Kevin Hillstrom: MineThatData

Case Study: Which Categories Bring In Valuable Customers?

I ran an analysis, measuring how much future value (demand/sales over the next twelve months) a customer will generate after being acquired within each merchandise category. If a category does a great job of bringing in new customers and those customers don't spend money in the future, well, we've got a problem.

Here's a summary table of what I learned.

Apparel Tops is a high-volume category, and fortunately it is a top-three category in terms of future value (NY Value).

Notice that most categories generate customers that buy from nearly two categories in the next year if the customer repurchases.

However ...

However, there is a problem in this table.

When a customer is acquired, regardless of category, the customer spends very little in the next year. Seasonal is worst ($6.40) ... Outside is best ($11.33).

In other words, there is very little customer loyalty associated with this brand. Newly acquired customers have a low chance of buying in the first year with the brand (between 14% and 18%), and if they buy the don't spend much ($46.00 to $63.00).

This is one of those moments when the Consultant realizes s/he is about to anger people. Yes, you can run a profitable business with a customer base that simply doesn't spend much, but it means everything regarding the p&l is dependent upon generating profit off of a first purchase.

Tomorrow, I'll share what the conversation looked like regarding exceptionally low future value metrics.

Brief Case Study Break: What Your Media Might Look Like In The Future

I'm writing this back on Sunday night.

Here are the two shows I just watched on YouTube.

The former is the trendy stuff ... well produced, powerful people explaining powerful issues. It's easy to see how people are attracted to the content. Unfortunately, you'll never appear on this show. It's the evolution of a Ted Talk pushed 20 years into the future.

The latter is your future. That's Nieve. About 15 years ago, Rog and Davo brought the Premier League to me. Rog made it accessible to somebody who only saw a handful of televised Premier League fixtures each year. His storytelling was all audio back then, a completely different style of storytelling, but appropriate for his (my) generation.

Nieve is able to take the concepts of the Men in Blazers and apply them to the entire English Football Pyramid, via video ... I mean, in the clip above, she's at the final game of the National League season (5th tier), and she captured the pure madness and drama of the last ten minutes of that match. Poor Rochdale (hint - it would end up a fairy tale for them today at Wembley Stadium).

She exudes raw, unadulterated humanity. There is no way AI is going to replace her, she's a force of nature, and if you have any empathy for the fans Exeter City FC, Nieve is going to help bring that empathy to you via humor and sadness in a way that modern "polished" / "scrubbed" activities cannot possibly achieve.

Nieve is your future. I realized you work for "Beans: The Internet's Only Variety Store". But every single one of you has a "Nieve" working for your brand ... a person uniquely qualified to bring storytelling to your customers. I am always amazed that almost none of you are willing to take that risk, and if you are willing to take the risk you shut it down long before anything positive could happen.

Instead of worrying about AI, why not apply stuff AI cannot possibly mimic (like a parrot) to your marketing efforts?

Case Study: Dispelling Legends

At "Beans: The Internet's Only Variety Store" there is a legend ... that a broad assortment "holds the brand together".

It's been my opinion that Leadership is violating this "legend", assuming the legend is true.

So ... I performed a classic Factor Analysis to demonstrate categories that customers like to purchase from. If dots on the image below are close together, customers like to purchase from the categories "near each other" on the image. If categories are far apart, it means different customers prefer the categories.

Here's the image from the Factor Analysis.

There appear to be three reasons why customers buy from this brand.

Apparel Tops: We know this is a high-volume category, and it is all by itself meaning that many customers ONLY purchase Apparel Tops.
Home / Outside: There are clearly customers who view this brand as a Home / Outside brand. There's some bad news here ... some customers clearly come for Home / Outside, but a few weeks ago I showed you that Home decreased from $6.0 million to $2.9 million over four years. No bueno.
Everything Else: There are customers who view this brand as an eclectic mix of categories (the right/middle side of the image).

