Can A Catalog Brand Survive As An E-Commerce Pure-Play?

The April survey question was "Can A Catalog Brand Survive As An E-Commerce Pure-Play, One That Does Not Mail Catalogs?" Here's how you responded to the survey question:

Can a catalog brand survive as an e-commerce
pureplay, one that does not mail catalogs?
Yes, Customers Will Just Shop Online	44%
Yes, But Sales Will Plummet	35%
No, The Cataloger Will Soon Be Out Of Business	21%

The reasonably even distribution of answers is congruent with the data I see across various Multichannel Forensics projects. Some companies would be out of business within a few months. Some companies would see a dramatic decrease in sales. And some companies would thrive.

Yes, Customers Will Just Shop Online:

• Brand has a retail channel that is dominant.
• Online channel is more than fifty percent of direct-to-consumer sales.
  
• Online channel has a broader merchandise assortment than the catalog has.
• Customer never enters catalog key-code when ordering online.
  
• Brand is not "over-mailing" customers.
• Brand is in "Retention Mode".
• Catalog is in "Transfer Mode".
• Customer is largely urban or suburban, age 18-45.
  
• E-Mail and Paid Search performance improves in mail/holdout tests.
  

Yes, But Sales Will Plummet:

• Brand does not have a retail channel, or has a small retail channel.
• Online channel is less than fifty percent of direct-to-consumer sales.
  
• Online channel has the same merchandise assortment as the catalog.
• Customer sometimes enters catalog key-code when shopping online.
  
• Brand is in "Hybrid Mode".
• Catalog is in "Equilibrium Mode".
• Customer is largely suburban, age 35-55.
  

No, The Cataloger Will Soon Be Out Of Business:

• Brand does not have a retail channel.
• Online channel is less than thirty percent of direct-to-consumer sales.
• Customer always enters catalog key-code when shopping online.
• Brand is in "Acquisition Mode".
• Catalog is in "Isolation Mode".
• Customer is largely rural, age 50-80.
  

In my experience, these general guidelines hold up pretty well. We could get away from a catalog marketing program at Nordstrom because our customers largely fell into the first classification --- middle-aged, urban/suburban customers offered a better merchandise assortment online and in stores. But if you are a cataloger of fine cheeses with an older/rural customer base, you'd be out of business without your catalog.

Square Inch Analysis (SQUINCH) and Monthly Item Profitability Reporting

Back in the 1990s, square inch analysis (sometimes labeled as SQUINCH) was the foundation of a successful multichannel catalog program.

Those days are remembered as fondly as we remember $1.30 per gallon gas, new episodes of Seinfeld, and the raging conflict between Bill Clinton and Newt Gingrich.

Back in the 1990s, we'd evaluate each item based on the sales generated in that specific catalog, divided by the space allocated to the item.

Here's a simple example. Assume we circulate a catalog to 1,000,000 individuals. On one page of the catalog, there are three items featured.

• Item #1 = 0.15 page, $1,200 sales.
  
• Item $2 = 0.35 page, $2,200 sales.
• Item $3 = 0.50 page, $3,200 sales.

Looks like Item #3 performed the best, right?

Let's control for the amount of space the item was given.

• Item #1 = $1,200 sales / (0.15 page * 1,000,000 circ / 1,000 pages) = $80.00 DMPC.
  
• Item #2 = $2,200 sales / (0.35 page * 1,000,000 circ / 1,000 pages) = $62.86 DMPC.
  
• Item #3 = $3,200 sales / (0.50 page * 1,000,000 circ / 1,000 pages) = $64.00 DMPC.

DMPC = Demand per Thousand Pages Circulated.

After controlling for the number of pages circulated, Item #1 actually performed the best!

In the 1990s, we'd evaluate every item in the catalog in this manner, giving more space to the items that performed best, limiting space to the items that performed worst.

Now fast forward to 2008. You still mail the catalog to 1,000,000 souls who haven't told a third party opt-out service that they are disgruntled with your activities. What has changed since 1990?

• Sixty percent of your transactions occur online, about half of those transactions are driven by catalog marketing.
  

• You also deliver eight e-mail campaigns during the time when the catalog is active, six of the eight e-mail campaigns offer free shipping, a perk not given to loyal catalog shoppers.

• Ten percent of your marketing budget is allocated to paid search, spread across 2,500 keywords.

• Affiliate marketing and shopping comparison sites contribute to your online sales.

• Portal advertising drives traffic to your site.

• Items featured on blogs account for 2% of your sales.

• Your online merchandise assortment is greater than your catalog merchandise assortment.

• You've learned that catalog marketing and e-mail marketing drive sales to items not featured in either marketing activity.

In other words, square inch analysis only tells you part of the story about the performance of an item.

Increasingly, I see multichannel wizards attempting to perform Monthly Item Profitability Reports. In other words, every item a multichannel brand sells is evaluated on the basis of the monthly profit generated across all advertising activities. Here's a sample Monthly Item Profitability Report.

MONTHLY ITEM PROFITABILITY REPORT
Items Sold		500
Average Price Per Item Sold		$39.99
Telephone Demand, Total		$8,000
Online Demand, Total		$12,000
Monthly Demand		$20,000
Final Fulfillment	94.0%	$18,800
Return Rate	20.0%	$3,760
Net Sales	75.2%	$15,040
Gross Margin	55.0%	$8,272
Less Catalog Marketing		$1,850
Less E-Mail Marketing		$50
Less Paid Search Marketing		$400
Less Affiliate Marketing		$275
Less Shopping Comp. Mktg		$225
Less Portal Advertising Exp.		$315
Total Advertising Expense		$3,115
Pick/Pack/Ship Expense	11.5%	$1,730
Variable Operating Profit		$3,427
Profit, % of Net Sales		22.8%
Ad to Sales Ratio		20.7%

Notice that all demand generated by an item is included in the report. Similarly, advertising expense by advertising channel is allocated to each item.

This isn't an easy thing to do, and quite honestly, few multichannel companies have the database infrastructure to conduct item-level profit and loss statements on a fluid and automated basis. Regardless, this is the direction our industry is taking, and it is a necessary step if we want to truly offer a profitable multichannel merchandise assortment.

Your thoughts? Who is doing this well? Have you made different decisions as a result of conducting an analysis of this nature?

Micro-Channel Challenges: Abacus And Co-Ops

I am continually told by traditional catalogers that there isn't a viable way to get away from a paper-based advertising model. Regardless of the sales success of folks at Zappos or Blue Nile or Amazon or Overstock.com, folks who do not use a catalog marketing channel, traditional catalogers usually have data (and more important, a belief system), to support the need for a paper-based advertising model.

Many (most?) catalogers have annual repurchase rates under fifty percent. In other words, fewer than fifty percent of 2006 purchasers buy again in 2007. When this happens, the business model demands a disproportionate focus on customer acquisition.

