Eyeonthewall
Let me explain my points, but first let me say that I thought as you did when I first started my E-bay business. I also want to ask you are you a full time E-bay seller?
But here goes.
I think you need first to distinguish between auction sales and fixed price retail BIN listings because they both work slightly differently. The first blush gut reaction is to think that because E-bay makes a 6.2% final value fee on the final selling price that they are sufficiently incentivized to not interfere in the display of items and to give items the maximum exposure on their platform. However, the final value fee on the overall amount of merchandise sold on the entire platform is does not change for fixed fee sales, as I will show. For fixed price sellers a more important revenue source is the monthly store fee. There is also the advertising fees charged to all the third party advertisers who clog up the site with ads, and now promoted listing fees on BIN listings. For now, I will focus on the store fees only.
The idea that E-bay will show all items and maximize profit doing so is based on the assumption that its buyer base grows at the same rate or better than gross merchandise value (GMV) and the number of sellers. However, if you look back over the last 10 years you will realize that E-bay has done very little if anything to advertise or attract new buyers, coasting on its established reputation. It's share price has been stagnant for several years now, despite constant fee increases and constant new schemes to introduce more types of fees.
This would not be happening if E-bay's buyer base were growing. What you would see instead is growth in their stock price, and sellers would be growing as well. I know that you think that all the hundreds of sellers who voice their complaints online are just a bunch of whiners. Indeed some are, but don't you think that is an overly simplistic way to look at them? Isn't it both possible and probable that if thousands of sellers make the same complaint and they are operating across multiple product categories that maybe there is at least a kernel of truth to what they are saying, or that maybe it is least worthy of some consideration?
If you accept the idea that the buyer base is at best stagnant and at worst shrinking, that is a game changer. Because now, in order to maximize revenue and profit, E-bay must look at which revenue source provides the most profit and ensure that source is optimized. Let's do a thought experiment here. Let's suppose that:
1. There are 1 million buyers with $10 each to spend, so $10 million every day at the start of the year. By the end of the year, there are 1.1 million buyers with $10 each to spend, so $11 million.
2. At the start of the year, there are 100,000 sellers each listing 500 items, for an average of $10 each. By the end of the year there are now 125,000 sellers, each listing 500 items for an average of $10 each.
3. E-bay's final value fee is 5% on each sale and each seller pays E-bay on average $50 a month to sell there, before the final value fee.
Ignoring the money E-bay earns from advertising, the amount of monthly revenue generated by E-bay from the store fees is:
$50 x 100,000 = $5,000,000 at the beginning of the year, and
$50 x 125,000 = $6,250,000 at the end of the year.
The growth in the number of sellers alone has increased E-bay's bottom line by $1,250,000 alone, before a single item has been sold.
At the beginning of the year there is gross merchandise listed of:
500 x 100,000 x $10 = $500,000,000 and $10 million of potential sales a day.
At the end of the year there is gross merchandise listed of:
500 x 125,000 x $10 = $625,000,000 and $11 million of potential sales a day.
The amount of merchandise has exploded relative to the amount of sales dollars available to absorb it. Total inventory has increased 25% while the total sales dollars available to absorb it has only increased by 10%.
Now, lets suppose at the beginning of the year, that the $10 million spent by buyers is spent as follows:
20,000 sellers sell 4 items each for $10 = $800,000
5,000 sellers sell 20 items a day for $10 = $1,000,000
40,000 sellers sell 6 items a day for $10 = $2,400,000
10,000 sellers sell 10 items a day for $10 = $1,000,000
5,000 sellers sell 40 items a day for $10 = $2,000,000
20,000 sellers sell 14 items a day for $10 = $2,800,000
E-bay generates 5% = $500,000 in final value fees per day, which in a month is 15,000,000 - higher than the store fees.
Now, if at the end of the year, the number of sellers has increased by 25%, but the amount of buyer dollars has not kept pace, then, in order to achieve the same sales results for the seller group as a whole, a lot more than $11 million is required:
If 20% of sellers sold 4 items at $10 each, then now 20% of 125,000 sellers is 25,000 sellers. 4 items each at $10 = $1,000,000
If 5% sold 20 items at $10, there are now 5% x 125,000 = 6,250 sellers. 20 items each at $10 = $1,250,000.
If 40% sold 6 items a day at $10, then there are now 40% x 125,000 = 50,000 sellers. 6 items a day at $10 = $3,000,000
If 10% sold 10 items a day at $10, then there are now 10% x 125,000 = 12,500 sellers. 10 items a day at $10 = $1,250,000.
