Office Hours are for Any Professional!!

FYI:  Anybody can sign up for Office Hours next week (details below). If you are CEO, sign up. If you are a 23 year old beginning your career, sign up. I used the football case as an example.

Sign up begins Monday at 1:00pm EST / 10:00am PST ... first 25 time-stamped responses are included, next ten are wait-listed.

Thanks,

Kevin

Details:

On January 6 at 1:00pm EST / 10:00am PST Bill and I will hold Office Hours for a small group of 25 students. The audience is limited to current catalog practitioners (there may be Office Hours in the future for different disciplines, but this is where we are starting). So if you want to participate, hold the date of January 6 at 1:00pm EST open on your calendar.

Frequently Asked Question?

• How do I sign up?

Here's how I am doing this.

• You can sign up at exactly 1:00pm EST / 10:00am PST on Monday, January 4. Not a minute sooner.
• The first 25 time-stamped emails I receive from current catalog marketing practitioners (send your email to kevinh@minethatdata.com) are in. If your email arrives one minute prior to the deadline, it is thrown out. The next 10 time-stamped emails go on a waiting list.
• You will receive e-mail confirmation that your Office Hours application has been accepted, wait-listed, or denied.

One catch:

• Your email application MUST include a link to one industry article that you think is interesting, an article that you'd like us to consider for discussion during Office Hours. Here's an example of what I'm talking about (click here). Go ahead and tell me what you find interesting about the article and what you'd like Bill & I to consider discussing in relation to the article.
• No link to an article, no acceptance of your application.
• I will collect all of the articles that are submitted by all applicants ... and I will forward the list of all articles to all applicants, regardless whether your application is accepted, wait listed, or denied.

That's what I'm experimenting with, peeps. Let's try something different, and let's see how it goes.

Let me know if you have any questions (kevinh@minethatdata.com). 

Office Hours Reminder

On January 6 at 1:00pm EST / 10:00am PST Bill and I will hold Office Hours for a small group of 25 students. The audience is limited to current catalog practitioners (there may be Office Hours in the future for different disciplines, but this is where we are starting). So if you want to participate, hold the date of January 6 at 1:00pm EST open on your calendar.

Frequently Asked Question?

• How do I sign up?

Here's how I am doing this.

• You can sign up at exactly 1:00pm EST / 10:00am PST on Monday, January 4. Not a minute sooner.
• The first 25 time-stamped emails I receive from current catalog marketing practitioners (send your email to kevinh@minethatdata.com) are in. If your email arrives one minute prior to the deadline, it is thrown out. The next 10 time-stamped emails go on a waiting list.
• You will receive e-mail confirmation that your Office Hours application has been accepted, wait-listed, or denied.

One catch:

• Your email application MUST include a link to one industry article that you think is interesting, an article that you'd like us to consider for discussion during Office Hours. Here's an example of what I'm talking about (click here). Go ahead and tell me what you find interesting about the article and what you'd like Bill & I to consider discussing in relation to the article.
• No link to an article, no acceptance of your application.
• I will collect all of the articles that are submitted by all applicants ... and I will forward the list of all articles to all applicants, regardless whether your application is accepted, wait listed, or denied.

That's what I'm experimenting with, peeps. Let's try something different, and let's see how it goes.

Let me know if you have any questions (kevinh@minethatdata.com). 

What Would Stop You From Doing This?

Watch the video (click here). 

Pay attention to what these folks are doing with young Professionals.

What would stop you from doing something like this at your company? Get a group of twenty young Leaders, and host an hourly session with them where you ask them for solutions to some of the challenges you face. Explain your thinking ... why you approach issues the way you approach them, why you select preferred solutions ... teach young Leaders how to assess risk.

At worst case you waste an hour a week. 

Best case? You develop Leaders while simultaneously solving problems.

Office Hours

I'm always asking you, the loyal reader of the past fifteen days to the past fifteen years (think about that) to try things, to experiment. Next week, I'm going to take my own medicine, and I'm forcing Bill LaPierre to take the medicine with me.

Poor Bill.

I got the idea for Office Hours from a video course on Transactional Analysis that I've worked on for the past six months with an online education brand. When their students take a course, they spend Office Hours (via video) with the instructor, allowing the students time to ask face-to-digital-face questions with the instructor. Of course, the student had to complete a bunch of homework to get to that point ... it's not a one-way street, but the idea is old and traditional and yet modernized for our COVID-paralyzed reality.

So let's try something. Let's try an experiment.

On January 6 at 1:00pm EST / 10:00am PST Bill and I will hold Office Hours for a small group of 25 students. The audience is limited to current catalog practitioners (there may be Office Hours in the future for different disciplines, but this is where we are starting). So if you want to participate, hold the date of January 6 at 1:00pm EST open on your calendar.

Frequently Asked Question?

• How do I sign up?

Here's how I am doing this.

• You can sign up at exactly 1:00pm EST / 10:00am PST on Monday, January 4. Not a minute sooner.
• The first 25 time-stamped emails I receive from current catalog marketing practitioners (send your email to kevinh@minethatdata.com) are in. If your email arrives one minute prior to the deadline, it is thrown out. The next 10 time-stamped emails go on a waiting list.
• You will receive e-mail confirmation that your Office Hours application has been accepted, wait-listed, or denied.

One catch:

• Your email application MUST include a link to one industry article that you think is interesting, an article that you'd like us to consider for discussion during Office Hours. Here's an example of what I'm talking about (click here). Go ahead and tell me what you find interesting about the article and what you'd like Bill & I to consider discussing in relation to the article.
• No link to an article, no acceptance of your application.
• I will collect all of the articles that are submitted by all applicants ... and I will forward the list of all articles to all applicants, regardless whether your application is accepted, wait listed, or denied.

That's what I'm experimenting with, peeps. Let's try something different, and let's see how it goes.

Let me know if you have any questions (kevinh@minethatdata.com).

