Employee Orders: A Barometer Of Business Success

Maybe your company offers employees a discount when they place an order. If so, good for you!

If you analyze customer information at this company, great for you! You have the inside track to fascinating information.

You're likely to have a merchandising team that has passion for the products they offer. This merchandising team might believe that they are just a competent marketing team away from having tremendous success.

If you find yourself being blamed by your merchandising team for not driving sales and profit, give this analysis a try:

1. Identify how many employees you had last year at this time.
2. Identify how many employees you currently have. Somebody in Human Resources would love to help you identify an accurate number!
3. Sum total demand from employees during September 2007.
4. Sum total demand from employees during September 2008.
5. Calculate spend per employee, September 2007 and September 2008 (i.e. $10.00 in September 2007, $8.50 in September 2008).
6. Calculate comp employee sales ($8.50 / $10.00 - 1) = -15%.

Twice in my career I was pummeled by a merchandising executive for being a lousy marketer. Twice I ran this series of queries. Twice I observed that employees didn't like the merchandise any more than customers liked the merchandise. Twice I ended up with a grumpy merchant, unable to blame marketing for sales shortfalls.

There are few things in database marketing more convincing than the sales generated by employees. If employees don't believe in the merchandise, how the heck are customers supposed to believe in the merchandise?

Starbucks Database Marketing

It wasn't that long ago that marketers lauded Starbucks, praising decisions like selling CDs and the like.

And then things happened. The business posts a quarterly loss for the first time in sixteen years, and the critics get to have their day while the marketing fans shy away.

Folks who work in Database Marketing departments like to diagnose the reasons why a business is struggling, from a customer standpoint. And when a brand is in Retention Mode, like Starbucks is, folks might look at a very simple set of metrics.

A typical dashboard might look at customers who shopped in a Starbucks store in June, measuring how likely the customers were to repurchase in July. The dashboard compares 2008 performance to similar customers in 2007. Of course, ninety percent of folks tell you "you don't capture every single customer, what about all of those customers paying with cash, customers you cannot track?" Those pundits would rather you do nothing than at least gaining some insight. I vote for gaining some insight.

This is what the a dashboard might look like within a specific market (the data are not representative of Starbucks, and are only presented for illustrative purposes).

	Jul-08	Jul-07	----Change
June Households	10,000	10,500	-4.8%
Repurchase Rate	0.782	0.831	-5.9%
Total Buyers	7,820	8,726	-10.4%
Orders per Buyer	8.341	8.492	-1.8%
Items per Order	1.243	1.184	5.0%
Price per Item	3.894	3.790	2.7%
Average Order Value	4.840	4.487	7.9%
Total Volume	$315,713	$332,500	-5.0%
All Other Buyers	3,941	4,782	-17.6%
Orders per Buyer	3.743	3.593	4.2%
Items per Order	1.143	1.074	6.4%
Price per Item	3.631	3.504	3.6%
Average Order Value	4.150	3.763	10.3%
Total Volume	$61,221	$64,660	-5.3%

Assuming you're able to capture the performance of some customers, you get the opportunity to get some level of insight. In this hypothetical case, June customers are less likely to visit the store, but are buying more items and spending more. This kind of simulates the "less traffic" situation you hear about.

Other customers exhibit a similar trend.

More often than not, pundits rip database marketers for making conclusions about customer behavior when not every transaction can be measured. Always remember to clearly state the limitations in the data being presented, but always remember that it is better to present something than to hide behind the crutch that you're not tracking cash customers. And web analytics pros --- you fall into the same boat!!

In no way am I saying that Starbucks does this ... I'm just using their brand for illustrative purposes.

Another tip --- when closing stores, you make strategic choices based on the customer base supporting stores. For instance, given two stores that are equally unprofitable, you kill the store that competes with more stores in the same geographic area. That's kind of a "duh", but, the data exists to make these kind of insights, so you may as well use the data to your advantage. Back in the day at Eddie Bauer, we evaluated every store based on estimated cannibalization rates --- understanding how each store was impacted by neighboring stores.

Multichannel Forensics A to Z: Database Marketing

In many ways, Multichannel Forensics (book, study) is a logical extension of popular techniques that fall under the title of "Database Marketing".

The goal of Database Marketing is to store information about the behavior of customers or users, then combine the information in an actionable way to either increase sales, or increase profit.

Unfortunately, the easiest way to increase sales or profit is to impact marketing campaigns. As a consequence, Database Marketing (as well as Web Analytics and Business Intelligence, both logical extensions of Database Marketing) became campaign-focused, looking to optimize short-term sales and profit. And by doing so, Database Marketing lost relevance among the mythical folks that occupy the coveted wing of the corporate office known as the "C-Suite".

Multichannel Forensics move beyond campaigns, looking instead to quantify the long-term health of a business, as a function of prior customer behavior and anticipated future trends.

If you want to capture the imagination of an executive, hold a crystal ball that tells the executive what the future looks like. Multichannel Forensics make for a good crystal ball.

Effective Use Of Your Database

At some point in the past five years, you probably invested in your customer database.

Maybe you built a series of normalized tables ... elegantly designed in a way that would make any IT professional proud. Maybe you hooked up Business Objects or MicroStrategy to the database, believing that you could answer any question you could think of.

Maybe you integrated your web analytics tool with your centralized customer data warehouse, expecting lightning bolts to appear from the sky about the casual visitor who browsed eight important landing pages before buying something in the store.

Or maybe you outsourced your database to a quality vendor who specializes in said activity.

I'm guessing that you're still dissatisfied with what you have.

You've probably learned the following equations:

• People > Database Design
• Database Design > Software
  

In other words, when crafting your database marketing platform, you focus on people first. One gifted query analyst or statistician means far more than any database you'll ever design. Far more!!

Database design means more than software. You need a series of summarized tables for campaign management. Don't ever let your software vendor or IT leader tell you not to store detail-level data (one row per item purchased, one row per page viewed). Your data expert needs the detail-level data to answer all the questions that cannot be answered by summarized fields.

Once those two aspects of the equation are solved, get good software.

