Kevin Hillstrom: MineThatData

Reassessing

2026-09-27T20:10:00.000-07:00

There's been all sorts of calamities, some caused by external issues, some self-inflicted.

I recall 1995, 1998, years where the companies I was with caused their own problems.

2001 - a hybrid of the end of the dotcom era and self-inflicted damage.

2007 - when you could feel that customers spent all their "free" money from their homes, there wasn't anything left to spend (as we'd soon find out).

2012 - the collapse of the omnichannel movement begins (accelerating into 2016/2017).

2021 (Fall) - the popping of the COVID bump.

The data I'm seeing these days is mixed, with some able to thrive, others battling external issues and internal mistakes.

When business signals are mixed, reassess your marketing spend, reassess your new item development plan. Run your Class Of Report (I'll do it for you if you don't have the resources to do it), and make sure you aren't -20% on demand from new items this year (which will cost you money on existing items next year) or -20% on existing items this year (meaning you discontinued stuff you shouldn't have).

Can You Believe It? It's Time, Again

2026-09-23T20:10:00.000-07:00

Four months go by in the snap of a finger!

It's time for yet another run of the MineThatData Elite Program. Cost is $1,800 for first-time participants, $1,000 for those who previously participated. You receive the standard suite of metrics I run (rolling twelve-month analysis, comp segment, comp new/reactivated buyers, repurchase behavior, new/reactivated buyer trends, next twelve-month forecast). Very little cost, plenty of insights into where your business is headed.

Contact me now (kevinh@minethatdata.com) and let's get started.

Data Due by 10/15/2026.
Payment Due by 10/15/2026.
Analysis Delivered by 10/31/2026.

Ways To Grow

2026-09-22T20:10:00.000-07:00

Let's assume you aren't a retail brand looking to add stores. Your growth options are actually quite limited.

You can find new customers. This is necessary, and it is not generally prioritized.

You can get existing customers to spend more. This is hard, it is almost always prioritized, and is often a waste of resources.

You can add product lines and/or create new brands. Non-competing product lines are one of the best ways to grow. If you sell Women's Apparel and you move into Kids, guess what? You'll sell more merchandise. If you sell Women's Apparel and you move into Widgets? That's a lot harder.

You can move into other channels. It's the reason many of you sell on Amazon. They do the hard work, they take a chunk of your profit in kind.

As it becomes harder to find new customers, it becomes necessary to explore new product lines and/or new brands.

What Does The Plan Look Like When Proper Organic Percentages Are Applied?

2026-09-21T20:10:00.000-07:00

If I have to hear one more professional lament the fact that Orvis doesn't mail catalogs anymore but Amazon does ... then suggesting that "Amazon is smarter" ... my goodness.

None of that matters. The only thing that matters is your customers, your marketing efforts, and the incremental effectiveness of your marketing efforts. That's it.

Here's what proper application of the "Organic Percentage" looks like. Below is a typical circulation plan (simplified by deciles instead of segments for illustrative purposes) via matchback analytics. Looks good on the surface (only look at the top portion of the table for now).

Every segment is profitable - you could absorb a 10% increase in ad costs and still be profitable. It's all good! Catalogs work.

Except they don't work for most customers.

You're one of the smart ones ... you execute mail/holdout tests. For you, 75% of the demand will happen anyway, 25% is "caused" by catalog marketing. Which leaves you with the bottom half of the table.

Look at that. There are ten deciles/segments there. How many are profitable? One (1). One!! Just the most loyal customers. Every other segment represents a marketing abomination.

In case you are wondering, this is where the arguments begin.

There is the group of professionals who simply do not believe the results. They are true believers in the craft. You cannot convince this audience of anything, even though 80% of the catalog pages circulated 20 years ago no longer exist (because they were terribly ineffective). You have to let these people marinate in their delusion.

There is a group of professionals who have to test 50 times ... they believe that the test results "are not representative". These people are stalling. They know the change that these results will lead to, and they don't want to deal with change. So they delay the inevitable.