Merry Christmas

For the fifteenth consecutive year, I wish you a Merry Christmas!

A year ago you probably couldn't have conceived how 2020 would turn out. It wasn't an easy year, was it?

So enjoy the season!

Moneyball

Yeah, that movie comes on and it is like catnip to me.

There's one quote in particular that sticks with me. If you've been a long-time reader, you'll probably recognize it. Brad Pitt as Billy Beane is visiting the Red Sox, who want to hire him after he transformed his corner of the baseball world via analytics. The John Henry character says this to Brad Pitt.

2021 is going to be a year of transition. We've thrown away the world "BC" (before COVID), but we won't fully settle on the future until sometime in 2022 (if then). And as the future emerges, keep the quote above in mind. When your favorite boutique agency tells you to go back to what you did "BC", keep the quote above in mind. When your favorite boutique agency tells you what the future will look like (hint - they have no idea what the future is going to look like), keep the above quote in mind.

Handling Fee

This goes back more than twenty years.

I'm running the Circulation Department at Eddie Bauer. Profit was scant. Merchandise productivity was awful. Our SVP of Marketing wanted to do something brazen.

• He wanted to add a $3 handling fee to every order.

And that's exactly what he did.

CUSTOMERS HOWLED. The customer contact center grumbled, and for good reason ... they were being howled at daily by customers.

Funny side note:

• Repurchase Rates remained constant.
• Orders per Buyer remained constant.
• Items per Order remained constant.
• Price per Item Purchased remained constant.
• Profit dramatically increased.

In other words, customers HATED the $3 fee. Customers grumbled about the $3 fee. Then customers bought merchandise and paid the $3 fee.

Think about this as UPS and FedEx pass costs along to you. You are howling about it. You are grumbling about it. And then you are paying them additional $$$ anyway.

Might your customers be willing to spend more if you asked them to?

Christmas Lights

My neighborhood is one of those that is lit up at Christmas. It's almost a competitive event, as each house and yard look absolutely beautiful from mid-November through the first week of January.

I have a block wall that borders the street. Along that block wall I string about ninety feet of blinking lights. A few days ago I was working on the lights when I cut right through them. Ninety feet of lighting became forty-five feet of workable lights and a gaping wall of darkness.

Unacceptable.

Off to the big box brands to solve the problem. On December 14. With a mask on. 

Home Depot was no longer selling Christmas lights ... just a small amount of clearance items.

Lowes was no longer selling Christmas lights ... just a small amount of clearance items.

Ace Hardware was no longer selling Christmas lights ... just a small amount of clearance items.

Amazon referred me to third parties who sold my lights ... they were sold out.

This is how Commodity Commerce works. They "have" to get that stuff out of the store because it doesn't sell well ... there aren't enough morons like me who cut through four strands of copper for Commodity Commerce to generate a profit. They need to sell through stuff and generate acceptable inventory turns.

The Performance Commerce brand finds a solution to this problem. That doesn't necessarily mean the Performance Commerce brand stocks the items (unprofitably). It might mean that the Performance Commerce brand has YouTube videos to help the customer fix the lights. It might mean that the Performance Commerce brand links customers to Electricians who can fix the problem. It might mean the Performance Commerce brand works with Influencers who help identify alternate solutions.

Here's an example of Performance Commerce in restaurants (click here).

In 2022, once we move past the pandemic but find ourselves in a changed world, we'll count on Performance Commerce brands to solve problems.

Shipageddon

a) It's not fun for my client base. Orvis gets blamed for disappointing customers when it is FedEx and UPS that failed to respond to COVID (and asking them to properly respond to this surge is asking too much, I get it ).

b) It's not fun for customers.

c) It's not fun for FedEx / UPS employees who haven't done anything wrong and have to deal with frustrated customers and clients.

d) It's more fun for Amazon, who invested in delivery alternatives.

e) It's not optimal that my client base wasted twenty (20) years of e-commerce prosperity not developing alternatives to FedEx and UPS. On the surface, you'd think the e-commerce industry might band together and figure out how to apply leverage and/or create an alternate solution. But I remember working at Lands' End in the early 1990s, measuring the impact of customers who received packages via "Alternate Delivery" solutions, so it's not likely to happen.

I realize it is terribly hard to just keep the wheels on the business bus right now ... with employees working from home and unprecedented demand for many e-commerce brands and illness/death plaguing some of us. Try to allocate a small amount of bandwidth to thinking about how packages will get from your warehouse to the customer in the future, and then develop a plan, ok?

Performance Commerce

Commerce seems to be headed in three directions.

1. Amazon.
2. Commodity Commerce.
3. Performance Commerce.

Now, you can argue this thesis until the cows come home, and nobody is going to be right or wrong.

Big Box Retail leans toward Commodity Commerce. How many people get a thrill buying a light fixture for their bathroom at Home Depot?

You (the vast majority of you who read this) are in the Performance Commerce category. If you were truly selling commodity products, you'd have already been drubbed by the big boxes and Amazon. If you survived that onslaught, you are in the Performance Commerce category.

What is "Performance Commerce"??

It's the opposite of boredom.

Have you ever watched a newscast from the 1970s? There are few things more boring in the modern world than watching Roger Mudd read text off of a piece of paper. If you "performed" the news in this manner in 2020, you'd have an audience of zero. Meanwhile, Fox News and CNN and MSNBC are calibrated toward "performances". I was getting an oil change a few weeks ago, and a fellow citizen was not wearing her mask (#chindiaper), telling the service rep all the reasons why he should watch "Hannity" on Fox News. That's the impact of "Performance Politics" or "Performance News".

Performance Retail used to be driving to a mall, spending $11 at Sbarro, then getting 50% off an item at JCP. That was entertaining, much more so than ordering online (in the early days of e-commerce) or than ordering via a catalog and waiting nine days for your order to arrive. Retail didn't evolve, hence, retail is crumbling all around us ... COVID or not.

