US20130238398A1

US20130238398A1 - System and method for dynamic product pricing

Info

Publication number: US20130238398A1
Application number: US13/872,435
Authority: US
Inventors: Simon Rothman
Original assignee: Glyde Corp
Current assignee: Glyde Corp
Priority date: 2007-12-21
Filing date: 2013-04-29
Publication date: 2013-09-12
Also published as: US8447645B2; US20090164383A1

Abstract

Embodiments of the present invention provide a system and method for dynamic product pricing. According to one embodiment, sale characteristics for a plurality of products are stored in a database. A user places a sale order including information associated with a product to be listed on a website, and a market price for the product is calculated based on the stored sale characteristics of the product. The sales characteristics include a queue of current list prices of the product as well as recent sale prices, with the queue having the number of the product available for sale at each different price. A suggested list price is displayed to the seller based on the market price. The seller is provided with a means for adjusting the suggested list price or listing the product at the suggested list price.

Description

CROSS-REFERENCES TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No. 11/963,382, filed Dec. 21, 2007, Entitled “System and Method for Dynamic Product Pricing” [Attorney Docket No. 91430-733983 (000200US)], the contents of which are incorporated by reference herein in their entirety for all purposes. Related applications are U.S. application Ser. No. 11/963,675, Entitled “Virtual Shelf with Single Product Choice and Automatic Multiple Vendor Selection” [Attorney Docket No. 91430-734064 (000100US)]; U.S. application Ser. No. 11/963,711, Entitled “Software System for Decentralizing eCommerce with Single Page Buy” [Attorney Docket No.: 91430-734065 (000300US)]; U.S. application Ser. No. 11/963,718, Entitled “3D Product Display on Internet with Content or Transaction Data on Back of Image” [Attorney Docket No.: 91430-734066 (000400US)]; U.S. application Ser. No. 11/963,470, Entitled “Product Distribution System and Method Thereof” [Attorney Docket No.: 91430-733984 (000500US)]; U.S. application Ser. No. 11/963,592, “System and Method for Providing Real-Time Search Results on Merchandise” [Attorney Docket No.: 91430-733831 (000600US)]; U.S. application Ser. No. 11/963,601, Entitled “System and Method for Integrated Payment and Shipping Information” [Attorney Docket No.: 91430-733832 (000700US)]; all filed Dec. 21, 2007.

BACKGROUND OF THE INVENTION

The present invention generally relates to the pricing of a product to be sold over a network, and in particular to determination of a market price for a product to be sold on a website.
The immense popularity of the internet has given millions of individual users the ability to buy and sell practically any given item. Amazon.com, eBay, and Craig's list are just a few of the many websites that provide the means for the purchase and sale of thousands of new and used goods. As a result, buyers are now able to comparison-shop various websites and sellers offering the same product in order to find the most favorable price and terms of sale.
Unfortunately, this type of background research consumes copious amounts of time for the buyer, and in the end, confusion may still exist as to whether a product has been properly priced. Shipping and handling costs are often embedded in the sales price, often to the surprise of the buyer. Sellers are also inconvenienced as inefficient price management makes it hard for the seller to know how to effectively price their goods. As the number of online buyers and sellers constantly increases in today's ever changing marketplace, the variety in pricing also increases, and a true market price remains obscure to both the buyer and seller alike.
Many pricing systems have been developed in an effort to address the aforementioned problems. For example, Demand Tec Inc., U.S. Pat. No. 6,851,604, discloses a system for updating prices for a particular subset of items. Alibris.com, U.S. Patent Publication No. 2005/0071249, discloses a method and system for repricing a good for sale in an online transaction. In particular, when a seller wishes to change a listed price due to varying market conditions, the seller sends the system a repricing request and selects a new price. Though these systems account for price changes relative to the market, the seller is still inconvenienced by having to reprice the item after its initial listing. Since the market constantly changes, the seller still remains unsure as to whether a product has been listed at an optimum price, thereby causing the market to remain unstable and the true market price for a particular product to remain unknown.
Accordingly, there is a need in the art for a more efficient system and method for pricing a product to be sold in an online transaction.

