File Power In Practice

So I'm exchanging emails with a digital marketing expert - this person is excited because he acquired new customers at a $10 ROAS.

Now, I already knew the answer (as do you), but I asked the expert if that was a profitable outcome?

His response? "I don't know. I just know that's a good ROAS".

In practice, you have an existing customer base. The existing customer base is capable of spending "x", you'll spend "y" marketing to the customer, yielding "z" dollars of profit.

Profit is a function of the life stage the customer is in. Somebody acquired customers five years ago, and the work that somebody performed back then ends up in your pocketbook via a bonus today, because those customers keep generating profit.

In practice, we want a powerful file. We want as many customers as we can afford, and we want them to generate as much subsequent profit as they can possibly generate. When we figure out ways to generate more profit out of a customer, we are allowed to spend more money acquiring customers ... this behavior is circular because then we have more customers, generating more File Power, allowing us to acquire even more customers.

In my projects, I keep seeing instances of companies that cannot acquire enough new customers to grow. This seems like a Customer Acquisition problem (and it most certainly is a Customer Acquisition problem), but it is also a Customer Loyalty problem. When we cannot figure out how to generate more profit out of a customer, we have to back off on Customer Acquisition to make sure we generate enough short-term profit. Our Customer Loyalty problem accelerates our Customer Acquisition problem.

What drives Customer Loyalty more than anything else?

Merchandise Productivity.

In other words, there's a lot of interconnected pieces. If we take our eyes off of any one of the connected pieces, we lose profit, which hurts our ability to acquire new customers, which shrinks the customer file, which lowers File Power, which costs us more profit, and the circular problem continues iterating through the business.

Everything we do impacts File Power.

So yeah, we want to study File Power, don't we?

Updated Project Offering

To reflect the style of work I'm performing in 2022, I updated my "Hire Kevin" page. Click here for details.

I do have an opening for a project beginning August 15, so if you were thinking about something regarding customer behavior, let's talk.

The Power of File Power

Nice use of words, huh?

Here's something that I frequently see in my work. Look at rebuy rates by segment.

In each segment, rebuy rates are identical on a year-over-year basis.

However, rebuy rates in 2022 are 26.3% whereas rebuy rates were 24.3% the year prior.

This happens because of File Power ... you have 50 more 1x buyers, 200 more 2x buyers, and 250 more 3x+ buyers in 2022. Those customers pay you back.

Management cannot take credit for the increase in Rebuy Rates.

Well, that's not entirely true ... the increase in Rebuy Rates isn't because of anything they've done special this year, it's because of the hard work done by the entire company in previous years.

Story-Based Customer Acquisition

Here's an ad I received. Tell me what the story is that the author is communicating to me.

Now tell me what story is being told here.

The clients I work with who have the best customer acquisition results also have what I'd call "Story-Based Customer Acquisition". They're not just slapping horrifically intrusive/boring ads upon people and saying they're leveraging an "omnichannel advertising approach".

Instead, the best clients have a story to tell, and they use channels to tell the story.

Northwoods Baseball Radio Network

Ok, for something completely different today ... I read this article last week (click here).

Now, if you don't like baseball, if you don't like fiction, if you don't have a problem sleeping, then the intersection of the three will really be jarring to you, so best to stay away.

If you want to enter a bizarre world (and this world must take a considerable amount of time to create), visit here: https://www.sleepbaseball.com/.

Here's A Gem

A vendor sales rep told me the following:

"People think my goal is to make an offer the client cannot refuse. That's not true. My job is to make an offer the client cannot understand."

I recently emailed with an Executive who told me that he felt frustrated because it just wasn't clear what the vendor he was paying agreed to do for him. He kept getting the "that's out of the scope of our relationship" comment that so many of us received over time.

For a lot of companies, things are messy and are about to get really messy. If you are supporting one of my clients, please give 'em a fair chance between now and next March, ok? If you aren't willing to do that, what does that say about you?

Because You Should Read Alternate Points Of View

I have a lot of opinions here - and I'll bite my tongue and let you read the article. You draw your own conclusions, ok? 

https://hbr.org/2022/07/how-paper-catalogs-remain-relevant-in-a-digital-age

P.S.:  The only thing I will say is that if you are going to publish something with conclusions this sweeping, you best have a sample size greater than 8,600 customers to draw sweeping conclusions against. At Nordstrom in 2005-2007, our control groups were 200,000 customers, and the results were still noisy. We got to 200,000 because the statistician who built sample sizes before my team leveraged 5,000 to 10,000 per control group and spent years trying to make sense of gibberish. He made horrible decisions based on gibberish. Only at 200,000 customers did we get reliable results, the kind of results you'd trust publishing against the good name of a major University. Other statisticians will differ with this statement - vet your heroes.

