Real-time offers and dynamic price adjustments presented to mobile devices

Information

  • Patent Grant
  • 8732018
  • Patent Number
    8,732,018
  • Date Filed
    Wednesday, May 11, 2011
    13 years ago
  • Date Issued
    Tuesday, May 20, 2014
    10 years ago
Abstract
The demand aggregation system includes deal room sponsored by a third party host. The third party host facilitates commercial transactions between a plurality of buyers and at least one seller. In exchange for sponsorship of such a deal room, the third party host can receive an incentive such as a percentage of sales, seller discount or the like. Furthermore, mechanisms are provided to aid discovery of sellers and/or offers that can be included in a group buying event for a buying group. The buying group receives a greater discount as the total purchase amount in the group buying event increases.
Description
BACKGROUND

The buying and selling of products and services (collectively referred to as “products”) has resulted in a vast array of buying or costing schemes, which are used to select the price at which such products are sold.


One of the most common costing schemes which consumers encounter everyday is known as fixed pricing. According to this costing scheme, sellers set a fixed price for their products based on a past demand for the product and/or anticipated future demand. Buyers desiring to purchase products from the seller are each required to pay the same fixed price regardless of the number of products purchased. If a seller finds that the demand for a given product is greater or less than expected, the seller may later adjust the fixed price of the product to account for such findings. Although the fixed pricing provides a simple way for a seller to conduct business with multiple buyers, one drawback of this costing scheme is that it fails to reward buyers willing to purchase greater quantities of products. Accordingly, the discount quantity pricing scheme evolved.


The discount quantity pricing approach to costing involves pricing a product at different levels depending on the quantity of products a customer is willing to purchase. The more products a customer is willing to purchase, the lower the price. Sellers have incentive to lower price for large quantity buyers since the fixed costs associated with producing the product is spread over more items. Thus, sellers are able to make equal or greater profits despite the lowered price of the product. While volume pricing offers a benefit to larger buyers who are able to purchase large quantities of goods at one time, smaller buyers are often unable to obtain the lowered prices and therefore are more likely to “shop around” for the best available deal. This, in turn, hurts both the buyer and seller. For instance, the smaller buyer is burdened with needing to search for alternative deals and still often ends up paying a higher price than larger buyers. The sellers, on the other hand, are faced with lost business since they are unable to reduce their price for the smaller buyers and still make sufficient profit.


Another common costing scheme for pricing a product is an auction. In an auction, a seller sets an initial price for an item and then multiple buyers are given an opportunity to bid against each other for the product. The buyer having placed the highest bid for the product at the end of the auction purchases the product at the final price bid. In order to provide a larger forum for buyers and sellers, a recent trend has been to auction goods electronically over the Internet. For example, one company known to operate an auction site over the Internet is eBay, Inc. Although auctions provide advantages when selling unique products for which customers are willing to competitively bid, the auction forum is not well suited for sellers desiring to sell large quantities of goods to multiple buyers given the inherent inefficiencies involved with selling one product at a time in a bidding environment.


Yet another costing scheme which has been advanced in recent years is buyer-driven bidding. According to this costing scheme, a single buyer desiring to obtain a product communicates a price at which the buyer is willing to purchase the product to multiple sellers. Each of the sellers is provided an opportunity to review the buyer's price. A sale is complete when one of the sellers agrees to sell the product to the buyer at the price suggested by the buyer. A buyer-driven bidding scheme is described in U.S. Pat. No. 5,794,207 assigned to Walker Asset Management Limited Partnership of Stamford, Conn. Another buyer-driven bidding scheme is provided in U.S. Pat. No. 5,897,620 assigned to priceline.com, Inc of Stamford Conn. While the buyer-driven bidding scheme provides advantages for certain types of transactions when, for example, sellers may be willing to sell products at lower than normal prices, the uncertainties involved with whether a buyer's offer will be accepted is often problematic for high volume commercial transactions in which the reliability that a transaction will be complete is of paramount importance.