BRIEF SUMMARY OF THE INVENTION

Embodiments of the present invention provide a system and method for dynamic product pricing. According to one embodiment, sale characteristics for a plurality of products are stored in a database. A user places a sale order including information associated with a product to be listed on a website, and a market price for the product is calculated based on the stored sales characteristics of the product. The sales characteristics include a queue of current list prices for the product, with the queue having the number of products available for sale at each different price. A suggested list price is displayed to the seller based on the calculated market price. The seller is provided with a means for adjusting the suggested list price or listing the product at the suggested list price. Accordingly, a specific product is given a true market price, or one true value at any one moment of time. The true market price thus varies with supply and demand. The specific product corresponds to a stock keeping unit (SKU), with a market price for SKU, which may be a particular version, color, condition, etc.
According to another embodiment, the seller is shown sale statistics concerning the likelihood of the product being sold at the suggested price or the adjusted price. The seller can either select the adjusted price or simply select the suggested list price as the list price. Next, the list price of the product is placed in a sale queue associated with the product.
In one embodiment, when the seller agrees to list at the suggested list price, the seller can choose a dynamic or static market order. In this way, the list price will change with the market until the product is sold (dynamic) or remain at the initial list price (static). In one embodiment, the market pricing is applied to a multi-vendor website where only a single vendor item is displayed to a potential buyer. Thus, the lowest priced, best vendor item will be displayed, and higher priced ones will wait in the sale queue until all the lower priced ones have sold. Thus, buyers see only one list price.
It is to be appreciated that embodiments of the present invention provide many advantages over conventional techniques. For example, according to one embodiment of the present invention, the market price is automatically determined and a suggested list price associated with the market price is displayed to the seller prior to listing the product. Accordingly, with just one click the seller can quickly list the product based on the current market price. Moreover, since sale statistics of the suggested list price and the adjusted price are shown to the seller, the seller can evaluate and determine an optimum price for sale. This technique enables a seller to quickly and effectively price a product relative to the supply and demand for the product, ultimately allowing the market price for the product to reach equilibrium, and giving the buyer and seller the confidence that a product was priced based on the current market for the product.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a simplified diagram illustrating the overall product pricing system according to an embodiment of the present invention.

FIG. 2 is a simplified flow diagram illustrating the process of the dynamic product pricing system according to an embodiment of the present invention.

FIG. 3 is a screenshot illustrating of the pricing feature according to an embodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

Embodiments of the present invention provide a system and method for dynamic product pricing. The following description is provided to enable any person skilled in the art to make and use the invention and sets forth the best modes contemplated by the inventor for carrying out the invention. Various modifications will remain readily apparent to those skilled in the art. Any and all such modifications, equivalents and alternatives are intended to fall within the spirit and scope of the present invention.

