Media + Shopping = A Customer Acquisition Strategy

Back to River Island. This is a video about a blogger and a model in London.

Then, they make the video shoppable - take a look:

And when you click on the clothing in the image, you are taken to a product page.

You are not doing a one-off here - the blog & YouTube & Facebook are used to promote the video ... the merchandise is shoppable ... and then you can buy the merchandise featured in the video.

I know, I know ... you sell widgets and you are never going to create your own videos, you are never going to outsource the idea either ... and if you did do that, you already know that the strategy would "not work".

Don't you have three or four employees who are talented enough to do something clever with video ... something at a low cost?

A Brand Response Marketer is going to do 25-30 of these things, knowing that 1-2 of them will work.

In so many ways, a modern e-commerce business is a media company. We just pick and choose the media we wish to leverage. A cataloger, for instance, acts as a traditional media company. River Island acts as a modern media company. But both, make no mistake, are media companies.

Siphoning Customers = A Customer Acquisition Strategy

Don't want to create your own mini-movie? I get it.

Look at what Nordstrom does to the River Island video we discussed yesterday? They pay to get an ad run right over the top of the video. You want to see River Island brilliance? You have to sit through an old-school Nordstrom ad.

Since you don't want to take a risk and do something with a low probability of success (but a high upside if success happens), why not consider doing what Nordstrom did? When somebody else does something brilliant, sit on their shoulders with an ad.

I know, I know, you don't like the idea of creating a mini-movie, and you don't like the idea of siphoning off customers. That's fine. But you're going to have to come up with something clever at some point, right? You have to try something, right?

Movies = A Customer Acquisition Strategy

River Island partners with a production company to create mini-movies that feature River Island merchandise being worn by the bloggers who "act" in the movie.

When you look at this production company, you frequently observe videos that have been watched more than a million times.

I know, I know. Nobody wants to watch a movie about widgets. You think this stuff only works for fashion brands. You tried creating a video with a flip phone in 2006 and only 98 people watched it.

This video appeared on the River Island blog, and on YouTube. And unlike your email campaign that has a life of eight hours, if done well, a video sits out there doing hard work for months or longer.

Ok, you're never going to follow this advice. Fine. Tomorrow, I will show you how a competing brand leveraged the work done by River Island.

Complementary Materials = A Customer Acquisition Strategy

How often do you buy a mattress?

So let's assume that your Sleep Number and Tempurpedic brands are equally comfortable and similarly priced. You run across Eve Mattress. Not as well known, right? How do you compete?

In this example Eve Mattress uses Facebook to promote an eBook about the "Grouchy Grouch".

What are the odds of delivering a return on investment doing this? Minimal.

Do you have to do something different to attract a customer if you are not Sleep Number and/or Tempurpedic? Absolutely!

The Brand Response Marketer is not afraid to try low-cost techniques, and is not afraid of failure. Maybe you spend $40,000 working with an illustrator. You might need to sell 25 or 30 mattresses to earn enough margin dollars to cover the cost of an illustrator. Seems like it is worth trying, don't you think?

Afraid of spending $40,000 with an illustrator? How about one of your creative employees? There's no incremental cost whatsoever ... and if you sell 5 mattresses because of your strategy, you generated profit, right?

The Brand Response Marketer is not afraid of trying things.

The Brand Response Marketer is not afraid of failure.

The Brand Response Marketer tries 20 different tactics, knowing that 3 will generate enough success to cover for the 17 that fail.

Inventory Position = A Customer Acquisition Strategy

Here's a newer slide from my customer acquisition presentation (click here).

Here, in this image from Olive via their Facebook presence, a customer complains that items are always sold out quickly. The employee responds ... suggesting that the customer visit often, because the merchandise assortment is frequently refreshed.

There is a difference in how classic brands view inventory management, and how newer digital/retail brands view inventory management. The classic brand doesn't want to disappoint a single customer. As a result, the classic brand doesn't create urgency through inventory ... maybe via 20% off or 30% off, but not through inventory.

