Marketers Impact Gross Margin Dollars

Sometimes you just look at the marketing folks and ask yourself, "why"?

Obviously there are valid reasons why marketers like to discount.

But when the discounting is applied in a targeted manner, well, what is going on?

Here's an example from our Category Analysis Tables. Let's look at our dominant category, category 09. Here are gross margin percentages by customer audience.

• 59% for Prior Category Buyers.
• 60% for Prior Buyers, No Category Experience.
• 60% for New/Reactivated Buyers.

Everything looks reasonable there.

Here's what the results look like for Category 19:

• 38% for Prior Category Buyers.
• 44% for Prior Buyers, No Category Experience.
• 46% for New/Reactivated Buyers.

First of all, margins for Category 19 are significantly worse than they are for Category 09. For every $100 you sell in Category 19 you make $17 less profit than you make in Category 09. Not a brilliant way to operate a category (and yes, I get it, there are many reasons why this happens).

But look at Prior Category Buyers.

In Category 09 margins are equal across segments.

In Category 19 margins are between six points and eight points worse for Prior Category Buyers.

In other words, the brand is discounting to prior category buyers. 

It's bad enough this company gives up $17 of gross margin within this category for every $100 spent ... but among Prior Category Buyers this brand goes the extra step to give up another $6 ... giving up $23 for every $100 spent.

It's not like these customers are loyal to this category ... in our Category Analysis Table the customers have a 15% chance of buying from the category again in the next year. That's low. So in the unlikely event that the customer does decide to buy again, you give up $6 of additional profit per $100 spent just to obtain the 15% chance of buying again.

This brand mismanages this category. Somewhere a marketer thinks s/he is doing the right thing by increasing "engagement" but by increasing "engagement" the marketer gives up "profit".

Three Types of Merchandise Categories

There are more, obviously, but we can simplify the story down to three, using our Category Analysis Table.

The first type of category is the dominant category. Customers shop this category as if it "is" the brand. I like to look at rebuy rates within the category vs. across all other categories. Here's an example of three categories and their metrics.

• Category 09:  Within Category Rebuy Rate = 47%. Other Category Rebuy Rate = 55%.
• Category 08:  Within Category Rebuy Rate = 23%. Other Category Rebuy Rate = 68%.
• Category 19:  Within Category Rebuy Rate = 15%. Other Category Rebuy Rate = 64%.

Next, I look at the share of annual sales spent by category purchasers.

• Category 09:  Share = 34% Within Category 09 Next Year.
• Category 08:  Share = 12% Within Category 08 Next Year.
• Category 19:  Share =   5% Within Category 19 Next Year.

Finally, I look at share of annual sales that come from last year's category buyers.

• Category 09:  $32.6 million of $50.0 million from last year's buyers.
• Category 08:  $3.2 million of $10.7 million from last year's buyers.
• Category 19:  $0.8 million of $3.0 million from last year's buyers.

Category 09 is a "dominant" category. Customers are coming to buy from this category, and they'll buy from the category again next year.

Category 08 is a "complimentary" category. Customers have reduced loyalty within the category and spend money outside of the category.

Category 19 is an "auxiliary" category. It is there to provide support for the entire brand, but is not the focus of the customer.

Dominant.

Complimentary.

Auxiliary.

Three types of merchandise categories.

Surely you are measuring how each category you manage impacts the customer, knowing what role the category plays in your assortment, correct?

Who Is Buying?

Here's our table.

Let's look at repurchase rates. At the top of the table we have rebuy rates within the category for customers who bought from the category in the past year.

• 47% This Year.
• 48% Last Year.
• 47% 2 Years Ago.
• 46% 3 Years Ago.

This is good news. Customers who bought from this category last year have nearly a 50% chance of buying from the category again next year.

How about all of the remaining 12 month buyers - those customers who haven't bought from the category in the past year but bought other merchandise?

• 10% This Year.
• 11% Last Year.
• 11% 2 Years Ago.
• 11% 3 Years Ago.

In other words, if you bought from the category last year you are 4 times a likely to buy again next year as are customers who haven't bought from the category in the past year but purchased in the past year.

At the bottom of the table we can see where all of the customers who bought from the category came from.

• 156,363 came from category buyers from last year.
• 63,899 came from non-category buyers who purchased in the past year.
• 97,242 came from new/reactivated buyers.
• 317,504 buyers in total.

We can also see where demand/sales came from.