System

FIG. 1 is a simplified diagram illustrating of an overall product pricing system according to an embodiment of the present invention. As shown, the system 100 includes terminals 102 and 108, network 104 (i.e. the internet), server 105, server application 110, graphical user interface (GUI) 120, and database 118. The terminals 102 and 108 are connected to server 105 via network 104. Terminal 102 is a buyer terminal, and terminals 108 are seller terminals.
The server 105 includes server application 110, GUI 120, and database 118. In a specific embodiment, the server 105 hosts a multi-vendor website that offers certain products for sale. The server may be implemented using multiple computing devices. The server application 110 includes a market price calculating section 112, sale probability calculating section 114, and projected time to sale calculating section 116. These components will be described in more detail below with reference to FIG. 2.
The database 118, among other things, is configured to store sale characteristics for a particular product. As an example, the database 118 is integrated in the server 105 and may also include multiple storage devices linked to one another. According to one embodiment, the sale characteristics of a product include a history of list and sold prices, the product condition, the product identification number (SKU, UPC, ISBN, etc.), current rate of sale, and sale queue information. For example, for a particular product (DVD, CD, book, camera, etc.), the database 118 stores the price at which it was originally listed, the final sale price of the product, the condition of the product (new, excellent, good), the number identifying the specifications of the product, the length of time from list to sale, and a queue of current list prices of the product. The database 118 may also store other information such as the number of products which have sold at a given price, and a minimum and maximum suggested list price. In addition, the database may store bid characteristics for a particular item including a list of offer prices and the current rate of bidding.
The user terminals 102 and 108 are shown connected to network 104 for browsing the multi-vendor website provided by the server 105 (for buyers, to search for products to buy; for sellers, to post products for sale). The terminals 102 and 108 may be any type of computing device that provides network connectivity and allows a user to browse a website. For instance, terminals 102 and 108 may be a personal computer, a cellular phone, or a personal digital assistant. In one embodiment, seller terminals 108 represent a plurality of sellers that offer products to be sold on the multi-vendor website. User terminal 102 represents a buyer searching for a desired product offered on the multi-vendor website.

Single Product Display On Multi-Vendor Site

In one embodiment, the market pricing of the present invention is applied to a multi-vendor website where only the lowest priced vendor item is displayed to a potential buyer. The lowest price item is typically the lowest priced item offered by any vendor, but can also be the lowest priced item offered by the best vendor (i.e. the vendor with a highest reliability rating). Thus, the lowest price, best vendor item will be displayed, and higher priced ones will not be displayed until all the lower priced ones have sold. Thus, an efficient market can be established. This model may vary based on region due to the shipping costs. For instance, if a vendor is in a region where the demand can only be met by distant sellers with higher shipping costs, the buyer's total purchase price may be higher, since when combined with shipping costs the purchase price may be the same as the lowest priced item but at the higher distant seller cost. In an alternate embodiment, multiple products are displayed to potential buyers at multiple websites or on one website, and the user is able to compare and is assumed to pick the lowest price product available. Thus, again the market price can be determined by the lowest priced products, taking into account the inventory at that price and the demand Details of such a multi-vendor/single product view system are set forth in co-owned application Ser. No. 11/963,675, filed Dec. 21, 2007 [Attorney Docket No. 91430-734064 (000100US)], the disclosure of which is hereby incorporated herein by reference.

