JP2004030591A - System and method for purchasing commodity - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a system and method for purchasing commodities by which articles having a plurality of specifications to be specified by a purchaser are promptly retrieved from a registered data base and with high degree of coincidence. <P>SOLUTION: When the purchaser specifies purchase desired commodity information 2a including the plurality of purchase specifications (information) Q1 to Q5, a control means (retrieval means) 10 accesses sale desired commodity data bases (DB) 22, 60, 62 in which sale desired commodity information 22a having one or more pieces of sale specification information P1 to P4 is stored in correspondence with a seller (information) S1, retrieves pieces of sale desired commodity information including sale specification information at least a part of which coincides among the plurality of purchase specifications (information) Q1 to Q5 from the sale desired commodity data base (DB) 22 and transmits the sale desired commodity information to purchaser terminal 70, 72. <P>COPYRIGHT: (C)2004,JPO

Description

[0001]
TECHNICAL FIELD OF THE INVENTION
The present invention relates to a merchandise trading system and method, such as a net auction, for searching for a desired product of a buyer from, for example, seller information registered on a Web site.
[0002]
[Prior art]
In recent years, with the spread of the Internet, so-called net auctions have been actively performed. Such an online auction is performed by a buyer or a seller registering product information on a Web site called an auction site in advance, and searching for a buyer / seller of a desired product using, for example, a product name as a key. In addition, usually, a search for a trading partner is performed on the system using a relatively small number of keywords such as the above-mentioned product name, price, delivery date, and the like. It is a target.
[0003]
[Problems to be solved by the invention]
However, the above-mentioned net auction has the following problems. First, the buyer needs to access a predetermined information source (auction site) himself to search for the desired product, and the buyer has a limited number of information sources himself. And the probability of a search hit is reduced.
Also, in the conventional search, a reliable search can be performed if the product name and the product uniquely correspond to each other. It is necessary to determine whether or not to search for the product desired by the seller. Such a judgment cannot be normally made unless the person is experienced in the product field, and it has been difficult to realize this on the system of the auction site.
[0004]
In particular, if the product to be bought and sold has many specifications, even if there is no product that satisfies all the specifications desired by the buyer, it is actually required to search for a product that is close to it, but any product Since it is difficult to realize on the system whether or not the product is "close" to the buyer's specifications, such a product cannot be used as a target of a conventional net auction.
[0005]
The present invention has been made in view of the above-described problems, and allows a buyer to access a variety of information sources that satisfy a plurality of specifications specified by a buyer quickly and highly from a registered database without accessing the various information sources. It is an object of the present invention to provide a merchandise trading system and method capable of searching for a degree of matching.
[0006]
[Means for Solving the Problems]
In order to achieve the above-mentioned object, the merchandise trading system according to the present invention is configured such that when a buyer specifies desired merchandise information including a plurality of purchase specification information, the desired merchandise information having one or more sales specification information is transmitted to the seller. A search for accessing a desired product database stored in association with the information and searching the desired product database for desired product information including sales specification information at least partially matching the plurality of purchase specification information. Means are provided.
[0007]
In the merchandise trading system, it is preferable that the merchandise trading system further includes a transmitting unit that transmits the desired product information searched by the searching unit to the buyer terminal.
It is preferable that the merchandise trading system further includes the desired merchandise database.
[0008]
Further, in the commodity trading system of the present invention, the purchase specification information is ranked, and a search information database that stores numerical information according to the ranking or the degree of coincidence between the purchase specification information and the sales specification information. Further comprising: when the predetermined sales specification information matches the respective purchase specification information, the search unit determines a degree of coincidence between the respective purchase specification information and the predetermined sales specification information based on the search information database. By digitizing, it is possible to search for desired product information that best satisfies the buyer's purchase conditions.
[0009]
In the merchandise trading system, it is preferable that the merchandise trading system further includes an evaluation database storing evaluation information of the buyer regarding the merchandise or seller with which the transaction has been established, and the search means preferably refers to the evaluation information in a subsequent search.
In the merchandise trading system, it is preferable that the merchandise buying and selling system further includes a search result database storing search results of the search unit regarding the merchandise for which a transaction has been established, and that the search unit refers to the search results in a subsequent search.