• $32.6 million came from category buyers from last year.
• $7.4 million came from non-category buyers who purchased in the past year.
• $10.5 million came from new/reactivated buyers.
• $50.5 million in total.

We'll explore more aspects of this table tomorrow. And in a few days I'll show you a category that is struggling, and fully dependent upon the rest of the business for existence.

Category Buyer Analysis

One of the most enjoyable tables I run in a Hillstrom's Profit analysis is the Category Buyer Analysis table. Here it is:

Yeah, I know, that's a table with a lot of numbers ... and that'll cause some in the audience to tune out. The rest of you earn a competitive advantage over that audience. Congrats!

Tomorrow we'll begin to dissect the information. There's a lot here and it means a lot when determining why a category is performing well or performing poorly.

AOV and AMV

Most of you measure Average Order Value ... AOV as it is often known. Your e-commerce business utterly depends upon the measurement of this metric.

How many of you track "Average Margin Value", or "AMV"?

Instead of summing up the amount the customer spent (three items ... $30, $30, $40 = $100), you sum up the amount of gross margin generated by the customer in that order ($18, $12, $22 = $52).

Too often, we provide 40% off with a hurdle, then celebrate a big order of $120. Let's pretend that your gross margin is 50%.

• No offer = $100 AOV.
• Yes offer = $120 AOV.

AOV increased with the offer.

How about AMV?

• No offer = $100 - $50 = $50.
• Yes offer = ($120 - $60) - ($120*0.4) = $60 - $48 = $12.

Do you prefer a $50 AMV, or a $12 AMV?

It's pretty obvious that you should be measuring AMV, correct?

Tell me what stops you from measuring it?

P.S.: In a Twitter poll, 36% of respondents measured AMV, while 9% responded that the metric is "useless". It's fun to have a competitive advantage, isn't it?

Then The Email Marketer Sub-Optimizes Profit While Optimizing Engagement

Allow me to share gross margin percentages by marketing channel for this brand. Tell me if you see something interesting:

• 47% = Call Center.
• 48% = Online Orders.
• 48% = Affiliate Marketing.
• 44% = Email Marketing.
• 51% = Search.

This company has a $120 average order value in search, and a $125 average order value via email marketing. How about profit?

• 0.51*$120 = $61.20 of gross margin.
• 0.44*$128 = $56.32 of gross margin.

The marketer is generating $5 more gross margin via search than via email marketing.

This marketer, of course, offers discounts to encourage the customer to buy via email marketing.

This marketer, of course, celebrates the fact that AOVs are $8 higher than in other channels.

This marketer, of course, is sub-optimizing profit.

I know, I know, here come the trolls arguing that the discounts lead to greater response levels and increased engagement and those gains offset the $5.00 given up in the process.

Ok - prove that your thesis is true. A/B test the discounts, and tell me if your thesis holds.

Until then, measure gross margin percentages by channel - are you, as a marketer, sub-optimizing profit in an effort to optimize engagement and average order values?

Gross Margin by Category: Feature Stuff That Generates $$

Take a look at this set of information. Here are gross margin percentages by Category for a brand.

• 43% = Category 0
• 52% = Category 1
• 47% = Category 2
• 47% = Category 3
• 37% = Category 4
• 00% = Category 5 (this is a gift card category)
• 52% = Category 6
• 50% = Category 7
• 55% = Category 8
• 43% = Category 9
• 53% = Category 10
• 52% = Category 11
• 59% = Category 12
• 52% = Category 13
• 55% = Category 14
• 63% = Category 15
• 58% = Category 16
• 42% = Category 17
• 53% = Category 18
• 60% = Category 19
• 51% = Category 20
• 58% = Category 21

Categories 12/19 are the primary categories that customers love within this brand. Notice that these categories have hefty gross margins. Good!

As a marketer, you should ask questions about categories 2/3/9/17. Specifically, why should these categories be featured in a marketing campaign or email marketing campaign? Why are you asking the customer to spend more to generate comparable profit?

Example: Customer could purchase from Category 14 at a 55% gross margin, or the customer could purchase from Category 17 at a 42% gross margin. If the average price of an item is $70, the customer generates $38.50 gross margin dollars at 55% but just $29.40 at 42%. Selling the Category 17 item sub-optimizes profit by $9.10. Said differently, you have to sell the Category 17 item at $91.70 to generate the same amount of profit as selling the Category 17 item at $70.00.

Now I get it - there are a thousand reasons why Category 17 is critical to your assortment.