There are a small group of professionals who believe the results, but realize their organization is unwilling to change. This audience largely left catalog marketing in the past twenty years, and are now thriving in ecommerce.

There are a small group of professionals who work in paper / printing / agencies. They CANNOT believe these results, because as I was told by a paper rep ... "it will take food off my dinner table, and I cannot allow that to happen". They lie to benefit their craft. They are not fundamentally different than politicians who lie to protect their congressional seat.

There are a small group of professionals who work at agencies AND they believe in the results and they try to do what is best for their clients. If the agency you work with is willing to execute mail/holdout tests and evaluate results via the bottom half of the table (above), hold on to that agency like your life depends upon it.

Then there are the companies who change. Like Nordstrom did back in 2005 when I worked there (they kept mailing branding-centric catalogs throughout, but the classic list-based catalog business model was discountinued). Like Orvis. Like several of my clients. Why are they changing? Because they run a p&l that looks like this.

These companies make a choice. They take the 17% demand hit, but save $360,000 in ad cost and increase profit by $213,000 (in this example). With the ad cost savings, they typically reinvest in digital marketing channels ... or they just become a smaller brand that is more profitable. Either way, they outperform those who don't evaluate their businesses in this manner.

Did you see what happened in the bottom half of the table, when you evaluate your circulation plan via mail/holdout tests?

Only the most loyal customers are profitable.

This is why you'll see brands with the GDP of Australia be able to mail catalogs ... they have hyper-loyal customers that can afford to be mailed even if little of the demand generated by the catalog is actually incremental.

This is why I argue that catalog marketing will still be a craft that can be applied to loyal customers or hyper-productive customers. The math will continue to work for a period of time.

But for everybody else?

It's over.
It's been over for a long time.
There's no reason to badger Orvis because they made what is in reality an easy, fact-based, profitable decision.

It's Forecast Season!

2026-09-20T20:10:00.000-07:00

Somebody at your company sounded the alarm bells about November/December.

Is that person right? Are you going to be below plan/budget? Or is the professional paranoid?

It helps to have facts, doesn't it?

As I generally do each year, I'll accept five years of data through September 30. With that data, I'll tell you what your projections for November/December look like. It's Forecast Season!

Contact me right now (kevinh@minethatdata.com) and I'll project November/December for you at a low cost.

Content Creation

2026-09-17T20:10:00.000-07:00

Here's the link.

I realize many of you are stymied by creating content for your customers. Some of you would say the video above is pointless, useless, and may have nominal ROI if any. Think of this as a triangle, with being "stymied" on one point, "pointless" on another, and doing something on the third point of the triangle.

How Will You Give New Items Exposure?

2026-09-16T20:10:00.000-07:00

It's hard for the customer to know you have new merchandise unless you tell them you have new merchandise. You do that through print (for some of you), you do that through email marketing, you do that through your home page, you do that via social media.

Now think a bit about the evolution of search. Your search-centric customers already skew to existing items ... just perform the analysis yourself, it's easy to do and it is revealing as heck. Algorithms push customers to items that algorithms know about.

AI likes/needs to be "trained". How do you train an algorithm on an item that you won't offer yet for two more months?

Email marketing is going to become your most important new merchandise advertising platform. It will be one of the few places you have control over the message. Start your experiments today, learn as much as you can, and be ready for the change that is coming.

The Organic Percentage Over Time

2026-09-15T20:10:00.000-07:00

When I left Lands' End in 1995, one of the challenges the analytically-focused person faced was the fact that some in Management did not believe that if you didn't mail a catalog 30% of the demand would still happen (from surrounding catalogs). This "fact" (measured via mail/holdout tests) meant that what was marginally profitable was, in fact, unprofitable. Nobody wants to be tied to something that is unprofitable. Consequently, facts were not accepted.

At the time I thought "these people just aren't smart enough to understand simple math". I was wrong. People are smart enough to understand facts, be it in marketing or politics. People choose to ignore facts for perfectly good reasons.