Calculation And Display of Market Price To Potential Seller

FIG. 2 is a simplified flowchart of the product pricing system according to an embodiment of the present invention. In step 202, sale characteristics of a particular product are stored in a database. When a product is listed for sale on the multi-vendor website, the sale characteristics of the product include the suggested list price of the item, the history of sold prices, and the current sale queue information. Moreover, a minimum and maximum price list price can be set based on external market information, internal market dynamics, and the condition of the product.
Further, the maximum list price of a particular product may be determined by calculating the price distribution of the same condition product from the stored sale characteristics or from external sources offering the product for sale. As for an item of highest condition (i.e. new or excellent), the maximum list price may be determined based on the current market price on the multi-vendor website and the price of the product on external sources. In one embodiment, a reasonable price range for the product is determined based on these prices, and a maximum range is set so that the product may not be priced above this range. Alternately, the maximum list price can be set by examining the demand for the product and the availability of that product at various prices, and determining a likelihood of selling above a certain price. The maximum list price can then be set at a threshold where the likelihood of selling is minimal With respect to the minimum list price, if shipping is not independently added, sale transaction fees plus the packaging fees (mailer fees) may be used as a minimum list price. Preferably, a product may not be listed below the minimum list price unless the seller indicates that the sale has a charitable component.
In step 204, the server receives a sale order from a seller. The sale order includes product information concerning a product to be listed on the multi-vendor website. The product information includes a product title, a unique product identification number (UPC, SKU, ISBN, etc.), and a product condition. For example, if a seller desires to sell a particular book on the multi-vendor website, the sale order would include the title of the book, the ISBN of the book, and the condition of the book (new, excellent, or good).
After receiving the sale order in step 204, in step 206, the server calculates a market price for the product to be listed (hereinafter “list product”). The server utilizes the market price calculating section of the server application, which queries the database for the sales characteristics associated with the list product. The market price calculating section identifies the prior list prices and sold prices of a like product of the same condition from the stored sale characteristics and from the pricing information on external sources, and then calculates a current market price. In one embodiment, the list prices in the sale queue, the prior list and sold prices, and the current pricing information on third party websites are weighed together in order to determine the current market price. When demand exceeds supply, the market price will go up.
In step 208, the server calculates a suggested list price, a sale probability and a projected time to sale for the list product based on the market price. In one embodiment, the market price is used as the suggested list price. However, the suggested list price may also be higher or lower than the calculated market price. For instance, the current demand (number of purchases per unit of time, such as the last hour or day) may be compared to the current inventory available. If the current demand exceeds the amount of products available, and the sellers are unwilling to sell the product at the current suggested list price, the suggested list price will be raised.
Further, the server utilizes the sale probability calculating section and the projected time of sale calculating section of the server application to calculate a probability that the list product will sell at the suggested list price, and a projected length of time for the list product to sell at the suggested list price, respectively. In one embodiment, the sale probability section calculates the probability of sale at the suggested list price within a predetermined time frame (e.g. five days) based on the number of times the list product has previously sold at the suggested list price. In particular, the sale probability calculating section queries the database for the sale characteristics of the list product (i.e. historic list and sold prices, sale queue length, current rate of sale, etc.). In addition, the sale probability calculating section may utilize the current market conditions such as the season (Christmas, summer), appreciation/depreciation factors (high demand/low demand), and even the price distribution from external sources. Through the use of such a large number of pricing factors, an accurate sale probability can be calculated giving the buyer a dependable likelihood of sale. The probability may be returned to the user via the GUI as a percentage or as wording in a message box.
Similarly, a projected time to sale is calculated based on the sale queue at the suggested list price and the current rate of sale for the list product. In step 210, the suggested list price, the probability of sale, and projected time to sale are displayed to the seller using the GUI of the multi-vendor website.