Effective use of a database requires us to realize that people are more important than database design, and that database design is more important that software. This spring, many of you are communicating to me that your organizations view this the other way around ... you are outsourcing your analytical staff to India, you are outsourcing control of your databases, and you are relying on simple BI tools to query against summarized fields that don't adequately answer questions.

Let's turn this trend around!!

Rebuild Your Database Marketing Department: Wrap-Up

Lather, Rinse, Repeat

Once you're knee-deep into year two, you'll realize that not everything went the way you thought it would go.

Your web analytics expert quit, leaving you in a bind.

Your e-mail vendor was bought out by another company, causing a temporary reduction in service and a new account manager to be assigned to your team.

Paper and postage costs required you to reduce catalog circulation by thirty percent.

You over-invested in e-mail marketing frequency, actually causing a loss, not the profit increase you promised.

You listened to the pundits and started a blog, only to be told you are behind the times and that you should be on Facebook, only to be told you are behind the times and should be on Twitter, only to be told you are behind the times and must be on Plurk ... all in a six month period of time!

Keyword inflation caused you to have to increase your paid search budget, and that increase caused you to not invest in your customer information systems.

A sour economy caused you to have to downsize your team by fifteen percent.

By the end of year two, nothing looks the way you thought it would. The world changed. It is your responsibility to change with it.

This means you have to start the rebuilding process all over again.

Given what you and your team learned the first time around, you'll be much better at the process this time.

This time, delegate the majority of the process to the leaders who work for you. They'll be tired of your antics if they have to implement your ideas all over again, just two years after starting the process. Put them in charge of the process, and where possible, embrace their ideas.

Life has a way of repeating itself every two or three years in the direct marketing world. There are natural business cycles. People have unique career interests. Systems need to be refreshed. Technology causes us to re-work our processes. The rebuilding process begins anew.

Hopefully, this series provided you with a framework for thinking about how to navigate challenging times.

Lather, rinse, repeat!

Rebuild Your Database Marketing Department: Org Structure

The third most asked question is "how should I structure my database marketing department?"

Too often, we're served an endless array of pap about abandoning "silos". You know all about silos. Silos are the org structure where functional areas work together and sit together, working sometimes without knowledge of what somebody else is doing. The e-mail marketer doesn't know what the catalog marketer is doing, the web analytics expert doesn't know when an important telemarketing campaign is happening, yadda yadda yadda.

You don't solve these problems by putting all of these departments under one individual. I've observed horrible problems created by a centralized and powerful team that "make the rules". I've also observed horrible problems created by silos.

So what's the answer?

Try hiring somebody (and give this person the authority to make decisions) who collaborates between silos. Think about States. Here in Washington, we have different laws than the folks in Oregon have. Yet as a loose federation, States have rights to do things their way, but theoretically benefit from a centralized government in Washington, DC, where they receive proportional representation (house) and equal representation (senate).

We can debate about how government is mucked-up. But the concept of having somebody coordinate activities between "silos" works. The individual must have the right personality --- an extrovert who gets folks to do things without direct reporting relationships is hard to find.

In instances where I've seen different marketing disciplines get along, there is always somebody who "makes this happen". This person is seldom the actual leader of any given team --- it is usually somebody who simply takes responsibility. She might be a circulation manager who gets the e-mail folks to talk to the web analytics team (I see this all the time). He might be the business intelligence Director who needs to get the retail marketing folks to talk to the paid search team (I see this one too).

If you're looking for a career niche, this is one that will need highly qualified individuals over the next five years.

I'd focus on finding a person who fills this role more than trying to identify the perfect org structure.

Rebuild Your Database Marketing Department: KPIs And People

Two questions come up all the time. Let's talk a bit about them.


Question #1: What are the two or three key metrics, KPI's (key performance indicators), that I should track in order to make sure that my business is being managed successfully?

Answer: Two or three? Try two or three hundred! I'm frequently asked about the half-dozen metrics that should be included in a management dashboard. Our businesses have become complicated, folks. In fact, they were always complicated, we just didn't have the proliferation of channels to help us understand how complicated they were.

Sr. Management seems to like monitoring two or three metrics, so make life easy for them. I personally monitor rolling twelve month buyers (new and existing), orders/buyer, items/order, price/item, repurchase rate. These metrics seldom steer you wrong. I also like creating a "comp customer" segment --- a definition of customers that does not change over time (though the customers in the segment change all the time). I monitor comp customer segment performance each month, reporting it like one reports comp store sales changes. This is the indicator I look to, to understand the health of my merchandise assortment.

But honestly, there are two hundred or three hundred metrics all of us should be tracking, across all advertising micro-channel, all physical micro-channels, and across all functions in the company (inventory management, creative, human resources, you name the department, there are metrics that should be tracked).

I'd have a notebook of hundreds of metrics, only sharing the ones that "tell a story" about why the business succeeded or failed that month.


Question #2: Can you tell me if my analytics person, e-mail marketing manager, web analytics leader, or circulation manager is talented enough to do the job?

Answer: This is the request I receive most often. And in almost every case, the answer to the question is "yes". Management, however, is asking the wrong question.

There are two questions that underlie the asked question:

• Can my analytics person translate technical facts into actionable tidbits that Sr. Management can use to run the business?

• Is my analytics person creative enough to find actionable tidbits not requested by Sr. Management?

In many cases, the answer to each question is "no".

Regardless of the field (e-mail marketing, catalog circulation, web analytics, paid search, business intelligence), technicians speak a "code" language unique to the profession (example: "I used the mean function within the aggregate procedure in SPSS to calculate the annual repurchase rate, so I know the metric is correct").

The code language does not translate to Sr. Management, folks who are looking for clear, concise language that reveals actionable steps to success. Without a mentor, folks struggle with this level of translation. Heck, I met a former EVP of Marketing colleague at the ACCM conference who told me, and I quote, "Your consulting business probably stinks because nobody can understand a word you say, everything you say is so complicated."

So unless we figure out how to talk to business leaders, using their language, we're sunk.

The question about creativity, however, is far more important. There are three types of database marketers.

• Those who do what management tells them to do.
• Those who creatively focus on topics not asked for by management, topics that are not going to be actionable within the current corporate climate.
• Those who creatively focus on topics not asked for by management, topics that are going to be highly actionable to management.

You might surmise that the middle database marketer is the one you don't want to have on your team, or want to mentor toward success.