[0010]
In the merchandise trading system, a plurality of the search means are provided, and each search means has a different search criterion, and when the buyer specifies the purchase desired product information, the buyer specifies which search means to use for the search. Preferably it is possible.
[0011]
In the merchandise trading system, when the number of desired products satisfying the buyer's purchase condition does not reach the buyer's purchase desired number, the buyer is notified of the purchase condition and the shortage number, and a notice for recruiting sellers. Preferably, it further comprises means.
[0012]
In the method for selling and selling commodities of the present invention, when the buyer designates the information on the commodity for purchase, the purchaser accesses the commodity for sale database, and the sales including the sales specification information in which at least a part of the plurality of purchase specification information matches. A step of searching for desired product information from the sales desired product database.
[0013]
BEST MODE FOR CARRYING OUT THE INVENTION
Hereinafter, an embodiment of the present invention will be described with reference to FIG. FIG. 1 is a configuration block diagram showing an embodiment of a commodity trading system (hereinafter, referred to as “this system” as appropriate) 50 of the present invention. , A buyer information database (hereinafter abbreviated as “DB”) 2, an evaluation DB 4, a search result DB 6, and a search information DB 8. Further, in this embodiment, a merchandise information integration DB 20, a desired merchandise DB 22, a purchase input information DB 24, a search means selection information DB 26, a seller recruiting page (notification means) 30 and the like are further provided. The control means 10 controls the entire system and can be realized as a central processing unit of a predetermined server device (not shown). The merchandise trading system 50 constitutes a Web site (auction site) as a whole.
[0014]
Buyer terminals 70 and 72 and seller terminals 80 and 82 are connected to the system 50 via a network 100 such as the Internet. Further, other websites (information sources) 200 and 210 are connected to the network 100, and each of the websites stores a virtual store or an electronic device that stores a desired product DB 60 or 62 similar to the desired product DB 22 of the present system. It has a mall. Then, each of the DBs 60 and 62 is accessed from the search means (control means) 10 included in the system 50, and predetermined information can be obtained. Note that, in the present system, it is not essential to provide the sales-desired product DB22, and the sales-desired product DB22 may be provided externally. In this system, if the system has access information to the external sales-desired product DB22, Good.
[0015]
As the network 100, a dedicated line, a LAN (Local Area Network), a WAN (Wide Area Network), or the like may be used instead of the Internet. Further, as the buyer terminals 70 and 72 and the seller terminals 80 and 82, terminals such as a personal computer and an STB (Set Top Box: home communication terminal), or a mobile phone, PHS (registered trademark), and PDA (Personal Digital Assistants): A portable terminal (a user A has) such as a personal information device can be used. In addition to the above, the mobile terminal may be a mobile (mobile) device such as a palmtop computer or a laptop computer. Each mobile terminal is appropriately equipped with a browser capable of browsing a Web page. In this embodiment, the terminals 72 and 80 are portable terminals, and are connected to the network 100 via the mobile communication network 110.
[0016]
In the present system 50, the buyer information DB2 stores desired product information (buyer information) including predetermined information (authentication information, name, and the like) on the buyer, information (product name, etc.) on the product desired to be purchased, and purchase specifications (Q1 to Q5). Data) 2a is stored. The buyer data 2a is input to the buyer terminals 70 and 72 by the buyers C1 and C2 who have accessed the system 50.
[0017]
The desired product DB 22 (60, 62) includes predetermined product information (authentication information, name, etc.) on the seller, information (product name, etc.) on the desired product, sales specifications (P1 to P4), and the like. Seller data) 22a. Here, if the seller data is described in a special code for merchandise service classification or a predetermined language in which information of different databases can be integrated, information of the DBs 60 and 62 stored in other Web sites is integrated. It is preferable because it can be searched. In this case, when the information of the DB 6 and the information of the DBs 60 and 62 of other Web sites are appropriately stored in the merchandise information integration DB 22 as appropriate, the search of the control unit (search unit) 10 is improved. As the language, for example, HTML (Hyper Text Markup Language) and XML (extensive Markup Language) can be used.
[0018]
The evaluation DB 4 stores the evaluation data 4a including the name of the product for which the transaction has been completed, its specifications (P1 to P4), seller information, and buyer evaluation. Here, the evaluation of the buyer may be that relating to the product such as the quality of the product, or that relating to the seller such as after-sales service. The search result DB 6 stores information (product name, purchase specifications (Q1 to Q5), sales specifications (P1 to P4)) on products for which transactions have been made, and buyer evaluations (matching evaluations) on product matching levels (matching levels). The search data 6a is stored, and the matching evaluation is described later.