Catalogers look to outside lists and co-op databases (with Abacus being the primary co-op) as the primary way to acquire new customers, looking at paid search and online marketing as a secondary source.

Micro-channels like Abacus / Co-Ops present unique challenges. We need to seriously look at WHO the customers are that we acquire via these channels.

Have you completed this exercise? The exercise is valid for any micro-channel (not just e-mail or co-ops or rented lists or paid search).

Some folks see that the names they acquire from Abacus / Co-Ops are disproportionately rural. These customers are likely to stay in the catalog / telephone environment (which, by the way, is a more measurable environment, making Abacus / Co-Op names appear to perform better, simply because the phone/mail channel is the most measurable ... an interesting and unintended outcome).

Some folks observe that the names they acquire from Abacus / Co-Ops buy fundamentally different merchandise than customers acquired from other sources. This implies that the future value of these names will be different (maybe better, maybe worse). This also implies that, depending upon how many new customers are acquired from these sources, the future merchandise assortment is being driven by co-op statisticians applying sophisticated algorithms.

There are significant differences between names acquired from various sources.

• Rented / Exchanged Lists are brand loyal, this loyalty to another brand drives their future behavior within your brand.
  
• Abacus / Co-Op names are selected by a human using an algorithm. Future behavior is driven by the choices made by the human using the algorithm.
• Paid Search names self-select themselves on the basis of an algorithm. Future behavior is driven by the needs of the person self-selected by the algorithm.

Profiling the names acquired via these micro-channels will give you an idea where your brand is heading. Increasingly, algorithms and outside individuals are driving the future success of our multichannel brands. This is neither good nor bad, it is simply part of our new marketing reality.

Use tools like Multichannel Forensics (or simple future value tables) to understand the long-term trajectory of customers acquired via micro-channels.

Micro-Channel Challenges: E-Mail

Attention E-Mail Marketers!! Next time you see your business intelligence or data mining or SAS programming expert cookin' up a bag of microwave popcorn (preferably buttered), ask them to profile your e-mail marketing list for you.

Keep your analysis simple. Take twelve month buyers, and split them into three groups ... those without an e-mail address, inactive e-mail subscribers, and active e-mail subscribers.

Pay attention to the trends:

• Urban, Suburban, and Rural Customers. Customers have different preferences. The rural e-mail subscriber might respond to free shipping promotions. The urban e-mail subscriber might appear to never respond, because she visits stores after receiving an e-mail campaign.

• Merchandise Preference. E-mail subscribers typically prefer a different merchandise assortment than non e-mail subscribers. You're likely to find that active e-mail subscribers are hyper-loyal to a subset of your merchandise assortment. Brand marketing individuals sometimes wish to use e-mail to communicate a holistic marketing message, whereas the profile might indicate that various e-mail / merchandise combinations represent vital "micro-channels" to customers.

• Advertising Micro-Channels. Do e-mail subscribers and active e-mail customers purchase using e-mail in combination with catalog marketing, direct marketing, search marketing, or any other kind of marketing? If the answer is yes, your multichannel expert may be right in seeking to align all marketing activities across the company.

• Future Channels. One of the unintended consequences of multichannel marketing occurs when one form of marketing (e-mail marketing) is effective, causing the customer to switch channels. Most of the Multichannel Forensics projects I work on suggest that customers are much more likely to switch channels than they are to become loyal multichannel shoppers. See if your e-mail marketing activities shift customer behavior. If e-mail marketing causes a shift to a lower-value channel, re-visit the purpose of e-mail marketing.
  

How Many Customers Should Receive My Retail Catalog?

If you are lucky enough to work in a retail environment that gives the database marketing professional the autonomy to determine retail circulation depth, you're probably using mail and holdout groups to aid your decision.

Here's how many folks approach the subject.


Step 1: Review last year's mail and holdout results. Let's assume you had a holdout group of 100,000 (yup, I said a big number like 100,000 ... if your customer buy more than three times a year, you'll end up needing a big holdout group). Compare performance between the mailed group and the holdout group.

• Mailed Group: Total = $15.00. Retail = $9.00, Online = $4.00, Phone = $2.00.
• Control Group: Total = $12.00. Retail = $7.00, Online = $3.00, Phone = $2.00.
• Incremental Lift: Total = $3.00. Retail = $2.00, Online = $1.00, Phone = $0.00.

We usually look at the incremental lift, in dollars, to decide if the mailing made sense or not. This time, we're going to look at the fractional change, and apply the fractional change to each of our segments.

• Fractional Change = $15.00 / $12.00 = 1.25.

Step 2: Apply the fractional change to each segment. Now, you're likely to have a half dozen statisticians tell you the twenty-nine assumptions you're violating. And they're right. But we're not managing clinical trials for Vioxx, are we? No, we're dealing with something less serious. So, we jump into Excel, and we look at what each segment is expected to spend during the three weeks this retail catalog is active. Once we have the estimate, we apply the fractional change to each segment. Then, we subtract the difference, yielding our expectation for the mailing.

• Segment 1 Expected Spend = $20.00.
  
• Fractional Change = $20.00 * 1.25 = $25.00.
• Expected Catalog Performance = $25.00 - $20.00 = $5.00.

• Segment 2 Expected Spend = $12.00.
• Fractional Change = $12.00 * 1.25 = $15.00.
• Expected Catalog Performance = $15.00 - $12.00 = $3.00.

• Segment 3 Expected Spend = $4.00.
• Fractional Change = $4.00 * 1.25 = $5.00.
• Expected Catalog Performance = $5.00 - $4.00 = $1.00.

Step 3: Run a profit and loss statement against each segment. Depending upon the cost of the catalog, and your flow-through rate from sales to profit, it is likely that only segment one, and maybe segment two, will be profitable.


Step 4: Apply your file forecast to each segment. Multiply performance by file counts. Now, you have a sales and profit forecast for your retail catalog!


Step 5: You can use the relationships in Step 1 to allocate expected sales by channel.


Again, statisticians will have your hide for using such a sloppy sales forecasting process. They'll criticize your assumption that each segment performs at the same level of fractional change. If you and your statistician disagree, go ahead and test within individual segments --- though my experience suggests this strategy isn't fruitful.

Retail Catalog Marketing

Retail catalog marketing is an inexact, imprecise science.

Let's assume that a major American retail brand sends you a catalog on April 1. Let's also assume that your small business purchases from this major American retail brand on the 15th of every month, regardless of marketing activity.

Did the catalog cause you to purchase merchandise?

The answer is probably "no".

The catalog may have influenced the merchandise you purchased. The catalog may have caused you to spend more than you normally would have. The catalog may have caused you to spend less than you normally would have.