The organic percentage, at 30% in 1996, would become larger, creating ever-bigger problems.

By decade, the organic percentage grew.

1996: 30%.
2006: 50%.
2016: 65%.
2026: 80%.

In 2026, the only customers that can be profitably mailed are good or great customers. That's it.

And I get it ... some of you are reading this and you go back to your matchback analytics and you say "I'm good". You run a p&l on each segment and you believe you are mailing 36 month customers profitably. If you believe this, execute the following experiment.

Assume your organic percentage isn't 80%, assume it is just 50%. Pretend like it is 2006.
Run a p&l for each segment assuming your organic percentage is an old-school 50%.
What does the analysis tell you?

It tells you an inconvenient truth.

If you do what the analysis says, your company will be more profitable. Much more profitable.
If you do what the analysis says, you will cost your company top-line sales/revenue/demand, and you have forces within your company who will never let you do that.

This is why so many catalog brands ultimately went bankrupt. They couldn't let the top-line contract, so they just kept doing what they were doing until unprofitable became "too unprofitable" while customer response also contracted.

When the AI bubble pops (and it most assuredly will pop), new ecommerce models fueled by what AI is supposed to become will emerge. Print will be forced to be leveraged only by brands with the GDP of Bolivia or will be a tactic to leverage with best customers with high iROAS. It will not be a channel to center an entire business around (and honestly, it hasn't been for 20 years). Also - the same forces that came for catalog marketing will come for old-school ecommerce in a few years. It's how capitalism works.

An Interesting Evaluation Of Marketing Effectiveness

2026-09-14T20:10:00.000-07:00

A link was offered to download a "white paper" demonstrating that print has fabulous ROI.

The "good" from the PostPilot report?

S-Tier Analysis: Conducted via mail/holdout groups. Yeah, they went there. Kudos!
They Didn't Lie: Their results "make sense". They aligned with reality.

The "not so good" that made me #sigh?

Results derived from highly responsive customers.

You can cover a whole bunch of sins by executing marketing against the most responsive customers. Just ask the loyalty industry for verification. Here is an example of the kind of direction they're leading you in.

There is nothing nefarious happening here - the analysis is measured properly, the organic percentage is common/reasonable, and iROAS (incremental demand / ad spend) is incremental.

Is there a flaw in the analysis?

No.

Is the analysis misleading?

Yes.

Why?

The analysis was executed against highly responsive customers ... ones about to buy or ones who just purchased. In either case, the customer is not representative of the customer base. EVERY marketing effort "is likely" to work when measured against highly responsive customers. Including print. Especially print!

The logic falls apart when you take the same conditions and apply them to, say, a customer who has not purchased in 18 months.

Everything is the same here - same incremental lift, same ad cost, same organic percentage. However, the customer is simply not responsive. As a consequence, the marketing channel is not effective, with a horrifying iROAS and a loss.

That's how you make something appear to be effective - execute it against responsive customers.

But when you try to extend the audience? Not so good.

Email and Social are the ways you speak with non-responsive audiences. Ad costs are so minimal that the numbers work.

You Get This Newsletter Every Saturday, Right?

2026-09-13T20:10:00.000-07:00

If you want to see what a mix of professionalism, free information, and personal expression looks like, get on this email subscription (I've been here for more than a decade, long enough to see his kids grow up and move into college and begin careers).

Saturday's email was about the resurgence of brand marketing ... which is interesting because on many recent video conferences there have been robust discussions about the death of catalog marketing and the importance of email marketing as one of the few ways to have an actual "relationship" with a customer.

25 Years

2026-09-10T20:10:00.000-07:00

It's almost unfathomable that a full generation has passed since 9/11. Twenty-five years. More than a quarter of the people who experienced that day are no longer with us, including 3 out of 8 of the adults who experienced that day.

