Catalog Marketing - Profit Means Everything!

You see it everywhere you go ... profit just laying on the ground ... with nobody motivated to bother to pick it up and stick it in their wallet!!

When a business is dysfunctional, profit leaks out, everywhere.  From analysts choosing to measure "conversion" instead of profit to email wonks looking at opens/clicks/conversions to cloud-based catalog circulation folks, we barely bother to measure profit.

Internally, we lack discipline ... high return rates, high pick/pack/ship expenses, all of it hurts the p&l.

Look at this example ... the first company does a credible job of generating profit ... with 45% of demand flowing through to profit.

The second company lets profit leak, or they fail to measure profit accurately and just stick a "40%" factor into their decision-making processes.

The first company, with a 45% profit factor, can mail down to 1,800,000 circulation depth ... generating $4,024,922 demand.

The second company, with a 40% profit factor due to either a leaky profit bucket or an analyst making a random, arbitrary 40% profit designation, can only afford to mail 1,400,000 customers, generating $3,549,648 demand.

Which business would you rather be part of?  I'd pick the first business ... the focus on profit allows the business to generate 13% more demand.

If the second business has a leaky bucket, then this is the true impact on the business.

• Scenario #1 = $4,024,922 demand, 40,249 orders, $911,215 profit.
• Scenario #2 = $3,549,648 demand, 35,496 orders, $719,859 profit.

If the second business is equally profitable to the first business, but the business has sloppy analysts who mis-estimate profit, then this is the impact:

• Scenario #1 = $4,024,922 demand, 40,249 orders, $911,215 profit.
• Scenario #2 = $3,549,648 demand, 35,496 orders, $897,342 profit.

The first example is the fault of every employee in the company, the penalty for being sloppy.

The second example is the fault of just one employee, making a bad decision estimating how much demand flows-through to profit.  If this company sends 10 mailings a year, then one analyst, one individual, is costing the company $5,000,000 in annual demand - 50,000 orders (and likely, 40,000 customers who would generate incremental future profit), and $140,000 annual profit.

One analyst - acting alone, costing the business a 13% sales increase.

In catalog marketing, profit means EVERYTHING!  There is no margin for error, there is a discipline that must be adhered to - without discipline, the business suffers - just because of one or two people.

And if you outsource your catalog circulation efforts, well, just how much attention to detail do you think you're getting vs. in-house resources?  Your outsourcing efforts could easily harm your business by 10%, if you are not telling your cloud-based circulation experts how to execute every single aspect of circulation management.

Catalog Marketing - Profit Means Everything!  Maybe business is in the tank because of a lack of discipline around measuring profit?

De--Leveraging

In the banking world, when you borrow too much money and you fail, you go through a period of de-leveraging.  It is a painful process.

Our worldwide economy is about five years into a de-leveraging process.  Many of us lost jobs, or took a beating on home values, all part of a de-leveraging process.  It stinks.

This happens in our world, too.  You can tell by looking at a profit and loss statement.

Here's a summary of a reasonably healthy profit and loss statement.

• Net Sales = $50,000,000.
• Ad Cost = $5,000,000.
• EBITDA = $6,000,000.
• Ad to Sales Ratio = 10%.

Three years later, we see something like this:

• Net Sales = $53,000,000.
• Ad Cost = $8,000,000.
• EBITDA = $5,000,000.
• Ad to Sales Ratio = 15%.

Clearly, the business is struggling.  Sales have plateaued, so Management is spending a ton of money to keep sales growing.  This hurts profitability.

Three years later, the business is in trouble.

• Net Sales = $55,000,000.
• Ad Cost = $10,000,000.
• EBITDA = $3,000,000.
• Ad to Sales Ratio = 18%.

Here's the problem.  This business probably needs to de-leverage.  But when it de-leverages, it will be much, much smaller.

• Net Sales = $35,000,000.
• Ad Cost = $5,000,000.
• EBITDA = $3,500,000.
• Ad to Sales Ratio = 14%.

Can you see why Management would balk at de-leveraging?  The business shrinks by close to 40%, and profit barely changes!

There's two issues with this.

1. Nearly $20,000,000 of sales is being generated for no benefit whatsoever.  Why generate sales that don't produce short-term or long-term profit? Be honest.
2. What could you be doing with the $5,000,000 of ad cost that is not generating any profit whatsoever?

Answering the second question is critical.  What could you do with the $5,000,000 you are spending to generate no benefit whatsoever?

Most of us cannot answer that question, and for a good reason.  It's a hard question to answer!

As a result, we keep plugging along, hoping that something will mysteriously change.

It's pretty darn important to have an answer to the second question.

P.S.:  I cannot tell you how often I run into the "$20,000,000 demand and $0 profit" problem.  It's everywhere.  Your paid search people cause this problem, and your catalog circulation people cause this problem.  You mail so close to break-even or by paying for clicks right around break-even.  Now, I get it, you're theorizing that the long-term value of these decisions pay for themselves.  That may be true.  But what the heck else could you be doing with that money?  You could practically start a new business!  But nobody wants to lose $20,000,000 of demand that generates $0 profit.  And I know, you're going to start leaving comments with MBA theory about why this is a good decision.  We can agree to disagree.

Do You Want To Prove That Engagement Leads To ROI? Try This Methodology

Are you one of millions of marketers/analysts trying to prove that engagement exists, and more important, leads to increased return on investment?