If 5% sold 40 items a day at $10, then there are now 5% x 125,000 = 6,250 sellers. 40 items a day at $10 = $2,500,000.
If the remaining 20% sold 14 items a day, then there are now 20% x 125,000 = 25,000 sellers. 14 items a day at $10 = $3,500,000.
So, the total purchasing dollars required to support the same relative sales levels, on average, per seller, being the totals of the above amounts is $12.5 million = $1.5 million more than the existing customer base at the end of the year is willing to spend.
At this point, E-bay is in a position where it might start losing revenue from sellers if sellers who sell too little decide to close shop. For the purposes of this example, let's suppose that 4 items a day is the absolute minimum daily sales that will keep a seller loyal and paying the monthly fee. So, unless E-bay does something to re-distribute the sales among the seller base, they are going to start losing the sellers at the bottom. At the end of the year, there are 25,000 sellers in this group paying on average $1,250,000 per month. If E-bay allows all the other sellers to make the same sales then it stands to lose $1,250,000 that it could have made if it took actions to effectively re-distribute the $1,500,000 shortfall from the higher performing sellers to the lower performing ones.
If it does this, it will still earn the exact same final value fees that it made before. In fact, it will now earn 5% on the entire $11 million each day. But in addition, it will have maximized its revenue.
The sellers at the bottom who only sold 2 or 6 items may not notice any change, but the ones at the top will. If E-bay takes the entire $1.5 million from the top tier, those sellers will, on average experience a decline in sales from 40 items a day down to 16 items, an over 50% decline. They will be bitter, frustrated, angry but they will not be at the point where they close their store.
How does E-bay accomplish this re-distribution? By limiting the exposure of items being sold by the top performing sellers, while at the same time bumping those listings up that are owned by the bottom tier sellers that it does not want to lose.
That is an example of a seller that has a store and pays a store fee. Now, let's look at an auction involving 7 identical stamps. Let's say in one week, there are 7 Bluenoses listed, all of which calalogue $400:
1. Bluenose 1 has a start price of $0.01, and a listing fee of $0.25.
2. Bluenose 2 has a start price of $10 and a listing fee of $2.
3. Bluenose 3 has a start price of $25 and a listing fee of $3.
4. Bluenose 4 has a start price of $99 and a listing fee of $8.
5. Bluenose 5 has a start price of $0.99 and a listing fee of $0.50.
6. Bluenose 6 has a start price of $150 and a listing fee of $12.
7. Bluenose 7 has a start price of $125 and a listing fee of $10.
Lets say that in that 2 week period there are 7 bidders interested in bidding on a bluenose. Bidder 1 is willing to pay $250, bidder 2 is willing to pay $150, bidder 3 is willing to pay $50, bidder 4 is willing to pay the full $400, while bidders 5, 6 and 7 are only willing to pay $125. Let's suppose further that the bidders go online at roughly the same time, one each day, and the bluenoses are listed each day one at a time. Lets suppose further that once a bidder starts bidding on a bluenose that he doesn't look for any more bluenose auctions unless he has had to drop out because he's reached his maximum bid. E-bay earns the usual 5% FVF on the sale.
If all 7 bluenoses receive at least the minimum bid, and sell, then E-bay will earn $35.75 in listing fees plus the final value fees. If all the bluenoses sell for the minimum bid, then E-bay earns $410.24 x 5% = $20.51.
Now, if the first bluenose is allowed to remain visible for the entire 7 days on the first day it received one bid, from the first bidder of say $100, but only shows as $0.01. on day 2, the second bluenose appears, but it has a higher start price than the first one, so the second bidder places his bid on the first bluenose and raises it to $150 and drops out because he is overbid. So he bids $150 on bluenose 2. On day 3, the third bluenose appears and now bidder 3 sees:
Bluenose 1 for $150, Bluenose 2 for $10 and Bluenose 3 for $25. So naturally, all things being equal, he sees that there are no bids on bluenose 3 and bids on that, bidding the full $50, but only showing $25.
So, now on day 4, bidder 4 sees:
Bluenose 1 for $150, Bluenose 2 for $10, Bluenose 3 for $25 and bluenose 4 for $99. He decides to bid on Bluenose 3, bidding $200 and raising it to $30.
On Day 5, bidder 5 sees:
Bluenose 1 for $150, Bluenose 2 for $15, Bluenose 3 for $30, Bluenose 4 for $99 and Bluenose 5 for $0.99. Naturally he bids on Bluenose 5 and bids his $125, but the bid shows as $0.99, as there are no other bids.
