Kevin Hillstrom: MineThatData

One of the analyses I run in a pricing project is measurement of customer response by price point. If inexpensive price point customers are willing to buy expensive price point items in the future, you're in good shape? If not? You need to maintain price integrity.

I'll run logistic regression models (#oldschool) of next year's response within price point bands ... always a fun and informative analysis!

The table shows the increase in rebuy rates ... for instance, if a customer buys from the low price point band, each item purchased there increases your probability of buying in the future regardless of price point band ... but adds the most in low prices and average prices.

Interestingly (in this case) if the customer buys from the highest price point band, the customer is most likely to keep buying in the highest price point band next year, though the purchase does help increase odds of buying in all price point bands.

There are companies I analyze that have all sorts of odd outcomes ... low price point customers that refuse to move up, high price point customers who buy from everything, average price point customers who default back to low price point bands. Regardless, it's important information you need to learn for your brand.

It's one of the Top 12 Analyses you respond to when we work together on a project! You have a few days left to take me up on my Top 12 offer. Contact me now (kevinh@minethatdata.com).

        

Midland Paper thinks you need to read this article (click here). They included the article in a newsletter this week.

Is there a rise in Slow Commerce? I asked one of the AI apps to tell me about Slow Commerce. Surely if it were a trend, AI would know about it, right?

        

This one is always a classic ... every one of you manages customers who ultimately gravitate toward specific merchandise categories or exhibit behavior that becomes actionable from a targeting standpoint.

I use what is called a "Factor Analysis" to reduce complicated customer behavior into actionable segments. The computer produces a visualization for me ... the visualization is what so many of you have enjoyed over the past twenty years, making the visualization one of the Top 12 Analyses I perform.

So many fun associations!

Customers buying for the first time lean to one-item orders (duh), which skew to expensive items. Yup.

Customers buying from Merchandise Category 02 tend to buy items below their average historical price point. This brand is discounting within that category, it's something I'd have to discuss with Management to understand if they were liquidating items or ... well ... just to figure out if they had a plan.

As customers become loyal (3rd / 4th / 5th / 6th-9th purchase) they align with new merchandise. Guess what? This one comes up frequently. Give your best customers want they want for crying out loud!!!!

My Top 12 Offer ($12,000 instead of $19,000) is valid for prior clients and blog subscribers through August 15. Contact me (kevinh@minethatdata.com) for details.

        

I started creating this analysis (Class Of Reporting) for clients back in 2012, rolled it out more formally in the 2013-2014 timeframe.

In nearly every project where this table provides enlightening insights, clients talk about the table ... a lot.

It's not all great talk. I shared the table with an Owner about a decade ago. A few weeks later the Chief Merchandising Officer calls me ... "your analysis got me fired". No, the analysis didn't get him fired, he got himself fired because the analysis revealed the fact the merchant was unable to effectively manage a merchandise assortment.

Through the years, the analysis remains relevant and actionable. In 2026, you'd be amazed how few ecommerce brands look at their business this way.

The merchant is failing this brand. New items went from 3,146 three years ago to 2,180 in the past year. This tactic "can" work if new items are more productive. In this case, they're not more productive. New item demand dropped from $14.6 million two years ago to $8.1 million in the past year. Unacceptable.

Look at the price of new items in the past year ... $20.80 vs. $15.23 the year prior. Chaotic management of pricing tiers.

These trends repeat all the time.

These trends get marketers fired all the time. The marketer does nothing wrong (well, the marketer should run this analysis), sales decrease, traffic decreases, and the merchant blames the marketing team for not generating enough traffic. The story has nothing to do with "traffic". It has to do with mismanagement of the merchandise assortment.

When one drills down by category, more truth is revealed.

This is the most popular table in my project work ... by far ... it's not even close. It can be yours, part of the Top 12 Analysis ... with pricing locked in at $12,000 through August 15. Contact me now (kevinh@minethatdata.com) for details.

        

Here's one of the analyses that "some" clients really appreciate. What you see below isn't the full analysis, it's a portion of the table with easy-to-understand metrics.

Every business has a "DNA", a hard-written code that dictates where the brand goes. The brand depicted above possesses the classic "discounting" DNA. It's a lazy, stupid brand (it's from my "Beans: The Internet's Largest Variety Store" study).

As the customer matures, AOV increases from about $42 at a first order to $48 after ten orders. On the surface, this should be a good thing. It's not. We can see that the increase in AOV is manufactured. Look at Average Margin Value (margin dollars per order). We start at $29, loyal customers finish at $31. AOV increases by 14% as the customer becomes more loyal. AMV increases by just 6% as the customer becomes more loyal. The brand (like so many) is creating empty calories ... discounting to get the customer to spend more, not pushing gross margin far enough in the process (and hint - that's what matters).

Look at the percentage of an order that is represented by new merchandise.

• 1st Order = 40%.
• 11th+ Order = 63%.