But as a marketer you need to ask tough questions. You control what is featured in marketing campaigns. Why ask the customer to spend $91.70 when you could ask the customer to spend $70.00?

• 
  

Past Gross Margins Predict Future Gross Margins

Here's an issue I recently analyzed ... let's say an item costs $50 and the cost of goods sold are $30, netting the brand a $20 gross margin on the item.

Second issue ... the item costs $50 and the cost of goods sold are $30, but the brand sells the item for $40, leaving only $10 gross margin on the item.

Why do we care about the two issues above?

Well, past gross margins predict future gross margins. In other words, I created a regression equation for a brand where I had two independent variables (gross margin dollars, cost of goods dollars) and one dependent variable (future gross margin dollars). Here's what the equation said:

• Future Gross Margin Dollars = $12 + $0.55*(Past Gross Margin Dollars) + $0.06*(Past Cost of Goods Sold Dollars).

Ok, that's a lot of geeky stuff there.

Now let's see how the equations forecast future behavior.

In the first "issue", here's how the equation plays out:

• $12 + $0.55*($20) + $0.06*($30) = $24.80.

In the second "issue" where discounting was present, here's how the equation play out:

• $12 + $0.55*($10) + $0.06*($30) = $19.30.

Do you understand what just happened there?

The model suggested that if a client discounted to a customer, the customer would generate $5.50 fewer gross margin dollars (and consequently, less profit as well) in the next year.

Of course, this should raise all sorts of questions ... cause and effect questions. Y'all will debate these for a long time, many will argue on the basis of an opinion.

Regardless of the questions, the equation suggests that past gross margin dollars predict future gross margin dollars. Do things to erode profit today, and you have less profit tomorrow.

Think about this topic, ok?

Margin and Price

Always look out for the way you treat low priced items. Example:

• Lowest Price Points = 41% Gross Margin.
• Low Price Points = 54% Gross Margin.
• Average Price Points = 58% Gross Margin.
• High Price Points = 57% Gross Margin.
• Highest Price Points = 53% Gross Margin.

A former VP of mine said "Units = Customers". Often, you'll have a lot of customers buying from low price points ... meaning you're making less profit on lower dollars, meaning, well, that's not very good, now is it?

Car Thing

Ok, three things (click here).

1) If they can name a product "Car Thing", you can be creative,

2) It sounds like Spotify disabled interfaces on some car stereos (i.e. Spotify Connect), making this product more amenable ... in essence, they killed a free function and are charging for what used to be free.

3) If they can create a product that acts as an interface between your car and phone when your phone already interfaces with your car and charge $89 for it, you can be creative as well.

Oh Boy

Here's some data I analyzed recently ... tell me what you observe when it comes to gross margin percentage:

• Grade "A" Customers = 44.3%.
• Grade "B" Customers = 46.9%.
• Grade "C" Customers = 48.4%.
• Grade "D" Customers = 49.7%.
• Grade "F" Customers = 50.9%.
• New Buyers = 53.7%.

Customer quality goes from "A" (best) to "F" (worst).

What do you observe?

Yeah, somebody in the marketing department decided to feature low-margin items or discounted the heck out of items to better/best customers to "tickle the customer's buying bone". 

Oh boy.

I know, I know ... here it comes.

• "But Kevin, if we discount then we get more orders and we get more gross margin dollars and the total sum of gross margin dollars is higher than if we don't discount then our marketing efforts were successful."

Sure.

If that statement is true.

Almost none of you ever do the work to determine if the statement is true. You just issue the statement assuming it is true.

Do the work.

Prove that your thesis is correct.

Gross Margin

Profit is highly dependent upon the gross margin of the products we sell.

You already know that, of course.

But do you ever actually analyze the situation?

Here are the top 500 selling items for a brand. What does the regression line tell you?

On the X-Axis we observe annual sales ... the best sellers have an average gross margin percentage under 45% ... while other good-selling items have gross margin percentages that average over fifty percent.

Now I get it ... you're going to tell me all the reasons why certain items have to be priced at a certain level, compromising gross margin percentages. I get it. 

But the marketers in the audience, given two equal items, should promote the item that has a better gross margin percentage, correct?

Product Preference vs. Gross Margin Dollars

I shared a business that has 22 merchandise categories. I created a regression model to measure whether customers buying from each merchandise category have higher/lower future value.

High Value Categories:  5, 7, 9, 12, 18, 19.

Positive Categories:  0, 2, 3, 4, 8, 10, 11, 13, 15, 16, 17, 20.