The pick up a broom and start sweeping ... I'll show you a method that loyalty marketers have been using for twenty years to prove that loyalty marketing delivers a return on investment.  I use more technical versions of this methodology to calculate the value of loyalty programs for current clients, running a full profit and loss statement on the outcome of this analysis.  Hint:  It works!


Step 1:  Create your engagement measure.  This will be a different metric for everybody, so there's no sense spending time discussing it, you are the expert at knowing your business.  Customers who you consider to be "engaged" receive a value of "1", while customers who you do not consider to be "engaged" receive a value of "0".  Only use the timeframe up to 10/31/2011 for your engagement period.


Step 2:  Create RFM-based variables.  For each customer, through 10/31/2011, calculate months since last purchase, number of 12-month purchases, number of 13+ month purchases, and historical average order value.


Your audience is comprised of all customers with 1+ purchase (via Step 2).


Step 3:  I will assume that you don't have profitability data, so let's make this really easy.  Create a variable called "Future" ... it has a value of "0" for all customers who did not purchase from 11/1/2011 to 11/30/2011 ... it has a value of "1" for all customers who did purchase between 11/1/2011 to 11/30/2011.


Step 4:  Match the query in Step 3 to the query in Step 2.  Then, match these queries to Step 1, all at a customer level.


Step 5:  Run a Logistic Regression (you can take this much further if you have profitability data ... Logistic Regression for response, OLS for spend/profitability).  Regress Future against Recency (usually Square Root of Recency), 0-12 Month Orders, 13+ Month Orders, Average Order Value, and Engagement.


If "Engagement" is a significant predictor with a positive coefficient, then you just proved that, for the month of November, engagement during October led to an increased probability of a customer purchasing in November.


Ok, here's the SPSS code required to run the Logistic Regression procedure I described above:



LOGISTIC REGRESSION VARIABLES future 
  /METHOD=FSTEP(WALD) root_recency freq12 freq99 average_order_value engagement 
  /CRITERIA=PIN(.05) POUT(.10) ITERATE(20) CUT(.5).
execute.



Here's the outcome of a trial I ran earlier today:

In this example, the square root of recency is easily most important.  Recent orders carry about 5 times the weight of older orders.  Large dollar orders result in customers less likely to buy again in the future.  And most important (while not terribly significant), customers who were "engaged" in October were more likely to buy in November, after accounting for all other RFM-based variables.


In fact, "engaged" customers were 22.7% more likely to buy again, all things being equal.


Armed with this outcome, we can put a profitability number on "engagement".  We'll make the financial analysis terribly simple, for demonstration purposes.


Let's assume that we have 250,000 customers in the database.  Of the 250,000 customers, 5,000 are considered "engaged".  Let's assume that our 250,000 customer database has a 3% chance of buying in November.  And let's pretend that, if a customer purchases, the customer will spend $100.  Finally, let's pretend that 35% of demand flows-through to profit, and let's pretend that one employee is responsible for improving engagement, at a cost of $8,000 per month (salary + benefits).


Total Expected Housefile Demand = 250,000 * 0.03 * $100 = $750,000.


Now, we know that 5,000 engaged customers are 22.7% more likely to purchase because they are "engaged", right?  So, our calculation changes a bit.


Total Expected Housefile Demand = (245,000 * 0.03 * $100) + (5,000 * 0.03 * 1.227 * $100) = $753,405.


The impact of engaged customers is ... $753,405 - $750,000 = $3,405.


At 35% profit, this translates to $3,405 * 0.35 = $1,192 profit.


But, we hired an individual to generate engagement, and we paid the employee $8,000 to get the job done in November.


How many "engaged" customers do we need to make the effort worthwhile?  Well, we have 5,000 engaged customers who generated $1,192 profit, prior to employee costs, or $0.2384 profit per customer.  To offset employee costs, we need 8,000 / 0.2384 = 33,557 engaged customers.


So, at this point, here's what we know:

1. We demonstrated that engaged customers are 22.7% more likely to purchase, all things being equal.  In this example, Engagement does lead to improvements in customer loyalty. And isn't that what you really wanted to demonstrate?
2. We only have 5,000 customers meeting "Engagement" criteria.  As a result, we only generated $3,405 of incremental demand.
3. After accounting for employee costs, our engagement efforts are not generating a positive ROI.
4. Every engaged customer is worth an additional $0.24 profit, per month, to the company.
5. If subsequent engagement activities result in having at least 33,557 engaged customers, we can demonstrate that increased engagement can be accomplished at break-even levels.

Statisticians will poke holes in this entire argument, and that's fine ... they can build on or change the methodology to be more appropriate for their needs.

Statisticians, however, are not the audience I am speaking to.  I am speaking to you, the Marketing Executive / Analytics Expert.  And I just showed you a method that can easily demonstrate the return on investment of "Engagement" ... a method that is more scientific and more accurate than what you're taught out on Twitter.

Now go take this methodology, and do something with it!! Stop talking about how hard it is to measure the value of Engagement ... it isn't hard, I just showed you, for free, how to do it!!  No more excuses ... just go do it!!!!

If you'd like for me to do this for you, hire me (click here), and I'll tell you what engagement means to your business.

If you think this was valuable, would you at least tweet is or share it on Facebook or on Linkedin, as a way of demonstrating that Engagement can be linked to ROI?

Thanks,
Kevin

But I'm Only Losing $0.03 Per Catalog Mailed!

There are days when you realize that we're failing at math.

Here's the argument, as presented to me.

