Kevin Hillstrom: MineThatData

Teams

Sometimes content and ideas just coalesce into a meaningful narrative.

I'm reading Prof. G's Friday newsletter about traveling to the Moon and "ding" everything came together. He talked about the Artemis 2 mission. On the one end, we have the AI gurus and those backing 'em with investments ... suggesting AI will bring the end of work as we know it and the only thing we can do is trust those who are bringing the end of work to us to ... well ... to do who knows what.

That's one end.

There's the other end of the spectrum. That's the end you are on.

You are part of an ecosystem of Teams.

Your marketing team is part of that ecosystem.

Your merchandising team is part of that ecosystem.

Other teams support marketing or merchandising ... creative, IT, website ops.

Your teams are supported by vendor-based teams ... really important people. They manage social media or your search budget (as examples). They help execute your email marketing program.

Teams aren't only represented by people. Your categories represent "teams" of product working together to support your customer. Your marketing channels represent "teams" that support the products that support your customer.

All these Teams interact. With each other. With your customers.

As every new technology evolves and advances, it seeks to become a Team that interacts with your existing human-based Teams and marketing/merchandising Teams.

The metrics we have to measure Teams are woefully inadequate. We measure the ROAS of digital advertising without regard to the effectiveness of the Team of humans managing the process or the long-term payback of digital advertising. FACEBOOK ROAS IS 3.43 THIS WEEK, DOWN 8%. So what? What if ROAS is down 8% but the Team of humans managing the process prevented ROAS from being -16%? I'll take the the Team of humans all day long. But how are you measuring the Team of humans?

What about a lousy Leader managing a category that is growing by 15% industry-wide? Is the lousy Leader responsible for good performance? Is Amazon responsible for developing a great marketplace that causes 5% of the 15% increase?

I'm going to frame discussions in terms of Teams and Storytelling in the near term. It has become painfully clear that we don't have a framework for thinking about the importance of Teams ... and not just human Teams ... we have Teams of categories that work together, we have Teams of marketing channels that work together. We need to do a better job before AI does our jobs for us.

Weird Categories

Every one of you managed Weird Categories.

In the data I'm analyzing, a customer could buy from a category last year or not ... then buy other merchandise (or not). This creates three twelve-month buyer segments. I segment based on behavior 13-24 months ago, then measure rebuy rates in the past year.

Here's what a normal category looks like:

Buy From Category 2 and Buy From Anything Else = 15.2% Category Rebuy Rate.
Buy From Category 2 no Purchase From Anything Else = 8.1% Category Rebuy Rate.
No Order From Category 2 and Buy From Anything Else = 2.4% Category Rebuy Rate.

Normal categories benefit from purchases in other categories, but benefit most from a purchase within the category. Duh!

Here's what a weird category looks like.

Buy From Category 6 and Buy From Anything Else = 12.4% Category Rebuy Rate.
Buy From Category 6 no Purchase From Anything Else = 16.2% Category Rebuy Rate.
No Order From Category 6 and Buy From Anything Else = 0.8% Category Rebuy Rate.

Very weird. The customer is less likely to repurchase from the category if the customer buys something else in the past year from other categories ... and ... the customer has virtually no chance of buying from Category 6 if the customer only bought from other categories last year.

If you are responsible for Category 6, you don't send batch-and-blast emails to customers who haven't bought from Category 6 very often because those customers just don't want to buy from this Weird Category! There are seasons that likely cause customers to consider Category 6, that's when you try to cross the customer over into this category.

Heavy Lifting

Every category plays a role in your customer/brand ecosystem.

Category 17 - the highest sales category - is responsible for bringing new customers to this brand. This category truly does the heavy lifting for the brand.

Loyal customers are attracted to categories 4 / 6 / 7 / 13.

There's a natural ebb and flow to your business. Customers enter via certain categories, develop in another set of categories, then spend their loyal efforts across a handful of categories. Knowing this ebb and flow allows you to calibrate your marketing efforts. It's stuff you need to know, correct?

New Logo

There are things a marketer can do to improve business performance. A new logo is not one of them.

At worst case, you become Cracker Barrel. At best case, absolutely nothing happens. Either way, dollars are spent and time is wasted.

Thirty years ago I worked for a Sr. VP who suggested that business was 70% merchandise, 20% marketing and 10% creative. If marketing is 20% of the reason why a business is successful (it's more than that, by the way, not a lot more, but more), the tactics you choose to work on define whether sales are +10% or -10% ... in reality, they're the reason why your business is profitable or unprofitable. Yes, correct, it's that important. All of the little things you should be working on add up and make the difference between profit/loss.

In other words, you can't waste your energy on a logo.

P.S.: Yes, I realize I just offended 40% of you.

Conflicting Data

As you've been told, I write a Weather Newsletter. I also write a Pickleball Newsletter, but that's a topic for another day.

About three weeks ago an epic heatwave gripped the Western third of the country. I received two themes of feedback.

This is what happens when climate change is amplified. The future is worse than this.
This weather pattern is a normal weather pattern with an extreme outcome and has nothing to do with climate change.

Both sides are very passionate about their argument. They're quick to educate, they're in some ways overconfident ... they surely believe they are "right".

Forty years of data analysis suggest that humans struggle with conflicting data. We struggle with feedback loops. We struggle with interactions.

It happens in ecommerce. Remember our Category Impact table.

Category 17 is the biggest sales driver (sales are not shared in this table). It is also the biggest source of new customers. It also negatively impacts Category 6. This means when Category 17 does a good job, Category 17 hurts Category 6.

Assume you are the CEO of this brand. The merchant in charge of Category 17 looks great. She's responsible for a high-volume category that brings in new customers. And yet ... every time she does a good job, the poor merchant in charge of Category 6 looks bad. His sales decrease.

Should the CEO fire the guy running Category 6 if sales decline in Category 6? Or is the guy running Category 6 at the mercy of the woman running Category 17?

It's a nuanced situation, isn't it?

Just like weather / climate is a nuanced situation.

Obviously, you need the right data to even consider a reasonable response.

Almost none of you have the data to answer this question.