But you would have purchased merchandise anyway, no matter what. You always buy something from this brand on the 15th of the month.

Now let's pretend you are the Database Marketing Executive at this major American retail brand. Your job is to measure the effectiveness of this retail catalog marketing effort. Using the tools and techniques available to the database marketers, let's see if you would decide to mail this sample customer future catalogs.


Methodology = Mail And Holdout Groups: Do Not Mail This Customer A Catalog

This is a classic direct marketing strategy, practiced for more than a century (and maybe for centuries). When measuring effectiveness by mail and holdout groups, we'd learn that this customer would purchase regardless of catalog marketing. Therefore, the segment this customer belongs to is not considered a "responder".


Methodology = Pattern Detection: Do Not Mail This Customer A Catalog

Pattern detection suggests that this customer buys on the 15th of every month. The database marketing executive learns that marketing doesn't influence this customer. Therefore, this individual customer would not be considered a responder.


Methodology = Matchback Analytics: Mail This Customer A Catalog

Matchback analytics, the kind offered by major list processing corporations, co-ops, and data compilers, match purchases within a window of time to a marketing activity. Let's say that the matchback window is three weeks (oftentimes, the matchback window is something silly, like ninety days or six months). Any retail purchase within three weeks of the catalog mailing is attributed to the catalog mailing. Therefore, this individual customer would be considered a responder. Here's a little secret. Matchback analytics grossly over-state the effectiveness of most retail activities. You've been warned!!


Methodology = Brand Marketing: Mail This Customer A Catalog

All too often, retail catalog marketing falls into the brand marketing arena. In other words, a budget is set, say $1,000,000. The database marketing team is asked to mail a million customers, to use up the entire budget. The database marketing team executes the strategy. In this case, if our sample customer buys every month, the customer is a "good" customer, and will receive this catalog. This is the most common scenario in retail catalog marketing --- the CMO determines a budget, the CMO determines the marketing tactics that will be employed, and the database marketing executive picks the best customers for any given strategy. In some instances, rogue database marketers set up tests to determine if the strategy actually worked or not. I've executed this rogue strategy myself --- I wanted to understand how much money my company was losing. For the most part, however, the effectiveness of the mailing isn't even measured.


Retail catalog marketing is an inexact, imprecise science. The corporate culture, the quality of information captured in the customer database, and the measurement technique used by the database marketing team determine whether you will receive a retail catalog from your favorite American retail brand.

How does your company execute measurement of retail catalog marketing activities?

If Multichannel Is Better ...

... then why do you purchase books at Amazon.com, and not at Barnes & Noble?

... then why do you rent movies from Netflix and not from Blockbuster?

... then why do you buy shoes at Zappos and not at Nordstrom?

... then why do you buy music at the iTunes store at not at Best Buy?

Quitting

You know the feeling.

Maybe your boss treats you bad. Maybe you aren't being paid enough. Maybe your business model is imploding, causing you to explore new opportunities. Maybe your spouse took a job in San Diego. Maybe you are being run out of your company without formally being fired.

So you decide you have to quit your job.

You probably told a few folks, in confidence, that you are quitting. How do you keep something like that quiet? And they probably told a few folks, in confidence, that you are quitting. And those folks probably told a few folks, in confidence, that you're quitting.

The ninety second walk to tell your supervisor the news seems to take an hour. There's no moisture in your mouth, you're sweating profusely. Am I doing the right thing?

If the circumstances of your departure aren't optimal, you might be inclined to flame out. I recall sitting through an hour of venom when one of my employees quit. After telling me what a horrible individual I was, the employee gave a final work day six weeks into the future. Imagine the damage that could be inflicted in six weeks?! I gave the employee twenty-four hours to inflict damage.

Another employee left, and said all the right things when announcing she was quitting. For the next two weeks, however, there was this vibe, this "I'm going somewhere special, while you labor in this rat hole" attitude.

Oh, I've made all the classic mistakes associated with quitting a job. Back in 1990, I quit a job, made a big stink, only to have the new job fall though the cracks just eight hours later. I had to ask to have my job back the next morning. My Director took the high road, while I learned a valuable lesson in humility.

One day, it will be your turn to quit your job. Consider the change in employment as an opportunity to celebrate the things that were good about the job you're leaving.

ACCM Conference: Your Story

Back in the early 1990s, there was no better way to gauge the vibe in the catalog industry than to attend the Catalog Conference.

Of course, the internet changed everything. The Catalog Conference became the ACCM, trying to hold on to both the hipsters working on e-commerce and the catalog establishment.

The hipsters fled to Shop.org. Shop.org had "the vibe" for awhile.

Then the hipsters fled to Web 2.0 and Blogging conferences. That was fun for about a year, then the hipsters fled to conferences about Facebook, and this year, everybody's a-twitter about Twitter. Who knows where the hipsters will go next month? Who even cares anymore?

So this year, I'm going back to ACCM after a six year absence. The conference organizers were kind enough to accept my application for a press pass, so I plan on doing something useful with the opportunity.

Of course, I'll accept invitations to meet with you about past, current, and future Multichannel Forensics projects. Send me an e-mail, and we'll set up time to meet on Tuesday, May 20 to chat about a Multichannel Forensics project.

I'll also have a limited number of copies of "Hillstrom's Multichannel Secrets" (pictured above) and "Hillstrom's Multichannel Forensics" to give away.

But most important is "your story". I plan on profiling several catalog executives and leaders at the conference, seeking to communicate "your story", describing to our audience what it is like to be a multichannel leader in the era of third-party opt-out engines, e-commerce, ecological disdain for the industry, outsourced databases and circulation, web 9.3, social media, co-op databases, matchback analytics, and falling response rates.

If you want to set up time to tell me "your story", send me an e-mail. I will be available all day May 20, and in the morning on May 21.

One Way To Increase Multichannel Sales

Click on the image to enlarge it.

New Book: Hillstrom's Multichannel Secrets! Get The Draft Version For Free Prior To April 26

My new handbook, "Hillstrom's Multichannel Secrets" will be available next week!!

I've taken a different approach with this handbook. Whereas "Hillstrom's Database Marketing" and "Hillstrom's Multichannel Forensics" focused on the math that supports our craft, "Hillstrom's Multichannel Secrets" outlines "Fifty-Nine Facts Every CEO Can Use To Improve Profitability".

The handbook is written primarily for the Catalog CEO, but applies to the Catalog Executive, Retail Executive, Online Executive, E-Mail Marketing Executive, and anybody who has to deal with multichannel marketing and advertising issues.

Inspired by two of the most popular posts in the history of this blog, 73 Vital Multichannel Catalog Marketing Tips and 53 Vital Multichannel Website / Online Marketing Tips, the handbook drills down on issues every CEO must understand. You'll read all about Catalog Choice, Co-Op Database Use, Matchbacks, Key-Codes, RFM, Test/Control Groups, Online Buyer Lifetime Value, Remail Catalogs, Clickstream Integration, Channel Compromise, E-Mail Marketing, Social Media, List Death, and dozens of additional topics.