1. Company has 1,000,000 lapsed buyers (last purchase 13+ months ago).
2. On average, 1% of these customers respond to a catalog, if mailed, after matchback.
3. On average, if the company mails these customers, the company loses $0.03 on every catalog mailed.
4. Company only mails these customers ten times out of twenty annual mailings (whew).
5. We're only losing $0.03 per catalog mailed, that's not so bad, and they are our existing customers, so why not boost our customer file???!!!
6. The long-term value of a reactivated buyer is $20.00 profit, so we only lose $0.03 to gain $20.00 profit.

Here's the argument, as presented by me:

1. You are mailing 1,000,000 * 10 = 10,000,000 catalogs.
2. Only 1% respond, after matchback (and we've debunked that one a million times on this blog, right), meaning that 10,000 customers purchase.
3. You actually lose $0.03 * 1,000,000 * 10 = $300,000 profit, per year.  $300,000 profit.
4. You actually lose $300,000 / 10,000 = $30.00 profit per reactivated buyer.
5. You actually lose $20.00 long-term gain - $30.00 reactivation profit = $10.00 per reactivated buyer.
6. Strategy = DON'T DO THIS!!

Pennies are seductive.  It's so easy to make the decision to lose a few pennies, who's going to notice?

Well, pennies are the difference between being a highly profitable company, and being just plain average, or below average.

Yes, pennies.

What would Kevin do (WWKD)?

1. Realize that half of the customers you are mailing would have reactivated anyway, due to your organic percentage being around 50%.
2. This means that you are actually reactivating half of the customers you think you are reactivating, meaning that you are actually losing $60.00 profit to reactivate a name, a rate of profit you'll never make up with $20.00 of future profit.
3. I would pocket half of the profit now, and re-invest half of the profit in new customer acquisition, growing your customer file more profitably in the process.  I mean, be honest, you're not losing $60.00 of profit acquiring new names from Abacus, right?  So spend a bit more with Abacus, be willing to lose $12.00 to acquire a customer that generates $20.00 of future profit, and you come out way ahead.

The difference between industry-leading profit and average profit is pennies ... pennies per catalog mailed.  When you say you're willing to lose a few pennies here and there, you're deciding to be average.

Profit Models

I get to see a lot of different business models.  Each model has a clear path to profitability.

There are businesses that have high return rates.  These businesses require high levels of customer productivity, in order to generate profit.

Demand		$5,000,000
Net Sales	75.0%	$3,750,000
Gross Margin	55.0%	$2,062,500
Less Marketing Cost		$750,000
Less Pick/Pack/Ship	10.0%	$375,000
Variable Operating Profit		$937,500

Many businesses do not have a returns problem, meaning that customers keep what they purchase.  When that happens, customer productivity doesn't need to be as great in order to generate profit ... in our case, productivity is twenty percent less, and yet, profit is the same.

Demand		$3,905,000
Net Sales	96.0%	$3,748,800
Gross Margin	55.0%	$2,061,840
Less Marketing Cost		$749,760
Less Pick/Pack/Ship	10.0%	$374,880
Variable Operating Profit		$937,200

I work with a lot of businesses that are struggling.  You can tell that the business had to manufacture profit via efficiency ... it becomes obvious when looking at the metrics.  Take a look at this one:

Demand		$2,540,000
Net Sales	90.0%	$2,286,000
Gross Margin	65.0%	$1,485,900
Less Marketing Cost		$457,200
Less Pick/Pack/Ship	4.0%	$91,440
Variable Operating Profit		$937,260

Productivity is really, really low in this case.  However, the business managed to optimize gross margin dollars, and are running an efficient distribution center.  As a result, the business generates a healthy amount of profit on low productivity.


The internet world loves business models that "scale" ... meaning that you generate profit on low margins and high volume.  Here's an example:

Demand		$14,525,000
Net Sales	90.0%	$13,072,500
Gross Margin	15.0%	$1,960,875
Less Marketing Cost		$500,000
Less Pick/Pack/Ship	4.0%	$522,900
Variable Operating Profit		$937,975

This is a very different business model, isn't it?  You need a high level of demand, a high level of marketing productivity, and an efficient expense structure.  Combined, you end up with the same level of profitability that you obtained via the other business models.


The pundits will tell you what kind of business model you have to employ ... hint ... they really like one that "scales", one with low margins and high volume.


The reality is that there are many ways to generate profit.  Chart your own course.

Promotional Analysis: Profit Calculation

It may well be that discounts and promotions are what are needed to stimulate business.  Unfortunately, the tools needed to analyze whether a promotion is profitable or not aren't always available to the Google Analytics Generation.  The savvy Web Analyst needs to go a step further, in order to determine if a promotion is likely to generate profit.

In our example, we're going to pretend the following:

• Our promotion is "Take 20% Off Of Your Order, Today Only".
• Average order value = $100.
• 35% of demand converts to profit.

Step 1 = Execute A Test:  Ok, I realize almost none of you are going to do this.  But if you had done this, you'd know exactly how much business would have have happened "organically", without the need of a promotion.

Step 2 = Talk To Finance:  Since you didn't execute a test, you'll need to guess how much demand would have happened.  Somebody in the Finance department has a forecast for total demand on the day of your promotion.  Let's pretend that amount is $100,000.

Step 3 = Measure Sales on Promotion Day:  Let's pretend that demand was $140,000 on the day of the promotion.

Step 4 = Calculate Incremental Profit:  Here, we measure the difference in profit between $140,000 at 20% off vs. $100,000 at full price.