No Value or Negative Value: 1, 6, 14, 21.

First of all, if you had to tell your merchants that four categories out of 22 delivered no increase in future value, you'd be run out of your meeting quickly, don't you think?

But second of all, you should also look at future gross margin dollars ... not future sales. Future gross margin dollars.

High Value Categories: 12, 19 (remember, these two categories are loved by all customers).

Positive Categories:  7, 8, 11,18, 20.

No Value or Negative Value: 0, 1, 2, 4, 6, 9, 10, 13, 14, 15, 16, 21.

Oh oh.

12 of the 22 categories do not deliver future positive gross margin dollars, based on a regression analysis.

As a marketer, you have a responsibility to share categories (particularly on your home page and in your email marketing campaigns) that deliver customers likely to generate positive gross margin dollars in the future. That's you job. If you aren't performing this style of analysis, you are hurting future profit ... that's on you, not your merchandising team.

Speaking of Product Preference: An Example

Your customers tell you specifically what their future preferences are.

The table below has one row for each merchandise category a customer purchased from last year. Each column represents the percentage of next year's sales that are generated by category.

Take a look. Click on the image - it is small and contains a lot of data.

How about an example? Look at customers who bought from Category 1 last year.

• 14.3% from Category 1 next year.
• 10.6% from Category 12 next year.
• 14.7% from Category 19 next year.

Ok, how about Category 7?

• 16.8% from Category 7 next year.
• 13.3% from Category 12 next year.
• 17.6% from Category 19 next year.

One more ... how about Category 15?

• 21.5% from Category 15 next year.
• 10.0% from Category 12 next year.
• 13.2% from Category 19 next year.

The pattern repeats throughout the table. Customers buy from the category the bought from last year, and they buy from Categories 12/19 next year. Even then, about 55% - 60% of future sales are from other categories.

This is an interesting case study.

Categories 12/19 represent the "sun" in the solar system of this brand. Everything revolves around those categories. You have a reasonable chance of selling those categories to "any" customer.

Every other category (see the red diagonal in the image) yields customers who come back to that category.

Customers are also willing to "sample" other categories.

Your marketing strategy is simple.

• Mass market Categories 12/19. 
• Personalize email campaigns for the category the customer bought from last year.
• Sprinkle in other categories on an as-needed basis ... adding freshness to your marketing efforts.

• 
  

Product Preference / Profit: New Merchandise

Here's a trend I'm seeing now.

In 2021 it was hard to source new merchandise (for some). This means that there were fewer new items sold in 2021, and less sales from new items in 2021.

Now it is 2022. Those new items have become existing items. Guess what? Those items are delivering reduced sales in 2022.

Example: Your brand might expect to offer 100 new items in 2021 and generate $10,000 per new item. 100 * $10,000 = $1,000,000. The following year those items generate 120% of the sales of the year prior. Therefore, 2022 should show $1,000,000 * 1.2 = $1,200,000.

• However: In 2021 only 80 new items were sourced, generating $8,000 per new item. 80 * $8,000 = $640,000. In 2022, those items should generate 120% of 2021 levels. $640,000 * 1.2 = $768,000.

Yup, you lose $1,200,000 - $768,000 = $432,000 in sales in 2022 because of new merchandise issues in 2021. If your "Profit Factor" is 40%, well, you just gave up $432,000 * 0.40 = $172,800 profit in 2022.

Trouble, folks.

In 2021, we had gains caused by the compound interest generated by all those COVID-buyers in 2020.

In 2022, some of us will lose money caused by having too few new items in 2021. I'm seeing the problem all over the place, now.

Analyze your data carefully. If you don't have the tools to do that, contact me for a "Hillstrom's Profit" project (click here).

Brand Stages

You have the merchandise - that's the most important stage. If you get your merchandise right, everything else is much easier.

You have brand presentation - this is a lost art. Think of what Progressive does with their TV commercials. Then think of a 20 second Discovery+ video ad on hoseheads.com. That's the opposite.

You have marketing channels ... the lowest common denominator of marketing.

Merchandise > Brand Presentation > Marketing Channels.

If you fix your merchandise assortment, your brand presentation works better and your marketing channels work better. You stack benefit upon benefit. This causes profit to significantly increase.

If you fix the Brand Presentation, you've done good work, but you haven't fixed your merchandise assortment. Yes, your marketing channels will work better and you will generate more profit, but if the customer doesn't want widgets you won't solve customer dislike of widgets by focusing on Brand Presentation.