There are no fancy charts or complex mathematical formulas in this handbook. You'll simply find 72 pages of high-level facts that CEOs can use to improve profitability, information that many folks believe are proprietary to their business. Given the forces conspiring against the multichannel marketing industry, it is important that all of us improve our base of multichannel marketing knowledge.

When available late next week, the paperback handbook will be available for $14.95. I am self-publishing the handbook using Lulu.

Many of you have been loyal blog readers, and have purchased my previous books. I'd like to give you a little perk for helping build this blog. If you would like to preview the handbook, please send me an e-mail prior to April 26, and I will forward you a PDF file of the next-to-last draft version of the handbook. The PDF will not include the cover (the cover may also change slightly between today and the release date), and the PDF is subject to modification in the final stages of being proofed.

As always, thank you for joining me in this multichannel marketing journey!

Multichannel Advertising Results: Take Charge

A key reason for writing about a typical multichannel results meeting is to help us think about the role of a true multichannel leader.

True multichannel leaders are sorely missing these days. Quick, name one person you've worked with who you would call a true multichannel marketing leader, a person who tells a compelling story, who gets things done across business units, a person who works with honesty and integrity, a person who is on the side of the customer, a person who drives sales and profit increases.

I'm waiting.

There are leaders out there. I'll bet you could name a half-dozen colleagues who are brilliant e-mail marketers, or web analytics geniuses, or catalog marketing mavens, or are a whiz at paid search, or know SAS, Business Objects, or MicroStrategy inside-out, or are masters at newspaper advertising, radio advertising, or television advertising. There are brilliant data miners, who finds nuggets of information buried in a data warehouse of 129,931 active customers.

In the next five years, somebody is going to step out of one of these disciplines and take charge. I've dedicated a book and 760 blog posts on the topic. More than a thousand people read each post. So it is clear there is a need for somebody to put all of this stuff together, at a level that is more detailed than "multichannel customers are the best customers" or "ten steps to integrate multichannel marketing campaigns" or "align inventory and pricing and creative across channels". There is a clear need for multichannel leadership.

Why don't you start by taking responsibility for compiling results across disciplines? Once the results are compiled, why don't you tell a compelling story about the findings?

Look at the table below, comparing catalog and e-mail test results this year, vs. last year.



Remember that in the prior post, catalog marketing performed worse than last year, drawing negative comments from the CMO. Test results show that phone demand decreased, but the catalog drove online and store volume at greater levels than in 2007. E-Mail marketing also drove sales increases. Even though performance at retail was way down, vs. last year, catalog and e-mail marketing (as demonstrated by test and holdout results) both drove profit increases vs. last year. Both were effective!!!

Keep taking initiative. Implement matched market tests for radio and newspaper advertising. Compare the results in the same way that are illustrated above for catalog and e-mail marketing.

Now talk to the online marketers, the paid search gurus. Get the catalog marketers and paid search gurus to work together to demonstrate how customers utilized marketing tactics in combination.

Now get key statistics from your web analytics team. And challenge your web analytics team to go beyond simplistic traffic and landing page and shopping cart and conversion rate metrics. Demand that they tell you who was acting in a positive way, across the entire sale event (not just within visits).

Next, talk to the SAS programmers and data miners down the hall, and have them demonstrate how comparable customers are performing, or have them demonstrate the mix of new and existing customers across years in this sales event.

Armed with the data, tell a story. You can do a lot better than this:


In spite of a very difficult economy, our Early April Sales Event was a resounding multichannel success.

Even though our retail channel experienced a 12% decrease in comp store sales, our multichannel marketing campaigns mitigated the decrease. Without improvements in marketing strategy, the comp store decrease would have been a whopping 17%.

Catalog and e-mail marketing combined to add an incremental $500,000 demand and $100,000 profit, compared with last year. Although customer response over the telephone channel was down, catalog marketing inspired paid search effectiveness. Forty-six percent of paid search purchasers received either a catalog or an e-mail marketing campaign prior to purchasing!

Even better, paid search performed twenty percent better in markets where we had radio and newspaper advertising. We learned that our mix of multichannel marketing tactics, mostly targeted to existing customers, caused improvements in spend among existing customers. Existing customers spent 12% more this year than last year, and were 20% more likely to visit our website.

New customers, however, performed significantly worse than last year, dragging down results (especially at retail). Next year, we recommend increases in radio advertising, because markets where radio advertising was tested had forty percent more new customers than markets where radio advertising was not tested.

Following the sale event, our multichannel customer base increased from 11% to 12% of the total file, while total customers decreased by 3% due to the new customer acquisition shortfall.


Obviously, you can do a much better job at summarizing findings than I can. Given the findings, recommend a course of action for next year. It is time for somebody in e-mail marketing, catalog marketing, web analytics, traditional advertising, business intelligence, data mining, creative, merchandising, inventory management, finance, human resources, customer retention, or customer acquisition marketing to take charge.

A Sample Multichannel Results Meeting

The day starts with an "integration meeting", to discuss the performance of the Early April Sale event.

• The E-Mail Marketing team is delighted to announce that 19% of customers opened the e-mail campaign, compared with 18% last year. 32% of those who opened the e-mail campaign clicked through to the website, and 2.98% of those customers purchased something online (spending $165 each), yielding a $-per-email of $0.30, a full two cents better than last year. The CMO (Chief Marketing Officer) asks if the e-mail campaign drove store traffic, the e-mail marketing team stares at the CMO, unable to answer. The CMO asks if the campaign was profitable or not ... again, no answer.
  

• The Catalog Marketing team appears embarrassed to share results. Response rates dropped from 2.2% to 1.9%. The catalog drove $3.10 to the phone, online, and store channels, and drove a total of $743,000 profit, compared to $840,000 last year. The CMO demands that the catalog marketing team improve their performance, and wants an action plan to do so by May 1.

• The Online Marketing team had budgets frozen at $100,000, in spite of the fact that they caused 22,400 orders at a CPA of less than $5. The CMO asks if this activity was profitable, the online marketing directors thinks so, but can enthusiastically say that the CPA was $13 last year.

• The Retail Field Marketing team thought the newspaper inserts were well executed, and that the radio ads were funny. The CMO praises this team for moving advertising in a "brand-right" direction.

• The Web Analytics team suggests that traffic increased 9.2% vs. last year, conversion rate increased from 2.44% last year to 2.56% this year, and that average order value improved from $175 to $181. The CMO asks why the website performed better, the "WA" team suggest a well-designed landing page. The CMO asks if the website drove more retail sales or less retail sales compared with last year, the "WA" team do not offer an answer.

