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?