If you fix Marketing Channels, you might earn a promotion within your marketing team. But you haven't fixed your merchandise assortment, and you haven't fixed brand presentation.

Each brand stage requires different employees working together in different ways to achieve a common goal. You are capable of managing each Brand Stage. Go get the job done!

Ad Cost Companies

Consultants get to see profit and loss statements. They know what to look for when reviewing a p&l.

Because of my preference for marketing, I look at the ad cost line. There are two kinds of companies.

1. Companies that spend their way to success or failure.
2. Companies that find other ways to attract customers without selling souls to Google / Facebook / Others.

Every dollar wasted on ad spend is a dollar that doesn't flow through to the bottom line. It's the most simple aspect of the p&l to understand. If you don't waste money on marketing, you make more money.

Look at the p&l on the right ... when the wasteful brand spends 5% more ad spend than the smart brand but gets nothing for it.

Waste $4.25 million on ad spend and cost yourself $4.25 million in profit.

I worked with a client that spent more than 30% of net sales on marketing spend / ad spend. This was a poorly run business. The President of the company said to me ... "BUT WE HAVE TO SPEND THE MONEY TO GENERATE SALES". That's a classic sign that the President has no idea how companies generate sales WITHOUT spending money.

A VP/Marketing told me one that "IT'S GOOD FOR EVERY ORDER TO BE GENERATED BY MARKETING - I CAN SELL ANYTHING!" Good, glad you can. But when you quit or are fired, you leave the brand to somebody who can't sell anything ... and that's it for the brand.

The best companies understand profit ... and they understand that you don't want to spend money to make money unless their customer value simulations show sufficient downstream profit to warrant it.

Hillstrom's Profit

In addition to providing Virtual Analytics Officer services (click here), I will begin describing what will become a new product offering - called "Hillstrom's Profit" ... a fusion of Customer Development and Product Preference work I have been performing recently.

During the "COVID-bump" period of 2020, we observed how important the Customer Development aspect of profit became. In 2021, supply chain issues illustrated how important Operational Excellence is. In 2022, war is the issue - which means that customers prioritize what they "need" over what they "want". In other words, Merchandise becomes really, really important.

So tomorrow we'll start talking about how various issues impact profit. The easy profit days of 2020 are over, and you are going to need to understand how profit is impacted by your decisions.

15th Anniversary Special

Fifteen years ago this week I launched MineThatData. Within five days I had a $40,000 project agreed upon ... days later I was off an running.

Fifteen years ago!

Think of what has happened between then and now?

As we start year sixteen, I want to offer you, the loyal reader, something different. For fifteen years I've worked on "projects" ... specific assignments based on something I've created ... based on the perceived needs of you, the loyal reader.

So here it goes. Let's perform a trial. I will agree to work on your advanced analytics issues ... whatever you need analyzed at an advanced level I'll analyze for the next three months at a 1/3rd time commitment. In other words, you get me for thirteen hours a week for three months. If we both agree that the three month trial went well and wish to extend it, we can do that as well.

Contact me quickly (kevinh@minethatdata.com) because there will likely be multiple offers for this opportunity. On my project pricing page, this is called the "Virtual Analytics Officer" project (click here).

Happy Anniversary everybody!

P.S.:  You are probably wondering, "what kind of work won't Kevin do?" I don't build databases, create dashboards, build database tables, write code in your preferred language, build campaigns, or execute campaigns. I don't write SQL to extract data from your database - you don't want an external consultant touching your database, do you? If you want me to analyze your key business issues on call, I'm here. If you want me to explain to your Executive Team what is happening, I'm available. If you want me to mentor your staff, I'm available. If you need help leading your team, I'm available. If you are a vendor looking for insight into how I do what I do, I'm available. If you can extract the information for me in a .csv file, I'm available to help you.

Your Dashboard

Back in 2005 Google Analytics did something that ultimately happens in most industries. They created a "standard" for how digital data gets analyzed. It no longer mattered that other people had better solutions, or customized solutions. Google told you what "the" solution was. End of story. 

Over on my newly created pickleball analytics blog, a reader asked me what I thought a future "Pickleball Box Score" would look like? In other words, baseball / basketball / football all have box scores that outline who won, and summarize what the allegedly important statistics are. The reader was astute enough to foresee a future where somebody creates the standard used for analyzing pickleball matches.