Management frequently believes that the best database marketer is one who does exactly what they are told to do. Unfortunately, this person is simply the easiest person to work with.

The best database marketer is the one who finds solutions to problems that management will ask about in the future, but does not have the context to ask about yet.


People are the number one problem I run across in my profession. Management thinks they don't have the right database marketing staff. Staff don't think management are asking the right questions. In general, there isn't an easy answer for resolving this disconnect without both sides giving way a little bit.

If you're tasked with rebuilding a database marketing team, spend a lot of time working on fixing this disconnect.

Rebuild Your Database Marketing Department: Part 7 (Salary Information Included)

Create A Career Path

Near the end of your first year, you know your people, you know them really well. Some have "it", that special intangible skill that enables them to become Executives. Some have "that", that special technical skill that allows them to be a subject matter expert at what they do. And then you have all the valuable employees who are needed to make sure the company keeps running.

You'll need to have multiple career paths for folks.

Folks will need to know what it takes to have your job.

Folks will need to know what it takes to have another leadership position in another department.

Folks will need to know what it takes to become the imperial wizard, the subject matter expert revered by all.

All three paths require "the juice", a combination of compensation, recognition, autonomy, authority, and accountability. "The juice" must be clearly stated, must be good enough for folks to stretch themselves to strive toward. And you must follow-through on "the juice" --- it isn't a carrot you dangle in front of folks forever.

You'll partner with Human Resources to develop the career paths. And if your Human Resources team (or Executive Leadership) fail to provide you with the authority to compensate folks, promote folks, or given them what they need, you need to communicate this fact to your staff --- allowing them to make decisions that are in their best interests.

Too often, the Human Resources / Compensation department carry out the wishes of Sr. Management --- by suppressing expense. How is a 3% cost-of-living increase going to pay for the gas required to get you to work? They aren't on the side of your employees --- YOU have to be on the side of your employees, defending their interests.

Part of the career path includes compensation. Entry level analysts will probably fetch $40,000 to $60,000 per year. Sr. Analysts and Managers might fetch between $60,000 and $100,000. Directors could earn $100,000 to $150,000 per year, and might command a 20% bonus. A well-qualified Vice President probably earns between $150,000 and $225,000 per year, with a 30% bonus.

The challenge is to create a career path for non-management folks, one that can get them into six-figure territory without having to manage staff. One might consider a significant incentive-based salary, one that depends upon the incremental profit the individual contributes to the organization.

So create some sort of career advancement plan that benefits them, be on their side!

Rebuild Your Database Marketing Department: Part 6

Hit The Road, Jack!

Now that you have a strategic plan in place for year two, you need to tell EVERYBODY about it!

If you work for a retailer, this means you visit stores if necessary, to communicate your catalog, e-mail, and paid search marketing strategy.

If you work for a cataloger, this means you visit the call center and distribution center. You tell every employee why you are doing what you are doing, you share with them how these strategies will benefit them. If you are an e-mail marketer, when is the last time you went outside your department, and clearly explained to all of your co-workers what you do or what your strategic direction is? How about those of you who are paid search marketers?

If you work for an online pure-play, you meet with every functional department in your company, explaining how customers behave, explaining why you have to make the changes you are making.

You meet with all the folks who you put a firewall between nearly a year ago, explaining why the information you learned shapes the direction you're taking your department in.

You visit your vendors. You communicate with them how their input in the "conferences" you held early in the year shaped this strategy. You remind them that they are an important part of your team.

And you LISTEN. Listen to what people have to say. Their input could influence changes in your strategic plan.

Hit the road, Jack!

Rebuild Your Database Marketing Department: Part 5

Create The Strategic Plan For Year Two

You are ten months into your rebuilding project.

You know your team, their strengths, their weaknesses. You know what your company needs. You know the capabilities of your vendor team. You picked up all of the low-hanging fruit.

It is time to set your strategic vision for year two of your rebuilding project.

This requires you to collaborate with many audiences.

• You need input from your Executive Leadership Team.

• You need input from key employees in the company.

• You need input from your leadership team.

The strategic plan for year two outlines what you will be working on, what you need resources for, and outlines how the company benefits from the investment they will make in your team.

You have thoroughly measured everything about customer behavior --- this knowledge is the basis for the strategic plan.

You'll probably need a significant investment in systems in order to accomplish your goals. The strategic plan tells folks why systems must be improved, and is defended by facts about your customers. If you don't get "x", the company fails to generate profit totaling "y".

The strategic plan tells your team what they need to focus on in the upcoming year. The strategic plan tells your Executive Co-Workers what you will be focusing on. The strategic plan informs the company what your team will do to drive the bottom-line.

Rebuild Your Database Marketing Department: Part 4

Know Everything About How Your Customers Behave

By now, you're six months into your rebuilding project. Your staff largely resent you, your vendors think you're about to fire them, and leaders in other departments want you out because you've blocked access to the folks they used to manipulate.

You probably know something about the skills of your team. You probably have an idea of how your team can contribute to the success of the company. You probably need ammunition to fuel the objectives you're going to set next year.

It is time to know everything about how your customers behave.

If you don't have the internal staff necessary to do a good job, hire somebody from outside the company. Execute a thorough mining of your customer base. Understand everything about the loyalty of your customers, their future value, their propensity to shop via multiple channels or multiple advertising channels, their migration patterns through different merchandise divisions.

This information will become the basis for your objectives next year. The information will determine how you invest in systems, how you invest in advertising, how you invest in people, how you invest in advertising. It means everything. Get this done by month nine, if you can!

Know everything about how your customers behave.

Rebuild Your Database Marketing Department: Part 3

Put Up A Firewall

All around you, well meaning Executives, Directors, and Managers have their own agenda for your team. In fact, they've always had their own agenda for your team. It is one of the reasons you must rebuild your database marketing team.

You have that Director in the Information Technology department who thinks your KPIs aren't appropriate for your business. He's working behind the scenes with a select group of leaders to create the customer information infrastructure that he believes will drive the business into the 21st century --- and he will have his team answer the customer questions asked by management (hint, this happens all the time, folks).