The modern digital/retail brand creates urgency via marginal inventory positions. When the brand has a reputation for running lean, purchases tend to happen NOW. Customers/Prospects visit more often. Inventory turns are faster. Liquidations are minimized. Profit is generated.

The downside, of course, is that the lean digital/retail brand misses out on purchases, simply because not enough inventory is maintained.

Urgency via Inventory Position is a strategy to convert prospects fast. You may or may not agree with the strategy. But at least think about it, ok?

Advertising Lizard Logic

It's Friday - you have time to read two articles, right?

The first one is a confession from a media agency CEO (click here). The individual laments nearly two decades of digital advertising nonsense. There are all sorts of fun quotes in the article, quotes like "... the industry fudges the metrics to make it (display ads) work".

An astroturfed confession will not draw enough eyeballs to help a trade journal generate ad revenue. You need a counter point to stir up additional fun. The counterpoint is offered here (click here).

The author of this article suggests proficiency in math. And there's no doubt that the author calculated numbers properly, concluding that twenty-five million impressions will generate 350 orders. Let that one sink in for a moment. Twenty-five million impressions will generate 350 orders. The author goes on to divide $100,000 in ad cost by 350 orders, yielding a cost per order of $285.71.

It's at this point that the author suggests that the "vast majority" of brands sell at price points well above $285.71. The author demeans folks who don't understand math, drops the mic, and leaves the stage as the ad industry enthusiastically applauds the math.

One problem.

The author didn't take the math far enough.

Let's assume a couple of key points ... your mileage will vary.

• An average e-commerce brand has an average order value of $150 (it's typically lower than this).
• An average e-commerce brand flows 45% of demand through to profit (maybe a 55% gross margin and a 10% pick/pack/ship expense per order). If you are Best Buy, you flow through half this rate, +/-. A jewelry brand flows-through more.

Ok, we'll run a profit and loss statement.

• 350 orders generated from a whopping 25,000,000 impressions at a $150 average order value  = $52,500 demand.
• $52,500 demand at a 45% flow-through rate = $23,625 contribution.
• We had to spend $100,000 in marketing to generate $23,625 contribution. This is a net loss of $76,375.
• $76,375 loss / 350 orders = -$218 profit per order.

The author concedes that if the math doesn't work, do something else, so please give the author some credit.

But for 95% of my client base, the math/logic outlined by the author would get you fired. A better return on investment would be to burn fifty-thousand dollar bills in a hand-warming bonfire, followed by returning the other fifty-thousand dollars to the CFO to put in a standard savings account.

Since the barriers to publishing content have been obliterated, we have been pummeled by advertising lizard logic. Too few individuals understand how a profit and loss statement works. Simple knowledge of a profit and loss statement would stop the rebuttal process, right? So either we don't know how to calculate profit, or we lie on purpose to protect an industry. Either outcome is unsavory.

I attended a major industry conference in 2014. A display ad executive spent forty-five minutes with me ... asking me to convince the Executive Team as a major retailer to invest much more in display ads because he could prove that nearly every customer who purchased from the website of the large retailer saw at least one ad. The executive claimed that he should get partial credit for every order.

This is also lizard logic. If we're going to go down that rat hole, then Panera Bread must attribute every delicious lunch sandwich to the union workers who paved the road that allowed customers to drive to Panera Bread.

Look, I know folks have to make a living. And it is really, really hard to dedicate years to a profession that yields marginal returns, at best. It would have to be painful to work that hard and then be attacked by folks who claim they are being ripped off.

But until we acknowledge the lizard logic inherent in so much of the nonsense we read, we are also part of the problem. I realize it is easier to pay for a whopping 25,000,000 impressions than it is to invent a creative strategy that actually causes customers to buy something. The brand response marketer focuses on the latter. Too many of us have been trained to believe in the former.

Items And Pricing In A First Order Matter

Recall our example?

Watch what happens when a customer purchases 2 items at $90 each, instead of 4 items at $45 each.

This is a common outcome. Your merchandising team raises prices, the customer trades off by purchasing fewer of the expensive items, and the net result is a less profitable customer.

See what happens when the customer purchased 3 items at $45 instead of 4 items at $45.

It's helpful to have more items, isn't it?