P.P.S.:  There is a way to make results of tests with 8,600 customers credible. You repeat the test a couple dozen times and evaluate the variability of your results. I have many clients who do this ... and a -8% lift and a +24% lift gets averaged to a +8% lift over time. But at least you know it is +8% and not +24% or -8%.

-188 + 192*x

Yeah, yesterday I got frustrated about sample sizes. I'm so tired of people who do not understand math using math to make a point that is vendor-friendly so that vendors make money. It's a form of lying, it is misleading, and it is corrupt.

So let me take you all the way back to Lands' End, in 1991. Yeah, 31 years ago. We were executing tests with 5,000 customers in a cell, and the test results were ALL OVER THE MAP. Not consistent.

I was asked to determine what an appropriate test sample size should be.

I measured the variance of test results at different demand-per-customer levels. There was a clear, linear relationship.

• -188 + 192*(demand-per-customer).

Now I had what I needed to determine if what we were observing might be statistically significant.

Let's say I expected a customer to spend $5 if catalog-version-one was mailed. I could estimate the variability expected at different sample sizes.

• q = SQRT(2*(-188 + 192*(demand per customer)/(sample size))).

For a result to be statistically significant, the result/difference would have to be greater than 2*q.

Let's assume that demand per customer = $7.00.

• Sample Size =   5,000:  Q = 0.68.  2*Q = $1.36.
• Sample Size = 10,000:  Q = 0.48.  2*Q = $0.96.
• Sample Size = 25,000:  Q = 0.30.  2*Q = $0.60.
• Sample Size = 50,000:  Q = 0.22.  2*Q = $0.44.
• Sample Size = 75,000:  Q = 0.18.  2*Q = $0.36.

If you expected the test group to spend $0.25 more than the control group (+3.5%), you would need more than 75,000 customers to detect that level of change.

If you expected the test group to spend $0.70 more than the control group (+10%), you would need about 25,000 customers to detect that level of change.

This is the problem with people executing tests with 8,600 customers. Using the equation above, 2*Q = $1.04. In other words, unless the test group is at $8.04 and the control group is at $7.00 (+15%), you don't know if what you are seeing is due to a change in marketing strategy or is due to complete unfettered random noise.

Again, at every company, this equation is different.

And if you don't know the equation, you don't know if your results make sense or not.

So when I get upset about test results that are published by a reputable university that should know better, this is why I get upset.

Know your stuff, dear readers.

Know your stuff.

P.S.:  If there is a credible statistician reading this, that person should have already sent me an email suggesting that I violated "heteroskedasticity" ... that what I was illustrating was a situation with non-constant variance. Yes! That person would be correct. And that means that my analysis is also flawed ... not that I have a choice because otherwise I could never analyze test results at all, but the point is that the results I illustrate above are likely biased as well.

Music

This article is a perfectly good read - should get you thinking (click here). Click on the link, make my stats look good here in the dog days of summer. I'll wait for you.

...

...

...

...

oh, welcome back.

The gist of the article is that by making everything perfect, by scrubbing out every little error, by replacing real instruments with a computer, we've sucked the soul of out music.

Let's go back to 1980. Listen to the breaths taken at about the 0:20 second mark (click here). Those would be scrubbed out today, and the vocal imperfections would be corrected via auto-tune.

So I'm exchanging emails with an e-commerce Executive. This person is confident. He understands his Google Analytics data than anybody else. He can tell you why his Facebook ads are less effective. He can tell you the reason why any digital advertising is more/less effective. He knows everything that Google Analytics allows him to know inside-and-out. It's impressive to speak with this individual. Smart.

He then says something along the lines of "... but I seem to me missing the soul of my business, the heartbeat that keeps my business going."

Google Analytics made his campaign-centric work "perfect". He knew everything about campaigns.

But he didn't know anything about his business.

He traded knowledge of existing customers for knowledge of returning visitors.

He traded knowledge of his merchandise assortment for knowledge of his digital marketing portfolio.

Via A/B tests he knew what creative treatments worked but he didn't know anything about why customers preferred various creative treatments.

He traded new customer knowledge for traffic knowledge.

He traded knowledge of profit for an understanding of engagement.

As with all things, when something new is introduced we give up knowledge but we gain insights. We lose art but gain science. Similar to modern music, we've given up a lot of art.

We can enjoy both, y'know. It's possible.

Three Levels of File Power

You obtain good outcomes via three different aspects of File Power.