You have the EVP of Merchandising who wants to dictate to your team the catalog and e-mail marketing targeting strategy. Heck, her job is on the line, and she's not going to let your team ruin her ability to keep her job.

Part of rebuilding a database marketing department involves letting your co-workers know that this is YOUR AREA OF RESPONSIBILITY!!

You don't tell your merchants what merchandise to source from China, do you? You don't tell the Information Technology folks which online order entry platform they must use, do you?

Conversely, nobody should dictate the work your team does except for you.

This requires you to walk a fine line. You must allow others to ask questions of your team, and you must allow your team to answer those questions independent of your leadership. And yet, you must make it clear to every person in your company that you set the agenda, you determine the priorities --- and if their request isn't a high priority, it won't get worked on.

You will communicate to the company what the top priorities are for the fiscal year. You will report, on a periodic basis, the successes and failures your team experience. You will set the agenda for the direction your department takes.

Too often, the database marketing department is being run by forces outside of the database marketing department. This leads to a rudderless ship, a fractured team working for the special interests of folks outside of the database marketing team. You'll never have a winning database marketing team when there are eight cooks in the kitchen, with seven coming from other kitchens!

Put up a firewall!

Rebuild Your Database Marketing Department: Part 2

The Vendor Conference

Now that you've put the fear of God in your team by demanding that they meet your high expectations (things like working a full work day or not tearing into each other), it is time to find out what everybody is made of.

In each functional area, invite the vendor that supports that area for a one day or two day conference. You pay the vendor for their time. You invite the staff that manage the functional area to participate --- everything is transparent, you don't betray trust by having a hidden agenda.

The conference is designed to illustrate what your staff know about their functional area. It is also designed to illustrate what your vendor knows about their area of expertise. Your staff are required to present their processes and results to the vendor. The vendor is required to present "best practices" to you and your staff.

More than anything, you get to see if your staff have what it takes to succeed. You get to see if your vendor is capable of being a "strategic partner". You get to benchmark yourself against competitors.

Don't be stingy --- invite every vendor you have, be it your co-ops, your e-mail vendor, the folks you outsource your database to, your catalog request fulfillment house, your paid search vendor, your statistical modeling joint, bring 'em all in.

It will probably take three or four months to get through your "conferences". Your staff are likely to rebel against you, suggesting that since you set such high expectations, they don't have time for this garbage. Your vendor is likely to not meet your expectations --- they may send the sales force instead of sending the CEO or EVP that you really need to meet (hint, that tells you something about the vendor).

Your job is to gather information, information that will shape the future of your database marketing department.

Rebuild Your Database Marketing Department: Part 1

Set High Expectations.

You've been handed a department that you believe is broken. People don't get along. Your staff fail to obey "best practices".

You can fix this problem by forcing everybody to do everything your way. How often have you seen this happen? The new boss comes in with her own "system", and requires that everybody do things her way.

A weak leader demands that everybody do things a certain way. A weak leader tells you to put the shopping cart in the upper right hand corner of an e-mail marketing campaign. A weak leader demands you participate in every catalog co-op. A weak leader demands that a spreadsheet be formatted a certain way, with certain columns populated a certain way.

A strong leader sets high expectations.

Here are some of the things the new database marketing leader might do in year one.

• Demand that all employees work a full work week. Don't demand the location they work from.

• Demand that all employees get along, or they will not keep their job.

• Demand that all employees attend at least one industry conference, and implement at least one thing they learned at their conference.
  

• Demand that all employees submit a career advancement plan to you, and it is perfectly fine for the employee to tell you that he is happy where he is.

• Demand that the entire department spend the first six months of the year calculating the profit they contribute to the company on an annual basis, and then demand that in the second half of the year, the department increase total profit by ten percent.

These are simple objectives.

More important, you aren't telling anybody "HOW" to do them. You are simply setting expectations that create a winning culture.

And then, you're going to HOLD people to these objectives. If they don't follow them, they don't get a raise. If they fight against the objectives and act in a subversive manner, they don't work in your department anymore. You act consistently, showing favoritism only for the folks who enthusiastically embrace the objectives and improve profitability. This is hard to do, and it is painful. But you do it.

The first step in rebuilding a database marketing department is setting high expectations. The second step is to follow through.

In my first six months at Nordstrom, in 2001, my expectations drove eight of ten employees out of the company, via retirement, via quitting, via being let go. It nearly cost me my job. But the rebuilding process made 2003, 2004, and 2005 among the best years I've seen a team have.

Set high expectations. This process begins and ends with YOU, not with software, not by implementing a system, not by hiring the right people. It starts with your leadership.

Rebuilding Your Database Marketing Department

The Seattle Mariners have a huge payroll. They also have the worst record in the American League. It is time for the ballclub to "rebuild", to start over, to find a new way to be successful in the future.

In sports, the system of metrics make it easy to know when it is time to rebuild. Wins and losses, divisional titles, playoff wins, championships, player statistics, fan attendance, television and radio ratings all tell a compelling story. In sports, the "KPI's", if you will, make decisions easy.

Now let's fast forward to your database marketing team in the year 2008. What are the metrics that tell you that you need to rebuild your database marketing team?

It isn't easy to identify the metrics, is it? Are your e-mail marketing campaigns generating $0.12 per delivered e-mail? Is that bad? And if it is bad, is it the fault of your e-mail marketing manager? How would you ever know if your web analytics expert is doing a good job? How would you ever know if your catalog circulation manager is transitioning your customer file to one that no longer needs catalog marketing anymore? How would you ever know if that should be your strategy?

We really don't have outstanding metrics to evaluate the performance of database marketers, do we?

This week, we're going to talk about rebuilding a database marketing department. Enough of you share with me that you perceive your database marketing efforts are broken, so the topic is worth discussing. We'll explore people, data, metrics, and vendors, all in the search for a highly functioning database marketing department.

We are not going to explore software. You don't succeed because you chose Coremetrics over their competition. You don't succeed by outsourcing your database to Abacus vs. building it in-house. You don't succeed by working with Return Path vs. CheetahMail, or by choosing SAS over SPSS. You don't succeed by having perfect KPIs perfectly presented on a management dashboard for all to see.

You succeed when you create a great environment that allows brilliant people to thrive, to be creative.