Now, let's try 4 items, and instead of having them at $45, we'll buy them at $60.

So the secret is to somehow increase prices and increase units.

Unfortunately, it is terribly hard to do both.

At least be aware of the tradeoffs that occur between prices and units. As a former CMO once told me ... "units equal customers".

October 2014 vs. December 2014

Ok, here's the same data as illustrated yesterday, but for recently acquired buyers, illustrating their downstream repurchase rates.

1st Time Buyer in December 2014:

• Cumm Rebuy Rate at End of 12/2014 = 2.4%.
• Cumm Rebuy Rate at End of 1/2015 = 3.9%.
• Cumm Rebuy Rate at End of 2/2015 =  4.9%.
• Cumm Rebuy Rate at End of 3/2015 = 6.1%.
• Cumm Rebuy Rate at End of 4/2015 = 6.9%.
• Cumm Rebuy Rate at End of 5/2015 = 7.9%.
• Cumm Rebuy Rate at End of 6/2015 = 8.9%.
• Cumm Rebuy Rate at End of 1 Year = 15.2%.

1st Time Buyer in October 2014:

• Cumm Rebuy Rate at End of 10/2014 = 3.8%.
• Cumm Rebuy Rate at End of 11/2014 = 7.4%.
• Cumm Rebuy Rate at End of 12/2014 = 9.9%.
• Cumm Rebuy Rate at End of 1/2015 = 11.0%.
• Cumm Rebuy Rate at End of 2/2015 = 13.7%.
• Cumm Rebuy Rate at End of 3/2015 = 15.5%.
• Cumm Rebuy Rate at End of 4/2015 = 16.9%.
• Cumm Rebuy Rate at End of 1 Year = 21.8%.

It's the same story for this company, simply condensed down to a year instead of a five year window.

Do the analysis - it's gonna be enlightening, and it will cause you to question what you are doing.

Or, send me a message and I'll analyze the issue for you (kevinh@minethatdata.com).

More On Weak Performance Among New Buyers From December

Let's review some data from a business from 2010 ... this allows me to evaluate long-term value for five years. But in the short-term, I want to show you the cumulative probability of a customer purchasing for the second time, by month. Watch this:

1st Time Buyer in December 2010:

• Cumm Rebuy Rate at End of 12/2010 = 2.7%.
• Cumm Rebuy Rate at End of 1/2011 = 4.7%.
• Cumm Rebuy Rate at End of 2/2011 = 6.1%.
• Cumm Rebuy Rate at End of 3/2011 = 7.9%.
• Cumm Rebuy Rate at End of 4/2011 = 9.4%.
• Cumm Rebuy Rate at End of 5/2011 = 10.9%.
• Cumm Rebuy Rate at End of 6/2011 = 13.1%.
• Cumm Rebuy Rate at End of 1 Year = 21.7%.
• Cumm Rebuy Rate at End of 2 Years = 26.9%.
• Cumm Rebuy Rate at End of 3 Years = 29.8%.
• Cumm Rebuy Rate at End of 4 Years = 31.8%.
• Cumm Rebuy Rate at End of 5 Years = 32.9%.

1st Time Buyer in October 2010:

• Cumm Rebuy Rate at End of 10/2010 = 4.1%.
• Cumm Rebuy Rate at End of 11/2010 = 9.5%.
• Cumm Rebuy Rate at End of 12/2010 = 13.3%.
• Cumm Rebuy Rate at End of 1/2011 = 15.1%.
• Cumm Rebuy Rate at End of 2/2011 = 16.5%.
• Cumm Rebuy Rate at End of 3/2011 = 18.7%.
• Cumm Rebuy Rate at End of 4/2011 = 20.6%.
• Cumm Rebuy Rate at End of 1 Year = 29.1%.
• Cumm Rebuy Rate at End of 2 Years = 34.4%.
• Cumm Rebuy Rate at End of 3 Years = 37.6%.
• Cumm Rebuy Rate at End of 4 Years = 39.8%.
• Cumm Rebuy Rate at End of 5 Years = 41.5%.