There's a reason why Amazon is somewhere between 30% and 45% of all e-commerce ... they captured all of the boring transactions. There is a small element of Performance Commerce at Amazon ... if you consider that you can order something this morning and have it delivered this evening in an Amazon van featuring a Ford Transit chassis as being Performance Commerce.

COVID temporarily changed the rules of "Performance Commerce". If you can't go eat at Texas Roadhouse (that's Performance Dining) you'll order from ButcherBox and then you are the Performance. That changes in 6-9 months, doesn't it? Then what?

It's time to start thinking ahead to 2022. Oh, I know, we're all figuring out our budget for 2021, and that's hard work with considerable uncertainty, but 2022 isn't far away and Retail is going to re-emerge from the darkness and we won't be buying meat from ButcherBox at the same rate because we'll be eating at Texas Roadhouse. Then what?

That's where Performance Commerce comes into play. We're going to have to do something "non-boring". Sending a catalog, having a "Friends and Family" event, offering $10 of free merch as a loyalty reward, or giving special discounts for email subscribers won't cut it. Nope. For a year-and-a-half, we had to give our own Performances. In 2022, it will be up to us to Perform for our customers.

Shared Catalog

Now that your favorite agencies and printers are encouraging brands to align and send out "shared catalog" (catalogs where 10-20 brands all contribute pages and contribute customers, sharing the expense of a mailing), you are probably wondering "Should We Do That Too"?

Quite honestly, you could have been doing this for the past two decades. This isn't an innovative idea. But it should catch your attention that traditional catalogers aren't doing this (click here). I know, I know, traditional catalogers will bark at me ... "that idea is stupid, it won't work".

Traditional catalogers are right to assume that the idea won't work under the definition of what works for a traditional cataloger.

But times are changing ... and the future is being split into three big pieces.

1. Amazon.
2. Commodity Commerce (Walmart / Target / Big Boxes / Department Stores).
3. Performance Commerce.

There's a reason that Sears and JCP and Macy's and so many traditional brands are slowly being starved. The "boring" purchases are being gobbled up by Amazon and Commodity Commerce, leaving Performance Commerce as the only option. Almost none of us are good at Performance Commerce.

We're going to have to become good at Performance Commerce.

And that means our definition of "what works" changes.

So is a "shared catalog" the answer? Probably not. But it is "something" that you could do to generate awareness. And you'll generate awareness the way you like to generate it (if you are a traditional cataloger) ... by mailing a catalog.

Tomorrow I'll share with you what Performance Commerce is.

Rick Barry

Forty-five years ago you'd watch the Golden State Warriors and you'd see Rick Barry shooting free throws like this (click here).

The percentage of free throws he made using this technique was ... quite honestly ... staggering. Here are the percentages from the final six years of his career.

• 1975 = 90%.
• 1976 = 92%.
• 1977 = 92%.
• 1978 = 92%.
• 1979 = 95%.
• 1980 = 94%.

Considering the average free throw percentage made is somewhere in the mid-upper 70% range, you'd think somebody would try to copy his style ... a style called "granny style".

Nobody wants to shoot free throws "granny style".

And if you are shooting 81%, it might not be worth changing your shooting technique.

But what about if you shoot 61%?

This brings me back to Welcome Programs. The data clearly shows that the first-time buyer is very active for 4-12 weeks following a first purchase, and then quickly fades away. If you want a loyal customer base (in time), you HAVE to convert the customer quickly following a first purchase.

And yet?

Nobody "wants" to execute a Welcome Program.

The data is overwhelmingly positive. Rick Barry positive.

Three Ways To Acquire A Customer

You honestly have three choices.

The first choice is to work your rear end off, being so darn creative that you acquire customers for free. This is hard work. And you can't just turn the switch on and go do it. You need a plan.

Since most of you operate with annual bonuses and the risk of being fired each year, you don't have the luxury to acquire customers for free. You have a budget. You feel like it is your job to spend money, and in exchange you get customers. This is how marketing has worked for a long time. Paid Search comes to mind. You pay per click. 98.5% of the customers bounce off of your site and return to Google ... and Google deposits your money while sending that very customer to another marketer who pays per click.

There's a third choice. You can pay somebody a percentage for access to customers. Like Amazon. An apparel brand might pay 17% of a transaction, hopefully less.

The first choice is what you should strive for.

The second choice must pay you back downstream, because you are likely to lose money up-front.

The third choice generally yields up-front profit. Downstream profit determines how effective this strategy is.

Segment all of your customers based on choice (1) (2) (3). Measure long-term downstream profit for each choice. The story of your brand will be revealed by this analysis. Remember, customers reveal themselves within a few weeks of being acquired. Their revelation determines how effective (1) (2) and (3) are.

Consistent Behavior

I've analyzed customer behavior for about 250 brands. And there is one things that is consistent across the 250 brands.

• When you acquire a customer, the customer quickly tells you who the customer is.  

What do I mean by that?

I've told you this story before ... when I worked at Nordstrom, Oprah blessed us by sharing with her audience of tens of millions of devoted viewers a key item that was ... sold at Nordstrom!

New customers rolled in the door. They flooded the customer file.

Thirty days later my team analyzed the glut of customers blessed upon us by Oprah. The customers weren't repurchasing. A retail newbie might have had an 8% rebuy rate in the first month after acquisition. An online newbie might have had a 5% rebuy rate in the first month after acquisition. The Oprah newbie? Maybe 2%.

We followed the cohort of newbies for a year or so, until we were convinced that the customer wasn't coming back. We should have been convinced after two weeks, but we gave it a lot more time just to be sure.

The customer tells you (when lumped in with similar customers) ... really, really quickly ... whether the customer wants to have a relationship with you. You can influence the trajectory. Take the 2% rebuy rate after thirty days for the Oprah customer and influence it up to 3%. That's a good outcome. But you won't move it up to 5% like the online buyer or 8% for the retail buyer.

