Catalog QuickScores and Gift Buyers

One of the challenges faced by Catalog Brands is dealing with a Gift Buyer. A Category Development project shows that these customers are unlikely to purchase the rest of the year.

Pretend that Gifts are 10% of a July catalog ... while all other merchandise is 90% of the catalog.

Pretend that we have a customer with a Gift QuickScore of $70.00 and a General Merchandise QuickScore of $30.00. Pretend that Gross Margin Percentages are 50% for all merchandise.

• Catalog QuickScore for Gifts = $70.00 * 10% of Catalog * 50% Margin = $3.50.
• Catalog QuickScore for All Other Merch = $30.00 * 90% of Catalog * 50% Margin = $13.50.
• Total Catalog QuickScore = $3.50 + $13.50 = $17.00.

Now, pretend we have a customer with a Gift QuickScore of $8.00 and a General Merchandise Quick Score of $92.00. Same Gross Margin Percentage of 50%.

• Catalog QuickScore for Gifts = $8.00 * 10% of Catalog * 50% Margin = $0.40.
• Catalog QuickScore for All Other Merch = $92.00 * 90% of Catalog * 50% Margin = $41.40.
• Total Catalog QuickScore = $0.40 + $41.40 = $41.80.

Mind you ... both customers are exactly equal in terms of quality ... but "what" you offer paired with "what" the customer likes to purchase results in two customers with two very different levels of value.

Seems like this is something you'd be interested in knowing, right?

Catalog Brands: Applying QuickScores to Category Development

Let's assume you have five (5) Merchandise Categories ... we'll assume something simple.

• Mens
• Womens
• Kids
• Gifts
• Accessories

Let's assume that the gross margin percentages for each category are predicted as follows:

• 60% for Mens
• 62% for Womens
• 55% for Kids
• 35% for Gifts
• 50% for Accessories

Ok. For many of you, I create QuickScores for each merchandise category. The QuickScore tells us how much you'll spend in each category. Now let's assume you are a Catalog Brand, and you have the following percentages of merchandise being offered by catalog for your July catalog.

• 20% Mens
• 30% Womens
• 10% Kids
• 20% Gifts
• 20% Accessories

Yeah, lots of percentages.

Pretend we have the following QuickScores for one customer ... one that loves Accessories:

• $20.00 for Mens.
• $30.00 for Womens.
• $5.00 for Kids.
• $5.00 for Gifts.
• $60.00 for Accessories.

What is an appropriate QuickScore for this Catalog?

• Mens = $20.00 * 20% Mens * 60% Gross Margin = $2.40 of Margin.
• Womens = $30.00 * 30% Womens * 62% Gross Margin = $5.58 of Margin.
• Kids = $5.00 * 10% Kids * 55% Gross Margin = $0.28 of Margin.
• Gifts = $5.00 * 20% Gifts * 35% Gross Margin = $0.35 of Margin.
• Accessories = $60.00 * 20% Accessories * 50% Gross Margin = $6.00.
• Gross Margin Score = $2.40 + $5.58 + $0.28 + $0.35 + $6.00 = $14.61.

Now, pretend we have the following QuickScores for another customer ... one that loves Womens:

• $10.00 for Mens.
• $90.00 for Womens.
• $10.00 for Kids.
• $5.00 for Gifts.
• $5.00 for Accessories.

What is an appropriate QuickScore for this Catalog?

• Mens = $10.00 * 20% Mens * 60% Gross Margin = $1.20 of Margin.
• Womens = $90.00 * 30% Womens * 62% Gross Margin = $16.74 of Margin.
• Kids = $10.00 * 10% Kids * 55% Gross Margin = $0.55 of Margin.
• Gifts = $5.00 * 20% Gifts * 35% Gross Margin = $0.35 of Margin.
• Accessories = $5.00 * 20% Accessories * 50% Gross Margin = $0.50.
• Gross Margin Score = $1.20 + $16.74 + $0.55 + $0.35 + $0.50 = $19.34.

These are two customers that have exactly equal future value ... but one customer skews to Women, and the upcoming catalog is also skewed to Women. Therefore, the latter customer is much more valuable.

When we develop categories, we make conscious choices. Sometimes we use models to determine who to send catalogs to. Sometimes those models have an "overall" score that does not take categories into account. If we align categories with gross margins per category and space allocated within the catalog, we obtain a different outcome.

Unprofitability of the Undifferentiated Middle

Here's what "the undifferentiated middle" looks like when you evaluate metrics down to profitability at a customer level.