Do you see what happens? In this case (your mileage will vary), the December buyer starts off with low repurchase rates (Jan/Feb are not big demand months), and the customer never catches up. Look at what happens to customers acquired in October 2010 ... they are immediately responsive ... you get the same percentage to repurchase in two months that you get from December 2010 buyers in six months. Why? In large part, this happens because Nov/Dec are highly responsive months. Look at the October 2010 data, especially once you get to January ... cumm repurchase rates slow down dramatically, because Jan/Feb are not big demand months.

You obtain an advantage when you acquire customers just before big demand months. If I were a catalog co-op, Google, or Facebook, I'd be selling that message very hard - heck, it isn't hard to run a life table to measure the dynamic, is it?

And if I were you, I would assign my analytics team this challenge ... they need to explain the dynamic to the whole company. Maybe your peak season is in April ... then you need to acquire customers in February so that those customers can purchase for the second time in April, right? Have your analytics gurus analyze this issue thoroughly. Pass the information along to your customer acquisition team. Pass the information to your Brand Response Marketing team. Then craft tactics that capitalize on this dynamic.

P.S. Critics will say that this is old data, and I should focus on new buyers from 2014. Ok. Tomorrow, we'll do that.

Speaking Of All Those Worthless Christmas Newbies

This from a recent project:

1st Time Buyers, November 2010:

• 1st Full Year Demand = $44.40.
• 2nd Full Year Demand = $19.66.
• 3rd Full Year Demand = $15.61.
• Three Year Demand Value = $79.67.
• Three Year Profit = $13.87.

1st Time Buyers, December 2010:

• 1st Full Year Demand = $25.36.
• 2nd Full Year Demand = $10.62.
• 3rd Full Year Demand = $9.25.
• Three Year Demand Value = $45.23.
• Three Year Profit = $3.09.

Your Brand Response Team takes advantage of this dynamic. They plant all sorts of customer acquisition seeds during the year. They harvest new customers in September/October. Those new customers pay back, immediately, in November/December.

Make sense?

Merchandise Categories Matter in Lifetime Value Calculations

Here's a typical story.

Now, let's assume that the customer purchased from Merchandise Category 3 instead of Merchandise Category 1.

#OhBoy.

Let's swap out Merchandise Category 3, moving Merchandise Category 6 in instead.

Now that you know this, there are several things you would be willing to do, right?

1. You feature Merchandise Category 6 items in your prospecting catalogs (you use prospecting catalogs, right?).
2. You gladly pay more for keywords from Category 6.
3. You pay less for keywords from Category 3.

But If I Cannot Attribute New Orders Properly, I'm Sunk, Right?

Wrong.

Attribution is a mirage. We've all done it wrong for decades and managed to grow businesses to ten percent pre-tax profit.

When I analyze an e-commerce-only business, I get to see unique and interesting trends.

For instance, it frequently takes a half-dozen visits to harvest a first purchase. Those visits tend to come from:

• Social Media.
• Facebook Advertising.
• Google / Paid Search.
• Email Marketing and/or Company Blog.
• Direct Load.
• Visit Resulting in Purchase.

Now, you give this problem to 10 attribution vendors, and you'll get 10 different answers. Every answer is right. Every answer is wrong. Worse, give this problem to Google, and they'll prove that advertising works and therefore they'll prove that you should spend more money, and then they'll ask you to use Google Analytics to prove that digital marketing works.

I'm not saying you shouldn't use attribution algorithms. If anything, I'm saying you should pay for three of them and have your in-house team execute a fourth routine and then average the results.

But what I'm saying is more important ... work every source you have ... work the low-cost or no-cost sources VERY HARD ... and seek to obtain new customers as a function of all activities, not as a function of a handful of optimized channels. When I worked at Nordstrom, we generated more than 10% pre-tax profit and acquired more than a million new buyers in stores each year and couldn't attribute almost any of them to any one marketing activity ... and because we didn't spend more than a percent or two of net sales on marketing, the new customers just kinda rolled in because we focused on the important stuff.