Customers exhibit consistent behavior. From day one, they tell you whether they're coming back or not. If you partner with an Influencer and you get 50,000 new customers, good, as long as you generated profit acquiring the 50,000 customers you did well. But from that moment forward, the customer is telling you who s/he is. If the customer isn't repurchasing after a few weeks, odds are the customer is already a lost cause.

P.S.:  Every month, you have a baseline performance for a new customer. Maybe it is the customer who buys online without attribution, maybe the customer is the customer who buys via paid search. Regardless, every month, take the baseline customer, segment them, and then follow the customer month-by-month. Compare all sources of acquisition against the baseline customer, measuring sales, return rates, gross margin percentages, ad cost expenditure, promotional expenditures, pick/pack/ship expenses. All of it. By segment. By month. Compared against your baseline. Then stop wasting money on sources of customers that do not meet your objectives.

Velocity

Velocity is a simple concept in marketing. Here is the metric:

• Velocity = (Life to Date Orders) / (Time on the Customer File).

Example:

• Customer has 2 life-to-date orders, and has been on the customer file for five months.
• Velocity = (2) / (5) = 0.400.

Example:

• Customer has 3 life-to-date orders, and has been on the customer file for thirty-six months.
• Velocity = (3) / (36) = 0.083.

Does Velocity matter? Yes!

Here is a graph for 0-3 month buyers with exactly two (2) life-to-date purchases. We're measuring repurchase rates in the month of October. Look at the odd relationship in the graph.

High-Velocity (two purchases in two months)?  A very high probability of purchasing again next month.

Mid-Velocity (two purchases in five months)?  A comparatively low probability of purchasing again.

Low-Velocity (two purchases in twenty months)?  A middle probability of purchasing again.

The High Velocity customer outcome is entirely expected ... again, this is why I harp on a Welcome Program all the time. Get that 1x buyer to a 2nd purchase immediately, and you end up with the case on the far right side of the graph. I wouldn't lie to you about the importance of Welcome Programs.

The Mid-Velocity customer outcome is somewhat unexpected in comparison to the Low-Velocity customer. The Low-Velocity customer has one advantage ... s/he has been with the brand for a long-time, and that "time with the brand" translates into Low-Velocity which translates into more familiarity and a modestly higher chance of buying again.

But the biggest takeaway of this analysis is on the far right side of the graph. Get that first-time buyer to purchase again immediately via a credible Welcome Program and you end up with a highly responsive customer who has a good chance of buying for a third time.

UPS

Reconcile this for me, ok?

UPS says (on December 2) they're overwhelmed and cannot support additional volume from the largest brands out there (click here).

Conversely, here they are on December 3 telling you as a customer to trust them and use them ... now!!

Why would they tell you that they can't handle your volume but they are spending the money you pay them to tell individual customers that they can handle their volume?

Notice that (in the article) Amazon doesn't have any constraints placed upon them.

I know, I know, this is hard ... and UPS / FedEx probably can hire more people but cannot build new warehouses and neither brand ever expected a pandemic to cause brands to surge online. So yes, there should be some empathy for their predicament. But YOU were also put in a horrible predicament, and somehow you grew your sales dramatically (in so many non-apparel e-commerce cases this year) and worked through serious constraints. If you can do it, your vendor partners can do it as well.

Calculating The Data In The Graph

Yesterday I shared with you a graph ... showing you how likely first-time buyers were to respond by month. Remember the graph?

The graph prompted a lot of responses. I could write 50 posts in a row and not get any feedback, but this one ... this one generated a lot of feedback. Here was the number one question:

• "How do I calculate the incremental rebuy rates in the graph?"

So let's walk through the process.

I create a dataset that looks like this:

Each column is populated with the order date of the first order, second order, third order, and so forth. If a customer did not place a, say, fifth order, then the column is populated with the value 99999999.

Next, I transform order dates into months. I arbitrarily choose January 2015 as a value of 1001, then February 2015 as 1002, then March 2015 as 1003. December 2020 is then assigned a value of 1072. Here is what the dataset looks like.

From here, I have everything I need to produce the graph at the top of this post. By subtracting the first order date from the second order date, I can calculate how many months pass between a first purchase and a second purchase.

Look at Customer 1:  Take the second order date (1063), subtract from it the first order date (1061), and you get 1063 - 1061 = 2. The customer purchased for the second time in the second full month.

Look at Customer 3:  1042 - 1030 = the customer purchased for the second time twelve months later.

From here, I create a frequency distribution of all second order month time intervals.

Let's pretend that we have 100 customers. 5 purchase for the second time in the same month as a first purchase (a value of 0 when subtracting months above). The incremental probability is 5/100 = 5%.

Now, I subtract the repurchasers out of my base, leaving me with 95 customers. Let's say that 6 customers purchased in Month = 1. 6/95 = 6.3% repurchase in the first full month.

Then, I subtract the 6 repurchasers from my base of 95 customers, leaving me with 89 customers. Let's say that 4 repurchased. 4/89 = 4.5%.

Subtract the 4 repurchasers from my base of 89 customers, leaving me with 85 customers. Let's say that 2 repurchased. 2/85 = 2.4%.

This process is replicated as long as you have data to replicate the process. If you have 36 months of repurchase activity, you'll have 37 data points.

I now have the data I need to produce the graph at the top of this post:

• Month 0 = 5.0%.
• Month 1 = 6.3%.
• Month 2 = 4.5%.
• Month 3=  2.4%.

This analysis can be replicated for 2nd purchases, 3rd purchases, and so on.

This analysis can be done by acquisition month (analyze what December newbies look like vs. April newbies ... always a compelling story).

This analysis can be done by source of acquisition ... by average order value ... by channel, you name it.

It's a simple analysis, it's flexible, and it is informative. It's called a "Life Table" analysis.

Go run the analysis for yourself!

