My Introduction to Pricing Variation

15. August 2012 23:45 by Jay Grossman in   //  Tags: , , ,   //   Comments (0)

When I was 10 or 11 years old (around 1985), I remember going to the local baseball card store with my friend Adam.  He was gung ho to buy some older card of Steve Carlton and he told his father how much it would cost and how much he thought it was worth. It followed with the following back and forth:

Adam’s father: “Why is that card worth $15?”
Adam : “because the printed price guide book says so”
Adam’s father: “Why does that matter? What if I told you it was actually worth $1 or $100? Would it matter?”

At the time, there were printed price books available to me, Current Card Price Guide (updated monthly) and Beckett’s Standard Catalog (issued yearly). The prices listed in these books seemed to be what me and all my friends would go by when buying or trading with one another. We pretty much accepted those values as being correct and tried to maximize our deals based on them.

Adam wound up spending his saved allowance and buying the card. But the exchange got me thinking about what was the right price he should have paid. Could he found it cheaper elsewhere (this was before the Internet, so data and options were limited)? Could he find someone who would pay what he did if he wanted to resell it? I began to realize there was a difference between a retail price (often referred to as blue book) and what a product would actually sell for in an open market scenario.

I had a card in collection that I knew most of my friends wanted, a 1984 Topps Don Mattingly rookie card. So I ran a little experiment, getting a handful of my buddies together who collected and see what was the highest amount I could receive for it. The card had a retail value of $16.50 and that was what it was selling for at the local card store. The highest offer I received was $13.00, which I grudgingly accepted (being a kid, I was hoping for getting the retail price).

I thought about what had happened and discussed it with my dad. I asked myself (and him) why the prices offered were different than the price we had been using as our standard and what we knew it sold for elsewhere. I could understand having to discount the price if there wasn’t high enough demand for it, but every one of the kids in the group were interested and had enough money to pay for it.

My dad explained to me that the price guide book we used was a guide or reference, something interesting to look at but not the authoritative source. He then asked how much I paid for the card. I told him $1.50 the year before and how great a card it was Mattingly was such a popular player. He then let me know that $11.50 profit is really good and I should be happy with it. Obviously he was right, a 700% profit is a great return on any investment.

But I still wondered about the gap between the perceived value and the actual market value. I ran the experiment several more times, sometimes with highly desirable items and sometimes with less desirable items in the same relative price range $5-15. I started to see that the more popular the item, the higher the demand and closer I would get to retail values – but only once getting offered the retail value.

I then tried to add a different wrinkle. I picked a few brand new cards (that none of my friends had)  that were not available in the printed price guides. I really didn’t know what to expect as we had nothing to go off. I actually received 5 to 10 times the values when the cards appeared in the price guides a month later.

It was more than just the cards we collected. I also noticed that ShopRite, Foodtown, and 7-11 had different prices on my favorite cereal and ice cream. 

So what did it all mean? I tried to make sense of it all. I knew demand and what we perceived the value should be had a lot to do with determining, but not really much else. It was not until years later that I would better understand how to determine market values, when I collected a representative sample of sales data and my math skills had progressed beyond elementary school level. I'll certainly touch more on this in future posts.

About the author

Jay Grossman

techie / entrepreneur that enjoys:
 1) my kids + awesome wife
 2) building software projects/products
 3) digging for gold in data sets
 4) my various day jobs
 5) rooting for my Boston sports teams:
    New England PatriotsBoston Red SoxBoston CelticsBoston Bruins

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