There are problems when you increase price points to cover cost of goods increases.

Here, we see that rebuy rates decreased from 35.0% to 32.5%. That's a consequence to increasing prices to cover cost of goods increases.

We see that units per repurchaser decreased from 5.00 per year to 4.57 per year. When the customer purchases, the customer buys fewer items to compensate for higher prices.

We see that the price per item purchased increased from $30.00 to $34.50 ... covering the cost of goods sold per item from $12.00 to $16.50. In this case, the brand simply passed the cost increase along to the customer.

However, the mix of fewer units times a higher price yields an increase in spend ... from $150 per year to $157.50. So yes, this brand got those who purchased to spend more. Unfortunately, fewer customers purchased ... so the math is about to fail.

Under the 2021 business model, we generate $52.50 of demand per customer ... under the 2023 business model we generate $51.19 of demand per customer (rebuy rate * spend per repurchaser gets us to $51.19). The higher cost of goods sold sinks the p&l, leaving us with $9.93 of profit today vs. $14.13 two years ago.

This is where the undifferentiated middle leaves us when we have a cost of goods increase.

No loyalty program fixes this.

A robust customer acquisition program fixes this challenge ... but you need a lot more new customers than you initially think.

This is why we turn to categories ... we have categories that yield more profit than average and have minimal cost of goods increases. Those become categories we have to feature, especially among new customers who may become attached to those categories going forward.

World Going in Three Different Directions

People grumble about dollar stores ... but those stores are the logical extension of the Walmart/Target models. If Walmart found a way to structure the Price/COGS relationship to their advantage, it makes logical sense that somebody else would find a way to use the Price/COGS relationship against both grocery stores and Walmart.

How about you? Your business?

Retail and e-commerce move in three different directions.

1. Lowest Possible Price (dollar stores, Walmart, Amazon).
2. Highest Possible Gross Margin Differential (fashion / experiences).
3. The Undifferentiated Middle (most of us).

You are going to tell me you cannot run a business at the lowest possible price.

You are going to tell me you cannot run a business that is fashion-centric with great experiences.

This means you are going to have challenges. It doesn't mean you cannot be successful, but you are constantly pressured by (1) and (2) above, on opposite ends of the spectrum. It's like a rubber band that you pull on each end until it breaks in the middle.

Tomorrow we'll look at a profit-and-loss statement at a customer level, showing what "the undifferentiated middle" looks like.

Dollar Stores

You aren't going to read about or hear a lot about dollar stores in the retail gurusphere.

So read this (click here).

The price point / cost of goods relationship is generally overlooked by the retail gurusphere. It isn't overlooked in a Category Development project. There are clear relationships identified in each project, and profitability is ultimately defined by the relationship.

More on the relationship tomorrow.

The DTC Index - And Giving Away Free Information

You read this and subscribe to this newsletter, correct (click here)?

Pay attention to what the author says about Marginal aMER. In my simulation / forecasting work, the relationship described comes through when measuring profit per new customer (though the relationship isn't identical to what is illustrated here).

P.S.:  A reader recently responded that he wanted "more free stuff". If you are that reader, click on the link and subscribe to their free stuff.

P.P.S.:  This is interesting. There is a clear relationship between giving away free insights and me staying in business. The relationship looks something like this ... the X-Axis represents the percentage of my blog posts where I give away my methodology for free ... the Y-Axis represents the percentage of annual income I generate as a result.

In other words, if I give away my methodology in 20% to 40% of my posts, I maximize my annual income. Give away everything in every post? I lose about half of my annual income. If I give you more free information, I eventually make less income and I'm out of business. Such is the relationship between a business and customers. Always remember that not all customers are customers ... some are consumers ... and there is a big difference. You make your profit off of customers, you generate improved vanity metrics from consumers.

An Interconnected Business

We've talked about your Category Development situation as being similar to a solar system ... you have a Star, you have Planets that rotate around the Star, you have Moons that rotate around Planets, you have Asteroid Belts (broken categories), and you have Comets that infrequently interact with your solar system (i.e. Gifts at Christmas).

In other words, your business is interconnected.

And when you fail in one category, you impact other categories.

If your Star category struggles, the struggles spill over into all other categories.

If a Planet category struggles, the Moons will struggle.

If a Comet category struggles? Meh.

But make no mistake. Your business is interconnected, and you are doing things that greatly help or hurt other categories.