We'll find that this analysis series comes up short. I don't have all the answers. I do want to inspire you to do better, to be successful.

Tomorrow, we begin.

Great Moments In Database Marketing #1: Incremental Value

Our top rated Database Marketing moment takes us back to 1993 - 1994. Yeah, way back then, people were doing sophisticated work. Honestly!

Way back in the early 1990s at Lands' End, we had seven different business units that marketed to customers, either through standalone catalogs, or though pages added to catalogs.

As growth became more and more difficult (pay close attention online marketers ... your world is heading in this direction), management elected to mail targeted catalogs to targeted customer segments.

In other words, a Mens Tailored catalog concept was developed, with a half-dozen or more incremental catalogs mailed to customers who preferred Mens Tailored merchandise. A Home catalog concept was developed, with nine or more incremental catalogs mailed to customers who preferred Home merchandise.

Seven concepts were developed. Each concept was growing.

But the core catalog, the monthly catalog mailed for three decades, was not really growing anymore. And total company profit (as a percentage of net sales) was generally decreasing over time.

Something was amiss.

We studied the housefile, and learned that the "best" customers were being "bombed" by catalogs ... upwards of forty a year. Every business unit, making independent mailing decisions, mailed essentially the same customers. And all of our metrics, when viewed at a corporate level, indicated that customers were not spending fundamentally more than they spent several years ago when the new business concepts didn't exist.

So we developed a test. We selected ten percent of our housefile, and created seven columns in a spreadsheet. We randomly populated each column with the words "YES" or "NO', at a 50% / 50% proportion. Each business unit was assigned to a column. When it came time to make mailing decisions for that business unit, we referred to the column assigned to the business unit. If the word "NO" appeared, we did not mail the customer (if the customer qualified for the mailing based on RFM or model score criteria).

In statistics, this is called a 2^7 Factorial Design.

There are two reasons for designing a test of this nature.

1. Quantify the incremental value (sales and profit) that each business unit contributes to the total brand.
2. Identify, across customers segments, the number of catalogs a customer should receive to optimize profitability.

What did we learn?

1. Each catalog mailed to a customer drove less and less incremental increases in sales. If a dozen catalogs caused a customer to spend $100, then two dozen catalogs caused customers to spend $141, and three dozen catalogs caused customers to spend $173. The relationship roughly approximated the Square Root Rule you've read so much about on this blog.
2. Each business unit, on average, was contributing only 70% of the volume that company reporting suggested the business unit was contributing. In other words, if you didn't mail the catalogs, you'd lose 70% of the sales, with customers spending 30% elsewhere.

The latter point is critical.

Take a look at the table below, one that illustrates the profit and loss statement reported by finance, and one that applies the results of the test.

Test Results Analysis		Finance	From
		Reported	Test Results
Demand		$50,000,000	$35,000,000
Net Sales	82.0%	$41,000,000	$28,700,000
Gross Margin	55.0%	$22,550,000	$15,785,000
Less Marketing Cost		$9,000,000	$9,000,000
Less Pick/Pack/Ship	11.0%	$4,510,000	$3,157,000
Variable Profit		$9,040,000	$3,628,000
Less Fixed Costs		$6,000,000	$6,000,000
Earnings Before Taxes		$3,040,000	($2,372,000)
% Of Net Sales		7.4%	-8.3%

The test indicated that what appeared to be highly profitable business units were actually marginally profitable, or in some cases, unprofitable. In this example, the business unit is "70% incremental", meaning that if the business unit did not exist, 70% of the sales volume would disappear, while 30% would be spent anyway by the customer, spent on other merchandise.

Imagine if you were the EVP responsible for a business unit that appeared to generate 7.4% pre-tax profit, only to have some rube in the database marketing department tell you that your efforts are actually draining the company of profit?


Why Does This Matter?

This style of old-school testing (which is more than a hundred years old, with elements of the testing strategy now employed aggressively in online marketing) tells you how valuable your marketing and merchandising initiatives truly are.

Catalogers fail to do this style of testing, not realizing that a portion of catalog driven sales would still be generated online (or in other catalogs). In 2008, most catalog marketers are grossly over-mailing existing buyers. Catalog Choice, in part, exists due to catalogers mis-reading this phenomenon.

E-mail marketers seldom execute these tests, not realizing that in many cases almost all of the sales would still be generated online. E-mail marketers, ask your e-mail marketing vendor to partner with you on test designs like the ones mentioned in this article. You may be surprised by what you learn!

Online marketers are more likely than most marketers to execute A/B splits at minimum, with some executing factorial designs. Many online brands evolve in a Darwinian style, fueled by the results of factorial designs. Online marketers know that you make mistakes quickly, and you correct those mistakes quickly.

Web Analytics folks have the responsibility to tell management when sku proliferation no longer contributes to increased sales. It is important for Web Analytics folks to lead the online marketing community, shutting off portions of the website in various tests to understand the incremental value of each additional sku.

What are your thoughts on this style of testing? What have you learned by executing tests of this nature?

Great Moments In Database Marketing #2: Multichannel Forensics

We've talked an awful lot about Multichannel Forensics on this blog. Maybe you noticed? Many of you purchased the book on Multichannel Forensics. Close to four thousand of you read the Multichannel Forensics white paper. In just the past year alone, I've put about forty brands through the Multichannel Forensics filter. Who knows how many you've analyzed?!

The reason we spend so much time talking about this topic is because it can be a challenge to understand micro-channels without having a tool that identifies how customers migrate between micro-channels.

E-Mail marketers typically evaluate the performance of their marketing strategies across only customers who click on an e-mail campaign. Catalog marketers are obsessed with allocating online orders back to catalog marketing. Web Analytics experts are focused on visit-specific conversion rates. Retailers focus on customer intelligence that drives comp store sales increases. Online marketers care about online marketing channels. Few people focus on long-term customer value. Almost nobody at your company can tell you what the five-year sales trajectory of your brand looks like, by product, brand or channel.

So many of you found Multichannel Forensics valuable because it provides a framework for understanding how customers interact with advertising, products, brands and channels.

Multichannel Forensics were born at Eddie Bauer in the late 1990s, when we tried to understand how markets evolved as new stores were opened in combination with the birth of e-commerce.