1. Number of Customers.
2. Quality of Customers.
3. Profitability of Customers.

In other words, you could have 1 customers spending $200 or 2 customers spending $100 ... either way you have the same general amount of File Power.

Then you have Profitability of Customers.

Customers aren't created equal. And marketers love to mess with customers. When you offer customers 40% off to purchase, you increase the Number of customers, you increase the Quality of customers, and you significantly impair the Profitability of customers. Marketers seldom measure Profitability, so they really don't care whether they've harmed profit or not as long as customers respond to promotions.

We, however, care about profitability.

My favorite story goes back to 1999 at Eddie Bauer. For six months, we didn't offer promotions to a randomly selected group of customers. At the end of six months, the non-promotional customer segment spent the exact same amount as the promotional customer segment.

1. Number of Customers purchasing was equal.
2. Quality of Customers purchasing was equal.
3. Profitability of Customers in the promotional segment was much, much worse.

File Power matters.

Measure Number / Quality / Profitability. Then act accordingly.

What 2022 Has Become

File Power has two different components.

1. Number of Customers.
2. Quality of Customers.

It turns out that it is really hard to impact the Quality of Customers. I mean, seriously, what could you possibly do to double the value of an existing customer? Almost nothing. You're sunk.

This means you really have to focus on Number of Customers.

At the start of 2019, maybe you had 100 customers, and 30 customers would repurchase. You might have had 70 new/reactivated buyers.

• 100 Customers * 30% Rebuy Rate = 30 Active Customers.
• 70 New/Reactivated Customers + 30 Active Customers = 100 Customers.

The business is stable.

Then in 2020 we had 110 New/Reactivated Customers instead of 70. The dynamics of the business changed.

• 100 Customers * 30% Rebuy Rate = 30 Active Customers.
• 110 New/Reactivated Customers + 30 Active Customers = 140 Customers.

You remember what your p&l looked like at the end of 2020. Your p&l looked good because you had 140 customers instead of 100.

In 2021 all of the new/reactivated customers ripped through the file, generating profit.

• 140 Customers * 30% Rebuy Rate = 42 Active Customers.
• 70 New/Reactivated Customers + 42 Active Customers = 112 Customers.

So we didn't generate 140 customers like we did in 2020, but we had 112 customers because all of those new/reactivated customers developed to some extent.

In 2022, it has become hard to acquire customers (especially for those of us who raised prices). Instead of 70 new/reactivated customers, we now have 60 new/reactivated customers.

• 112 Customers * 30% Rebuy Rate = 34 Active Customers.
• 60 New/Reactivated Customers + 34 Active Customers = 94 Customers.

Did you notice that in each scenario the rebuy rate stayed the same? Now, that's not what I'm seeing in my work, but rebuy rates don't have a lot to do with File Power. Nope. What matters is your effectiveness at generating new/reactivated buyers. In 2022, there are fewer new/reactivated buyers, causing headaches. We're causing part of the problem ... well ... those of us who felt compelled to raise prices, we're causing the problem.

File Power leans heavily toward new/reactivated buyers. There is a one-year lag ... you do a good job of acquiring customers this year, you get sales next year from those customers. We had an ok 2021 because we grew the customer base in 2022. We're going to have a lousy 2023 (at this point) because we are doing a poor job of building the customer file in 2022. That's what 2022 has become ... a battle for 2023 survival given our ability to find new/reactivated buyers at an acceptable cost in 2022.

File Power

Sometimes you think "people already know this stuff".

Sometimes you realize that Google Analytics give smart analysts almost no opportunity to ever even consider the concept. Thus, I need to write about it.

75% of my projects in the past three months have dealt with the concept of File Power.

File Power is a term used to represent the future potential of your customer file to generate sales and profit. There are two dimensions to File Power.

1. Number of Customers.
2. Quality of Customers.

In other words, you could have one customer who will spend $200 in the next year, or you could have two customers who will spend $100 each in the next year.

1. File Power of Scenario #1 = 1 * $200 = $200.
2. File Power of Scenario #2 = 2 * $100 = $200.

In each scenario, your File Power is $200. In the next year, you can expect your customer file to deliver $200 regardless of scenario.

In "the literature", almost all analytically-minded professionals focus on Scenario #1. They want customers with tremendous lifetime value. Marketers work hard to increase lifetime value.

Hint - you don't care about lifetime value. You care about File Power.

Of course, I'm exaggerating here. But the biggest thing we learned during the COVID-bump was that having a 50% increase in new customers caused A TON OF PROFIT to be generated. We learned that "Number of Customers" drives business success.