The same thing happens in your business ... many vendors don't want you to know this, of course, because they don't get paid. If you work your platform and low-cost / no-cost channels VERY HARD, you will get a ton of new customers independent of marketing activities. Focus on getting the details right, and the return on investment takes care of itself. Then you can have an argument about which attribution algorithm gets closest to your biased version of the truth.

But The Customer Is Worth Less

Here's what you keep telling me.

Source #1 = Catalog Co-Op.

• Profit per New Customer = ($11.00). You lost $11.00 profit to acquire the customer.
• Year 1 Profit Per New Customer = $17.00.
• Year 2 Profit Per New Customer = $12.00.
• Two Year Net Profit = ($11.00) + $17.00 + $12.00 = $18.00.

Source #2 = Some Form Of Digital Marketing.

• Profit per New Customer = ($13.00).
• Year 1 Profit Per New Customer = $13.00.
• Year 2 Profit Per New Customer = $9.00.
• Two Year Net Profit = ($13.00) + $13.00 + $9.00 = $9.00.

At this point, you tell me that the catalog co-op customer is worth twice as much as the customer acquired from digital marketing.

At this point, you tell me that you don't care about acquiring customers via digital marketing, because they are "worth less".

Two years from now, you'll call me to tell me that your co-op sourced names are all 65 years old and that they are driving your merchandising assortment into an array of merchandise preferred by retired customers ... and the merchandise assortment is no longer appealing to customers sourced from digital marketing ... and therefore, you cannot afford to leverage digital in a meaningful way.

Oh, wait, this all actually happened between 2010 - 2015.

Here's how thinking can evolve.

Be content with acquiring two customers that generate the same profit as one customer. Treat these customers differently downstream. You'll end up with a bigger customer file, but one that is less productive. Regardless, profit is the same, right?

And isn't profit what matters most?

I know, I know, I just talked about how December buyers tend to have lower lifetime value. You'll tell me you just need to ramp-up your efforts in December. But for most catalog-centric brands, market share is being lost in December to online brands, to Amazon, and to retailers who really stepped-up their e-commerce efforts. We need to find other times of the year to find new customers.

And if we cannot do that, and if our primary source of new names is shrinking, well, then we have to think long and hard about finding new customers from other sources, regardless of reduced lifetime value.

Profit per New Customer

Ok, you have your "war room" plastered with five years of customer acquisition history, right? You publish all of your customer acquisition metrics from all sources on the wall in your "war room", don't you?

On the walls, you have key metrics you share with your company, by source of acquisition.

1. Total Demand Generated by Year.
2. Ad Dollars Spent by Year.
3. Total New Customers, by Year.
4. Total Profit, by Year.

And then, you have these important metrics:

1. Marketing Cost per New Customer (Total Ad Dollars / Total New Customers).
2. Profit per New Customer (Total Profit / Total New Customers).
3. Year 1 Profit per New Customer.
4. Year 2 Profit per New Customer.
5. Year 3 Profit per New Customer.
6. Year 4 Profit per New Customer.
7. Year 5 Profit per New Customer.

You are probably saying to yourself, "Hey, idiot, when we acquire a customer from a new source, we don't know anything about years one through five." True. But it is your job to estimate those figures. That's what you are being paid to do. So make a guess, based on what you see with other sources of acquisition.

Compare profit per new customer at the point of acquisition with profit in year one. Do you lose twelve dollars of profit acquiring the customer, and then make twenty dollars of profit in year one? Yes? Then it might be a good idea to acquire that customer, right?

Sit down with your CFO and share your data - heck, it's posted on the walls of your "war room", so just invite her in to take a look. Ask her how deep she is willing to invest in a new customer ... you might be surprised to learn that she is willing to lose money for up to three years in order to grow the business. Or, you might learn about the financial distress your company must deal with ... and that's the reason you can only prospect to break-even.

The key, of course, is to use profit per new customer as the driving metric in this analysis. Don't use marketing cost per new customer, as that metric does not cleanly align with future profit (yes, if you do the math, there is 100% correlation between profit per new customer and marketing cost per new customer, but most people don't do the math to learn the relationship, you included, so just use profit per new customer).

Make sense?

Lifetime Value - Free Shipping

This one is interesting. Look at a customer acquired in June.