Multichannel Forensics allowed us to demonstrate that catalog marketing wasn't needed at Nordstrom, that e-commerce and stores interacted in a way that benefited the customer (customers evolved from catalog to e-commerce, then e-commerce to stores).

As micro-channels continue to proliferate, Multichannel Forensics will be the preferred method for understanding how customers migrate through the many "touchpoints" a brand possesses.

Great Moments In Database Marketing #3: Micro-Channels

A small number of marketers are doing an exceptional job of evaluating micro-channels. The focus on micro-channels yields actionable and strategic insights that are not part of the mainstream marketing conversation.

These folks are linking data from various systems. These folks don't care whether they have 100% coverage or not, they simply link what they have. If they can't link visitation information to every purchaser in the database, they don't. They work with what they have.

These folks maintain a customer database with fields like these:

• Months Since Last Purchase, Life-To-Date Purchases, Life-To-Date Items, Life-To-Date Demand/Sales, Life-To-Date Returns, Twelve-Month Purchases / Items / Demand / Sales / Returns
• Total Company
• By Physical Channel (Mail, Telephone, Internet, Retail).
• By Advertising Channel (E-Mail, Catalog, Google Paid Search, Yahoo! Paid Search, MSN Paid Search, Portal Advertising, Affiliate Marketing, Shopping Comparison Marketing, By Most Popular Blogs).
• By Merchandise Division.
• By Store Or Region
  

• Months Since Last E-Mail Click-Through, Total E-Mail Click-Throughs, Total E-Mail Twelve-Month Click-Throughs.

• Website Visitation Data
• Months Since Last Visit
• Number Of Life-To-Date Visits, Number Of Twelve-Month Visits.
• Average Time Spent On Site Per Visit.
• Number Of Pages Visited.
• Months Since Last Visit By Key Landing Page, Merchandise Division, Key Links.
• Months Since Last Shopping Cart Abandonment, Number Of Carts Abandoned.

• Outbound Marketing History
• Catalogs Mailed, E-Mails Mailed, Telemarketing Calls, Direct Mail Pieces.

• Self-Service Marketing Initiated By Customer
• RSS Subscriber And Items Subscribed To.
• Paid Search And Natural Search Activities.
• Visits From Key Blogs, Facebook, MySpace, Social Media.

When I speak with the marketers who maintain this information, they most important thing is to simply accumulate what you can accumulate. Then, you get busy analyzing the information!!

I've worked on a few projects with data of this nature. The findings are fascinating.

• Websites are a separate channel from e-commerce. There is an information element to the website that supports other channels. There is a social element to a website that allows customers to interact with each other. There is an entertainment element to a website that causes customers to visit again. And there is an e-commerce component to the site. Customers self-segment themselves into one of these micro-channels.

• E-commerce customers have unique dynamics.
  
• Those from paid search have a very different relationship with your brand ... unless they use another form of advertising (e-mail, catalogs) in combination with paid search.
• Once the catalog customer tries e-commerce, they become unlikely to go back to ordering over the phone.
• Once the e-commerce customer purchases in a store, they become less likely to go back to ordering via the internet. This does not mean they become unlikely to use the internet --- in fact, they become information/entertainment/social users.

• Trigger-based e-mail marketing is ideally suited for customers who last visited the website within ten days.

• You learn that you have a couple hundred important micro-channels, combinations of advertising, self-service activity, and purchase channel. You learn not to "force" customers into micro-channels --- instead, you let customers self-select themselves into a micro-channel, and work with the customer based on her natural, subsequent behavior.

• Customers evolve across micro-channels, often migrating to a "most popular" micro-channel over time.

Examples of micro-channels:

• E-Mail click-through customer who visits website frequently and buys merchandise in-store.

• Paid search customer who does not subsequently repurchase.

• Rural customer who buys online after receiving a catalog.

• Customer who visits site after reading a blog post about merchandise, visits frequently, does not buy merchandise.

• Customer visits site after seeing portal ad, signs up for e-mail marketing.

• Customer buys in-store only.
  

• Customer only shops via landing pages (i.e. needs a merchandising assortment presented to her).

• Customer only shops via site search (i.e. a self-service customer who picks and chooses what she wants).

From what I've observed, the future of database marketing is the identification of micro-channels, the classification of customers into micro-channels, and then market / no-market decisions based on micro-channels.

The folks I've seen do this style of marketing are producing very interesting results.

Great Moments In Database Marketing #5: Free Friday

If you are a database marketer, one who specializes on answering questions using SPSS/SAS/SQL, you've met up face-to-face with the concept of the "time crunch".

You begin your work day with a clear vision of what you want to accomplish. By 8:43am, your day has gone sideways. Elsie in Customer Service wants you to query the customer records of an individual who is upset that she no longer receives e-mail campaigns. The angry VP down the hall wants you to count how many customers responded to his promotion using a specific discount code last Wednesday. The earnest search marketer wants you to calculate how many customers visiting your site with a specific keyword place subsequent orders.

Before you know it, you spend your entire day writing queries for folks who do not have the skills necessary to query a database. If you go down this path, you lose your identify. You are no longer a valuable employee --- instead, you become a hybridized version of software.

Worse, you spend almost no time working on strategic issues. Everything you do is calibrated toward answering random "point in time" questions.

How do you fix this problem?

You don't!

But you can do something to mitigate the problem. I called it "Free Friday".

The idea isn't a new one. In 1996 at Eddie Bauer, I was stuck in a rut similar to the one I mentioned earlier. So I declared Friday to be "Free Friday". I would not answer any business question on Friday ... ANY Friday! Friday was "my time", time to research strategic issues and obtuse problems others didn't find important.

There was a price to pay for this freedom. I had to work forty hours a week Monday - Thursday to meet the needs of my co-workers. But then Friday was all mine.

Almost every key strategy that we employed in catalog marketing in 1998 - 2000 came from the "Free Friday" days of 1996 - 1997. Multichannel Forensics are almost entirely the result of "Free Friday". Our new store scoring algorithm and cannibalization metrics were the result of "Free Friday". Understanding online cannibalization was the result of "Free Friday". Interestingly, none of these topics were requested by co-workers or Sr. Management. They came from having the time to think clearly, to research ideas, to freely explore concepts.