In step 212 the seller determines whether to list the product at the suggested list price, or adjust the suggested list price to an alternate price. The GUI of the multi-vendor website provides a means for easily adjusting the displayed suggested list price. If the current suggested list price is not adjusted, and the seller selects the suggest list price using one-click functionality, the suggested list price is then stored in the database as the list price of the list product in step 218. This configuration provides a “single click market order” technique, enabling a seller to easily list a product based on the existing market price for the product. In one embodiment, the seller can also select a dynamic market order or static market order. In the case of the dynamic market order, the product is listed at the suggested list price, and as the market price changes, the seller's list price is automatically adjusted to the current market price. If the seller selects a static market order, the suggested list price is again selected as the list price, but the list price does not automatically change as the market changes. However, the server is also configured such that a seller can later adjust the list price to a dynamic or static market price after the initial pricing.
If the seller adjusts the suggested list price in step 212, in step 214, the probability of sale and the projected time to sale are recalculated based on the adjusted list price. The sale probability calculating section and the projected time to sale calculating section are utilized in the same manner described above with respect to the suggested list price. The adjusted list price, the sale probability, the projected time to sale, and the sale queue position at the adjusted list price are then displayed to the seller.
In step 216, a determination is made as to whether the adjusted price is selected by the user. If the user adjusts the suggested list price and uses the one-click functionality to select the adjusted price, the adjusted price is stored as the list price for the list product in step 220. Following step 220 or 218, in step 222, the list price is added to the sale queue of the list product.
FIG. 3 is a screen shot illustrating the GUI of the product pricing system according to an embodiment of the present invention. A sell window 300 is displayed to a user. The sell window includes an availability option 320, product condition setting 324, sale information 328, suggested list price 304, sell button 332, list product 316, and adjustment arrows 308 and 312. In this example, the suggested list price 304 is shown as the calculated market price described above in reference to FIG. 2. The adjustment arrows 308 and 312 allow the seller to adjust the suggested list price up or down, respectively. In one embodiment, the suggested list price 304 is adjusted in increments of $0.25, however, the increments may also be much smaller or much larger. For example, if the seller wanted to list the list product 316 for $10.25, the seller simply clicks the adjustment arrow 312 once, adjusting the suggested list price 304 from $10.50 to $10.25. Furthermore, sale information 328, which includes the probability of sale 334, the projected time to sale 336, and the sale queue position 338 associated with the suggested list price or the adjusted price, is shown to the right side of the adjustment arrows 308 and 312.
Thus, features of the present invention act to drive sellers to a common market price that takes into account changing supply and demand, similar to the stock market. Sellers will be motivated to list at the lowest price in order to assure a sale of their products. By providing this information to the sellers, this behavior is encouraged.
The product pricing system is not limited to the embodiments described above. For example, if an adjusted price is selected as the list price, the seller may later return to the multi-vendor website and using the one-click functionality, place a “mark-to-market” order to change the list price to the current market price (static or dynamic). Similarly, the seller may also opt to change all products currently being sold by the seller to a dynamic or static “mark-to-market” order. This technique allows a user to rapidly and efficiently adjust to changing market conditions.
In addition, embodiments of the present invention can equally apply to the buyer side. In this way, bid information including a bid queue may be used to track the number of buyers and offer prices for a product. In this case, for a given product, a list of offer prices will be stored in the database. The market price calculating section would then calculate a market price based on the number of products offered by the seller, the number of bids, and the current list of offer prices in the bid queue. Based on the calculated market price, a suggested offer price is displayed to the buyer. This scenario is especially beneficial in the case of pre-orders, as sellers are able to know the true market value of a product pre-release, and buyers are given the opportunity to be the first to acquire a newly released product. For example, a new release of a product in limited numbers may cause its sale price to be bid up, with buyers paying a premium for early delivery from a limited supply, while knowing how high to bid up and still get the product.
It will be recognized by persons of ordinary skill in the art that the method of the invention has many applications, and that this description has not attempted to enumerate all possible variations. For example, the invention applies equally to individual, amateur sellers and to professional sellers. It applies to a single, multi-vendor website or multiple websites where sales data is collected from other websites and used in the market price calculations. In addition, the market price can be based on a combination of a price at a multi-vendor website and other websites. The invention can also be applied to non-Internet sales, such as text message sales promotions to mobile phones or hard copy listing of products in catalogs or other media.
Although the embodiments have been described with reference to products such as DVDs, CDs, and books, the product distribution system can also apply to video games, consumer electronics (i.e., PDAs, cell phones, etc.), jewelry, toys, software or any other product or service. In addition to sale transactions, the system and method according to embodiments of the present invention may also apply to rental or barter transactions. The scope of the invention also extends to various combinations and modifications that may fall within the spirit of the appended claims.