Once the standard has been created, a market opens up ... for advanced analytics. The NFL / NBA / MLB all are supported by organizations turning out advanced metrics ... for a fee. Just because a MLB player (assuming there is an MLB season) goes 1-3 doesn't mean the MLB player had a good day. Did he swing at bad pitches and get lucky? Did he swing at good pitches and strike out? The dashboard / box score can't tell you those answers.

For nearly fifteen years, I've made a living going beyond the box score.

If your dashboard is a summary of what Google Analytics tells you to look at, you haven't done anything special. You've done something practical, sure, but not special.

In the next few years, you are going to see an evolution in Dashboards ... you'll have introductory views of customer behavior ... and then you'll have advanced views of customer behavior. Marketers currently refer to these advanced views as "journeys" ... that aspect of analysis is in the embryotic stages of the life of information. 

Exciting times are coming, folks!!

A Poorly Run Business

Yesterday we evaluated a healthy business.

Today we'll explore a comparison between a healthy business and an unhealthy business. In both cases, the brand generates $100,000,000 in demand. The problem is what comes "after" demand is generated. Take a look.

Oh my goodness.

The business on the right can't do anything right. They have more cancels, and their customers return more merchandise than the brand on the left. They have to liquidate more merchandise, resulting in a 54% gross margin instead of 60%. Pick/Pack/Ship expenses consume an additional three percentage points of net sales. The company spends $1.4 million more on marketing and gets nothing for it. There's nearly a million more in fixed costs.

As a result, the brand on the right operates at break-even with a 32% profit factor ... significantly different than the brand on the left which generates $11.9 million in earnings before taxes at a profit factor of 42%.

The brand on the right has a lot of work to do. A new CEO would look at this as a hot mess capable of "being fixed".

These are fun businesses for Management Teams to inherit, because they can be "fixed". 

"Fixed", of course, as long as company culture will allow the brand to be fixed.

Soldouts / Cancels / Returns

You've probably analyzed the living daylights out of this issue ... and if you haven't, you must not have any business issues.

On a recent Zoom the Executive (who clearly hadn't researched the issue) said the following to me.

• "I just hate disappointing the customer when we don't have a product available. It has to really hurt our brand, don't you think?"

Well, the answer is "probably not".

Here's what you'll commonly observe.

• Rebuy Rate of customer where order is 100% perfect:  40%.
• Rebuy Rate of customer where 1 items is soldout / cancelled / returned = 43%.
• Rebuy Rate of customer where entire order is soldout / cancelled / returned = 33%.

Your customers are remarkably patient with you. As long as the entire order isn't nuked, your customers understand the process and move forward ... often with higher rebuy rates in the future.

Control for customer history and then look at future activity ... you'll see that your customers tolerate some level of returns, and they tolerate some level of poor product availability. They don't tolerate extreme situations.

Understanding Your Business

I've told this story multiple times on Twitter, but it is worth repeating here.

Back in the day at Nordstrom, Neiman Marcus decided to open a new store in a market where an existing Nordstrom store performed well. The CEO publicly stated how the new store would damage Nordstrom. A reporter followed up on the juicy quote, asking our CEO if we were concerned about the threat?

Well, our CEO asked my team to quantify what happened in the past when new Neiman Marcus stores were opened in our markets. Guess what? Our stores performed BETTER when Neiman Marcus opened a new store in an existing market.

Better!

Our CEO politely responded to the question, citing data showing that when Neiman Marcus opened a store in a market we owned our sales increased. He told the press that we welcomed competition because competition brought in new customers, new customers who would purchase from our brand. 

We didn't hear anything from Neiman Marcus for years after that comment.

Some companies simply know more about business than other companies. The words/actions of a company reveal what a company knows about business.

It's one thing to understand your customers.

It's quite another thing to understand business.

You need to understand both, obviously.

But too few of us understand business. We've sat at the trough of the customer, not realizing that we weren't learning how our businesses really operate. Ask StitchFix. The algorithmic genius of the 2010s can't make money right now while sales are GROWING. They might prove us wrong, absolutely. But at this time, they might not understand how their business actually works.

When I arrived at Nordstrom in 2001, the online side of the business ... those folks ... they did not understand business. $300,000,000 in sales and a -10% EBIT. Our team didn't understand Nordstrom customers, but we understood business ... and within two years the online business was a breakeven.

The "omnichannel movement" of the past twenty years? Authored by folks who did not understand business.

Invest in increasing your understanding of how business works. Your career trajectory depends upon having a knowledge of business.