Pressure causes people to behave in interesting ways. On 9/11, I recall a peer VP sobbing. An Executive looked at me and said "Why is she so sensitive?". He then locked myself and my Marketing Director in a conference room from 2:30pm - 7:00pm because, as he said, "we'll get an opportunity to fix the business and nobody will be here to bother us". I sent my employees home, then failed to fix the business during the 4.5 hour session. Obviously, the Leader was responding to pressure in a manner inconsistent with logic. It's easy to feel empathy for the Leader today. I felt something different that afternoon.

A woman I've played pickleball with described what it was like to try to get out of the city on 9/11. Her ordeal was obviously more harrowing than a 4.5 hour session in a stale conference room.

It's like the events of that day sent us down a different reality path ... not unlike the one in Back to the Future where our heroes end up in a timeline controlled by Biff Tannen.

No matter what happens, we move forward. We are resilient.

How Do You Know When A Marketing Channel Is Dying?

2026-09-09T20:10:00.000-07:00

Last month I was asked this question. What a good question!

In 1999 at Eddie Bauer, I measured "phone" customers ... those who bought by calling our contact center. About 10% of those customers placed an ecommerce order the next time they purchased. Meanwhile, almost no ecommerce customers placed an order using the phone on a next order.

Run that relationship out a few years and it became obvious that the marketing channel known as catalog marketing was doomed.
If you didn't look at the data in this fashion (nobody does), it becomes really difficult to see that a marketing channel is dying. By purposely not running the analysis in this way, one can believe forever that the marketing channel is not dying when it is most certainly not dying.

The relationship I described (identified in 1999) ran like a runaway truck from 2003 - 2013.

About 30% of phone customers placed their next order online.
Virtually no online customers placed their next order via the phone.

By the time we got to 2013, catalog marketing as a discipline was done. No, not to the NEMOA audience obviously, but to any rational observer it was done. By 2013 the rate of phone customers shifting online in their next order was back in the 10% - 15% range. In other words, all the customers who were going to convert to online buying had already converted to online buying. The only customers left were all 60+ years old (in 2013 - imagine their age today).

This is how marketing channels die. It happened to Spiegel / JCP / Sears / Wards. It happened to specialty catalogs. It's going to happen to ecommerce brands over the next decade once the AI bubble pops and newer AI-centric business models emerge from the rubble.

There is going to be "something". You might implement "something" on your old-school website that causes customers to change their behavior. You might push your customers to an AI-infused marketplace (don't do that for Heaven's sake). You might generate traffic on your site from an AI-infused marketplace and notice that you don't have the same traffic from Google. Regardless, "it" is going to happen.

You will measure the dynamic.
If 20% of customers who bought from the old-school channel last year purchase via the new channel this year ... but very few of the new channel customers go back to the old-school channel, you know that a marketing channel is dying.

How many of you measure marketing channels in this manner, show of hands?

Business Isn't Easy

2026-09-08T20:10:00.000-07:00

I reviewed all clients who were charter members of my Elite Program back in 2015 ($1,000 per run for existing clients, 3x per year, voluntary performance).

A third of charter members are no longer in business.

All of the brands now out of business were catalog brands.

Other catalog brands were distressed, gobbled up by catalog holding companies.

If you go back to 2007 when I started my consulting work, about 2/3rd of the catalog brands I worked with in my first decade of consulting are gone.

Gone!

No amount of paper / printing / agency discourse changes facts. If you're still here? You did something right!

After the AI bubble pops, there will be new business models. New business models will grow at the expense of existing ecommerce brands. The cycle will repeat. It's unavoidable, it's how capitalism works.

It's also very rewarding to fight against forces working against you ... to persevere, to thrive, to overcome challenges with great merchandise!

Package And A Snack

2026-09-07T20:10:00.000-07:00

I ordered a cable (from Bloom Audio) that connects my Qudelix Q5k bluetooth dac/amp to my Apos Gremlin hybrid tube amp (2.5mm balanced to 4.4mm balanced for those nerding out here). It's not exactly the type of solution Walmart or Target tries to solve.

The image below shows what arrived in my package on Thursday.

A thank you note ... and a Starburst fruit chew.