And if you can't run the analysis for yourself, for just $1,200 I'll run the analysis for first-time buyers, for 2x buyers, for 3x buyers, and for 4x buyers. I can turn the analysis around in a few days, max. Email me (kevinh@minethatdata.com) for file format and additional details.

First-Time Buyers

Show of hands ... how many of you measure how likely a first-time buyer is to purchase for a second time, by month? How many of you produce a graph that looks like this?

You take all first time buyers. If the buyer purchases for a second time in the month the customer was acquired, you tabulate the response rate for that month (month = 0). Then take all customers who have yet to repurchase, and measure the response rate for that month (month = 1). Pull out all purchasers, repeat for month = 2. And so forth.

This is the most important analysis you can do. You learn how first-time buyer behave. You're not going to like what you learn. Tomorrow, I'll discuss how one Chief Marketing Officer interpreted this information.

Discounting Behavior

Earlier this year my annual subscription to The Athletic automatically updated for the modest fee of $49.

Of course, The Athletic proudly promoted a discount over the Thanksgiving Weekend ... for new subscribers, it's $1 a month for 12 months (click here).

Somewhere the CRM gurus are clinking their wine glasses ... happily counting up all the new subscribers. "DISCOUNTS WORK!!" they yell, proudly telling their followers how brilliant their tactics are.

How do you feel about buying a product as a loyal customer, only to see customers who have never purchased from the company get to pay about 75% less for the product you are required to pay full price for? Discuss.

The Rancho Gordo Bean Club

You probably saw the story on CBS Sunday Morning (click here).

11,000 Club Members.

11,000 on the Waiting List.

The secret over the past two years seems to be an exclusive subscriber list that you treat better than your average customer / prospect.

Makes me think about my own business ... hmmmmmmm ... what ideas do you have for your business (or mine)??!!

Does The COVID-Bump Help You In 2022?

If you are a restaurant in Los Angeles, you don't get a COVID-Bump. You get to be closed, with no assistance from anybody. Good luck!!

But if you are a direct-to-consumer e-commerce brand not selling apparel, you might still be benefiting from a massive COVID-Bump, fueled mostly by new customers. You are stunned by what has happened in 2020. What will likely be 400,000 deaths and millions of hospitalizations netted you +50% or +100% sales gains. As I was told earlier this fall ... "I'm torn between feeling awful for society and feeling blessed because my company is performing well and I have a job."

What is the question I'm asked to analyze most often this Fall?

• "What does the COVID-Bump mean for my business in 2022?"

The answer is a simple one. If your Annual Repurchase Rate is under 40%, the benefit of the COVID-Bump evaporates quickly, giving you a small sales increase in 2022 and nothing thereafter.

If your Annual Repurchase Rate is greater than 50%, well, it's a whole different world. You get to enjoy the magic of Compound Interest for several years. God smiled upon your business model.

For any business, however, 2021 is a "setup year". It's like in baseball when you have a 4-2 lead in the 8th inning. You bring in your setup relief pitcher. It is his job to bridge the gap between the 7th inning and the 9th inning, when you bring your closer in to finish off the game. If you want 2022 to be as successful as possible, you need to set up 2021 to be as successful as possible.

• Until there is a vaccine, keep your foot on the Customer Acquisition gas pedal.
• Welcome Program ... Welcome Program ... Welcome Program. Convert customers to a second purchase IMMEDIATELY. This is non-negotiable, and if your Marketing Leader tells you that you do not need a Welcome Program, go find another resource to do this for you.
• Keep the customer clicking via email marketing.
• If you have print, separate out those who need print to purchase from everybody else, and only spend money/resources on customers who need print to purchase.

Use 2021 as your "bridge year" ... so that you are as ready for a "New Future" in 2022 as you can be. Customer behavior is likely to fundamentally change and not go back to where it was. Why not influence customer behavior as much as possible in 2021 so that you play an active role in creating the future you need to create?

Tony Hsieh

Certainly you've heard the news by now ... maybe not from the trade industry, but if you are on Twitter the outpouring of support was unavoidable for the founder of Zappos (click here).

Mr. Hsieh was an early reader of this blog. When you are getting started in this business, it's helpful to have a somebody read what a nobody has to say.

Mr. Hsieh was one of four people (Don Libey, Ben Chestnut of MailChimp, Robert Kestnbaum are the other three) who thought differently in a way that shaped how I viewed things. Three of the four are gone now. Make sure you appreciate those you think highly of. Say something to them while they are still here.

Do you have examples of individuals in our industry that have shaped how you view the world? Share those individuals with our audience ... pass me a note and I'll publish credible responses.

P.S.:  If you are a cataloger, read up on the stuff that Robert/Kate Kestnbaum wrote about in the 1990s. They used math 25-30 years ago that was smarter than the math you are using today. Hint - their math forms the basis of the catalog optimization work I perform today.

P.P.S.:  If you love email marketing, read what Ben Chestnut has to say. Also notice that he didn't choose to dominate email marketing ... he helped small businesses be excellent at email marketing, and that difficult choice made all the difference.

P.P.P.S:  Don Libey taught me how to run a consulting business as an independent consultant. He gave away his knowledge, for free. He's largely the reason that the work I perform is mostly shared ... for free ... via this blog.

New Buyers From Here On Out

Most of my project work shows two important facts (yes, there are exceptions):

1. It is easy to acquire customers from Thanksgiving through Christmas.
2. Customers acquired between Thanksgiving and Christmas have the worst long-term value.

This is such a challenging balancing act. In general, we don't have the tools to convert the Christmas buyer into a Jan/Feb/Mar/Apr buyer. Heck, the customer doesn't want to be converted.

Most digital marketing analytics packages don't tell you that the Christmas newbie doesn't want to buy again ... software is designed to tell you who converts, not who will convert again.

Tag all of the first-time buyers you acquire over the next five weeks, and watch them going forward. You're going to see the problem in Spring. Then you'll want to develop a credible Welcome Program to solve the problem for Spring 2022.