Consider the concept of "Free Friday" in your work environment.

Great Moments In Database Marketing #6: Long-Term Impact of Promotions at Eddie Bauer

We go back to 1998 for this Great Moment in Database Marketing.

At the time, I was Director of Circulation at Eddie Bauer, a brand that was punch-drunk on promotions. Anytime a customer failed to purchase in six months, the "CRM/Circulation" process offered the customer a "20% off $100" promotion ... twenty percent off your next order of one-hundred dollars or more".

We tested these promotions until we were blue in the face. Continually, they showed that the customer spent about twenty percent more if offered this promotion.

So, the promotions became part of "what we did". And then my team decided to execute a long-term test. For the next six months, we would not offer a segment of lapsed customers a single promotion.

What do you think happened?

Take a look at the following table, a table that approximates the actual results of the test.

Eddie Bauer Six Month Promotion Test: 1998
	Receive	No	Incr-
	Promos	Promos	ement
Month 1	$10.80	$9.00	$1.80
Month 2	$9.00	$9.30	($0.30)
Month 3	$10.80	$9.60	$1.20
Month 4	$9.00	$9.90	($0.90)
Month 5	$10.80	$10.20	$0.60
Month 6	$9.00	$10.50	($1.50)
Demand	$59.40	$58.50	$0.90
Net Sales	$41.58	$40.95	$0.63
Gross Margin	$22.87	$22.52	$0.35
Marketing	$9.00	$9.00	$0.00
Promos	$4.07	$0.00	$4.07
Pick/Pack/Ship	$4.99	$4.91	$0.08
Profit	$4.80	$8.61	($3.80)
% of Sales	11.6%	21.0%	-9.5%

Oh oh.

Here's the 411 folks. When customers are continually promoted to, they delay purchases until the promotion is offered to them.

In our test, if customers were not offered promotions, they slowly began to "build momentum". Instead of the every-other-month cadence of promotions to this audience (the actual test had a different rhythm than illustrated above), the customer waited for promotions, did not receive them, then started spending more.

After six months, we noticed that customer spend in the two groups was nearly identical!

Now look at profit. Sure, the group that received promotions appeared profitable --- they appeared profitable via every system we had in the company, via every A/B test we executed.

But when viewed via a long-term A/B test, the results were significantly different. We were losing a boatload of money promoting to customers who would ultimately spend the same amount of money if we didn't execute the promotion.

In 1999, we dramatically pulled back on promotions. Total Net Sales decreased by maybe five or six percent. Total profit hit an all-time record high.

The core fundamentals of direct marketing are often violated in the world of "instant metrics" we've created. Our e-mail marketing friends read open rates and conversion rates from a "Free Shipping" e-mail within an hour of blasting the campaign. The adrenaline rush felt from obtaining instant access to customer behavior fuels strategy.

My challenge to the e-mail marketing and web analytics community, two communities that live and die by a steady diet of exhilarating and instantaneous metrics, is this ... do your metrics allow you to understand if what we observed at Eddie Bauer in 1998 is happening in your business? And if your visit-specific metrics don't allow you to observe a trend like this, what kind of systems/software/human investment is needed to allow for this style of measurement?


Hillstrom's Multichannel Secrets: Fifty-Nine Facts For CEOs!

Great Moments In Database Marketing #7: S&P 500

Back in 2001, I was brought in to help change the trajectory of Nordstrom Direct. The direct-to-consumer arm of Nordstrom struggled through another amazingly unprofitable year in 2000. A host of former Lands' End leaders partnered with in-house talent, tasked with turning things around.

The business began to crater in November 2000, with performance hitting rock bottom in Spring 2001. By September 11, any glimmer of hope was shattered by the events of the day. Soon thereafter, the focus shifted to enabling donation buttons for the Red Cross, and to anthrax in the mail system.

Our President was a plucky data hound named Mike Smith, current leader of Bag, Borrow or Steal. Mr. Smith felt that any problem could be solved by analyzing customer information. Mr. Smith charged me with figuring out "what was wrong with business".

Business is influenced by multiple factors. You self-inflict damage with the dumb things you do to yourself. Your competitors inflict damage with their strategies. And the economy can inflict damage.

You might recall that 2000 - 2001 was known as the "dot com bubble". Surprisingly, these bubbles just keep on happening!

I was able to develop a non-linear set of equations that correlated changes in the S&P 500 with changes in Nordstrom Direct sales performance. In fact, the equations explained sixty percent of the shortfall in business.

Not easily impressed by answers that fail to immediately fix the business, Mr. Smith panned the analysis. It is the responsibility of business leaders to improve business today, so the response was directionally appropriate.

But that doesn't mean you stop quantifying the impact external factors play in the trajectory of your business. Mired in yet another self-inflicted bubble, a business leader might want to know when we're "about to pull out of this mess". Pundits chattering on CNN probably won't give you the information you need.

So build relationships that correlate economic factors with changes in business performance. Use the equations as a forward-looking indicator to tell you when you're ready to pull out of an economic slump. Understand how much of the damage is created by the economy, and understand how much is self-inflicted.

Great Moments In Database Marketing #8: The Rolling 12 Month File

The rolling twelve month file is one of the most under-utilized metrics in all of Database Marketing.

I was exposed to the metric in the early 1990s at Lands' End, after a few folks from Fingerhut made their way onto the Dodgeville campus.

The metric was put into use at Eddie Bauer in the mid 1990s. At the time, Eddie Bauer was a highly profitable brand, a brand going through an amazingly brisk retail transformation.

The rolling twelve month file is the "Dow Jones Industrial Index" of the Database Marketing world. It is a trailing indicator, telling you how many customers purchased from a product, brand, channel or store in the past twelve months. During times of change, the metric tells you what happened. It cannot tell you why something happened --- it is your job to figure out why!

We'd pick a market, say Omaha. Omaha did not have a retail store until the mid 1990s. We would measure how many customers purchased via the catalog, online, and retail channels in Omaha on a rolling twelve month basis.

When a store opened in a new market, the market was transformed. Catalog buyers decreased, online buyers flattened out, and retail buyer grew at a rapid rate. In other words, the new retail store was cannibalizing direct-to-consumer customers. And this is the way it generally works at brands that have a strong direct channel, then choose to add stores to the mix. Sure, you're now a multichannel brand, but the transformation comes with a cost.

