Player Development

It should not surprise you in the least bit that I'm in charge of Player Development in my local Pickleball Club, now should it?

We have a program in place to teach players serves, returns of serve, ground strokes, dinking, drop shots, lobs, and overheads. The coursework is similar, but is modified for players who are at a 2.5 level vs. players who are 3.5 or above.

The goal, of course, is to accelerate the development of players. If we can accelerate the development of players, then we have more good players and more good competition and happier club members. Everybody wins!

The concept of Player Development directly ties to two issues that we talk about.

• Customer Development.
• Merchandise Development.

If you can speed up the time between a first purchase and a second purchase, you improve the Development of the Customer and ultimately generate more downstream profit. Yeah, Welcome Programs.

If you can speed up the sales launch of a new item, you improve the Development of the Product and ultimately generate more downstream profit. Yeah, New Product Programs are important ... not just offering 'em but finding creative ways to expose customers to the newness you already have. No, an email with a subject like of "NEW ITEMS" doesn't count.

Take Player Development tactics and apply them to Customers and to Merchandise.

Different Winners

Another challenge some of you are communicating to me is the "different winners" conundrum.

In other words, the type of items that became winners in 2019 changed (for obvious reasons) in 2020.

As inflation hit, some of the items that used to sell well stopped selling as well ... because they became too expensive. So here we are in 2022 and there are now "different winners" populating your business.

Pay attention to "different winners" ... if the items that are now selling best lead to lower repurchase rates, well, you have one additional challenge to consider. But again, you'd prefer that I warn you about this sooner than later, correct?

New Product Nightmare

One of our readers forwarded information regarding new item performance replicated via their "Class Of" report from the 2013 work I performed in Merchandise Forensics. Here's the table (all numbers in millions):

Can you see the problem? The problem is outlined via the colored numbers in the table above. New items did $3.1 million in 2018, $2.8 million in 2019, $4.4 million in the COVID-year of 2020, then an awful $1.9 million last year due to product availability issues, and another awful projection of $1.5 million this year as new products are just hard to source.

When you fail at finding new items, you not only fail this year, you fail for subsequent years as well. In other words, the problem so many of you are telling me about (hard to find new products in our post-COVID supply chain environment) will result in downstream challenges as well.

I know you don't want to hear this message ... but you likely also want to have enough time to do something about it, right?

It's Time Again!!

Four months go by just like a snap of a finger!

It's time again for the next run of the MineThatData Elite Program. This time, in addition to the usual array of analytical masterpieces you enjoy perusing, you'll learn how each of your merchandise categories generate sales ... do sales come from prior category buyers, from cross-over buyers, or from new/reactivated buyers? In 2022 projects it is becoming clear that we don't understand what drives category success - we measure what Google Analytics tells us to measure and as a result we're not understanding how to capitalize on the categories that truly drive business success.

Cost?

• $1,000 for existing Elite Program members.
• $1,800 for first-time Elite Program members.

Data?

• Five years of item-level purchase history, delivered in .csv format.
• June 1, 2017 to May 31, 2022.

Timing?

• Agree to participate by June 10.
• Data delivered to me no later than June 15.
• Results delivered to you no later than June 30.

Inflation and Price Bands

I run regressions based on future spend, dependent upon the price bands the customer previously purchased from in the past year.

The analysis looks something like this.

When prices increase, customer response changes. Customers who buy from Very Low price bands tend to spend less in the future per dollar spent the prior year. Notice the coefficients ... from $0.33 per dollar three years ago to $0.24 two years ago to $0.19 one year ago to $0.16 as of today. Basically, customers buying from Very Low price points are worth half as much as they used to be.

But wait - there's a good story here! Look at Very High price points ... the coefficients were $0.07 per dollar three years ago to $0.08 two years ago to $0.14 one year ago to $0.15 last year.

Let's pretend that customers spent $1,000,000 on Very Low price point items in the past year and $3,000,000 on Very High price point items in the past year.

• Very Low Price Points = (0.16-0.33)*$1,000,000 = ($170,000).
• Very High Price Points = (0.15-0.07)*$3,000,000 = $240,000.

In this simple example, you gained $70,000 of future spend as customers vacated Very Low price points and migrated to Very High Price Points during an inflationary timeframe.

You'd continue the math for Low/Average/High price point bands, and then you know what impact pricing shifts by pricing band are having on customer behavior.

I Brought This Up A Few Weeks Ago, But The Topic Keeps Popping Up Regardless

Let's look at a couple of merchandise categories.

Category A

• Last Year's Buyers Have a 20% Chance of Buying From The Category Next Year.
• If They Buy, They Will Spend $200.00.
• The Gross Margin Of The Items Purchased Next Year = 60%.
• Future Margin Value = 0.20 * $200.00 * 0.60 = $24.00.

Now let's look at Category B

• Last Year's Buyers Have a 23% Chance of Buying From The Category Next Year.
• If They Buy, They Will Spend $187.00.
• The Gross Margin Of The Items Purchased Next Year = 45%.
• Future Margin Value = 0.23 * $187.00 * 0.45 = $19.35

Which category, as a marketer, do you want to develop customers within? And I get it, some of you are going to say "both" just to be combative.

The answer, of course, is Category A. From a sales standpoint, the Category B customer is worth a bit more. But any gain is quickly offset by the difference in gross margin percentage (60% vs. 45%).

For every one of your categories, make sure you know the following:

• The fraction of last year's buyers who will purchase again next year within the category.
• How much the customer will spend within the category if the customer repurchases.
• Expected gross margin percentage next year.

Then rank-order your categories from highest Future Margin Value (FMV) to lowest.

Then prioritize your marketing efforts around these differences.

Stop wasting marketing dollars on categories that do not deliver sufficient Future Margin Value.

Tradeoffs

Let's say your average price per item sold is $40.00. Your average cost of goods is $20.00. Your annual rebuy rate is 30%, if a customer purchases the customer spends $160.

• Average Future Margin (AFM) = 0.30 * ($160 * (1 - 0.50)) = $24.00.

Now your suppliers tell you that your cost of goods increases to $24.00. If you keep prices where they are, your Average Future Margin changes.

• Average Future Margin (AFM) = 0.30 * ($160 * (1 - 0.60)) = $19.20.

Nobody likes that scenario. Your CFO demands that you increase prices by 20%. Two things happen in this scenario.

• Rebuy Rates Decrease by 20%.
• Spend per Repurchaser increases by 10%.

Here is what Average Future Margin looks like:

• Average Future Margin (AFM) = (0.30 * 0.80) * (($160 * 1.1) * (1 - 0.50)) = $21.12.

Two things happen here.

• You recoup some of your AFM via the price increase.
• You hurt your Customer Development efforts because your rebuy rate dips from 30% to 24%, meaning you'll have fewer customers next year, meaning you'll have less profit next year.

These are the tradeoffs every single one of you should be evaluating.

I've been amazed, in the past year, how many of you have emailed me to tell me you are not evaluating the scenarios.