What Was The Optimal Spend Level, Anyway?

Here's our base case.

When I increased marketing spend by 25% among my 0-12 month "A" customers, I generated less profit - in fact, the ratio between demand and profit wasn't good, was it?

I ran different scenarios. After 10 years, here's what profit looked like by scenario.

• 0% Marketing Spend = $14.3 million profit.
• 10% Marketing Spend = $15.6 million profit.
• 20% Marketing Spend = $16.0 million profit.
• 30% Marketing Spend = $16.2 million profit.
• 40% Marketing Spend = $16.4 million profit.
• 50% Marketing Spend = $16.4 million profit.
• 60% Marketing Spend = $16.5 million profit.
• 70% Marketing Spend = $16.5 million profit.
• 80% Marketing Spend = $16.4 million profit.
• 90% Marketing Spend = $16.4 million profit.
• 100% Marketing Spend (current situation) = $16.3 million profit.
• 125% Marketing Spend = $16.0 million profit.
• 150% Marketing Spend = $15.6 million profit.
• 175% Marketing Spend = $15.2 million profit.
• 200% Marketing Spend (double) = $14.6 million profit.

Profit is maximized when marketing spend among 0-12 month "A" customers is at 70% of current levels ... in other words, if we cut back on marketing spend by 30%, we generate optimal levels of profit.

I know, I know, you want sales to grow. And when I doubled marketing spend, in ten years, demand is $121.8 million instead of $112.2 million. And worse, I know that many of you would happily give up $1.7 million in profit to grow demand by $8.4 million ... you'd be happy with that, so long as it doesn't come out of your pocket.

But if the profit comes out of your pocket, well, you'd want to know this fact, wouldn't you?

Tomorrow, I will let you download the spreadsheet, and I will give you a homework assignment for the weekend.

Spend Some Money On Those Loyal Buyers!! Or Not?

Here's our example:

In our 0-12 month "A" buyer segment ... the best 20% of the twelve-month buyer file, we are spending $40 marketing dollars per year ... between catalogs and email and affiliates and paid search and social and whatever else, we're pumping a lot of marketing dollars into this segment.

Also notice the next column. This is the "organic percentage". It's the percentage of demand the segment will spend if marketing is altogether discontinued. Needless to say, this is the most important metric in the whole darn simulation.

A show of hands ... how many of you know your organic percentage by segment, or overall? The smartest companies know it at an overall level. Genius-level companies know it by segment. Where do you stand?

Among our "A" customers, this company knows that 75% of the demand is organic ... it's going to happen because customers love the brand. The remaining 25% is caused by marketing activities. Therefore, if we want to see what happens if we bump up marketing spend, we have to measure the impact only on the 25% of demand that is impacted by marketing, right? Right??!!

So let's try something. Let's increase marketing spend by 25% within just this segment, for each of the next ten years. How does demand and profit/loss change, as a consequence?

For the next five years, here's the baseline demand/profit scenario for the company.

• Year 0 = $88.3 million demand, $15.1 million profit.
• Year 1 = $92.3 / $15.4.
• Year 2 = $95.7 / $15.7.
• Year 3 = $98.6 / $16.0.
• Year 4 = $101.1 / $16.1.
• Year 5 = $103.3 / $16.2.

Now, I change cell D6 in my spreadsheet (next week, I will provide a link to the spreadsheet so that you can play with it on your own), from 1.00 to 1.25, to simulate a 25% increase in marketing spend. Here's what I get.

For the next five years, here's the changed demand/profit scenario for the company.

• Year 0 = $88.3 million demand, $15.1 million profit.
• Year 1 = $93.2 / $15.0.
• Year 2 = $97.0 / $15.3.
• Year 3 = $100.2 / $15.6.
• Year 4 = $103.0 / $15.8.
• Year 5 = $105.3 / $15.9.

Demand grew, but we generated less profit.

#OhOh.

In Year 1, we generate $900,000 more demand, but we lose $400,000 profit. That's a bad equation, isn't it?

In Year 5, we are $1.9 million bigger, but are losing $300,000 profit compared to the base line problem.

For this company, for this segment, a 25% increase in marketing spend is not a good idea. Demand increases. Profit sinks.

What is the appropriate investment level for this segment?

We'll find out tomorrow!

This Business Is Cookin' Right Along, Isn't It?

Remember our business from yesterday? Click the image below to take a peek.