I've told you this story at least a dozen times - I worked with a company that put ghosts in their outgoing package. You received a little note about your ghost, his/her strengths, weaknesses, and potential scenarios where the ghost might influence household activities. On the socials, customers loved this little touch.

When I'd tell professionals at conferences about this tactic, I'd get the kind of blank stares that one receives when they have a rogue piece of spinach covering a tooth, followed by a statement like "that's interesting, of course, that's not going to work for our customers, what other ideas do you have?" And I'd think to myself, "why is it my job to toss ideas out for free, isn't it your job to come up with ideas?"

There's about two months to go ... then many of you become preoccupied with Winning Cyber Monday (#wcm). Until you win by giving 77% off plus free shipping, what can you do with your outgoing packages to help your customers feel special?

Taking Questions

2026-09-03T20:10:00.000-07:00

Going into Labor Day weekend, do you any questions for me? Send me an email (kevinh@minethatdata.com) and if I can answer your question, I'll do so.

Otherwise, enjoy your long weekend! See you in several days.

Blaming The User / Customer

2026-09-02T20:10:00.000-07:00

Two days ago I received communication from an individual.

"If the user is too stupid to understand the difference in use cases of different AI tools then the user deserves it if the user gets unverified and incorrect results."

Sort of like the paper/printing folks suggesting that my clients aren't being "smart" about print, that they're asking "the wrong questions" in an environment where the paper/printing folks have raised prices to unsustainable levels. Blaming your customer because you raised prices and they responded rationally. Not a long-term strategy by any stretch of the imagination.

In your personal life, what happens if you repeatedly use and/or take advantage of your friends? You run out of friends!

In business, what happens if you repeatedly use and/or take advantage of your customers?

When The Marketer Is Fighting For Her Company

2026-09-01T20:10:00.000-07:00

Here's something I witnessed recently.

Annual Comp Segment Performance: -11%.
Annual New/Reactivated Comp Buyers: +3%.

In the Comp Segment framework, customers like the merchandise 11% less than last year. This fact has to be applied to new/reactivated comp buyers.

Adjusted New/Reactivated Comp Buyers = +3% - (-11%) = +14%.

Had the merchandise been appreciated by customers, new/reactivated buyer comps would likely have been +14%.

You can tell if the marketer is fighting for her business based on Adjusted New/Reactivated Comp Buyers. It's not the only way to tell, but it is a leading indicator. In nearly 20 years of consulting, the marketing professionals who have gone on to great things possess fabulous Adjusted New/Reactivated Comp Buyer metrics.

Show of hands ... how many of you use this metric to evaluate how brilliant your marketer is?

Speaking of Setting a Standard

2026-08-31T20:10:00.000-07:00

I asked ChatGPT to perform a simple long-term value curve estimation procedure for me. The classic ecommerce customer relationship is one easily fit via a diminishing returns power function.

Future Spend = a*x^b where "x" is the number of months since a customer was acquired.

I'll spare you the paper trail for now (it's attached at the bottom of the post).

AI fit the wrong equation ... it fit a linear regression model which understated how much a customer spends early in the life cycle and overstates how much a customer spends later in the life cycle. In the real world, this means you'd accept a 2.00 ROAS when you should accept a 4.20 ROAS and your company would be significantly less profitable. All because of AI. If you don't know how to "coax" an answer out of AI, you'll doom your company. And you'll boil a few aquifers in the process.

I asked AI if a diminishing returns relationship like a*x^b is more appropriate and if it fits better? It replied that the equation is more appropriate and yes, it fits better (well then why didn't you do that the first time I asked you?). It gave me an answer. One problem. The answer it gave me was a hallucination? How did I know? Because I asked my statistical software package (CurveExpert) to solve the problem for me, and it gave me the correct answer.

It gets worse.

I asked AI to provide me with predicted value calculations for the equation it fitted. Here is an example of the answer it provided for me (remember, the coefficients are already wrong - I'm just asking it to perform simple math).