 

Virgil Carter

It's a lot easier in Sports to see how strategy evolves over time than it is to see how strategy evolves in Business. Sports is measured in terms of wins, losses, and Championships. As a consequence, good strategies tend to be moved into the future, where they are evolved. In business, some of the best strategies I've seen are buried in small businesses that never evolve or change, and as a consequence those strategies never see the light of day.

This brings me to the story of Virgil Carter. Virgil was a Statistics Major at BYU, and he was a good college Quarterback. In the NFL, Mr. Carter had a weak arm, so the Cincinnati Bengals had to develop an offense that would suit what he did well (he released the ball quickly and was an accurate thrower). Who was his offensive coordinator? Well, it was none other than Bill Walsh, who won multiple Super Bowls with the San Francisco 49ers in the 1980s. Bill Walsh developed what became known as the "West Coast Offense" to suit Mr. Carter's skills, then evolved the offense to a comprehensive "system" for running a football organization. Heck, Mr. Walsh wrote a book with a limited number of copies on how to run a football organization. I bought one of the copies on eBay for $$$ ... if you carefully look at the bookshelf of any NFL coach, you might just see one of the copies.

Back to Virgil Carter.

Remember when I told you that Mr. Carter was a statistician? Well, it turns out that Mr. Carter also contributed to the future of football by analyzing the outcome of plays (click here). He learned how many expected points you would generate if you took over possession of the ball at your own 33 yard line, for instance.

So Virgil Carter played two key roles in the evolution of football.

1. His limitations (weak arm) led to the development of the West Coast offense and short-passing game, which took advantage of his strengths (accuracy, smarts). This offense eventually branched into two different directions ... one developed by Andy Reid for his MVP quarterback (Patrick Mahomes) ... and one that was evolved by Mike Shanahan (for John Elway) that was further evolved into the offenses currently run by the San Francisco 49ers, Los Angeles Rams, and Green Bay Packers (among others).
2. His college major (statistics) led him to develop his own version of "expected points" ... which ultimately became "advanced analytics" that are employed all across football today. You'll see "expected points" used repeatedly as teams now routinely go for it on, say, 4th and goal at the one yard line (expected points = 3.5 with a 50% chance of scoring a touchdown and a 50% chance of failing, greater than the 3.0 points you'll get for kicking an easy field goal). 

By next September - November, a vaccine will be prevalent enough to help us return to a "new normal".

And when that happens, the next "Virgil Carter" will have spent the prior year developing a methodology for how to adapt a business in a post-COVID world. That person will have an enormous head start over everybody else ... a huge competitive advantage that will be difficult to overcome.

Why can't that person be you?

Opting Out

Last week was fun ... I wrote about risk ... and close to 1% of subscribers opted-out, citing that "CONTENT IS NO LONGER RELEVANT".

I've always judged that when many people unsubscribe because CONTENT IS NO LONGER RELEVANT that I am headed down the right path. I lost a ton of subscribers back in 2013 when I started talking about the importance of merchandise performance ... then I generated more annual revenue over the next three years than during any other three year period ... because you (the loyal reader) hired me to analyze merchandise performance.

I've learned a lot about the audience over the past fourteen years. A key finding is that the audience tends to want very specific answers to very specific questions. If I write about general topics that relate to general questions, the audience rebels.

In recent years, a fraction of the audience has become more combative. These individuals want very specific answers to very specific questions ... and more important, they want to ARGUE about specific answers. The arguing is the end result that "some" readers seem to embrace ... sort of like in politics. The reader can "appear" smart by arguing a small fact in a large argument, without ever having to apply any smarts to a challenging business situation.

I had one subscriber who was with me for several years. This person held a C-Level position with a company that was headed toward bankruptcy. This person always argued ... he wasn't mean (he was very kind to be honest, I assume a very good person), but he was always nitpicking 5% of an argument in an effort to invalidate 100% of an argument. He was quite good at this. I can't imagine how frustrating it would have been to work for this individual. Worse, he had answers to every specific argument you could imagine ("here are four reasons why Amazon will not take over e-commerce") but didn't have a single argument for solving the problem at hand ... that being, of course, the fact that his own company was headed into bankruptcy. 

His company went bankrupt.

You didn't opt out last week ... I know that because you are still reading today's post. That means you are at least somewhat open-minded to different concepts. Frequently I develop ideas as a stream-of-thought over several days/weeks, and those ideas infrequently become products that eventually help your business. That's how I use this blog. I use it to develop concepts. I'm not trying to provide a specific answer to a specific question. I'm trying to hover a level or two above specific answers to specific questions. If I do that successfully, your business performance can improve.

P.S.: Speaking of highly specific answers, here is an example of what I am talking about, one that everybody can form an opinion of (click here). This is what so many readers want ... a highly specific solution that everybody can "weigh in on".

Profit and Risk

I promised you I'd share how variable profit is under normal circumstances.

10% of the time profit will be below $2.0 million.

25% of the time profit will be below $2.3 million.

50% of the time profit will be around $2.8 million.

25% of the time profit will be above $3.2 million.

10% of the time profit will be above $3.6 million.

Our CFO ... she's not going to be pleased with profit numbers that could vary between $2.0 million and $3.6 million.

But this is what we're dealing with when we craft a plan. We do all of this work, hard work, to produce a certain outcome. But the outcome is not certain. The outcome is highly variable. I mean, half the time profit could be between $2.3 million and $3.2 million. And the other half of the time? It's an outcome more variable than that.

And that's under normal circumstances.

Every one of you is dealing with a business that has that kind of variability. Your estimates for what "will" happen next year are filled with risk, filled with variability.

Then you layer COVID on top of it.

It's going to be darn important to communicate risk to people. Unbelievers. Folks who think because a spreadsheet says you will generate $62,000,000 means you are promising to deliver $62,000,000. In a normal year you could not make that promise, though you've done so for a long time. In 2021? You are facing more risk than you've faced since 2020.

