over. Few e-commerce experts and web analytics experts have had to deal with the pressures of a stalled business, so they haven't ever had the need for a tool like the OMS. Over the next five years, you will see an evolutionary push toward advanced tools like the OMS. The marketplace and a stagnant economy will force it to happen.

Question: Your presentations are too vague. I don't think you're doing a good job of communicating this topic to your audience. What can you do to improve your presentation of this topic?

Answer: I'll try to improve and offer more concrete examples. This isn't an easy topic to communicate. I'll continue to work hard to improve the communication of this topic.


Question: Google gives away Google Analytics for free, so why shouldn't you give your programming code away for free? If you believe so strongly in this concept, why not evangelize it by giving it away, and then find some other way to monetize your activities?

Answer: I invested more than half of my professional career writing and testing the programming code necessary to create an application that predicts sales by micro-channel. This tool is perfect for the forward-looking CEO, an individual who wants to understand the future of an online, retail, or direct marketing business. I've invested tens of thousands of hours on this topic. That being said, I did outline the exact methodology in the presentation. If you are handy with programming code, and are a wiley analyst, you can replicate the algorithm based on the information in the presentation. Go do it!!

Question: "Our web analytics data is cookie-based, and we all know about the problems with cookies. So I think that invalidates the Online Marketing Simulation, right?"

Answer: "Absolutely not. Use the data you have, and where you don't have good visitation data, use your purchase data, which is much more important anyway. Please do not become paralyzed because you have incomplete data!"

Question: Have Omniture, WebTrends, Unica, or Coremetrics approached you about incorporating your algorithm into their software applications? It would be great if we could do this right from the platform we do all of our analyses from. Why not partner with them if you want this tool to become widely used?

Answer: No, they have not approached me about incorporating the methodology in their software applications. But representatives from every one of those companies are reading this series and are actively downloading the presentation, based on my blog/site web analytics data. The same holds for the major Web Analytics bloggers and consultants, my web analytics data show that they're all downloading and reviewing the content. If you like what you've been reading, communicate your interest to them, because people are paying attention.


Question: Must we use a Factor Analysis as part of the simulation routine? Must we use regression models to rank customers from best to worst? Why make this so complicated?

Answer: Absolutely not. Create your own segmentation scheme, and run the simulations with your version of segmentation. It's the simulation/algorithm that matters, not the methodology that is used to place customers within segments.


Question: How is this different than the Multichannel Forensics work you've done for catalogers?

Answer: The core of the Multichannel Forensics methodology is the core of the OMS tool. We're simply shifting the focus now, from figuring out how catalog advertising impacts the business, to figuring out how a myriad of online micro-channels and merchandise categories interact to impact the future of your business. Think of this as Multichannel Forensics on steroids. All of the concepts in the Multichannel Forensics book hold up well in the OMS framework.


Question: What is the most interesting thing you've learned while running Online Marketing Simulations for clients?

Answer: The way that subtle changes in the merchandising strategies of advertising channels impact the future merchandise preferences of customers. When you optimize e-mail campaigns based on the merchandise sold in e-mail campaigns, you impact the merchandise divisions that will sell well in the future. When you focus on various keywords, you impact the merchandise divisions that will sell well in the future. When you focus on discounts and promotions, you dramatically alter the responsiveness of your customer file to full-price merchandise in the future. It is amazing how things like discounts and promotions act like a virus (or a poison) that spreads through the whole customer ecosystem, reducing your ability to sell full-price merchandise. The OMS is perfectly suited for illustrating the poison of discounts and promotions, showing you how a heavy season of promotions in Fall 2008 dampen full-price business in 2011. The OMS tool literally allows you to see how you "infect" your business with viruses, even though you strongly believe you are optimizing your business for positive results today.

Give the presentation a read, and let me know what questions you have. If we get enough questions, I'll dedicate another post on the topic.