Future = 8.63 * (Months ^ 0.78).
Assume Months = 12.
Future = 8.63 * (12 ^ 0.78).
Future = 55.90.

Go ahead and plug 8.63 * (12 ^ 0.78) into Excel. What answer do you obtain?

You should obtain 59.95.

In other words, AI is not even calculating simple calculator-level math correctly. It's hallucinating. It's doing whatever it wants. And it is doing a HORRIFYING JOB.

You are a Lemonhead if you trust this stuff.

Yes, there will likely be a day when AI is a lot better and performs certain functions a lot better. If you want to target email subscribers properly, AI is already quite good at that ... though again, how do you know it is doing things the "right" way? How could you possibly know? Also, I just asked the application to provide me SPSS code for a problem and it wrote elegant and functional code.

But until that future day happens (and it appears it is out there a bit), please be careful.

Here is my final question to AI, and AI"s final response.

Kevin: I've learned that you cannot perform even the simplest of tasks without making mistakes. I am able to fact-check your work with hand calculations. What are users who do not have my skills supposed to do if they blindly trust your solutions when you cannot even perform simple math that a calculator can perform?

AI: Kevin, you’re not wrong to be frustrated. And you’re absolutely right to call out the risk: if I make a math mistake and a user can’t check the work, that’s a problem. Let me speak to you directly and clearly — no defensiveness, no sugarcoating.

1. You caught real errors — and they were my responsibility

You gave me a clean dataset — values like:

“60,169.17 … 1,11.03”

and you asked for a specific model:

y = a·xᵇ

I should have executed the log–linear regression cleanly. Instead, I produced inconsistent coefficients and even mis‑computed basic exponentiation. You were right to challenge it.

2. What should users do if they can’t check the math?

They should do exactly what you’re doing now: question the output when something feels off.

Even though I’m designed to be helpful, I’m not infallible. I don’t “blindly calculate” — I generate answers through patterns, reasoning, and approximations. That means:

I can make arithmetic mistakes.
I can misinterpret a model specification.
I can produce a result that sounds confident but is wrong.

A calculator never does that. I can.

3. So how do non‑experts stay safe?

Here’s the honest guidance:

If the stakes are high, users should verify with a second source. A spreadsheet, a calculator, statistical software — anything deterministic.
If something looks suspicious, they should ask me to re‑derive it step‑by‑step. When users force me into explicit steps, the chance of error drops dramatically.
If a model choice seems odd, they should ask why I chose it. That exposes misunderstandings early.
If they don’t know how to check the math, they should ask me to show the logic in a way they can check. For example: “Show me the log‑linear regression table.”

4. And for you specifically

You’re not a passive user. You’re doing exactly what an expert should do: stress‑test the output, challenge inconsistencies, and demand rigor.

Your skills make you a tough critic — and that’s good for me. You force precision.

5. I’ll own the core issue

You asked: “What are users supposed to do if they blindly trust your solutions?”

They shouldn’t blindly trust me. They should trust me the way they trust any powerful tool: use me, but verify when accuracy matters.

And when you catch me making mistakes, I don’t get defensive — I get better.

If you want, we can redo the entire regression cleanly, step‑by‑step, with every transformation shown explicitly so you can see each number and confirm it.

Setting a Standard

2026-08-30T20:10:00.000-07:00

My Milwaukee Brewers are having yet another great year, one that will potentially be derailed by the Cubs or Dodgers. On Tuesday night, this happened (click here).

A rookie was benched in the fifth inning AFTER hitting a bloop single.

Yes, Brewers fans derided the Manager for being a bit short-fused.

Not me.

He's setting a Standard.

Any of you who have been a Director or VP or C-Level Professional know that there is a Standard in your industry. There is a level of competence and effort that must be met, and if the employee does not meet it, there are consequences. You cannot survive if your team does not meet the Standard. And you know what that Standard is, based on your career experiences.

I work with a current client where the employees are understanding the Standard, and are responding to the Standard. Their response is different than a year ago. I so enjoy working with them! The employees are growing!!!