Of interest ... Apparel Bottoms does not align with Apparel Tops ... it aligns with "everything else".

I have to analyze new customers by these three groupings ... if the future value of a customer who aligns with "Everything Else" is higher than other categories, we have a lot of freedom as marketers to be clever. If "Apparel Tops" drives new customers, we have to concede that those customers might not appreciate the "entire assortment". Messaging to Leadership doesn't always go well on that topic.

P.S.: If you like what you are seeing here and are interested in a Category/Customer centric analysis, send me an email (kevinh@minethatdata.com).

Case Study: Customer Response to a Dying Category

We talked about Apparel Tops yesterday. We've previously mentioned that Fashion is a dying category, largely because the merchandising team appears to be killing the category. How does customer response change when a category is being killed off?

Similar to Apparel Tops, most demand comes from new/reactivated category buyers (80%). Again, the marketer has to know this, because the marketing plan has to include a lot of $$$ and attention in awareness (organic social) and search (product listing ads). If the marketer doesn't acknowledge this fact and act upon it, well, the marketer is equally culpable with the merchant at killing off the category.

This likely applies to your business as well. Most of your categories offer products that largely appeal to new/reactivated buyers and/or prospects. A marketing department that does not understand this dynamic is a marketing department that sub-optimizes the potential of the category/business.

Ok, what have the merchandising team done with their assortment-contraction initiative?

Rebuy Rates over time.

12-Month Fashion Buyers = 2.0% to 3.0% to 2.8% to 1.5%.
All Other 12-Month Buyers = 1.6% to 2.5% to 2.2% to 1.2%.

What happened in the past year is telling ... 40% or greater decreases in rebuy rates (albeit very low rebuy rates). With less merchandise available, existing buyers become less likely to repurchase.

The astute reader should say "Hey, Goober, you just told us that almost all demand comes from new/reactivated buyers, please tell me how many new/reactivated buyers the category had over time".

I can do that.

36,236 to 54,438 to 52,418 to 27,308.

We see the same (ugly) trend with new/reactivated buyers ... counts are down nearly 50%.

This comes up repeatedly in my work ... if you trim the assortment, you harm demand/sales. If you grow the assortment, you increase demand/sales but introduce other challenges (inventory / liquidations / margin erosion).

I'm going to hold off on communicating this fact to Paisley Ingram (the owner) until have a few more data points. I need to find a simple way to tell a complicated story.

Case Study: Customer Response To Merchandising Changes

Let's approach this discussion in bite-sized pieces.

This table reviews repurchase activity for Apparel Tops ... the best-selling category that Beans: The Internet's Only Variety Store sells.

Yes, there's a lot going on here.

An introductory tidbit ... in the past year, 79% of demand in Apparel Tops comes from customers who haven't bought in at least a year or are first-time buyers. Only 16% of demand came from last year's Apparel Tops customers and just 5% of demand came from other twelve-month buyers.

If you are the marketer trying to grow Apparel Tops (your best-selling category), what might your approach be?

Awareness (organic social) and Search (product listing ads).

You could try to squeeze more out of existing buyers, but what is the point? If your efforts were positive and increased sales among existing Apparel Tops buyers by 10%, total demand would grow by 16%*10% = 1.6% ... meaningless.

When a merchant tells you that the marketer is not getting her product in front of the "right customers", the merchants is both wrong and right at the same time.

Wrong, in that the merchant usually has minimal experience with marketing techniques.
Right, in that most categories benefit from exposure to prospects who haven't bought the product previously.

Pay attention to rebuy rates over time.

16% to 15% to 14% to 11% for existing buyers.
7% to 6% to 6% to 4% among all other twelve-month buyers.

This is a mystery that requires professional levels of communication.

The category is stable because new/reactivated customers are buying the product.
The category is stable because new/existing items are being managed reasonably.
The housefile ... twelve-month buyers ... are increasingly less likely to buy this product, but their share of total demand is not sufficient for management to notice there is a problem.