[0019]
The search information DB 8 stores a search matrix used as a criterion at the time of a search, which will be described in detail later, and the purchase input information DB 24 stores a purchase input template used at the time of a buyer's purchase input. When there are a plurality of search means, the search means selection information DB 26 stores past search results of each search means (e.g., matching of seller data with buyer data, evaluation of buyers, and the like). To use the search means. Further, the seller recruiting page 30 posts the purchase conditions and the missing number on the Web when the number of sellers satisfying the purchase condition of the buyer is insufficient, and recruits sellers who can provide the product.
[0020]
The above-described desired product information (seller data) and desired product information (buyer data) are shown in detail in FIGS. 2 and 3. In FIG. 2, the seller information 22a includes a seller ID (Identification: identification information) 22s, a seller name / provider name 22t, a seller face information (name, etc.) 22u, and a desired product information (product name, quantity, sales specification, etc.). 22v, means for contacting the seller 22w, charge information 1 (desired selling price, commission, settlement means, etc.) 22x, charge information 2 (hammer price at the time of auction (described later), etc.) 22y, exchange information links (P1 to Pn) , Link to predetermined information) 22z. In FIG. 3, the buyer information 2a includes a buyer ID (Identification: identification information) 2s, buyer face information (name, etc.) 2u, purchase desired product information (product name, quantity, purchase specification, etc.) 2v, and communication to the buyer. It is composed of means 2w, charge information 1 (purchase desired price, settlement means, etc.) 2x, and charge information 2 (purchase designated price (described later) at the time of auction, etc.) 2y.
[0021]
Next, with reference to FIG. 4, a processing flow of commodity sales in the present system 50 will be described. In FIG. 4, first, the seller inputs information (seller data) relating to a product to be sold from a predetermined seller terminal to the system for selling information DB on this system or another Web site (step 400). The input items may be, for example, those shown in FIG. The control means 10 of the present system appropriately registers the information registered in the sales desire information DB in the product information integrated DB 20 (step 500).
[0022]
Next, the buyer accesses the present system by specifying, for example, a URL (Uniform Resource Locator) from a predetermined buyer terminal and inputs authentication information (step 300). The control means 10 of the present system performs an authentication process based on a DB (not shown) storing authentication information for each buyer (step 510), and if it is determined that the authentication information is correct, the buyer terminal 70, 72 asks the buyer terminals 70, 72 to purchase the product. Is transmitted, and the buyer terminals 70 and 72 display the screen on the display unit of the terminal (step 310). The buyer inputs purchase information (buyer data) of the desired product from the buyer terminal, and selects one of a plurality of search means in a predetermined case (step 320).
[0023]
Based on the buyer data, the control means 10 of the present system appropriately searches the seller data registered in the product information integration DB 20 for suitable information (step 520). Then, an auction described later is appropriately performed on the searched seller data and buyer data, and sellers, buyers, and transaction prices are determined according to the results (step 530). The control means 10 transmits the transaction result, and the buyer terminal and the seller terminal respectively receive the information (steps 330 and 410). The buyer inputs payment information from the buyer terminal based on the information (step 340), and the control means 10 performs a payment process based on the information (step 540). The control means 10 transmits the settlement result, and the buyer terminal and the seller terminal respectively receive the information (steps 350 and 420). If the seller's sales quantity is insufficient with respect to the buyer's desired purchase quantity at the time of the transaction, the control means 10 calculates the shortage quantity from the seller data and the buyer data (step 550), and a predetermined notification means (seller) The information on the purchase conditions and the number is posted on the recruitment page) to recruit sellers (step 560). In the case of a successful transaction, the administrator of the present system may collect a predetermined fee from the buyer and the seller. In this case, the control means 10 appropriately transmits the billing information to the buyer terminal and the seller terminal. .
[0024]
Next, a search method performed by the control unit (search unit) 10 will be described with reference to FIG. FIG. 5 shows an example of a search matrix when a frame relay switch (data exchange device) is used as a product. In this figure, a plurality of specifications of this product (frame relay switch) are listed, and each specification is ranked in any one of ranks A, B, and C.