Claims

What is claimed is:

1. A method for facilitating online transactions via a server computer connected to a network, the method comprising:

generating, by the server computer, for each of a plurality of products offered for sale by a plurality of sellers, a sale queue, the sale queue including, for the product associated with the sale queue and for each seller offering to sell the product, a current list price indicative of a price of the product at which the seller has offered to sell the product;

identifying, by the server computer, for a selected one of the products offered for sale, a lowest list price indicative of a lowest price among the current list prices associated with the selected product; and

causing the lowest list price to be displayed to a potential buyer of the selected product while suppressing the display of current list prices for the selected product other than the lowest price.

2. The method of claim 1, further comprising:

determining whether all of the products offered for sale at the lowest list price have been sold;

upon determining that all of the products offered for sale at the lowest list price have been sold, identifying a new lowest list price indicative of a lowest price among the current list prices associated with the selected product, the new lowest list price having a higher price than the lowest list price; and

causing the new lowest list price to be displayed to a potential buyer of the selected product while suppressing the display of current list prices for the selected product other than the new lowest price.

3. The method of claim 1, further comprising:

receiving a sale order from a seller, the sale order identifying one of the plurality of products as a product to be listed for sale by the seller;

determining a suggested list price for the product to be listed for sale; and

causing the suggested list price to be displayed to the seller.

4. The method of claim 3, further comprising:

determining a market price for the product to be listed for sale, wherein determining the market price includes weighing together prior list prices of the product to be listed for sale, prior sold prices of the product to be listed for sale, current list prices in the sale queue for the product to be listed for sale, and current pricing information for the product to be listed for sale from a source external to the server computer,

wherein the suggested list price is determined at least in part on the market price.

5. The method of claim 3, further comprising:

determining a sale probability indicative of a probability that the product to be listed will sell at the suggested list price within a certain time period, wherein the sale probability is determined at least in part on a number of times the product to be listed has previously sold at the suggested list price; and

causing the sale probability to be displayed to the seller.

6. The method of claim 5, wherein the sale probability is determined at least in part on current market conditions, appreciation/depreciation factors, and a price distribution from a source external to the server computer.

7. The method of claim 3, further comprising:

determining a projected time to sale indicative of the expected duration of time after which the product to be listed will sell at the suggested list price, wherein the projected time to sale is determined at least in part on the suggested list price and a current rate of sale for the product to be listed.

8. A server computer system, comprising:

a database configured to store information;

a communication interface configured to communicate information with buyers and sellers of products; and

a computer processor coupled to the database and the communication interface, wherein the computer processor is configured to:

generate, for each of a plurality of products offered for sale by a plurality of sellers, a sale queue, the sale queue including, for the product associated with the sale queue and for each seller offering to sell the product, a current list price indicative of a price of the product at which the seller has offered to sell the product;

store the sale queue in the database;

identify, for a selected one of the products offered for sale, a lowest list price indicative of a lowest price among the current list prices associated with the selected product; and

cause, via the communication interface, the lowest list price to be displayed to a potential buyer of the selected product while suppressing the display of current list prices for the selected product other than the lowest price.

9. The server computer system of claim 8, wherein the computer processor is further configured to:

receive a sale order from a seller, the sale order identifying one of the plurality of products as a product to be listed for sale by the seller;

determine a suggested list price for the product to be listed for sale; and

cause the suggested list price to be displayed to the seller.

10. The server computer system of claim 9, wherein the computer processor is further configured to:

determine whether the seller indicates an adjustment to the suggested list price.

11. The server computer system of claim 10, wherein the computer processor is further configured to:

upon determining that the seller does not indicate an adjustment to the suggested list price, add the suggested list price to the sale queue.

12. The server computer system of claim 10, wherein the computer processor is further configured to:

upon determining that the seller indicates an adjustment to the suggested list price resulting in an adjusted list price, add the adjusted list price to the sale queue.

13. The server computer system of claim 10, wherein the computer processor is further configured to:

upon determining that the seller indicates an adjustment to the suggested list price resulting in an adjusted list price:

determine a sale probability indicative of a probability that the product to be listed will sell at the adjusted list price;

determine a projected time to sale indicative of the expected duration of time after which the product to be listed will sell at the adjusted list price; and

cause the sale probability and the projected time to sale to be displayed to the seller.

14. The server computer system of claim 13, wherein the computer processor is further configured to:

determine whether the seller indicates acceptance of the adjusted list price.