• The $140,000 demand yields $140,000 * 0.35 = $49,000 profit.  However, we gave up 20% of the $140,000 revenue, or $28,000, yielding $21,000 profit.
• $100,000 demand yields $100,000 * 0.35 = $35,000 profit.

Now, honestly, the CFO folks are going to jump all over me, telling me that there are hundreds of subtleties involved in calculating profit.  Go ahead, jump all over me.  This is an example, folks, the idea here is to stimulate thought among the Google Analytics Generation.  Savvy Web Analysts will work with their CFO to do this analysis and calculate profit.

Another thing to note here.  In many cases, companies offer a promotion, and the customer chooses not to use it ... the customer fails to enter the promo code, for instance.  So the Savvy Web Analyst will apply a "utilization rate" here, saying that 88%, for instance, of customers utilized the promotion.


Step 5 = Calculate Incremental New Customers, And Incremental Existing Buyers:  This is important.  Let's pretend that our average order value was $100 in each case.  This means we had 1,400 customers purchase via discount, and we had $1,000 customers who would have purchased at full price.  Carefully measure how many customers are new vs. existing.

• Discount Example:  400 new customers, 1,000 existing customers.
• Full-Price Example:  100 new customers, 900 existing customers.

Step 6 = Know 12-Month Profit By Customer Type:  People have been arguing for lifetime value analyses for decades.  For the Google Analytics Generation, it's hard to use software to calculate lifetime value.  The savvy Web Analytics analyst exports data out of existing Web Analytics platforms and analyzes long-term value.  I like to use 12-month profit.  You use whatever you want to use.

• Discount Newbies = $10 of 12-month profit.
• Discount Existing Buyers = $15 of incremental, additional 12-month profit.  This is the profit you get by converting, say, a three-time buyer into a four-time buyer.
• Full-Price Newbies = $15 of 12-month profit.
• Full-Price Existing Buyers = $17 of incremental, additional 12-month profit.  This is the profit you get by converting, say, a three-time buyer into a four-time buyer.

Step 7 = Calculate Expected Long-Term Profit:

• Discount Newbies = 400 * $10 = $4,000.
• Discount Existing Buyers = 1,000 * $15 = $15,000.
• Full-Price Newbies = 100 * $15 = $1,500.
• Full-Price Existing Buyers = 900 * $17 = $15,300.
• Discount Long-Term Profit = $19,000.
• Full-Price Long-Term Profit = $16,800.

Step 8 = Calculate Short-Term + Long-Term Profit:

• Discount Strategy = $21,000 short-term + $19,000 long-term = $40,000.
• Full-Price Strategy = $35,000 short-term + $16,800 long-term = $51,800.

In this case, the discount/promotion strategy yielded less short-term profit, more long-term profit, but not enough total profit.


Again, there are countless experts out there who will take exception with the methodology outlined here.  That's ok, those experts should publish their take on this, letting everybody see how they would approach the topic.  I'm trying to create a framework here for the Google Analytics Generation to see how one might measure whether discounts and promotions yield profitable outcomes.  In this case, there's no denying that the promotion yielded a significant sales increase, but does not appear to generate enough profit, short-term or long-term, to pay for the promotion.

CEO Questions About Online Marketing And Profitability

There are two hot CEO topics in 2009, based on my e-mail inbox:

1. Help me reduce advertising expense without a drop in sales.
2. Help me calculate the true profitability of my online marketing efforts.

Online marketing experts ... your fifteen year run of management by conversion rate is coming to an end. And that's a good thing!

The discussions are different than they used to be. Lately, the online marketing employee is being considered a scarce resource. Allocation of scarce resources is becoming a trendy topic ... and it should be, given the scarcity of employees after layoffs.

One individual asked it if was ok to add the human costs associated with managing a blog and maintaining a presence on Twitter to the variable costs associated with the website traffic generated by those activities, and then link those costs to the variable costs associated with picking, packing, and shipping merchandise generated by those activities.

Another individual wanted to know if she could calculate the incremental variable cost of each website visit, and then allocate that expense against visitors that browse the website on a frequent basis, calculating the true profitability of "best" customers.

A CEO wanted to allocate the cost of all website visits driven by an e-mail marketing campaign back to the e-mail campaign that caused the visits to happen --- holding e-mail marketing accountable for the 19 of 20 visits that did not result in a conversion but did chew up website expense.

So the scarcity of employees is causing a renewal of focus on activities that generate profit over buzz.

Ten years ago, the catalog industry went through a transformation. All expenses were carefully monitored, and all revenues were carefully tied to the catalog marketing effort that may have been responsible for generating the sales. This was the genesis of the matchback algorithm. The popping of the internet bubble resulted in a new era of accountability.

Today, the online / e-commerce industry is about to go through a similar transformation. The popping of the housing bubble is leading us to a new era of accountability.

Profit

Here's a quiz question to offer to your staff on this first Monday of December:

"You spend $1,000 on a paid search campaign. 3,000 users click through to your site, with 1% converting to a purchase. Customers spend a total of $3,000. 30% of the sales flow-through to profit. Was the paid search campaign profitable?"

Profit is missing from the language of marketing.

I reviewed the language of the twenty-five most popular marketing bloggers. During the life of the blogs on the list, the average marketing leader mentioned the word "profitable" in a median of just six blog posts ever, "profit" in a median of just thirty blog posts ever (and that includes the phrase "non-profit", and includes press releases about corporate profit). In fact, fifteen of the twenty-five bloggers used the phrase "profitable" three or fewer times ever --- and that's across an average of 250 to 1,000 posts.