• The Social Media team noted that there were 147 references to the sale event this year, 104 positive, 43 negative, for a net score of 61. Last year, there were 96 references to the event, 63 positive, 33 negative, for a net score of 30. The most common complaint was a lack of pricing parity between the website and the catalog ... the website took steeper markdowns once the first three days of the sale indicated that results were well below forecast.
  

• The Business Intelligence team analyzed customer behavior during the sale event. They noticed that comparable customers spent the same amount this year as last year, across channels, indicating customers abandoned catalog marketing for store purchases. The CMO notes that retail comp store sales decreased by nine percent, so this finding doesn't make any sense. The "BI" team is asked to go back to the drawing board, and see if there are errors in the database that cause this contrary business finding. The Business Intelligence team says that sales decreased because of a fifty percent decrease in new customers during the sale event. Since the catalog and online marketing teams increased their customer acquisition budget, and the retail field marketing team did more radio advertising than last year, folks generally don't believe the results. The Business Intelligence team also comments that the e-mail campaign drove an additional $0.12 into stores, based on mail/holdout results, but nobody believes this finding, because comp store sales decreased. The BI team also shares that the share of multichannel buyers purchasing during this event actually increased, though nobody believes this result because comp store sales decreased.
  

• The CMO asks if this attempt at integrated marketing "worked". Was this a successful multichannel marketing campaign? The team believes that the catalog marketing effort really dragged down the performance, or it would have been a successful campaign.

• The CMO asks for a total sales and total profit comparison, this year vs. last year. Nobody takes leadership on this topic, as all in the room feel they don't have the "systems in place" to accurately calculate this for the CMO.

• The CMO agrees to outline the performance of all activities "on the back of an envelope", estimating the profit of all activities. The Business Intelligence team is worried about "double counting" transactions, though nobody really understands what this concern is all about.

Ok, folks, this is a typical multichannel results meeting. In this case, everybody reports to the CMO, so you don't have silos competing against each other.

What is wrong with this meeting?

What metrics should be used to analyze the results, this year vs. last year?

Who should own measurement of this event?

Who should be responsible for determining the advertising budget for next year's event? What additional data do you need to properly allocate advertising dollars across e-mail, catalog, online, newspaper, and radio?

What is your Rx, your prescription, for analyzing the next sale period in late June?

The Seattle Sonics Are Moving Their Multichannel Brand To Oklahoma City

NBA owners voted 28-2 to allow the Sonics to move to Oklahoma City. Only Paul Allen of the Portland Trail Blazers (obvious Seattle ties) and Mark Cuban of the Dallas Mavericks felt that forty-one years of fan loyalty mattered a little bit.

Ultimately, a sports team leaving a city is no different than Sears electing to close down an unprofitable store, though a Sears store doesn't bring together a community like a sports team does.


"Back in the day" at Eddie Bauer, President and CEO Rick Fersch footed the bill for a suite at Key Arena. Mr. Fersch allowed garden variety employees (like me) the opportunity to enjoy a smattering of games in the suite. If you were lucky enough to attend, Mr. Fersch was democratic about seating in the suite. He required attendees to switch seats at the end of every quarter so that all employees could enjoy each other's company, and enjoy the perspective of different areas of the suite. This is one of many reasons I fondly remember the leadership of Mr. Fersch.

I was lucky enough to attend two Sonics games in my four years at Eddie Bauer. One was a playoff game in 1998 against the Los Angeles Lakers, an elimination game won by Los Angeles. Actor Leonardo DiCaprio, donning a Lakers jersey, was sitting about ten rows below the Eddie Bauer suite. He had just starred in a movie (maybe you heard of it) called "Titanic".

During a timeout in the second half, when it appeared that the Sonics were going to lose, the crowd became depressed and quiet. Suddenly, one of Mr. Fersch's teenage daughters uttered a high-pitched, ear-piercing scream heard as far away as Bellingham ... "LEONARDO ... I LOVE YOU!". Mr. DiCaprio turned around, identified the young lady who seconds ago joined Mariah Carey as one of only two females to ever reach that octave, and politely nodded his approval.


We were told that if every seat for every game were sold, the Sonics would still lose money.

The Sonics had multiple channels to generate revenue. Corporations could purchase expensive seats. Corporations could purchase sponsorships. Wealthy fans could purchase season tickets. Garden variety fans could purchase individual game tickets. Any fan could purchase concessions, or souvenirs. Revenue came in via a local radio contract. Revenue came in via a local cable television contract. Revenue came in from at least two national cable broadcast stations and one national television network. Taxpayers funded a renovation of Key Arena in the mid 90s to improve the revenue generated from the stadium. I'm sure I'm missing another dozen channels that the Sonics harvested for revenue.

We're told that "multichannel customers are the best customers". In Seattle, multichannel customers (radio, television, in-game attendees, concession stand shoppers, etc.) couldn't generate enough revenue to keep the team here.

This will someday become a problem for our humble little multichannel brands. As we expand our online presence, as we build stores, execute direct mail and e-mail campaigns, manage paid search programs, participate in social media, treat our sites like entertainment brands, we will demand that our customers return the favor by providing us with more and more cash. In the NBA, player costs increase. In multichannel cataloging, the USPS increased costs, and may make life more challenging in 2009. Importing goods from China will cost more. Fuel will cost more. We'll demand that our customers pay the freight, just like an NBA owner demands that the residents of his geography foot the bill.

We're likely to learn, like the NBA in Seattle learned, that no matter how many channels we offer our customers, customers only have so much they can spend. We'll need to be very thoughtful about how we approach using incremental channels to generate sales and profit.

Free Spreadsheet: Calculating The Multichannel Purchase Index (MPI)

Why calculate something by hand when somebody can create a free spreadsheet for you?!

Download the Multichannel Purchase Index (MPI) Calculation Worksheet Here.

I spent some time modeling a three-channel relationship, which is included in the spreadsheet. The spreadsheet will only work if you manage two or three physical channels. If you have more than three channels, it is perfectly acceptable to modify your query to analyze a subset of channels.

The spreadsheet gives you clear instructions about how the index is to be interpreted.

• MPI of 0.00 to 0.99 = You have multiple channels, but your customers do not generally shop multiple channels.

• MPI of 1.00 to 1.49 = You have multiple channels, and your customers are willing to try multiple channels. You're a classic multichannel business.

• MPI of 1.50 or Greater = You have multiple channels, and you have multichannel customers. Being "multichannel" is really important to your business.

The metric is interesting to view, when calculated for the past several years. You'll quickly see whether your customer base is becoming "more multichannel" or "less multichannel". I've witnessed fascinating changes in some of the businesses I've looked at.

Why not leave an anonymous comment, sharing with The MineThatData Blog audience your annual frequency, percentage of multichannel customers, and the MPI for your business? I'm sure our readers would like to see anonymous results.