And here, in mid-2022, we're learning that we don't have enough customers (in many cases), causing profit to slump.

More on the topic in upcoming posts.

Lies

If you want to understand why clients don't trust vendors and trade journalists, read this little peach from a week ago:

Direct Mail is not, I repeat ... "is not" ... making a comeback.

All you have to do is measure the results to know it is not making a comeback.

I know, I know, your boutique agency (I am awaiting hate mail from one agency head as we speak) tells you that some random retailer "reinvented itself" with direct mail. Wrong. The agency needs direct mail to be successful because they make money when you spend money the way they tell you to spend it.

Yeah, the National Retail Federation makes money this way. And the vendor needs you to believe them so the vendor can make money.

But yeah, look at actual data, real / actual customer response data, actual Customer Development metrics, and you'll clearly see that Direct Mail is Not Making a Comeback. Doesn't mean you should abandon it if you use it effectively, but it is not making a comeback.

Shortfall

There's probably more going on than what I will outline here ... but this is generally what I am observing:

• Down 7% due to a lack of file power.
• Down 8% due to higher prices.
• Down 5% due to a lack of new merchandise.

So if business is headed toward a -20% vs. last year (as an example), some of it is because of not having enough new/reactivated buyers in the past year, some of it is due to higher prices, and some of it is due to a lack of new merchandise over the past two years.

Hint - none of these problems are easily/quickly solved. That's why I'm worried about Fall/Winter 2022 into Spring 2023. If your business is already weak, this will be a set of challenges that are difficult to overcome.

If your business is reasonably healthy, well, you have time to overcome the challenges. Get busy! And I get it, you think you are busy trying to solve these problems. I don't think you are busy enough trying to solve these problems. These are huge problems! But they are problems you can solve. You will need merchandising creativity and you will need the kind of marketing creativity you've likely weeded out of your business over the past fifteen years.

Go get 'em!

Compounding The Problem, Part 2

We talked about this post numerous times ... because it is the most important thing that is happening in direct-to-consumer Customer Development. Worse, it is going to create enormous problems for below-average performing brands.

Yesterday I covered the fact that new merchandise development has fallen far behind levels needed to fuel future growth. This will cost companies millions in sales next year when a dearth of new items becomes a dearth of existing items.

The second issue compounding the rough ending of the COVID-bump?

Prices.

Based on my analyses and what many of you have told me, rebuy rates are trending -10% this year. That's a bad thing ... not as bad if your rebuy rates are < 33%, but still, not good.

You're also telling me that your average price per item purchased is up somewhere between 5% and 10%.

Now, I realize that correlation does not mean causation.

But, come on.

I get it ... you perceive you had no choice but to raise prices to offset cost increases.

When cost of goods sold increase, you have two choices, and they're both bad.

1. Increase Prices, Sacrifice Customers, Sacrifice Profit.
2. Hold Prices, Keep Customers, Sacrifice Profit.

When prices increase, your marketing team typically throws their hands up in the air and grumbles about how their ROAS gets worse. This is not the time for marketers to grumble, this is the time for marketers to dig in and help the rest of the company mitigate challenges.

If you need to see what the relationship is between prices and rebuy rates, send me an email (kevinh@minethatdata.com) and we'll get busy.

Compounding The Problem, Part 1

We've talked about this issue for a few weeks (click here). It's everywhere, and it's gonna sort out weak companies from strong companies over the next nine months.

There are two issues that compound the problem. We'll tackle one of the issues tonight.

Here's what many of you are telling me is happening with new merchandise. Look at the "Class Of" table below.

Look at new merchandise sales by year ... $9.5 million then $9.0 million then $9.3 million and this year all the way down to $5.5 million. Yikes! And I get it, your merchandising team is going to tell everybody how hard it is to source merchandise during a pandemic-fueled supply chain crisis. Fine.

However.

However, look at what happens to each class of new merchandise in the next year. Three years ago new merch went from $9.5 million in the introduction year to $8.9 million. Then it went from $9.0 million to $8.5 million. Then it went from $9.3 million to $7.3 million. What do you think is going to happen to the paltry class of new merchandise from the past year? It's not going to go up from $5.0 million to $7.0 million ... it's going to go down, which means you will be short millions of dollars of sales next year because of the woeful Class of 2022.

You need to know about this now, correct? If you know about this now, you can plan your merchandising tactics for 2023 while asking your marketing folks for help to make up the sales shortfall.

This is one of the problems compounding what looks to be a difficult Fall/Winter season. Contact me (kevinh@minethatdata.com) if you want to see if this is a problem for your brand.