These are your favorite marketing experts. The majority seldom if ever talk about profit.

Profit becomes part of the DNA of a business. It has been my experience that profit knowledge is kept in small tribes.

• Business Intelligence. BI employees are great at creating and querying cubes. Too often, the components of profit are not contained in the cubes.
• SAS Programmers. A completely different family of employees than BI experts. These crafty workers revel in writing neat code more than they focus on measuring profit. Of all employees, this is the one place where everything could be brought together.
  
• Web Analytics. This KPI-enamored throng of earnest employees use software that can, but frequently doesn't integrate profit components. So we've created an entire generation of good analysts who do not have profit as part of their DNA.
• E-Mail Analytics. Our e-mail community thinks about return on investment, and that is good! Because e-mail is almost free on a variable cost basis, there hasn't ever been a need to teach profitability. E-mail is always profitable.
• Catalog Circulation. These folks measure profit down to the penny, and for good reason. When you spend $0.75 sending out catalogs, your finance team requires that you become excellent at calculating profit.
• Paid Search. Another group that is really good at measuring profit, and for good reason. When you spend $0.75 per click, your finance team requires that you become excellent at calculating profit.
• Portal Advertising. This group can measure profit, but requires really good systems in order to build this discipline.
• Affiliate Marketing. Since you pay a commission, this style of marketing is generally profitable, and as a result, profit isn't always measured.
• Social Media. By and large, these folks do want to measure influence.
  
• Brand Marketing. By and large, these folks do want to measure influence.

More than anything, a profit culture requires a leader, somebody who wants to understand how everything fits together. The problem isn't solved by combining silos, it is solved by a passionate leader. The emergence of e-commerce and then social media have only served to further fragment the ability of a company to create a profit culture.

So why couldn't you be the profit expert? Sit down with your finance team, learn each piece of the profit and loss statement, and start measuring profit!

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!

Unified Multichannel Metric

A pet project over the next few months is the development of a Unified Multichannel Metric.

Why?

If you executed a multichannel marketing campaign, how would you know if it worked or not?

• If customers responded to the campaign at significantly increased rates, but the number of multichannel customers did not increase, was the campaign successful?

• If the series of campaigns, across channels, generated a loss, but increased the number of multichannel customers, was the campaign successful?

• If a retailer went from having 100 stores to 200 stores, thereby doubling the number of multichannel customers, was the brand successful at generating multichannel customers?

• If a cataloger reduced circulation by fifty percent, dramatically increasing profit, but reducing the number of multichannel customers, was the marketing plan a success?

• If a online pureplay used multiple online advertising vehicles, lowering response and profitability across all campaigns, but increased the number of customers buying, was the multichannel advertising campaign successful?

It's probably time for a Unified Multichannel Metric.

Profit Week: Three Customer Segments

This week, the topic is profit.

Enough talk about the economy being lousy (ask the folks at Urban Outfitters if they think the economy is lousy! Heck, check out the Urban Outfitters blog if you want to see innovation from a retailer).

Enough talk about postage increases. It happened a year ago, it was damaging. Time to move on.

Enough talk about third parties and their contempt for various forms of direct marketing.

The only way to stay in business is to generate profit. Lots of profit.

Direct Marketers are transitioning to a new reality, one that views the customer in three different, unique ways:

1. Customers who do not purchase unless they are advertised to.
2. Customers who are advertised to, then research product, then purchase product.
3. Customers who are self-sufficient, purchasing without the need for advertising.

Guess which customer segment is most profitable?

Guess which segment of customers we focus our efforts on?

We do everything in our power to identify customers who require advertising, then invest all of our energy in deciding how to advertise as efficiently as possible to this audience.

We spend almost no energy thinking how to move customers along the direct marketing customer continuum. We need to figure out how to facilitate the process whereby customers simply love us, trust us, and support us.

Here is a typical profit and loss statement for a segment that is dependent upon advertising.

Demand		$100,000
Net Sales	80.0%	$80,000
Gross Margin	55.0%	$44,000
Less Adv. Expense		$16,000
Less Pick/Pack/Ship	11.5%	$9,200
Variable Op. Profit		$18,800
% of Net Sales		23.5%

Now let's take a look at the same segment of customers, a segment not dependent upon advertising.

Demand		$100,000
Net Sales	80.0%	$80,000
Gross Margin	55.0%	$44,000
Less Adv. Expense		$0
Less Pick/Pack/Ship	11.5%	$9,200
Variable Op. Profit		$34,800
% of Net Sales		43.5%

Now the critic will use the traditional phrase "yabut" to express the fact that historically, a direct marketer had to market to the customer to get the customer to purchase something.

The world is different today. Your e-commerce site is more like a retail store than a traditional direct marketing piece. Think of your own behavior. You don't need a lot of direct marketing to shop at Home Depot. You need something to kill weeds in your lawn, you go to the Home Depot. Websites serve a similar function. You need shoes, you go to Zappos.com. Sure, Zappos uses online advertising. But they get a ton of volume from word of mouth, a ton of volume just because "they are Zappos".

In the chart at the top of this post, Zappos has a customer base that is split between the middle box, and the box at the far right.

Most catalogers cultivate a customer base that requires advertising in order to purchase something. Catalogers spent the past decade proving (via matchbacks) that customers needed advertising. Via this self-fulfilling prophesy, catalogers are now at a significant disadvantage, because all of the costs associated with advertising are increasing. Simultaneously, customers are moving from the left to the right side of the direct marketing customer continuum slide.