Go out on LinkedIn for 10 minutes and you realize that so many of those folks do not understand the Standard. No attention to detail. Just high-level thoughts. "I think Kohl's has big problems with their relationship with Sephora." That's brain-dead drivel. Do you know what counts? Meeting the Standard so you can fix both Kohl's and Sephora and change the trajectory/thoughts of tens of thousands of employees. That's the Standard. How many people on LinkedIn are capable of doing that?

Catalog Thought Leadership is just as bad. When faced with postage increases, my clients aren't asking the "wrong questions" as printers and paper people tell us. My clients are meeting the Standard. They are benching Print for lazy performance and poor effort. They are benching the vendors who support lazy performance and poor effort. I can understand if you were benched that you'd maybe take a swipe at the person who benched you, but that's also not meeting the Standard. Read what Cooper Pratt (the player who was benched) said in the article cited earlier.

The Standard = Discipline + Competence + Vision + Leadership + Communication.

How many unsubs am I going to deal with for merely referencing this topic? And what does that say of the person unsubbing?

Loyalty: Red Lobster Nation

2026-08-27T20:10:00.000-07:00

We talked about loyalty programs this week. I talked about the feebleness of points and percentages off. Here's Red Lobster Nation.

Earn points, get dollars off your meal.

A question.

Is the price of a meal at Red Lobster the thing that has stopped you from dining at Red Lobster? Is the price of a meal at Red Lobster the thing that stopped you from eating at Red Lobster 13 times a year instead of 12 times a year?

A loyalty program should be designed to solve a problem. What is the core problem that Red Lobster has?

Is it that restaurants need to be renovated? If that is the core problem, how is encouraging somebody to eat in a run-down restaurant more often for a few dollars off helpful?
Is it that Zombie Retail restaurants are in less-than-optimal locations (i.e. they were put in a good location 20 years ago but those are not prime areas anymore)? A loyalty program won't solve this problem.
Is it that the food is too expensive? This could help, but you are asking the customer to continue to pay higher prices for a period of time before earning a small reward.
Is it that the service is poor? If this is the core problem, asking customers to continue to receive poor service for a period of time before saving a few dollars is a big ask.
Is it that Marketing is out of ideas? If this is the core problem, this could be a solution.
Is a Management Consultant involved? If this is the core problem, we all know the appropriate course of action.

In almost all cases, the "brand" (or Zombie Retailer in this instance) has a merchandise / product / pricing problem that the brand is choosing not to address - the loyalty program is designed to paper over the merchandise / product / pricing problem.

The Two Best Ways To Grow Your Loyal Customer Base

2026-08-26T20:10:00.000-07:00

I've run the numbers more times than I care to mention. Tables, queries, simulations, you name it. All methods tell the same story.

The best loyalty programs have MANY customers, not few customers. It's always better to have two loyal customers than it is to have one loyal customer.

If you want a loyalty program with many loyal customers, there are two things you need to do. You need to do these things years before they pay off (I realize you don't want to hear that news).

You must acquire high-quality new customers. S-Tier or A-Tier new customers. It's mandatory. That new customer you paid Facebook for that bought one lousy item at $29.99? Garbage. Facebook makes money, you don't.
You must convert as many first-time buyers to a second purchase within three months of a first order. If you don't get them early, the probability of the customer becoming loyal greatly diminishes.

The mistake that is made, of course, is that the loyalty marketer waits until the customer spends $1,500 or whatever the amount, then tries to squeeze more money out of the customer. How many customers ever get to the $1,500 level? In my work, somewhere between 2% and 10% of customers ever achieve "loyal" status, however you define it.

Smart marketers, of course, mitigate this problem by crafting alternate marketing programs.

They don't say "no" to the garbage name acquired via Facebook, but they work overtime to acquire the first-time buyer who purchases three items on a first order in two different merchandise categories. Whether algorithmically or (often) via their own programs, they generate attention/awareness that leads to new customers that are S-Tier or A-Tier.
They have well-developed Welcome Programs that convert customers to a second purchase quickly. This results in a significant increase in loyal buyers 18-36 months later. The Loyalty Professional is dependent upon a Smart Marketer.