15. The server computer system of claim 14, wherein the computer processor is further configured to:

upon determining that the seller does not indicate acceptance of the adjusted list price, add the suggested list price to the sale queue.

16. The server computer system of claim 14, wherein the computer processor is further configured to:

upon determining that the seller indicates acceptance of the adjusted list price, add the adjusted list price to the sale queue.

17. A tangible non-transitory computer readable storage medium having instructions stored thereon that, when executed by a computer processor, cause the computer processor to perform operations including:

generating, for each of a plurality of products offered for sale by a plurality of sellers, a sale queue, the sale queue including, for the product associated with the sale queue and for each seller offering to sell the product, a current list price indicative of a price of the product at which the seller has offered to sell the product;

identifying, for a selected one of the products offered for sale, a lowest list price indicative of a lowest price among the current list prices associated with the selected product; and

18. The tangible non-transitory computer readable storage medium of claim 17 wherein the instructions, when executed by the computer processor, cause the computer processor to perform additional operations including:

determining a list price for the product to be listed for sale; and

adding the list price to the sale queue such that the product to be listed for sale by the seller is a product listed for sale by the seller.

19. The tangible non-transitory computer readable storage medium of claim 18 wherein the list price is determined at least in part on a market price of the product to be listed for sale.

20. The tangible non-transitory computer readable storage medium of claim 19 wherein the instructions, when executed by the computer processor, cause the computer processor to perform additional operations including:

receiving an input from the seller indicating a selection of a dynamic market order, wherein as the market price of the product listed for sale by the seller changes, the seller's list price for the product listed for sale is adjusted to the changed market price.

21. The tangible non-transitory computer readable storage medium of claim 19 wherein the instructions, when executed by the computer processor, cause the computer processor to perform additional operations including:

receiving an input from the seller indicating a selection of a static market order, wherein as the market price of the product listed for sale by the seller changes, the seller's list price for the product listed for sale is maintained.

22. The tangible non-transitory computer readable storage medium of claim 18 wherein the instructions, when executed by the computer processor, cause the computer processor to perform additional operations including:

identifying a plurality of sellers offering to sell the selected product; and

determining a best seller from the plurality of sellers, the best seller having a highest reliability rating as compared to other sellers of the plurality of sellers offering to sell the selected product,

wherein the lowest price displayed to the potential buyer is associated with the best seller.

23. The tangible non-transitory computer readable storage medium of claim 17 wherein the instructions, when executed by the computer processor, cause the computer processor to perform additional operations including:

determining a minimum list price for the product to be listed for sale by the seller, the minimum list price being indicative of a minimum price at which the seller may offer to sell the product to be listed for sale; and

determining a maximum list price for the product to be listed for sale by the seller, the maximum list price being indicative of a maximum price at which the seller may offer to the product to be listed for sale.

24. The tangible non-transitory computer readable storage medium of claim 23, wherein the minimum list price and the maximum list price are determined at least in part on external market information, internal market dynamics, and the condition of the product to be listed for sale.

25. The tangible non-transitory computer readable storage medium of claim 23, wherein the maximum list price is determined based on the price distribution of a same condition product from stored sale characteristics or from one or more external sources offering the product for sale.

26. The tangible non-transitory computer readable storage medium of claim 23, wherein the maximum list price is determined based on a current market price of a same condition product and a price of the product from one or more external sources offering the product for sale.

27. The tangible non-transitory computer readable storage medium of claim 23, wherein the maximum list price is determined based on a likelihood of the product being sold above a certain price.

28. The tangible non-transitory computer readable storage medium of claim 27, wherein the maximum list price is set at a threshold where the likelihood of selling the product is minimized.

29. The tangible non-transitory computer readable storage medium of claim 23, wherein the minimum list price is determined based on sale transaction fees plus packaging fees.

30. The tangible non-transitory computer readable storage medium of claim 29, wherein the minimum list price may be adjusted based on whether the seller indicates that the sale has a charitable component.