Ok, now let's see what future value looks like for those who took advantage of free shipping.

This company generates an average of $10.00 of shipping/handling revenue.

In other words, free shipping caused the company to lose $10.00 ... and the customer paid back $6.15 of incremental profit in year one.

If I ran the analysis forward another year, we'd probably see that all ten dollars have been recouped. But it took two years to recoup the profit. Two years! And in so many of my projects, the profit is NEVER recouped.

Make sure you are measuring what you lose up-front with free shipping.

Make sure you are measuring what you gain, downstream, from a customer acquired via free shipping.

Lifetime Value

You should know that Lifetime Value projects are currently the second-most popular, after Merchandise Forensics projects. When you talk a lot about customer acquisition, people want to learn more about the customers they are acquiring.

Most companies don't measure lifetime value. Which is interesting, of course, because your investment strategy is 100% dependent upon lifetime value calculations.

I tend to create two different analyses ... one being a twelve-month value analysis ... the other a five year customer migration simulation, designed to measure how lifetime value declines as the customer changes/ages.

In any lifetime value analysis, we care about repurchase rates and customer spend ... but we care much more about profit. This is the other interesting thing about lifetime value work in the industry ... most lifetime value projects measure annual demand or downstream demand ... which makes it impossible to measure the trade-off between how much you invest acquiring a customer and how much the customer pays you back.

In my twelve-month profit models, I evaluate many different attributes. Here is a sample, based on real data from a real company.

Here, we observe a customer with a set of attributes. This customer generates $6.54 downstream profit. This would not be the kind of customer you want to lose $30.00 profit acquiring, do you?

I've mentioned the "December Effect". The example above is for a customer acquired in June. Watch what happens when we acquire a customer in November.

We've already lost three dollars of profit. Now look at what happens in December.

#OhBoy.

Let me state this differently ... for this company, they have to acquire ten times as many customers in December as they have to in June to obtain the same amount of future profit.

Is it any wonder it is so hard for companies to generate profit? I work with many companies that generate half or more of their new buyers in November/December, because that is when it is "easy" to acquire a customer.

Think about this. Is it any wonder we work so hard to encourage "loyal" behavior? If we keep acquiring disloyal buyers in November/December, prospects who are looking to meet a Christmas need at a point in time, it is going to be very hard to move the customer along to loyalty.

Run your lifetime value analytics at a modeled level - combine many interesting attributes, and learn where you are succeeding and where business isn't so good.

Evolution of the Thesis

In 2007 I wrote a book arguing that customers overwhelmingly preferred the online channel, and that the online channel would eventually capture most orders. When that happened, many traditional catalog strategies would begin to falter.

In 2010, I argued that the organic percentage could be measured, and if measured properly, allowed companies to save a fortune on advertising expense because orders were going to happen anyway and were being incorrectly attributed to catalogs and paid search and online marketing. 

In 2011, I argued that the online channel had "won", cutting catalogers off from younger customers. 

In 2013, I argued that without a healthy focus on new merchandise, we are slowly starving our customer files from growth. 

In 2014, I argued that the omnichannel thesis was dead on arrival, simply because customers do not spend more when they have access to many channels, and that this would ultimately cause sales to transfer online and cause stores to close and cause expenses to rise until the stores were closed (at which time sales declined, of course).

In 2016, I am arguing that we need Brand Response Marketing to plant enough seeds so that we can acquire enough new customers at a low cost to fuel our future success. 

The secret to success ultimately comes down to profitable management of new merchandise and new customers.

A Five Tool Analyst

If you are an analyst early in your career, you are probably already listening to my podcast (click here), right?

RIGHT??!!

A few months ago, I talked about what makes what I call a "Five Tool Analyst".

The concept is similar to baseball, where the coveted five-tool prospect becomes a major league All-Star.

The podcast has been interesting, in that I get feedback on two fronts.

1. Analysts who think Execs are knuckleheads.
2. Execs who think Analysts are knuckleheads.

Only the Analyst can change this dynamic - by earning the requisite skills necessary to become a Five Tool Analyst.