In the short term, direct marketers need to cope with recessionary issues and expense inflation.

In the long term, direct marketers must migrate their customer base from an "advertising-needs" customer to a "self-serving customer", one that doesn't require advertising. This is where a boatload of profit exists --- profit that can be pocketed, or reinvested in free next-day shipping or other customer-friendly strategies.

For those of you about to say "yabut", this can be done. Pay attention to Zappos, Blue Nile, Amazon. Use Multichannel Forensics to see if your current customer is willing to make this transition with you.

E-Mail And Catalog Profit Visualization

"Back in the day" at Lands' End, we had a team that measured the profitability of every spread in our core catalogs.

Even though this information was stored in a database for easy retrieval, the most effective presentation of the profitability of each spread (in my opinion, or IMHO to use the parlance of the day) occurred in a conference room.

Each spread was adhered to colored tag board.

• Gold Tag Board = 30% or better variable operating profit for that spread.
• Green Tag Board = 20% to 29.9% VOP for that spread.
• Blue Tag Board = 10% to 19.9% VOP for that spread.
• Red Tag Board = Worse than 10% VOP for that spread.

When we sat down to review a catalog, each spread was posted in the conference room, in order, from page 2-3 to the back cover.

Instantly, the "profit story" became clear. Visually, a rookie database marketer like myself could see what worked, what didn't work. Visually, I could see how merchandising and creative themes interacted to generate profit. I could see how one model yielded gold/green results, while another model turned customers off.

If you are an e-mail marketer, and you wish to effectively communicate with old-school marketers at your company, give this strategy a try.

Maybe you sent 20 e-mail marketing campaigns last quarter. For each campaign, sum the performance of all of your targeted versions, and adhere the main creative treatment to a piece of colored tag board. Do this for each of the twenty campaigns, and post the performance for all to see.

Each targeted version gets real estate on the tag board as well, with its own background color (gold, green, blue, red, or whatever scheme you wish to employ). Most certainly, you're measuring the profitability of each targeted version of an e-mail campaign, rolling the profit of each version up to a total level of profitability, right?

Invite your old-school CMO into the conference room, and review your twenty campaigns in this manner. Stop talking about open rates, click-through rates, conversion rates, landing pages, Outlook 2007, HTML vs. Text, rendering problems on mobile phones, and all the other gobbelty-gook that causes your old-school CMO to tune out. Simply focus on the colors. Explain how you're going to do more "gold and green" strategies. Explain why the CMO's recommendations resulted in "blue and red" performance.

And then, behind the scenes, build an OLAP-styled repository to store your historical results. Store open rates, click-through rates, conversion rates, dollars-per-e-mail, sales driven to the telephone, sales driven to stores, test results, profitability, and "gold/green/blue/red" status.

By the time your CMO is comfortable with your presentation style, you might even be able to surprise her with your OLAP-styled repository. Ok, maybe not!

And if you practice web analytics for a profession, would it be so hard to apply these principals to your landing pages, so that you can bridge the gap between all of your fancy data and the old-school marketers who don't understand what you're talking about? Give it a try!

Profitability

Profit is the reason we are allowed to remain gainfully employed. Conversion rate doesn't keep us employed. Profit keeps us employed.

How often do we hear e-mail marketers talk about, or ever demonstrate the profitability of their activities? I'm not talking about "ROI", nor an 8% improvement in open rate. How often do these industry experts talk about "profit"? Same for search marketers, or other online marketers.

In some ways, a generation of marketers are being trained to look at the business in unique and different ways. That's good. However, this generation isn't always focused on the metric that matters most.

"Back in the day", Lands' End measured the profitability of every spread in a catalog. Every major catalog was analyzed by a team of merchandising, creative, inventory and circulation staffers.

If I remember correctly, each spread in the catalog was grouped into one of four categories.

• Spreads that generated 30% or better variable profit (profit before fixed costs) were coded "GOLD".
• Spreads that generated 20% to 30% variable profit were coded "GREEN".
• Spreads that generated 10% to 20% variable profit were coded "BLUE".
• Spreads that generated less than 10% variable profit were coded "RED".

Each spread was hung on the wall of a conference room, in sequential order, hung on tag-board of different colors ... the color representing the profit category the spread fell into. At the bottom of the spread, the profitability of each item in the spread was itemized --- demand, fulfillment rate, return rate, net sales, gross margin, marketing cost, and pick/pack/ship expense.

Visually, a story was told in that conference room. One could visually understand why a catalog worked, or why it didn't work. We'd have a discussion about how to present merchandise, how to merchandise the front of the catalog (an important factor that more folks could pay attention to).

Fast forward to today. How many online marketers can give you, the direct-to-consumer executive, a set of metrics that clearly and easily tell you the profitability of items online. Do you have any reporting that tells you the profitability of a landing page? How about the home page?

Every employee should intuitively understand the connection between selling merchandise, marketing merchandise, and generating profit.

Seriously ... take a spin through the e-mail marketing and search marketing literature/blogosphere/vendor-speak. Count how many times you see the word "profit" mentioned.

Let's help these bright marketers make the connection between their efforts, and the profitability of the businesses we manage. We're failing these individuals, we're not training them to be the accountable leaders we need them to be. We need to protect the future of our industry.

Return On Investment (ROI) In Direct Marketing

Click on the image to enlarge it.