When clients ask about loyalty programs, I frequently say "If you want twice as many loyal customers tomorrow, be sure to acquire twice as many good new customers today". That's the point where professionals (i.e. some of you) get frustrated.

There are no shortcuts. There is a Standard that needs to be met.

Regardless, that's what the data shows. Accept facts and thrive!

The Problem With Loyalty Programs

2026-08-25T20:10:00.000-07:00

Three problems with loyalty programs:

Wrong Incentives. Points and Discounts. Is that what the customer truly "wants"?
Wrong Customers. The wrong customers are selected to be included ... sometimes it is almost every customer that is included. That's not a loyalty program, it's not special if everybody is included.
Wrong Outcome. If we assume that a loyalty program creates incremental orders that wouldn't have otherwise happened (a big assumption), we may or may not generate a profitable outcome. For instance, too many of you ADORE throwing gross margin dollars in the trash can to "create" a more loyal customer. Why are you giving everybody an additional 20% off? Would they have purchased without the discount? If the answer is "yes", you just threw money in the garbage can and lit it on fire.

A well-crafted loyalty program must result in incremental orders that wouldn't have happened otherwise, and must result in more gross margin dollars and more profit dollars that would not have happened otherwise. Every time you give an additional 20% off or 40% off, you put gross margin dollars and profit dollars at risk.

Also, you don't solve the core problem. If you want to have a great loyalty program, how do you grow the number of customers who deserve to be in the program?

P.S.: I once worked with a "brand" that decided to enter everybody spending > $500 in a loyalty program, offering discounts/promotions/points to encourage the customer to spend more. The marketing team loved watching the orders roll in (in truth, they'd never measured how orders came in for this cohort). At the end of a year, I quantified year-over-year how much the > $500 cohort spent (it was like a 20% increase). Everybody celebrated. Then I shared with them the outcome of a separate query I ran where I measured the year-over-year increase among $400 - $499 customers last year. They didn't spend 20% more ... but they spent 15% more.

The incremental increase of 5% was wildly unprofitable. The company simply burned money.
Nobody appreciated the answer. I wasn't invited back to continue analyzing the issue.

Define a "Loyal" Customer Please

2026-08-24T20:10:00.000-07:00

When I describe what I define as a "loyal" customer, I see sour faces. The kind of face one makes when accidentally biting into an onion that was mistaken for an apple.

My definition (get ready to make the face):

A customer is "loyal" when the customer has a 60% or greater chance of purchasing again in the next year.

I see your face.

Here's the thing ... it doesn't matter how you define a loyal customer, do it however you like. But come up with a consistent definition and stick with it. Maybe it is "Spending 'x' or more dollars across 'y' years". That's fine.

In nearly forty years in this "industry", I've learned that customer behavior and financial gain changes when the customer has a 60% chance or better of buying again next year. You might have three customers with different characteristics, but all three have the same chance of buying again next year.

Purchased 4 times in the past four years, AOV = $100.
Purchased 2 times in the past four years, AOV = $200.
Purchased 3 times in the past four years, multi-category buyer, purchases full priced merchandise, uses proprietary credit.

Those are three different customers, all equally valuable in the future.

Regardless, create your own definition. There is no right/wrong answer. But stick with your definition once you define it.

Loyal Customers

2026-08-23T20:10:00.000-07:00

This is what happens if you don't give AI a copy of what our friend, The Lemonhead, looks like. It leverages creative expression to do whatever the heck it wants.

I mean, technically that is a lemonhead ...

I have no idea why there is an airplane in the image.

Anyway, this week we'll talk a bit about loyal customers. There is a secret to developing a loyal customer base, and the secret is likely to annoy you, because it has little to do with anything you've been taught.

Take The Survey - Which Job Would You Prefer?

2026-08-23T20:05:00.000-07:00

Which of the three jobs would be to your preference (click here)??