A flexible and adjustable plan, one where you clearly communicate a range of possible outcomes ... that's what is needed in 2021.

Putting Together the Puzzle

Yesterday I shared a high level sales plan, one where we figured out that our business would generate $28.2 million in sales and $2.6 million in profit.

Is the plan something we can take to the bank?

Well, you have the "bottom's up" crowd that estimates a business plan based on individual segment performance in marketing campaigns. It's a lot of work, and it isn't any more accurate than doing the simple calculation I performed yesterday. I know this because I spent a decade building plans at Eddie Bauer & Nordstrom and have the scars to prove my point.

The plan, of course, is subject to a lot of variability.

For instance, over the past five years, annual rebuy rates have varied as follows for this brand:

• 36%.
• 34%.
• 38%.
• 35%.
• 37%.

In Excel, it's easy to calculate the mean & standard deviation:

• Mean = 36%.
• Standard Deviation = 0.016.

If results are normally distributed (and they usually are), this tells us something about the variability around rebuy rates.

That's the outcome of 10,000 simulations of rebuy rate, given how rebuy rates have varied over the past five years.

We perform the same exercise for other key metrics ... rebuy rate, spend per repurchaser, new + reactivated buyers, spend per new/reactivated buyer.

For each of 10,000 simulated outcomes, we calculate projected net sales, and we calculate projected profit. Here is the histogram for projected net sales.

Oh oh.

Based on a normal range of results from prior years, we observe quite a range of possible outcomes, don't we?

• 10% of the time, net sales will be under $26.5 million.
• 25% of the time, net sales will be under $27.4 million.
• 50% of the time, net sales will be +/- $28.5 million.
• 25% of the time, net sales will be above $29.6 million.
• 10% of the time, net sales will be above $30.6 million.

Honestly, in our business, that's not a lot of variability.

But for your CFO, that is WAY TOO MUCH VARIABILITY.

Now imagine having to layer in the impact of COVID on top of those numbers.

Tomorrow I'll share with you what profit looks like for our business.

Is My Plan Risky?

You start with a high-level plan for the upcoming year, based on actual data from the year prior. This is a common-sense approach to planning, one that so darn many companies use.

12 Month Buyers:

• 200,000 buyers, 36% repurchase rate, $160 spend per repurchaser.
• 200,000 * 0.36 * 160 = $11,520,000 sales next year.

New + Reactivated Buyers:

• 130,000 New/Reactivated buyers, $128 spend per purchaser.
• 130,000 * 128 = $16,640,000 sales next year.

Total Volume:

• $11,520,000 + $16,640,000 = $28,160,000 sales next year.

Other Metrics:

• 40% of sales flow-through to profit.
• Expected Ad Cost expenditure = $5,632,000.
• Expected Fixed Costs = $3,000,000.

Expected Earnings Before Taxes Next Year:

• $28,160,000 * 0.40 - $5,632,000 - $3,000,000 = $2,632,000.
• 2,632,000 / 28,160,000 = 9.3% of Net Sales.

Is your plan "risky"?

In other words, you are signing up for $2,632,000 profit on net sales of $28,160,000. How likely is it that your "promise" will happen? Could you end up with a lot more in sales? A lot less? And how would that impact profit?

Tomorrow I'll show you how variable forecast "could" be.

Communicating Risk

Remember yesterday, when I shared that something you pencil out in a spreadsheet as a "good decision" is actually a decision that has risk? In my example, what appeared to be a profitable decision actually had a 23% chance of being unprofitable.

Here's the biggest reason people don't evaluate risk. It is "risky" to communicate risk.

I worked for a person who took a few stat classes in college and therefore thought he was a brilliant statistician. When I communicated risk to him, he got uncomfortable, then he got angry, then he misinterpreted what he learned in his three stat courses, then he said things that were completely wrong but said them as if he were right so anybody in his orbit took his side, causing everybody in the room to be wrong.

What did he misunderstand about risk?

He believed that the "average" outcome was a "certain" outcome.

And if actual results came in "below average", well, that was your fault.

And if actual results came in "above average", well, that was because the merchant was brilliant.

I learned to NEVER communicate a probability to this person, because this person was incapable of understanding probabilities. He'd have been a terrible Texas Hold 'em player and a really sore loser if he had to deal with a "bad beat" on the river.

Instead, I sandbagged everything.

I never submitted a business plan assuming an "average" outcome. I'd calculate the probability of a less-than-optimal outcomes, then submit a less-than-optimal outcome. Business would then "hopefully" perform at an average level, in which case my plan would be exceeded, and everybody would be happy ... including my boss who didn't (couldn't) understand probability and risk.

It's awfully hard to properly communicate risk to individuals who struggle with assessing risk. Come up with a strategy that mitigates the downside while promoting an upside that makes people happy.

Decisions and Risk

You have a paid search program, and you expect the program to deliver the following metrics this month:

• Conversion Rate of 1.5%.
• Average Order Value of $90.
• Average Cost per Click = $0.50.
• Profit Flow-Through = 40%.
• Expected Profit = 0.015 * 90 * 0.40 - $0.50 = $0.04.

You tell your agency that all efforts need to break-even. The data suggests that given the metrics, you should make a few pennies per click, on average.

But how much "risk" is there in that situation?

Here's the result of a 10,000 simulated runs, runs where I apply variability surrounding the conversion rate.

On average, you are generating $0.04 of profit per click ... but the amount of profit could vary between a loss of $0.10 and a profit of $0.17 in most cases. In fact, you'll lose money 23% of the time. In other words, even though your plan suggests that you should make money, 23% of the time you will not make money.

If you were told that your decisions needed to be profitable, would you make a decision that will lose money 23% of the time?

Almost every reader out here fails to perform this style of analysis.

But every reader out here SHOULD perform this style of analysis. All decisions have some sort of risk tied to 'em. At minimum, you need to understand how much risk surrounds your decision.