This is a business that generated $88.4 million in demand last year ... and is projected to generate $92.3 million next year, then $95.7 million, then $98.6 million, and then the business grows by one or two million a year thereafter. In other words, the forecast for this business isn't as optimistic in the long-term as it is in the short-term.

Variable Operating Profit, as a percentage of demand, isn't bad ... between 16% and 17% of demand in the short-term ... which will yield a reasonable EBITDA ... so the business is reasonably healthy.

Or is it? 

Tomorrow, we will begin to explore how the future trajectory of this business could change.

When I create my simulations, I try to keep the segmentation system simple. I create a statistical model that grades 0-12 month buyers (A / B / C / D / F) ... "A" customers are in the top 20% of the 0-12 month buyer file, "F" customers are in the bottom 20% of the 0-12 month buyer file. Then, I segment customers by 12-month recency chunks. Finally, I have new customers as an additional segment.

For each segment, I measure the following:

• Probability of Repurchase, Next Twelve Months.
• Spend per Repurchaser, Next Twelve Months.
• Probability of Repurchasers Migrating to A / B / C / D / F Segment Next Year.

This simple table of counts, probabilities, spend amounts, and migration patterns yields half of the magic above.

The other half of the magic comes from marketing spend. Customers are frozen as of a year ago, and then the marketing spend allocated against each of those segments is summed. I build laws of diminishing returns for housefile buyers and first-time buyers, allowing me to estimate how response increases as ad spend increases. I use the "square root rule" for housefile buyers ... meaning that for demand attributed to marketing activities, I estimate that a doubling of the marketing budget yields a 41% increase in response. Conversely, halving the marketing budget reduces response by about 30%. For customer acquisition, the diminishing returns relationship isn't as curved, it is flatter.

Tomorrow, we will begin to play with the relationships. This is where the simulation makes a huge difference. We get to see how the business evolves over a five or ten year period of time, given various investment strategies.

You Talk About Loyalty And Running Simulations - What Are These Simulations, Anyway?

When I talk about customer loyalty, and in particular the need to prioritize new customer acquisition over housefile optimization, I get the "blank stare" look.

You know what this look is like. It's the same look you get when you tell one of your staff members that you are cutting his/her pay by 6% due to a "corporate efficiency initiative".

Moments after the blank stare look, I get the "but conventional wisdom tells us that it is cheaper to retain a loyal customer than it is to find a new customer" comment, a comment that is 100% true and is completely inappropriate all at the same time.

Simply put, if you want to do the right thing for your business, you have to run the math.

Almost none of you run the math.

I visited a company that ran simple math - they calculated short-term return on investment for new customers, and they optimized housefile spend on a break-even basis. But they didn't know what the right "mix" was for their business, long-term. What was the right mix of spend across housefile segments and new customer acquisition, a mix of spent that yields the healthiest business in five years or ten years?

I am confident that you don't know the answer, either. Nobody bothered to teach you. And your vendor partners and/or industry consultants and/or Google don't want you to know that answer (if Google wanted you to know that answer, they'd have a simulation tool in Google Analytics that allowed you to answer the question - they're smart people, you know, they can invent self-driving cars, so they can build a simulation tool for you that tells you if you are spending too much).

So, I'm going to take some time and share with you a simulation tool that I use. Here's a peek:

The tool enables me to identify how much to invest in new customer acquisition. The tool enables me to determine just how much I need to spend on lapsed housefile buyers and best customers, in an effort to have a healthy business not only today, but in several years. The tool allows me to see the impact of merchandise productivity on the business.

In other words, the tool allows me to see things that your vendor partners are unable to see when they are telling you how much to spend.

Let's see where the tool takes us over the next week or two.

You Can See The Catalog University Presentation Free, For One Week

Click now if you must see it for free ... click here. Please support the folks at Catalog U who paid for extra bandwidth to make sure the overflow crowd could see the presentation live.

The session is worth watching. I move my hands a lot. That has to mean that the content is overwhelmingly important.

The Path To Loyalty Is Bumpy / Spiky / Curvy

This is what it looks like, folks. The first-time buyer repurchased about every six months, in this case.

The customer is responsive ... then becomes progressively less responsive ... then purchases ... then becomes progressively less responsive all over again (but at a higher rate) ... and so on and so on.

It's the six weeks after a purchase when the customer is most likely to purchase again. That's when our marketing programs should be operating in overdrive, don't you think?

But we don't do much in those six weeks, do we?

Instead, we focus on trying to "win-back" the customer who has not purchased in 42 months ... we overlay co-op data and social data and demographic data and we apply complex models that combine discounts and promotions that the customer has already had access to for forty-two months.

