Reposted From LinkedIn

Ok, here's something I posted over on LinkedIn. Send me an email with your answers, or leave a comment over there with your thoughts.

This topic came up earlier today and generally comes up every two weeks - it's a topic that is challenging for my client base to deal with effectively. 

A company generates 40% of annual new customers in the late November - mid December timeframe. An analysis of new customers illustrates the following:

Jan - October Newbies (60,000): Profit per New Customer = ($4.00). Year 1 Future Profit = $12.00. Year 2 Future Profit = $10.00. Year 3 Future Profit = $8.00. Year 4 Future Profit = $6.00. Year 5 Future Profit = $5.00. Total Five Year Future Profit = $41.00.

November 1 - December 31 Newbies (40,000): Profit per New Customer = $2.00. Year 1 Future Profit = $7.00. Year 2 Future Profit = $5.00. Year 3 Future Profit = $3.50. Year 4 Future Profit = $2.50. Year 5 Future Profit = $1.75. Total Five Year Future Profit = $19.75.

A few questions for you, the intrepid marketer.

Is it a good idea to acquire new customers in November/December (hint - the answer is yes)?

From a marketing standpoint, how should you as an e-commerce marketer treat new customers acquired in November/December? Should these customers be treated differently? If the answer is yes, explain how you would treat these customers differently?

Should you ever not acquire a customer if you can acquire the customer profitably at the point of acquisition?

Are you able to see these fundamental differences in customer behavior using ROAS reporting? If the answer is no, what do you need to be able to see these fundamental differences in customer behavior?

In this case, the brand lost money acquiring customers from January - October. How long of a payback window do you believe is acceptable to lose money acquiring a customer?

Discuss!

Investing Marketing Dollars

All sorts of things impact your marketing investment in customers ... you already know this.

But we should also talk about some of the things we don't always consider.

In Category Development work, we know that customers acquired in some categories clearly outperform customers acquired in other categories in the future.

In this example, the "good" category brings in fewer customers for the same ad cost, but delivers customers with higher rebuy rates and higher spend per repurchaser metrics.

As a consequence, when comparing acquisition profit and subsequent twelve-month profit, this brand is better off acquiring customers from the "good category" - the brand nets six (6) fewer customers at a profit (loss) per new customer that is nearly four dollars worse ... however, after acquisition the "good category" delivers customers worth $6 more in the next year.

The tradeoff is obviously worth it!

Know which categories deliver customers with good future value ... then take action upon what you learn, ok?

It's Just So Interesting!

Here is a set of Category Development metrics for a category. It's just so interesting to parse this category!

Let's just go to the bottom of the table for today. The final three rows tell us a story. We observe the percentage of annual demand that comes from three customer groups ... the top row represents customers who bought from the category the year prior ... the second row represents customers who bought the year prior but not from the category ... the third row represents new/reactivated customers.

What do you see here?

This category does not generate sales from customers buying from the category the year prior, does it? 4%? It's virtually nothing.

47% of demand last year came from customers who, the year prior, bought from the brand but not the category. This category is fueled by customers previously buying from other categories.

49% of demand last year came from new/reactivated customers. This is a category that prospects consider.

Let's pretend you work in marketing, and are responsible for managing this category. Tell me what your marketing strategy is for this category?

Just Read The Text Here

If I were writing this post back in 2006, I'd offer one thousand of the most scathing words in the English language about the image below.

But it is 2023 and I'm older and wiser. So I present the following "ad" without comment:

So What Do You Do?

I talked yesterday about how Chat GPT, the popular AI tool, offered a "trained opinion" that the value of my projects were worth between a few thousand dollars and tens of thousands of dollars (click here).

We're headed down an interesting path.

Assume you are a digital analyst ... you grew up in the era of Google Analytics. Five years from now or ten years from now when the software application (which put CRM-style analysts out of work) is tied in with AI and reports are automatically written by the app, what will you do?

Most marketing analytics are going to be automated by AI. You won't need an analyst when the AI can draw comparable conclusions. Yeah, I can hear you yelling at me already ... "we can't be replaced, we provide too much value." You replaced the prior generation ... some poor IT guy writing C++ or Easytrieve was displaced by you ... you will be displaced by what comes next. That's how capitalism works.

Marketing and Marketing Analytics can easily be automated, and will be automated.

Merchandise Analytics can be automated, but is fluid and changing (especially in fashion) and will be automated far later in the process than Marketing Analytics will be. Inventory Management will be automated. Knowing what is likely to sell next? Knowing which categories matter most and are interdependent upon each other? That problem will be solved later. It will be solved, but later.

So if you want to buy yourself some time?

Focus on merchandise analytics. Your company needs you, and you can find a niche that protects you for awhile.

P.S.:  I get it, the automation might take 20 years to happen. Most likely. But what if it happens in four years? Start planning, folks. You can adapt!

Chat GPT / Category Development

I asked Chat GPT (a popular AI tool) the following question:

How much should a consultant charge for a Category Development project similar to what Kevin Hillstrom performs?

This was the final paragraph in the answer.

Given these factors, the fees for a Category Development project similar to what Kevin Hillstrom performs can range from a few thousand dollars to tens of thousands of dollars. It's important to discuss the specific details of the project with the consultant and negotiate a fee that both parties are comfortable with.

When a software application determines your value as a consultant (and this won't happen soon, but it is coming), tell me how as a consultant you overcome what the algorithm says you are worth?

Now take this a step further ... you write copy for Macy's. How are you going to defend your value against an application custom-built to write compelling copy to move products on an e-commerce site?

The automation of your warehouses ... a process you've all been through ... is coming for professional jobs. 

Special Catalog QuickScore Offer For Readers!

You are familiar with my Catalog QuickScores project.

You are familiar with my Category Development project work (click here).

So let's try something, based on your feedback.

Based on what I wrote last week (click here), let's combine the two projects in a way ... I will perform a mini-Category Development project that results in a Catalog QuickScore for each category. You can then combine/weight each score based on the composition of upcoming catalogs.

Contact me (kevinh@minethatdata.com or 206-853-8278) or visit here for additional details, price, file formats, and data requirements. Let's get busy on a unique/hybrid project, ok?