We hear a lot of talk about ROI, or "Return On Investment", when evaluating direct marketing programs.

Catalogers know that paper drives more total sales, and more total profit, than any other form of direct marketing.

E-Mail marketers know that e-mail drives the best "ROI", measured as "total profit divided by total cost". E-Mail marketing has almost no cost associated with it, making it a tool marketers must use, and use properly.

Paid Search marketers know that they reach customers at a "time of need", thereby providing the most "efficient" form of advertising known to-date. No other form of advertising cuts out the waste of uninterested shoppers like paid search ... except I guess for natural search, which has no cost associated with it.

Portal marketers know that they make the brand known to customers who have not purchased previously. They know their investment is best measured on a "lifetime value" basis ... short-term metrics are not appropriate for portal advertising.

In the table attached to the top of this article, each form of advertising has various strengths and weaknesses. Your job is to evaluate your advertising objectives.

Objective: Drive large volume of sales/profit from existing customers.
Solution = Catalogs.

Objective: Precisely target merchandise to existing customers.
Solution = E-Mail, Paid Search.

Objective: Precisely target merchandise to customers in-need.
Solution = Paid Search.

Objective: Make your brand aware to potential customers.
Solution = Portal Advertising.

Objective: Acquire new customers.
Solution = Catalog, Portal Advertising, Paid Search

I didn't even talk about affiliate marketing or shopping comparison marketing, which also fit into this story.

Obviously, there are many different objectives and solutions, my list above is abbreviated and short. Strategically, consider what you want to accomplish, and allocate your advertising mix on the basis of total sales, total profit, and your objectives.

Don't be swayed by folks who tell you that one form of advertising is "better" than another. Each type of advertising has a purpose. Each type of advertising excels within one specific set of metrics.

Catalog Profitability

Click on the image to enlarge it.

One of the challenges catalogers have to manage is determining the right circulation depth, and the right page count in a catalog.

Circulation depth is pretty easy to determine, once the number of pages are assigned. A straight forward calculation of sales and profit determine the right number of households to circulate to.

Page count presents more challenges. Merchants like to add pages, offering the customer more merchandise to purchase. Creative folks occasionally want to reduce density, adding pages that are less dense, easier to read.

More pages = more cost.

Are more pages better?

In the example at the top of this page, last year's catalog had 80 pages, and was mailed to 1.5 million households. The catalog drove $7,000,000 demand through the telephone and online channels.

When planning this year's catalog, the analyst builds a relationship between pages and demand. As pages increase, demand increases, but at an ever decreasing rate. Therefore, demand is maximized by sending as many pages as possible to as many households as possible.

Using a straight forward profit calculation, notice where profit is maximized. Based on last year's results, profit is maximized by sending a smaller catalog to as many households as is possible.

Here's a fundamental truth in catalog marketing:

• Increased Circulation Depth > Increased Pages

In other words, given the choice between adding pages to a catalog, or mailing a smaller catalog to as many households as possible, try to mail a smaller catalog to as many households as possible.

You can clearly see this when evaluating circulation plans. Businesses that like to mail catalogs with many pages tend to have shallow circulation, tend to be unable to do a lot of prospecting.

Businesses that are parsimonious with pages tend to circulate to many households, have robust prospecting programs, and a healthier housefile.

How Much Investment Is Too Much Investment?

Click on the image to enlarge it.

There are a series of fundamental truths about direct marketing that, while generally understood, are not actively practiced.

We all know that if you don't market to a customer, generating significant sales and profit become unlikely.

We also know that if you market too much to a customer, customers rebel, or the marketing is highly unprofitable.

The best direct marketers measure marketing effectiveness over time. In other words, the best direct marketers segment customers at the start of the year (calendar or fiscal). Next, customers are placed into different test groups. Some customers receive almost no direct marketing. Some customers receive too much direct marketing. At the end of the year, the direct marketer measures the repurchase rate, spend per repurchaser, average spend, and average profit, based on the contact strategy test the customer participated in.

Click on the attached image. This is what test results typically look like. In this case, customers received anywhere between six and sixty-six catalogs during a twelve month period of time.

At just six catalogs (one every other month), the customer segment had an average response rate of ten percent. The annual repurchase rate was 46.9%. The average customer generated $15.00 of profit.

At twelve catalogs (one per month), the customer segment had an average response rate of 7.1%. This is a very common situation --- by adding catalogs, we artificially cause each catalog to perform slightly worse. However, the annual repurchase rate increases from 46.9% to 58.5%. Better yet, annual profit increases from $15.00 per customer to $17.70 per customer.

Clearly, it is better to mail twelve catalogs than it is to mail six catalogs.

The table shows that profit is "maximized" at eighteen catalogs.

Now take a look at the scenario where twenty-four catalogs are mailed. Response rates continue to deteriorate. Annual repurchase rates continue to increase. Annual profit begins to decrease.

It is at this point that things become very interesting in your average catalog-based business. As you go from twenty-four to thirty catalogs (in this example), profit begins to erode, faster and faster as catalogs are added to the contact strategy.

There is an unusual dynamic that occurs in catalog companies that reach this stage. The CFO quickly points out that the "ad-to-sales" ratio is increasing at an unacceptable rate. The CFO might even want to cut back on catalog mailings.