On Day 6, bidder 6 sees:
Bluenose 1 for $150, Bluenose 2 for $25, Bluenose 3 for $30, Bluenose 4 for $99, Bluenose 6 for $150 and Bluenose 5 for $0.99.
Bluenose 6 is too expensive for this bidder, so he passes on it and instead bids $125 on Bluenose 5. He is overbid though, as the bid is now $125 and he is not willing to go any higher. He Then bids on bluenose 2, but is outbid and bluenose 2 goes to $125. So he tries bluenose 3 and raises it to $50.
Finally on day 7, bidder 7 sees:
Bluenose 1 for $150, Bluenose 2 for $125, Bluenose 3 for $50, Bluenose 4 for $99, Bluenose 5 for $125, Bluenose 6 for $150 and Bluenose 7 for $125.
Naturally he bids on Bluenose 3 and raises it to $125, but cannot raise it enough to win. So then he bids on Bluenose 4 and bids $125 on $99.
So, at the end of the 7 days:
Bluenose 1 sells for $150,
Bluenose 2 sells for $125
Bluenose 3 sells for $125
Bluenose 4 sells for $99.
Bluenose 5 sells for $125
Bluenose 6 does not sell either.
E-bay's take is $35.75 plus 5% of $624, which is $31.20 for a total of $66.95.
Now, let's suppose that E-bay only shows each bluenose at certain times:
On day 1, bidder 1 bids $150 on Bluenose 1 and is the high bidder at $0.01. It is not visible for the rest of the day.
On day 2, bluenose 2 is listed but does not show right away because E-bay knows that any bidder will try and bid on bluenose 1 because they think it is $0.01. Bidder 2 bids $150 on bluenose 1, so that it pushes bluenose 1 to $150. As soon as bidder 2 goes back to search, Bluenose 2 appears. So he bids $150 on it and it shows at $10.
On day 3 bluenose 3 is listed for $25. E bay now knows that it has 2 bids of $400, so that there is a good chance that any new bidder will be bidding over $125. Therefore it does not show bluenose 3 right away either. Bidder 3 is shown bluenose 2, and bids $50, pushing it to $50. They are outbid, but then when they go back and exit the listing they see bluenose 3 and place a $50 bid, which shows as $25.
On Day 4 bluenose 4 is listed for $99. E-bay shows it and bidder 4 bids $400., which is recorded as $99.
On Day 5 Bluenose 5 is listed at $0.99. However E-bay does not show the listing on day 5 because it knows that there are currently 4 bidders who are willing to pay far more than the minimum bid. Because the start bid is so low E-bay knows that in the next 7 days there will be a bidder in all likelihood. So instead it shows bidder 5 bluenose 3. Bidder 5 bids $125 on it, pushing it to $55. Bidder 3 is outbid and looks for another bluenose and is shown bluenose 5, bidding $50 and showing at $0.99.
On Day 6 Bluenose 6 is listed for $150. E-bay knows that Bidder 3 will pay $50 for bluenose 5 but someone else will likely pay more for it. But it has a bid of $400 on bluenose 4 and no other bids. So now it makes bluenose 4 visible rather than bluenose 6. to bidder 6. Bidder 6 bids on it, bidding $125, which pushes it to $125, but Bidder 6 is unsuccessful. Then Cassini makes bluenose 3 visible to bidder 6 and bidder 6 bids it up to $55 forcing bidder 3 out.
On Day 7, bluenose 7 is listed at $125. Now, when bidder 7 logs on and searches,
ebay wants to show bidder 7 bluenose 7 because it knows that on average chances are very good, based on the maximum bids entered by the other bidders that bidder 7 will be willing to bid the $125, since it was only bidder 3 that was only willing to bid less than $100. So bidder 7 bids and wins for $125.
So at the end of the period under this scenario:
Bluenose 1 sells for $150
Bluenose 2 sells for $50
Bluenose 3 sells for $55
Bluenose 4 sells for $125
Bluenose 5 sells for $55
Bluenose 6 does not sell
Bluenose 7 brings $125
So, the total realization is $560, a little less ($64) than the first scenario. However this is only because bidder 3's maximum bid was so low and the highest bidder, bidder 4 came in when he did, as well as the order in which the listings appeared. However, with good AI machine learning and with bidding history Cassini can very likely achieve better overall realization for e-bay, even if it does not maximize the realization for all sellers. So E-bay clears all the items and increases the chances that the sellers will list more items in the future, since all the items did sell for more than the minimum bid. But the sellers of bluenoses 2 and 3 only receive half as much as they would have if all the listings had been visible all the time.
These scenarios are simplified, but they do show that there is a reason for E-bay to use manipulation to make more money from sellers and bidders.