Testing Budget

Earlier in the week, I mentioned that I used to negotiate with the CEO of the Online Division at Nordstrom for my testing budget.

In other words, we had a discussion each year, and we pre-agreed upon the sales/profit impact of my tests.

I recall in 2003 that the budget was set at 3% of sales. For a $350,000,000 division, this was roughly $10,000,000 in sales and $3,000,000 profit. The CEO was willing to lose $3,000,000 profit because what was learned in executing the tests was worth $3,000,000 profit.

If you do your job as a Virtual Chief Performance Officer properly, you'll generate enough downstream profit to more than make up what you lose executing the tests.

Do you have a testing budget?

Odds are 90% of you don't have a testing budget, and that says something about your historical ability to prove that what you learn from testing has long-term value.

For instance, the testing budget at Nordstrom was what we used to determine that catalogs (via holdout tests) generated no incremental profit to the company ... which allowed us to allocate $36,000,000 of ad-cost to other activities ... half to paid search ... which generated a profit ... which caused our online sales to increase when we pulled all that paper out of the ecosystem. The testing budget (where we were willing to lose $3,000,000 profit per year to learn) allowed us to learn enough to make tens of millions of dollars of profit.

That's what you can accomplish as a Virtual Chief Performance Officer ... implementing a simple testing budget and a credible testing plan and a communication plan for the results of your tests.

-188 + 192*x

It was 1991 at Lands' End. We were greatly ramping-up our testing work. And when we wanted to execute a test, we needed to understand how the results might "vary".

Back then, a test was sampled from the population who would receive a catalog. Maybe that audience was 4,000,000 customers. If the catalog was a productive catalog, it might generate $10.00 per catalog mailed. If the catalog wasn't productive, circulation would be reduced and the catalog might generate $4.00 per catalog mailed.

If you want to measure a 10% difference in sales for two groups performing around $4.00 per book, you need fewer customers than if you are trying to measure at 10% difference in sales for two groups performing around $10.00 per book. This is an issue called "heteroscedasticity".

So I built an equation that measured variability around different dollar-per-book estimates. The equation was a simple one:

• -188 + 192*(Expected Dollar per Book).

If we expected one group to generate $4.00 per book and the control group to generate $3.60 per book, we'd calculate the variability at point estimate:

• $4.00 = -188 + $192*4.00 = 580.
• $3.60 = -188 + $192*3.60 = 503.

Then we'd enter the data into our statistical equation.

• (4.00 - 3.60) / SQRT(580/25000 + 503/25000).
• T = 1.92.

As long as T > 2.00, we would execute the test with the sample size promoted by the equation.

In this case, the sample size was too small, so we had to increase it.

• (4.00 - 3.60) / SQRT(580/30000 + 503/30000).
• T = 2.11.

You probably already have a calculator that you enjoy using. If not, contact me and we'll get something set up for you for your data at minimal cost (kevinh@minethatdata.com).

But I Cannot Afford THAT Many Customers

This is the part of the discussion where the Virtual Chief Performance Officer hears the grumbles, from near and far.

• "We cannot afford to test THAT many customers!"

You can't afford NOT to test THAT many customers.

When I worked at Nordstrom, the Online CEO and I had to negotiate the size of the "testing budget". I needed a lot of customers, he needed a lot of sales, and he needed to learn things. So compromises had to be met.

I'd pull out a graph that looked something like this (don't worry about the y-axis at this time ... worry about where it is high vs. where it is low).

If we only sampled 10% of the audience, we had a lot of sampling error ... and that meant we'd never be certain we had the "right" answer.

If we sampled 40% of the audience, we had minimal sampling error ... and that meant we'd likely have the right answer but would give up a lot of sales to learn the right answer.

So we'd agree that "x" percent of the population was appropriate for how much we wanted to learn vs. the amount of sales/profit we were willing to pay to learn the information.

That's what we're talking about:

• How much profit are you willing to pay in order to learn something about your business?

For too many of you, the answer is $0. You're not willing to pay anything to learn.

And as a result, you don't learn anything.

It costs money to learn something. You already know this, you attended college, right? So as a 20 year old, you were willing to pay something to learn. But as a seasoned 40 year old Professional, you're not willing to pay anything to learn. Hmmmmmm.

Be willing to pay something to learn something.

Lots of Variability

Yesterday I showed you what happens when you sample 25% of customers from a full population with a known outcome ($14.42 per customer, average) ... you end up with noise.

That's what happens when you aren't dealing with the entire population.

What happens when you deal with an even smaller fraction of the original population? Look at the x-axis and compare the values in the histogram to the image above.

Oh oh.

Notice that the overall average is "similar" ($14.32 sampling 5% of customers vs. $14.39 sampling 25% of customers vs. sampling 100% of customers and getting $14.42).

But the spread is huge!

Huge!

Some of the outcomes are around $13.75 ... and you CANNOT know if that outcome is the real outcome or a blip due to sampling variability. One of the outcomes was > $15.50 and you cannot know if that outcome is the real outcome or a blip due to sampling variability.

Look at the standard deviation metric ... 0.412 ... so much higher than the 0.113 we saw when sampling 25% of the original population. It means that your results will vary by +/- $0.82 instead of +/- $0.23.

The Virtual Chief Performance Officer has a job ... and that job is to STEER YOU AWAY from situations where you are measuring something with +/- $0.82 of variability ... steering you toward outcomes that are within +/- $0.23 of expectations.

Here's the problem we all face. We're told we're supposed to TEST outcomes, aren't we? You are supposed to be "data-driven".

But if you are "data-driven" and you make one little mistake ... testing without enough cases to test properly, well, you provide your company with GARBAGE, don't you?

This sin happens repeatedly in business. Smart data-centric folks making bad choices, not understanding variability, creating chaos in a company and then defending the chaos.

The Virtual Chief Performance Officer steps the company away from these situations. We'll talk more about these situations tomorrow.