In a new market, the rolling twelve month file for the retail store would stabilize within fifteen to eighteen month after a new store opened. After eighteen months, the market maintained a new balance between the channels, with each channel able to once again grow or thrive at the rate previous to the opening of the new store.

When you open a bunch of new stores, it is a good thing to conduct rolling twelve month file analysis for each market. The charts are also telling in saturated markets ... open a new store in a market that already has five stores, and watch what happens!

Any metric can be tabulated on a rolling twelve month basis. The key is to look for changes in the metric over time, then, dig into the data to understand why the metric is changing.

At Eddie Bauer, market saturation became obvious when viewing channels and stores through the rolling twelve month metric.



Hillstrom's Multichannel Secrets, Now Available!!

Great Moments In Database Marketing #9: The Square Root Rule

This is the second in a ten part series of key database marketing moments that shaped the focus of The MineThatData Blog.

We go back to 1991 for the origin of The Square Root rule.

"Back in the day", catalogers were experimenting with statistical models. At Lands' End, statistical models had been used to decide who received catalog mailings since at least the mid 1980s.

But statistical models can make deciding how much a segment of customers might spend a real headache.

Consider this example.

• A segment has 10,000 customers.
• Only 8,000 customers were selected by the statistical model to receive the mailing.
• The segment of 8,000 customers spent $3.00 per customer, $24,000 total, when mailed the catalog.

How much would the total segment of 10,000 customers have spent, if all customers were mailed the catalog?

It would take nearly seven years to find a simple solution to this problem.

Honestly, one can use "rules of thumb", or statisticians can create unique models for every catalog to solve this problem.

After witnessing the results of maybe 300 catalog mailings over a seven year period of time, a simple solution was created. In 1998 at Eddie Bauer, we developed "The Square Root Rule".

• The 8,000 customers above spent $3.00 per catalog, $24,000 total.
• If 10,000 customers would have been mailed, total spend would increase by the following factor:
• (10,000 / 8,000) ^ 0.5 = 1.25 ^ 0.5 = 1.118.
• In other words, 10,000 customers would have spent $24,000 * 1.118 = $26,832.
• Dollar per catalog for 10,000 customers = $26,832 / 10,000 = $2.68.
• The remaining 2,000 customers would have spent $2,832 / 2,000 = $1.42 each.

By simply knowing the percentage of customers mailed in each segment, this simple rule allowed the circulation analyst to "guesstimate" what might have happened if all customers in the segment were mailed.

The Square Root Rule applies to advertising budgets and page counts and items offered per e-mail campaign ... basically any situation where you have limited information and no good history to estimate what might happen.

Of course, the approximation has numerous limitations. Don't use it to extrapolate too far ... if you only mail 10% of the customers in a segment, the equation might fail. If you want to mail 3x as many customers as were mailed last year, the equation will fail.

But for many instances, this equation solves problems, especially if you have limited data and you don't have a statistician sitting next to you, awaiting your beckon call!

Great Moments In Database Marketing #10: The 3/2/1 Rule

During the next two weeks, we'll explore some of the unique things teams I've worked with have learned during the past twenty years about customer behavior.

#10 is the "3/2/1" rule. I once worked with a large retailer that did a spectacular job of linking website visitation data with store visit survey information and purchase data across all channels. The retailer learned that multichannel customers visit the e-commerce website three times a month, shop the store two times a month, then purchase once a month (with 85% of the purchases occurring in-store, 15% online).

How does your view of customer behavior change when you know this fact? It should cause your head to pop with possibilities!!!

First of all, you realize that your Web Analytics information is largely incomplete. Who cares if the visit-specific conversion rate is 3.04838290%? Within this project, we realized that conversion, when measured on a monthly basis (counting e-commerce and store purchases) was utterly staggering. Staggering!! More than ten times the visit-specific conversion rate.

All of a sudden, that cross-channel inventory system sounds like a good idea!

The web analytics corner of the world doesn't have enough data to tell you about the true power of your e-commerce website. You need your Business Intelligence team (and they better know SAS or SPSS, not just basic tools like Business Objects or MicroStrategy) to lead you down this path. And most important ... you need your BI team to mentor your Web Analytics team, you need them to teach the Web Analytics folks how customer behavior works across and between channels.

The true power of your e-commerce website is measured in a monthly or yearly conversion rate, combining conversions from all channels. You'll never view your website (or your analytics team) the same way, once you identify your version of the 3/2/1 rule!

Seasonal Buyers

When times are tough, and profit is of the utmost importance, take a look at buyers who purchase seasonally.

For instance, today is May 6. There are two kinds of customers who may have varying levels of response in May.

• Customers who last purchased (or first purchased) in May 2007, May 2006, May 2005, May 2004, May 2003, you get the picture. If these customers only purchase in April, May or June, they're worth taking another shot at during May 2008.

• Customers who last purchased (or first purchased) in December 2007, December 2006, December 2005, December 2004, December 2003. These are holiday shoppers, and they don't generally care that "spring is gardening season". Save your pennies!

Seasonal buyers --- you're not likely to hear about this little profit-saving trick from the purveyors of today's "best practices".

Best Answer: E-Mail Analytics Challenge

One hundred twenty one of you attempted The MineThatData E-Mail Analytics And Data Mining Challenge. Kudos to all who investigated a potential solution! If you want to try a solution, download the dataset here.

No solutions were submitted from the e-mail blogging community, or the e-mail vendor community. Considering that a quarter of our audience represents the e-mail marketing community (including readers from all major US-based e-mail marketing vendors), I was disappointed that thought leadership failed to emerge from this audience.

The winning solution from the academic and data mining community was submitted by Nicolas Radcliffe of Stochastic Solutions. Mr. Radcliffe also hosts a blog, discussing the advantages of his methodology, called Uplift Modeling.

His paper is titled, "Hillstrom's MineThatData Email Analytics Challenge: An Approach Using Uplift Modeling".

A copy of "Hillstrom's Multichannel Forensics" will be sent to Mr. Radcliffe. Congrats to Mr. Radcliffe on his winning entry!

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?