[0025]
Here, the specification belonging to rank A has the highest importance, and the specifications of the seller data must all match the specifications belonging to rank A of the buyer data. Here, "both agree" means that the seller data has the specifications of the buyer data and the specific conditions of each specification (for example, the numerical value of "4096 bytes" in the case of "maximum packet length", the "INS net backup""" Means that it is possible or not "). Then, in order to quantify the matching degree (matching degree) described later, when the specifications of the buyer data and the seller data match, the highest score (100 points in FIG. 5) is given as compared with other ranks. Has become.
[0026]
On the other hand, the specifications belonging to rank B have relatively high importance, but the specifications belonging to rank B of the buyer data do not have to match all the specifications of the seller data. That is, among the specifications of the buyer data, there is no need for the seller data to have a specification that matches this. Here, when both match, the score is lower than rank A (30 in this example). Further, a case where the specific numerical value of the specification of the seller data is within a predetermined range (for example, ± a%) with respect to the specification of the buyer data is regarded as “partial match”. The score in this case is set lower than the score when both match completely (15 in this example).
[0027]
Further, the specifications belonging to rank C have low importance, and the specifications of the seller data do not need to all match the specifications belonging to rank C of the buyer data. In addition, when both match, the points are lower than the other ranks (5 points in this example).
[0028]
Then, the control means (search means) 10 searches for seller data that most satisfies the buyer's purchase conditions by calculating the degree of matching (matching degree) of each specification based on such a search matrix. FIG. 6 shows a search flow performed by the control means (search means) 10.
[0029]
In this figure, the search means 10 assigns purchase specification information included in buyer data to ranks A, B, and C based on the search matrix (step 1000). In addition, the search means 10 uses the product name (or product category) included in the buyer data as a key and extracts seller data having a corresponding (same) product or category from the product information integration DB 20 (step 1010). . Then, the search unit 10 narrows and searches the extracted seller data for those having specifications that match all of the specifications belonging to rank A of the buyer data (step 1020). For example, when the specifications belonging to the rank A of the buyer data are B1 and B2, the seller data having all the specifications matching the specifications B1 and B2 is extracted.
[0030]
Next, the search means 10 searches each of the narrowed-down seller data for specifications that match the specifications belonging to the ranks B and C of the buyer data, and searches each seller along the search matrix shown in FIG. By digitizing the data, the degree of matching (matching degree) between the buyer data and the seller data is calculated (step 1030). In addition, the search unit 10 appropriately searches for information on matching evaluation from past search results stored in the search result DB 6 (step 1040), and searches the evaluation DB 4 for buyer evaluation of the product or seller as appropriate (step 1040). Step 1050). Then, the search means 10 appropriately digitizes the information, adds the information to the matching degree, and extracts seller data that most satisfies the buyer's purchase conditions based on the value (step 1040).
[0031]
FIG. 7 specifically shows the processing of the step 1030, in which the data of the sellers S1 to S4 having all the specifications that match the specifications P1 and P2 of the rank A of the buyer data are narrowed down and searched. Then, for the data of S1 to S4, it is searched whether there is a specification that matches the specifications P3 and P4 belonging to the rank B of the buyer data and the specification P5 belonging to the rank C, and the score based on the search matrix is displayed. For example, in the data of the seller S2, specifications Q13 and Q14 that partially match the specifications P3 and P4 of the buyer data are searched, and a predetermined score (15 points) is given. Similarly, a specification Q15 that completely matches the specification P5 of the buyer data is searched and assigned a score. In this figure, the display of the specifications of the buyer data is omitted for the data of S2 to S4. By summing up the scores at each rank in this way, the degree of matching (matching degree) between the data of S1 to S4 and the buyer data is calculated. In this example, the data of S1 and S2 have the highest degree of matching. Is determined (total score 235).
[0032]
FIG. 8 specifically shows the processing of step 1040 described above, and the search means 10 searches the search result DB 6 for past search data on the product to be searched this time. In this figure, the search data includes the specifications of the merchandise of sellers S100 and S200 that have transacted with the specifications P1 to P5 of the buyer data, and an index (matching evaluation) evaluated by the buyer regarding the degree of matching (matching degree) of the goods. Contains. Then, from these data, the search means 10 finds that, for rank B, there is one seller specification that completely matches the buyer's specification (corresponding to the data of S100), so that the seller's specification that partially matches the buyer's specification is obtained. It is understood that the two (corresponding to the data in S200) have higher buyer matching evaluation. Then, with reference to this matching evaluation, the value is added (appropriately multiplied by a predetermined coefficient) to the score of the matching degree of the data of S1 and S2.