Thanks,
Kevin

The Multichannel Purchase Index (MPI) And Multichannel Forensics

Let's take a look at three examples of the interplay between the Multichannel Purchase Index (MPI) and Multichannel Forensics.


Example #1: A brand utilizes Online and Retail channels.



This is a typical situation, one where customers transfer from the online channel to the retail channel. Retail customers, however, stay in the retail channel, not being as willing to shop online.

Because the online channel transfers customers to retail, multichannel marketing is important. The Multichannel Purchase Index (MPI) is 1.229, suggesting that this brand is much more "multichannel" than the average brand.


Example #2: Another Online and Retail example.



In this example there is very little interplay between the online and retail channels. The online channel is in equilibrium mode, sending a small number of customers to retail. Retail is in isolation mode, not sending many customers to the online channel. Predictably, only 4.7% of the file is deemed "multichannel", yielding a Multichannel Purchase Index (MPI) of 0.844, below average.

When both channels are in isolation mode, you'll see MPIs between 0.400 and 0.750.


Example #3: Catalog and Online channels.



In this case, each channel is in equilibrium. Each channel passes customers to the other channel. Customers are fully immersed in the "multichannel" experience.

Even though the average purchase frequency is low (1.82), and the percentage of the customer file with multichannel status is only 9.8%, the MPI is very high, 2.522.

This is the beauty of the MPI. It is able to simultaneously adjust for purchase frequency and multichannel status, telling you what is really happening.

Multichannel Forensics and the Multichannel Purchase Index are highly correlated. When channels are in isolation mode with each other, the MPI will be low (<> 1).

Since is it so easy to compute the MPI for your two-channel situation, why not give it a try?

(PERCENTAGE OF 12 MONTH FILE BUYING FROM MULTIPLE CHANNELS LAST YEAR) divided by (0.00559 + 0.05536 * LN (AVERAGE PURCHASE FREQUENCY LAST YEAR)).

Micro-Channels: How Dell Arrived At Their Twitter Strategy

Dell responded to the post on their Outlet/Twitter strategy --- they point us to this article in New Communications Review that outlines the genesis of the strategy and early results.

Thanks, Dell!!

Multichannel Customers: The Multichannel Purchase Index (MPI)

We're told that multichannel customers are the best customers. And from time to time, we hear about somebody who increased their base of multichannel customers.

But how do we know if we're doing a good job of increasing our customer base? Or how do we compare with other companies? Is it good to have 5% of the twelve-month file purchasing from multiple channels? Should 35% of the twelve-month file be purchasing from multiple channels?

One of the problems we face when understanding multichannel customer behavior involves purchase frequency. Take two brands. One brand has a customer base that purchases five times a year. Another brand has a customer base that purchases two times a year. Which brand needs to take multichannel marketing more seriously?

Yup, you guessed correctly! The brand with customers purchasing five times a year needs to take multichannel marketing more seriously than the brand with customers purchasing two times per year. The customer buying five times a year is more likely to bump into more channels than the customer buying two times a year.

Next time you see your Business Intelligence staffer hanging out by the water cooler, ask her to run this query for you. This query assumes you have two channels (online & retail or online + telephone).

• Step 1 = Retrieve all customers who purchased in the past twelve months.

• Step 2 = Calculate the average number of purchases per customer in the past year (assume 2.0 for illustrative purposes).
  

• Step 3 = Calculate the percentage of customers purchasing from multiple channels in the past year (assume 7% for illustrative purposes).

Now, plot these two components against the line in this chart:



If you are above the line, you are, on average, outperforming peer companies. Your customers are more "multichannel" than peer company customers are. This doesn't mean, of course, that you are doing a good job of multichannel marketing. It simply means your customers are purchasing across channels at a greater rate than at peer companies.

If you prefer, use the following equation to calculate the Multichannel Purchase Index (MPI):

(PERCENTAGE OF 12 MONTH FILE BUYING FROM MULTIPLE CHANNELS LAST YEAR) divided by (0.00559 + 0.05536 * LN (AVERAGE PURCHASE FREQUENCY LAST YEAR)).

In our example, this equation equals (0.07) / (0.00559 + 0.05536*LN(2)) = (0.07) / (0.044) = 1.59.

This equation works for 2-channel companies. If the resulting index is > 1.00, your customers are more "multichannel" than at peer companies. If the resulting index is < 1.00, your customers are less "multichannel" than at peer companies.

Let our readers know what you find out when you calculate the Multichannel Purchase Index (MPI).

Thanks,
Kevin

Micro-Channels: Dell Outlet on Twitter

Have you ever had the challenge of having to clear out six pair of shoes, or a single couch, or a handful of sundresses?

Social media guru Shel Israel points us to Dell Outlet, who is using Twitter to clear out various items.

Think about the contrast in this style of marketing, and traditional direct marketing.

• Direct mailers identify an audience, send direct mail at a cost of $0.25 to $1.00 per piece, and generally do a good enough job to make money targeting a list of "x" likely buyers.

• E-Mail marketers identify an audience, send an e-mail campaign that is virtually free, then sit back and enjoy as 1 in 700 customers purchase something.
  

• Micro-channel marketing combines an advertising channel (Twitter) with an e-commerce sub-channel (Dell Outlet) and a community (subscribers to Dell Outlet via Twitter). Those who wish to participate actually participate, those who don't want to don't have to. You're marketing to avid fans on their terms.
  

Given the cost of this marketing platform (hint, it is nearly zero), it is almost embarrassing to consider how few catalog/multichannel brands are willing to test micro-channel strategies.

We're in the very early days of micro-channels. Clearance strategies are a logical place to start testing micro-channels.

Now go give the strategy a try!!!

Zappos Sales Trajectory And Customer Metrics: 2000 - 2012

Copy this hyperlink if you wish to forward this post about Zappos to your colleagues.

When Jim Novo e-mailed me a link to a Catalog Success article outlining facts provided by Alfred Lin, Chairman/CFO/COO of Zappos, I felt compelled to fit the data into the Multichannel Forensics framework! I love analyzing Zappos. They went from zero to almost a billion in sales in less than a decade, during a time when catalogers openly wonder if they would still be in business without paper-based advertising.

Please click on the image to enlarge it.

Here's the data Mr. Lin volunteered to the attendees of the NCOF conference last week.

2007 Customer Metrics:

• 3.4 million twelve-month buyers.
• 7.6 million buyers, ever.
• $247.06 spend per customer in 2007.
• 75% of sales come from existing customers.
  

Historical Financials:

• 2000 Sales = $1.6 million.
• 2001 Sales = $8.6 million.
• 2002 Sales = $31.9 million.
• 2003 Sales = $70.1 million.
• 2004 Sales = $181 million.
• 2005 Sales = $370 million.
• 2006 Sales = $597 million.
• 2007 Sales = $840 million.
• 2008 Sales = $1 billion (projected).