Our efforts are too-often focused on when the customer becomes inactive.

Why not focus on the customer when the customer is highly active?

Amazon and Loyalty and the Future of the Catalog Brand

During yesterday's Catalog University presentation, several attendees asked questions about Amazon.

This is interesting, of course, because the focus of the presentation was really about how we in the catalog industry separated ourselves from modern e-commerce through a myriad of tactics that made sense in 1999 and 2003, but in retrospect, were not smart tactics and ultimately trapped catalogers in a demographically challenged corner.

After sharing fifty slides of information, the audience referred back to this image above ... and began to ask questions about Amazon.

I don't want to say that folks were blaming Amazon for cataloger struggles, because that was not the case. But if you take the four or five Amazon-centric questions and roll them together, you get a picture that attendees had strong opinions about Amazon.

For instance, I mentioned that catalogers must, and I repeat must find ways to dramatically reduce catalog marketing expense, so that catalogers can be competitive and offer free shipping. At one point, I said something about Amazon, and was reminded that Amazon customers do not get free shipping - the customer pays for shipping up until a $35 hurdle - or the customer pays a hundred dollars a year or more for Amazon Prime.

Let's go with the latter ... you pay $100+ for Amazon Prime, or you get free shipping with your favorite catalog brand. Think about the magnitude of that statement. The customer would rather pay Amazon to have merchandise shipped than to get comparable merchandise from you via free shipping. That goes against nearly every economic principle that exists, don't you think?

To me, and this is simply an opinion that you may differ with, Amazon offers free shipping as part of a loyalty program. The loyalty program is Amazon Prime. And unlike all other loyalty programs that give away the farm, Amazon gets you to pre-pay for the right to buy from Amazon. It's exactly like a Personal Seat License that NFL teams use when they build new stadiums to rip off existing season ticket holders. You pay the team a fee, and that fee gives you the right to buy Season Tickets. Oh, sure, you can sell that Personal Seat License, but my goodness.

Here's the thing about "competing" against Amazon. If a customer is willing to pre-pay Amazon for the right to have merchandise shipped quickly instead of being offered free shipping by a cataloger, then the cataloger is not competing against Amazon. Amazon already won.

So why compete against Amazon? Stop it!

I know, I know, the stuff you sell can be purchase on Amazon, so you are "unique" and "different". Sure.

The time to "compete" against Amazon was in 2001, when catalog trade journals were mocking Amazon, counting the months until Amazon would run out of cash.

Today, the cataloger has to fight a different battle.

• If you sell the same merch that Amazon sells, consider selling it on Amazon (I know, I know, you don't want to be an Amazon vendor. Ok, good luck).
• Sell different stuff.
• Tell a story. Any story. Amazon does not tell a story. Amazon is like the Costco store in the movie "Idiocracy" (click here for the video) ... "Welcome to Costco, I love you ... Welcome to Costco, I love you ... Welcome to ..." If you must send paper, use paper to tell a compelling story.

Most important, going forward, catalogers are facing the three mega-trends.

1. Merchandise Productivity.
2. How will we find a new customer in 2020?
3. How will we avoid paying tolls?

When we look ahead to 2025, it is not difficult to see a catalog future that is dominated by the following:

• An average customer age of 72-75 years old.
• +/- 10 Private Equity or Holding Companies who each own one-hundred catalog brands, and by doing so, have access to every Baby Boomer and older Gen-X customer, thereby putting the co-op business model out of business while making sure that they have access to the names that still buy from catalogs.

Seriously. Use a little bit of imagination. That's where we are headed.

So historically, we may have competed against Amazon - up until maybe five years ago. That battle is over. Catalogers lost.

Going forward, catalogers are going to compete against each other. A Darwinistic battle is forming, one where a small number of businesses own a large number of catalogers, stripping HR and IT and Marketing and Creative and Merchandising fat out of the businesses in favor of centralized databases and merchandising synergies, using sister brands to find new customers - cutting the co-ops out of the process - eliminating tolls in the process. And by catering to a 70+ year old customer, catalogers avoid the tolls inherent in the online ecosystem. What comes five or six years after this is not pleasant to think about.

This is the battle of the future.

It's time to stop worrying about Amazon. That's a tactical process that cannot be won.

It's time to think about that moment when ten Private Equity / Holding Companies own a hundred catalogers each. What does that look like? What's the end game in that situation? What happens to your thirty-year career in that scenario?