[0033]
FIG. 9 specifically shows the processing of step 1050 described above. The search means 10 searches the evaluation DB 4 for past evaluation data on sellers S1 to S4 to be searched this time. Then, from these data, the search means 10 reads out that S1 and S2 for which the degree of matching was calculated in step 1030 indicate that the seller S2 has a higher evaluation of the buyer. Then, referring to this evaluation, the value is added to the score of the degree of matching of the data of S1 and S2 (by appropriately multiplying by a predetermined coefficient).
[0034]
In this way, the search unit 10 satisfies the buyer's purchase condition most by quantifying and adding the past matching evaluation value for the corresponding product and the evaluation for the seller in addition to the matching degree calculated in step 1030. Seller data can be extracted. Then, each time a transaction is made, the information in the evaluation DB and the search result DB is updated, and thereafter, the search for the desired product information that satisfies the purchase condition of the buyer most quickly becomes faster and the matching degree is higher. You can search. The extracted seller data may be one with the highest numerical value, or a plurality of seller data may be extracted in order from the highest numerical value.
[0035]
After the seller data that satisfies the buyer's purchase conditions is extracted as described above, the transaction may be established as the transaction price using the price specified by the buyer or the seller, but the transaction price is determined by an auction. You may. In particular, it is convenient for buyers and sellers to determine the transaction price by conducting an auction when a plurality of buyers or sellers occur. FIG. 10 is a conceptual diagram showing an aspect in which a transaction price is determined by an auction.
[0036]
In this figure, it is assumed that both sellers S1 and S2 have products that satisfy the purchase conditions of buyers C1 to C4. Each seller has registered a “start price” and an “end price” corresponding to the “hammer price” in FIG. 2, and these indicate the set prices at the start and end of the auction, respectively. On the other hand, each buyer has registered the “designated purchase price” in FIG. 3, which indicates the buyer's desired purchase price. For the seller S1, buyers C1 and C2 whose purchase specified price is higher than the start price of S1 and whose purchase specified price is lower than the end price are to be auctioned, and among them, the buyer C2 whose purchase specified price is higher. The transaction is established with. Similarly, for the seller S2, buyers C3 and C4 whose purchase specified price is higher than the start price of S2 and whose purchase specified price is lower than the end price are auctioned, and among them, the buyer C4 whose purchase specified price is higher. A transaction is established between the two. Then, after the transaction is completed, the settlement processing is appropriately performed as described in FIG.
[0037]
Further, in the above-described embodiment, a case has been described in which the number of search means is one. However, a plurality of search means may be provided, and each search means may perform a search based on different criteria. In this case, since each search means has a different search matrix, different search results are presented to the same buyer. Then, in the search means information DB, for example, the degree of coincidence of the seller data with the purchase condition of the buyer is stored for each search means (or for each product), so that the buyer can perform the most reliable search based on this information. Can be selected.
[0038]
The present invention is not limited to the embodiments described above. For example, the search means may access the information source of each desired product information for each search without storing each desired product information in the product information integration DB. Alternatively, after the search by the search means, the price specified by the buyer or seller may be used as the transaction price without conducting an auction. Also, after calculating the degree of coincidence between the buyer data and the seller data according to the search matrix, the seller data that most satisfies the purchase conditions of the buyer is determined as the degree of coincidence without referring to the information in the evaluation DB or the search result DB. It may be determined accordingly. Further, instead of the seller recruiting page, the seller may be recruited by sending an e-mail to the address of the seller terminal.
[0039]
The merchandise trading system of the present invention can be realized by a computer, various peripheral devices such as a communication device, and a software program executed by the computer. The software program executed in the system is a computer. It can be distributed via a readable storage medium or a communication line.
[0040]
【The invention's effect】
As described above, according to the present invention, the buyer searches for a target seller only by performing a predetermined purchase input to the system, and the buyer himself accesses various auction sites. No need. In addition, since the present system appropriately accesses other information sources (Web sites) and searches for sellers, the probability of finding the product desired by the buyer increases.