Given this data, can Multichannel Forensics be used to guesstimate the evolution of the customer file at Zappos? Can we use the guesstimate to forecast future sales at Zappos? Let's try!

Mind you, this exercise is for entertainment and illustrative purposes only.

Key guesstimates:

• 55.5% of last year's buyers will purchase again this year (placing Zappos in "Hybrid Mode").
  
• If one of last year's buyers buys again this year, s/he will spend $365.
• Each new customer will spend about $115 in the year the customer is acquired.
• Lapsed customers have significantly lower purchase rates.

Given these assumptions, and the metrics kindly offered by Mr. Lin, we have a series of customer metrics that have been estimated from this exercise.

• 2000 New Customers = 13,913.
• 2001 New Customers = 50,274.
• 2002 New Customers = 169,013.
• 2003 New Customers = 223,212.
• 2004 New Customers = 863,522.
• 2005 New Customers = 1,104,294.
• 2006 New Customers = 1,501,606.
• 2007 New Customers = 1,575,553.
• 2008 New Customers = 1,620,025 (Kevin's Forecast).

New customers fuel future loyal customers. Watch how the estimate of twelve-month buyers grows by year.

• 2000 12-Month Buyers = 13,913.
• 2001 12-Month Buyers = 57,966.
  
• 2002 12-Month Buyers = 203,263.
  
• 2003 12-Month Buyers = 345,442.
  
• 2004 12-Month Buyers = 1,089,198.
  
• 2005 12-Month Buyers = 1,773,903.
• 2006 12-Month Buyers = 2,674,787.
• 2007 12-Month Buyers = 3,400,963 (total buyers, ever, = 7.3 million, I got within 4%, sorry).
  
• 2008 12-Month Buyers = 4,047,348.

Of course, new customers drive file growth. Here is the number of last year's buyers who purchase again this year.

• 2001 Repurchasers = 7,722.
• 2002 Repurchasers = 32,188.
• 2003 Repurchasers = 112,811.
• 2004 Repurchasers = 191,720.
• 2005 Repurchasers = 604,505.
• 2006 Repurchasers = 984,516.
• 2007 Repurchasers = 1,484,507.
• 2008 Repurchasers = 1,887,534.

And then we have customers who did not repurchase a year later. These customers might purchase in future years. Here's how this segment of customers contributes to the customer file.

• 2002 Lapsed Buyers Electing To Purchase Again = 2,062.
• 2003 Lapsed Buyers Electing To Purchase Again = 9,419.
• 2004 Lapsed Buyers Electing To Purchase Again = 33,956.
• 2005 Lapsed Buyers Electing To Purchase Again = 65,104.
• 2006 Lapsed Buyers Electing To Purchase Again = 188,665.
• 2007 Lapsed Buyers Electing To Purchase Again = 340,904.
• 2008 Lapsed Buyers Electing To Purchase Again = 539,788.

These dynamics yield a percentage of sales coming from existing customers. Here's how this metric evolved:

• 2000 = 0% From Existing Customers.
• 2001 = 33% From Existing Customers.
• 2002 = 39% From Existing Customers.
• 2003 = 63% From Existing Customers.
• 2004 = 45% From Existing Customers.
• 2005 = 66% From Existing Customers.
• 2006 = 71% From Existing Customers.
• 2007 = 78% From Existing Customers.
• 2008 = 82% From Existing Customers.

Clearly, I missed this metric by three points. Given how little data Zappos offered, it wasn't easy to get this close!

Here's an estimate for sales per customer, probably not terribly accurate historically, but close in 2007.

• 2000 Sales Per Customer = $115.
• 2001 Sales Per Customer = $148.
• 2002 Sales Per Customer = $157.
• 2003 Sales Per Customer = $203.
• 2004 Sales Per Customer = $166.
• 2005 Sales Per Customer = $209.
• 2006 Sales Per Customer = $223.
• 2007 Sales Per Customer = $247.
• 2008 Sales Per Customer = $262.
  

Basically, the data suggest that Zappos had a massive customer acquisition effort from 2004 - 2006, and that effort is paying off in 2007 and 2008. The data suggest that sales growth was fueled by new customers from 2000 - 2004, and has been fueled by loyal customers since.

The data also suggest that Zappos might be reigning in increases in customer acquisition spend, or has hit a wall at how many new customers can be profitably acquired. This stalls future growth, with the brand forecast to grow by a one-hundred-fifty million to two-hundred-million a year, per year, over the next four years.

The framework allows me to guesstimate future value of each newly acquired customer.

• Sales In Acquisition Year = $115.
• Sales In First Full Year = $203.
• Sales In Second Full Year = $164.
• Sales In Third Full Year = $141.
• Sales In Fourth Full Year = $124.
• Sales In Fifth Full Year = $110.
• Sales In Sixth Full Year = $98.
• Sales In Seventh Full Year = $88.
• Sales In Eighth Full Year = $78.
• Sales In Ninth Full Year = $70.
• Sales In Tenth Full Year = $63.

The estimated $1,138 of future sales (over ten years) provides Zappos with an enormous opportunity to lose a ton of money per customer they acquire, because the customer will pay back so much in the future. This simulation suggests Zappos may have done a comparable analysis at some point in the past, dramatically ramping-up customer acquisition spend.

Again, this exercise is for entertainment and illustrative purposes only. I plugged very general assumptions into the Multichannel Forensics framework, yielding a profile of the brand that directionally illustrates future trajectory (assuming a 2% CAGR in new customers).

• Projected 2008 Sales = $1,060,000.
• Projected 2009 Sales = $1,262,831.
• Projected 2010 Sales = $1,451,895.
• Projected 2011 Sales = $1,626,714.
• Projected 2012 Sales = $1,787,229.
  

You, too, can use the Multichannel Forensics framework to build simulations like this!

Akin Arikan's Multichannel Marketing Metrics Blog

Akin recently initiated a blog called Multichannel Marketing Metrics. He works at Unica Corporation. Unica supports the "Affinium" suite of products used for campaign management during my time at Nordstrom.

If you have a chance, check out his blog!

Sally McKenzie at the E-Commerce Consulting Blog

I worked with Sally "back in the day" when Eddie Bauer had an online channel that generated $15,000,000 of business a year. Sally shepherded the growth of the online channel at Eddie Bauer during those unique times.

Today, she contributes content at the E-Commerce Consulting Blog. Give her content a peek!

The Catalog Chronicles Blog

There aren't many of us who talk about multichannel issues (formerly known as catalog issues).