CREATIVITY:  Here's what I've learned in the past twenty-eight years of analytical work ... creativity is sorely missing. When an Exec asks a question, an analyst provides a dry, non-living query that yields a boring answer that never anticipates the next question the Exec will answer. Consequently, the Exec keeps running the analyst in circles, and both parties end up hating each other. The best analysts come up with new techniques (i.e. stuff you cannot do in Google Analytics) that surprise and delight Execs. 

CREDIBILITY: In my consulting work, I'm frequently hired because an analyst failed in some way. If in-house analysts pleased Execs, nobody would hire me. And if I pleased everybody, I would have earned enough money to retire already. Since truth is somewhere in-between, it is really important to earn credibility. You won't please everybody all the time, but if your answers are unbiased and always accurate and tend to anticipate the next question, you will undoubtedly earn credibility. When people think you are credible, you get invited into situations that you have no right being in. When you are in those situations, many people get to see your work, and your career advances.

CURIOSITY:  The best analysts perform work nobody asked for, because they identify problems before Execs see the problems coming. This gets the analyst in trouble ... I was nearly fired once because I spent too much time focusing on an issue that the CEO believed to not be an issue at all, and then felt that I was 100% wrong and he was 100% right. Regardless, you will identify issues and you will play a key role in pushing your company in the right direction if you have sufficient curiosity.

COMMUNICATION:  The best thing that ever happened in my career was being forced to attend Dale Carnegie sales training. In just eight weeks, sixteen hours, I learned how to sell a message. Nobody teaches analysts how to SELL. It turns out that Execs buy what analysts sell. Work hard on your sales skills.

CHOPS:  I once worked with an analyst who ran a Monte Carlo simulation. The analyst then claimed that he had the answers to a problem because he could simulate different outcomes. The analyst knew a methodology - but the analyst didn't realize that the results were simulated results and were not actual findings. Naturally, the analyst crashed and burned when the findings where shared with analysts who possessed "chops". It is really important to know how to code, preferably in multiple languages. It is really important that the analyst know, at minimum, Generalized Linear Models, Ordinary Least Squares Regression, and Logistic Regression. The combination of coding and models / regression enables the analyst to do just about anything. The combination of Google Analytics and Excel allows the analyst to do what Google / Microsoft wants the analyst to do.

Ok, you've made it this far. How many of the tools do you possess, if you are an analyst? And if you are an Exec, how many of the tools do you perceive your analyst possesses?

Catalogers & Christmas Customer Acquisition Best Practices

Here's a slide from my updated Customer Acquisition presentation (click here).

Now, I've been publicly holding this little fact back for quite a while (not to paying clients, of course) ... but in repeated lifetime value simulations, this always comes up. I'm repeatedly asked why customers are not loyal ... and the data consistently points to our own issues.

Here's how the story goes.

1 - For the average pure catalog brand (i.e. was a cataloger before the internet arrived in 1990), 85% or more of new customers come from one of the catalog co-ops, of which there are a handful. 85% of your customer base has been recruited by the co-ops. The same thing goes for Google/Facebook in e-commerce, FYI.

2 - Catalog circulation plans overload names into Nov/Dec, because those are more "responsive" timeframes. Names are acquired.

3 - On average, most catalogers and e-commerce brands do not measure lifetime value. 

4 - For most catalogers not possessing a strong seasonal business in Spring, between 25% and 50% of annual new customers are acquired in November / December.

5 - To acquire these customers, %-off and free shipping promotions are offered. These promotions frequently harm customer acquisition costs.

6 - Companies that measure lifetime value observe this dynamic, outlined in a lifetime value simulation I ran for a cataloger last week.  Look at the three year profit of names acquired in December, vs. other months:

7 - The customers you acquire in March - June repurchase during responsive times ... and then repurchase during November/December. They are more valuable. December buyers are recent in January/February, when they are not likely to buy again. The customer goes dormant until November/December, at which time the customer purchases with a discount and free shipping.

8 - The dynamic is not limited to Customer Acquisition. Look at customers who place a third order, by month of third order (for a client analysis conducted last week). I then measure three year lifetime value. It's the same story, just at a different magnitude.