[0041]
Then, based on the desired product database, a search is made for product information having sales specification information that at least partially matches the buyer's purchase specification information. Near product information can be searched quickly and with a high degree of matching from the database.
[0042]
In addition, if the degree of coincidence between the purchase specification information and the sales specification information is quantified based on the ranking of the purchase specification information or a numerical value according to the degree of coincidence between the purchase specification information and the sales specification information, a search is performed. Is quantified, and it is possible to search for desired product information that satisfies the purchase condition of the buyer most quickly and with a high degree of matching. Further, when a past search result or evaluation data of a corresponding product is referred to, the search becomes more accurate. In particular, since the information in the evaluation DB and the search result DB is updated each time a transaction is established, the reliability of subsequent searches increases.
[Brief description of the drawings]
FIG. 1 is a block diagram showing a configuration of a commodity trading system of the present invention.
FIG. 2 is a diagram showing a structure of desired product information (seller data).
FIG. 3 is a diagram showing a structure of purchase desired product information (buyer data).
FIG. 4 is a diagram showing a flow of commodity sales.
FIG. 5 is a diagram illustrating an example of a search matrix.
FIG. 6 is a diagram illustrating a flow of a search process.
FIG. 7 is a diagram showing an aspect in which the degree of coincidence between buyer data and seller data is quantified.
FIG. 8 is a diagram illustrating an example of search data stored in a search result DB.
FIG. 9 is a diagram showing an example of evaluation data stored in an evaluation DB.
FIG. 10 is a conceptual diagram showing a method for determining a transaction price by an auction.
[Explanation of symbols]
2 Buyer information database (DB)
2a Product information for purchase (buyer data)
4 Evaluation database (DB)
6 search result database (DB)
8 Search information database (DB)
10 control means (search means)
12 I / O control means (transmission means)
22, 60, 62 Product Database (DB)
22a Product information for sale (seller data)
50 Commodity trading system
70, 72 Buyer terminal
80, 82 seller terminal
100 networks
110 mobile communication network
200, 210 Other websites

Claims (9)

If a buyer specifies desired product information that includes multiple purchase specification information,
A desired product information having one or more sales specification information accesses a desired product database stored in association with the seller information, and sales including sales specification information at least partially matching the plurality of purchase specification information are obtained. A merchandise trading system comprising a search means for searching for desired merchandise information from the desired merchandise database. 2. The merchandise trading system according to claim 1, further comprising a transmitting unit for transmitting the desired product information searched by the searching unit to the buyer terminal. The merchandise trading system according to claim 1, further comprising the desired merchandise database. Each of the purchase specification information is ranked, and further includes a search information database that stores numerical information corresponding to the ranking or the degree of coincidence between the purchase specification information and the sales specification information,
The search means, when predetermined sales specification information matches each purchase specification information, quantifies the degree of coincidence between each purchase specification information and the predetermined sales specification information based on the search information database. 4. The merchandise trading system according to any one of claims 1 to 3, wherein the search for the desired merchandise information which satisfies the purchase condition of the buyer most is performed. Further comprising an evaluation database that stores the buyer's evaluation information on the merchandise or seller for which the transaction was established,
The merchandise trading system according to any one of claims 1 to 4, wherein the search means refers to the evaluation information in a subsequent search. A search result database that stores search results of the search unit with respect to products for which transactions have been made;
The merchandise trading system according to claim 1, wherein the search unit refers to the search result in a subsequent search. A plurality of said search means, and each search means has different search criteria,
The merchandise trading system according to any one of claims 1 to 6, wherein when the buyer specifies the purchase desired merchandise information, it is possible to specify which search means is used for the search. When the number of products desired to be sold that satisfies the buyer's purchase condition does not reach the buyer's desired purchase number, the system further comprises notification means for notifying the buyer's purchase condition and the shortage number and recruiting sellers. The merchandise trading system according to any one of claims 1 to 7, characterized in that: If a buyer specifies desired product information that includes multiple purchase specification information,
A desired product information having one or more sales specification information accesses a desired product database stored in association with the seller information, and sales including sales specification information at least partially matching the plurality of purchase specification information are obtained. A method for buying and selling commodities, comprising a step of retrieving desired merchandise information from the desired merchandise database.

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