A new blog, called The Catalog Chronicles Blog, is hosted by Tom Kothman, Principal of Thomas Associates, and former CEO of Motherwear International. Following a brief review of his content, I was heartened to see somebody publicly acknowledge the challenges the industry faces.

Shocking Multichannel Profitability Findings

The blogosphere tells us we're supposed to use compelling subject lines if we want to get your attention.

You should run this query against your own customer information. You probably won't find this information on your corporate customer information dashboard. Click on the image to enlarge it. Here's how we obtain the data necessary to run the query.

Query, Step 1: Identify all customers who purchased during 2006.

Query, Step 2: Sum 2006 demand/sales, sum 2006 channels purchased from, for each customer.

Query, Step 3: For the customers in Steps 1-2, sum 2007 demand/sales, also sum 2007 advertising expense allocated to each customer.

Query, Step 4: Bucket each 2006 customer into one of five quintiles, based on 2006 spend.

Query, Step 5: For each combination of total channels purchased from in 2006, and demand/spend quntile in 2006, calculate the average 2007 demand/sales for that segment, average advertising spend, and average profit.


What Do The Trends Suggest?

Learning #1: Multichannel customers are not the best customers. Would you rather have a customer in the second quintile who bought from one channel, or a customer in the third quintile who bought from three channels? Historical multichannel activity is not nearly as good an indicator of future demand/profitability as is historical spend.

Learning #2: Multichannel customers are not necessarily the most profitable customers. Why? Because each additional channel a customer purchased from in 2006 resulted in an incremental increase in advertising to that customer in 2007. In fact, take a peek at the information. Customers from 21% to 60% (40% of last year's customer file) are less profitable in 2007, in spite of having purchased from more channels in 2006. Many multichannel marketers over-advertise to the "best" customers, actually reducing corporate profitability.


Recommended Strategy: If your brand has customers who exhibit this behavior, this requires a re-think of your multichannel marketing strategy. Do you send catalogs, postcards, e-mail campaigns, RSS feeds etc. to the same multichannel customer, announcing the same sales event, or do you cut back on your ad-spend across this audience, focusing on finding new customers that generate future sales? I recommend the latter.


If you don't believe what is illustrated here, run the query against your own customer data. See if you identify similar trends. If you don't host your own customer database, have the co-op or database organization that hosts your database run this query for you.

Tell us what you learn!

Celebrate Express Q3 Catalog Implosion

Celebrate Express (NASDAQ: BDAY) announced a third quarter loss (before taxes) of $4.7 million (on sales of $13.3 million).

Wow.

Catalog circulation strategy was cited as a key contributor to the implosion. According to the 10-Q statement, increased postage costs drove changes in circulation strategy. The company blamed sub-optimal catalog selection and mailing strategy, saying "... certain circulation decisions and execution problems resulted in catalog mailings to a mix of customers and prospect customers which we believe were less productive".

The company states that a new data warehouse and hiring of marketing talent are expected to improve results. Long-time readers of this blog know a pair of fundamental truths about catalog and online marketing strategy, truths that will serve Celebrate Express well:

• Smart & Experienced People + Strategy > Data Warehouse + Data Mining

• Smart & Experienced People + Data Warehouse + Data Mining + Strategy = Profit
  

The company recently hired long time multichannel marketing whiz Harry Egler to help solve key challenges in catalog and online marketing. I worked for/with Mr. Egler, he's one of the kindest individuals you'll ever meet.

Celebrate Express enjoyed profitable performance a few years ago. Here's hoping that Harry can help return the brand to prominence.

Multichannel Challenges

Your response to "A Day In The Life Of A Multichannel Leader" indicates the parable is comparable to your own experiences.

On purpose, I didn't tell you the org structure of this brand. That piece of information doesn't really matter.

In many multichannel businesses, there are commonalities in the reporting structure. Listed below are a few gross over-generalizations:

• Department Managers Report To Store Managers, Who Report To Regional Managers, Who Report To A Store Marketing Officer.
  

• E-Mail Managers, Paid Search Managers, And Online Marketing Managers Report To An Online Marketing Director.

• Catalog Acquisition Manager And Catalog Customer Retention Manager And Catalog Operations Manager Report To A Catalog Marketing Director.

• Store Marketing Managers And Field Marketing Managers Report To A Traditional Media Marketing Director.

• The Online Marketing Director, Catalog Marketing Director, And Traditional Media Marketing Director Report To The Chief Marketing Officer.

• The Chief Marketing Officer And Store Officer Are Members Of The Executive Team.

• The Executive Team Might Also Have An Online Officer, A Catalog Officer, A Chief Financial Officer, A Chief Human Resources Officer, And A Chief Merchandising Officer.

If the structure is similar to this, there are "practical positives" and "matrixed challenges". Multichannel pundits look at all the matrixed challenges (the e-commerce head wanting to do something different than the store officer), demanding that a non-silo-based structure eliminates these challenges.

Your challenge is to think about how you would structure an organization in a way that eliminates the challenges outlined in the "A Day In the Life Of A Multichannel Leader" post. It isn't easy, folks.

You don't easily stop the back-biting that happens when somebody makes a mistake executing an e-mail campaign.

You don't easily reconcile the challenges of excess inventory in the retail channel with the ease with which merchandise is cleared online with the fact that prices can stay fixed in a catalog for six months.

You don't easily reconcile the challenge of creating a landing page in a half hour online with the need to plan a catalog spread for three months prior to the in-home date with the challenge of flexibly managing floorset timing in retail.

You don't easily reconcile the holistic ideals of a Human Resources Leader with the cold, financial reality of a Chief Financial Officer.

Multichannel marketing is really hard to execute well, so much harder than just plopping in a "one view of inventory management" system, executing seamlessly integrated multichannel marketing campaigns, and creating a simple org chart realignment that gives some uber-leader control over everything.

Multichannel marketing is about getting a set of diverse individuals to work together in a professional, collaborative, and respectful manner. This challenge occurs any time more than one person is involved in a project, and seems to be one of the key reasons we were put on this planet. If you know of a company that does this well, let's arrange for a field trip to visit that company!

Lands' End Free Shipping. Do You Follow The Rules?

At dinner Thursday evening, a guest asked me about my profession. When I mentioned the companies I've worked for, she said, "Oh Lands' End! Did you know that I get free shipping from Lands' End on every order?"

She told us that she assembles her order online, then calls the 1-800-356-4444, and reads the items residing in her shopping cart. Then she "gets crabby", telling the agent she will not pay for shipping and handling. The agent, being a kind, humble person from Southwestern Wisconsin, waives the $16.95 fee on her $210 order.

The obedient soul who follows directions pays 8% more than the crabby individual.

I've sat in executive meetings where this topic comes up. In every case I can remember, my leadership partners and I elected to give a better price to the crabby customer.

Our industry will have made progress when we figure out how to not be punitive to kind customers who follow the rules.