What is the dynamic I'm talking about?

1. Your co-ops do a good job of optimizing for Nov/Dec response. They find buyers who are likely to buy in Nov/Dec.
2. These customers often purchase via a promo (#cybermonday), and are therefore less profitable in their a first order.
3. Because the order happened in Nov/Dec, lifetime value is less.
4. Because you try to maximize Nov/Dec, your loyal buyers are less valuable in the future as well.

What should you do about it?

1. Plant your customer acquisition seeds early in the year. Harvest your yield by early Fall. Enjoy Christmas repurchases. Generate profit next year. Do this by reviewing the tactics in my Customer Acquisition presentation (click here) and build out your Brand Response Marketing team.
2. Your co-ops know this happens, they've had your data forever. Ask then why they do not optimize for long-term success?
3. Stop worshipping November/December.
4. Calculate lifetime value. Any analyst and/or vendor should do this as a matter of practice. Contact me (kevinh@minethatdata.com) if you need help. I use a simulation of 100,000 customers over "x" years to measure lifetime value for any segment. Your vendor partners don't do this.

Are you at NEMOA this week?

• You are paying NEMOA a lot of money to attend. Your vendor partners are paying NEMOA a lot of money for prime speaking gigs, so that they can get you to spend a lot of money. How about using the conference as a forum to teach your vendor partners to optimize for long-term value, so that you, your vendor partners, and NEMOA can all make a lot more money? Seem reasonable? Everybody wins! How is that a bad thing?

The same logic applies to Google/Facebook in e-commerce. I see the same thing, repeatedly. Challenge them as well.

Your vendor partners are optimizing for immediate conversion/response. They tell you to be data driven. They are using data to sub-optimize customer loyalty and future profit. That's not acceptable.

You can fix this problem. But you need to speak up.

Big Trouble During The Christmas Season For Customer Acquisition

Allow me to show you summarized results from a lifetime value simulation I ran for a client.

• Customers Acquired January - October:  12-Month Future Demand = $60. 12-Month Future Profit = $14.
• Customers Acquired in November:  12-Month Future Demand = $45. 12-Month Future Profit = $8.
• Customers Acquired in December:  12-Month Future Demand = $35. 12-Month Future Profit = $4.

Show of hands ... how many of you look at future value by month of acquisition? Three of you? That's not good enough!!

Which customer would you prefer to acquire?

• The customer worth $14 next year?
• The customer worth $8 next year?
• The customer worth $4 next year?

When I go back to the late 1990s at Eddie Bauer, I recall a strategy my team used to grow our business.

1. Acquire customers in September/October.
2. Get those customers to repurchase in November/December, when the customer is very recent, before the customer lapses.
3. Be willing to spend $5 additional marketing dollars to acquire the September/October customer, because that customer will pay us back in November/December, and we still end up with more long-term profit than obtained by being lazy and acquiring a November/December customer with a discount/promotion.

How many of you employ that strategy? Show of hands, please.

I know, I know, you are executing real-time optimization, employing the most brilliant search algorithm coupled with a co-op model that overlays external data to create a rich, robust, responsive outcome. Or so the vendors tell you.

Go look at your own in-house data for once. Do you see the same trend that I observed above for a client? If the answer is "yes", does that not change your customer acquisition philosophy?

Customer Acquisition is all about planting seeds. You have to acquire the customer before Christmas, and then turn that customer right around into a second purchase at the time of the year the customer is most likely to repurchase. That's how you grow customer value.

But here's what is most important ... so many of you acquire a significant minority to a majority of new customers in November/December. You tell me that this is the "easiest" time of year to acquire customers. Then, those customers fail to purchase during the following year, so you grumble that you have poor customer loyalty so you plug in a bunch of discounts and promotions and other nonsense to stimulate a customer who only likes to purchase in November/December.

Might it be smarter to spend more to acquire customers in September, given that long-term value may well be so much greater? Is it possible that our industry is simply creating problems by acquiring a customer on December 1 at 30% off plus free shipping ... a customer that is unlikely to purchase for the next ten months?

Please analyze this issue. What do you see happening?