Your merchants might view things differently. Merchants are charged with increasing sales --- one of the ways to do this is to increase pages, or increase the number of mailings. A merchant might recommend a new catalog title, focusing on a slightly different assortment of merchandise, targeted to a slightly different customer. The merchant might recommend six additional mailings, asking for a two year trial to see if sales can be grown, to see if a new target audience can be harvested.

Often, two or three merchants recommend this strategy. Suddenly, there are thirty-six or forty-two mailings in the catalog plan.

The merchants are under pressure to "grow sales". The way to do this is not to spend a ton of time prospecting for new customers. The way to do this is to mail "best customers".

This strategy artificially lowers catalog response rates, increases annual repurchase rates, and lowers profit per customer.

Eventually, something gives. If the business fails to meet plans by maybe ten or fifteen percent, the CFO gets enough power to enact change.

If the CFO isn't as strong a leader as the merchants are, circulation changes come in the form of cuts in circulation depth --- instead of mailing 1,000,000 customers per mail date, circulation depth drops to 850,000 customers per mail date. This is a short-term fix ... profit is slightly improved. The long-term problem of having too many catalog in the mail plan causes us to invest too much in our "best customers".

If the CFO is a strong leader, an excellent communicator, then real change can happen. Various catalog titles are dropped, various in-home dates are dropped.

Things get interesting when going down this path. Taking this approach cases the annual repurchase rate to decrease. This dynamic causes a reduction in the strength of the "housefile". With fewer active buyers, next year's sales potential is reduced. This will cause various leaders to want to advertise more next year, or the year after, in order to grow the housefile back to a level of perceived strength.

Of course, the way to balance this dilemma is to manage customer acquisition and customer reactivation activities in a manner that fuels total file growth.

But at an executive level, the concepts of customer retention, customer reactivation, and customer acquisition are too "geeky" to pay attention to. It is easier to think about adding catalogs, developing new products, presenting products differently, or to find new "target" audiences.

In almost every company I've visited or worked for, investment in direct marketing is overly focused on "best customers". Catalog mailings, e-mail mailings, loyalty programs, postcards, you name it --- everybody marketer wants to be successful. The best chance for success is with "best customers", right? Or is it?

Three Ways To Increase E-Mail Sales

Businesses with customers who purchase fewer than three times a year seldom benefit from trigger-based e-mail marketing campaigns (with the notable exception of shopping cart prompts, which often work well).

There are at least three key factors that can be managed, to grow e-mail sales.

Factor #1 = Incremental List Size, Managed By Contact Frequency

Factor #2 = Incremental Demand Per Contact, Managed By Contact Frequency

Factor #3 = Demand Per E-Mail, Managed By Number Of Targeted Versions


Incremental list size is ultimately determined by the number of e-mail campaigns sent per week. When a customer is contacted too often, too many customers unsubscribe, driving down the total size of the e-mail list. Strategically, management may choose to execute "x" campaigns per week. Mathematically, the number of e-mail contacts per week can be determined by the number that still cause a healthy increase in the number of valid names available to be e-mailed. In the table below, you'll see that two e-mails per week are optimal, as the e-mail list continues to grow.

Incremental demand per contact is also important. As you increase e-mail frequency, you will decrease the performance of any one e-mail contact. Increased frequency will probably cause cannibalization between e-mail campaigns. The table below shows that the combination of unsubs and performance dictate two e-mail campaigns per week.

Targeted versions of an e-mail are important as well. Few retailers have the ability to dynamically create unique e-mail campaigns for each customer. As a result, management creates "x" versions of an e-mail campaign, offering different merchandise in each version. The analytics team decide which version of an e-mail campaign the customer receives, on the basis of past purchase behavior, stated customer preferences, clickstream history, and other factors. From a staffing standpoint, it could be a challenge to produce numerous versions.

In the table below, I assume that a company managed one version of an e-mail, one time per week, to the entire e-mail file. This strategy yielded $20,700 of demand per week.

Going from one campaign a week to two campaigns per week kept the file size increasing, reduced volume per e-mail, but resulted in $30,030 of demand per week. Clearly, this is a better strategy than sending just one e-mail campaign per week.

Going from one version per campaign to nine versions per campaign drove $40,040 of demand per week. Assuming this strategy can be managed with existing staff at minimal cost, this strategy could work.

Notice that the combination of list size (dictated by frequency), demand per contact (dictated by frequency), and version contribution cause a doubling in e-mail volume, on a weekly basis.

Catalogers have long mastered this type of analysis, assigning profitability to each strategy. With e-mail, profitability is not as big an issue, so if one can avoid the fixed costs associated with incremental staffing, a move to moderate frequency with increased versions can yield a significant increase in e-mail sales.

Obviously, there are many ways to increase e-mail volume. These three basic strategies almost guarantee a positive return on investment.

No Targeting Strategy
Contacts	List	New	Unsubs	Net	$ per	Weekly	Total
per Week	Size	Subs	& Invalids	Names	E-Mail	Demand	Demand
1	100000	1000	650	100350	$0.20	$0.20	$20,070
2	100000	1000	900	100100	$0.15	$0.30	$30,030
3	100000	1000	1150	99850	$0.12	$0.36	$35,946
With Targeting Strategy: 2 Contacts Per Week
Targeted	List	New	Unsubs	Net	$ per	Weekly	Total
Versions	Size	Subs	& Invalids	Names	E-Mail	Demand	Demand
1	100000	1000	900	100100	$0.15	$0.30	$30,030
5	100000	1000	900	100100	$0.18	$0.36	$36,036
9	100000	1000	900	100100	$0.20	$0.40	$40,040