While the costing schemes described above have various advantages and disadvantages in different situations, a commonality among all of the costing schemes is that each buyer operates independently with one or more sellers to set a purchase price of a product. For example, in the fixed pricing scheme and discount quantity purchasing scheme, buyers individually determine whether the sellers preset price schedule is acceptable regardless of whether other buyers have decided to purchase the product or not. In an auction, not only do buyers operate independent of other buyers, but, in fact, each buyer's decision to place a bid has a negative effect on all other buyers desiring to purchase the same good since the price of the good increases. Similarly, in a buyer-driven bidding scheme, each buyer is completely unaware of the amount other buyers are bidding for a given product.


The independent operations of the buyers stems from a combination of the fact that: 1) the costing schemes discussed above provide little incentive for buyers to work together and 2) there are large inconveniences for buyers to facilitate communication about their buying activities to other buyers. Unfortunately, such independent operation by buyers can result in missed opportunities for both the buyer and seller. For example, in instances where two independent buyers are unable to afford a product, neither buyer informs the seller of their respective desire to purchase the product. Accordingly, sales of the product to these buyers do not take place. Due to the independent operations by each of the buyers, such information is never communicated thereby resulting in missed opportunities for both the buyers and seller alike.


SUMMARY

The following presents a simplified summary in order to provide a basic understanding of some aspects of the claimed subject matter. This summary is not an extensive overview. It is not intended to identify key/critical elements or to delineate the scope of the subject invention. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is presented later.


In brief, the subject disclosure pertains to systems and methods to facilitate e-commerce transactions and demand aggregation. More particularly, mechanisms are provided to assist interaction with and/or establishment of deal rooms, or electronic forums, for buying and/or selling goods and/or services at volume discount as a function of collective room transactions. Both suppliers and consumers can benefit from such deal rooms in various ways. For example, suppliers can utilize deal rooms for optimal production scheduling and/or inventory reduction, while consumers can be grouped and benefit from bulk discounts that may not otherwise be available to them.


While buyers and/or sellers can host deal rooms, intermediaries can also host deal rooms in accordance with an aspect of the claimed subject matter. According to one aspect of the disclosure, a third-party sponsor or maven hosts a buying group and employs an offer discovery component to discover offers of potential interest to the maven's buying group. After selecting an offer, the maven establishes a deal room to facilitate purchasing between the buying group and the seller making the offer.


In accordance with another aspect of the claimed subject matter, a mechanism is provided to track orders by a buying group in the deal room. A current price or discount amount earned by buyers in the buying group is maintained based upon tracked purchases and a price curve. The price curve can be, among other things, a function of a discount amount based on the total amount purchased under an offer. The price curve can be modified by the maven to provide a sales commission.


According to yet another aspect of this disclosure, a system is provided for management of the buying group. The maven can establish and manage various aspects of the buying group. For example, the maven may add or remove a buyer from the buying group for violating of the terms and conditions of the buying group. The maven may also add or remove sellers available to the buying group.


In accordance with an aspect of the claims, mechanisms are provided to facilitate discovery of buying groups and/or sellers. Geographical relationships among buyers in the buying group may be utilized to locate new sellers that may have an interest in making an offer to the buying group. Further, a buyer can find buying groups to join by supplying a search engine with specified criteria (e.g., type of product and/or service, price, geographical area . . . ).


To the accomplishment of the foregoing and related ends, certain illustrative aspects of the claimed subject matter are described herein in connection with the following description and the annexed drawings. These aspects are indicative of various ways in which the subject matter may be practiced, all of which are intended to be within the scope of the claimed subject matter. Other advantages and novel features may become apparent from the following detailed description when considered in conjunction with the drawings.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 is a block diagram of a demand aggregation system.



FIG. 2 is a block diagram of a demand aggregation system including a representative deal room.



FIG. 3 is a block diagram of demand aggregation system including a host.



FIG. 4 is a block diagram of representative tools available to a host.



FIG. 5 is a block diagram of a buying group management system.



FIG. 6 is a block diagram of a geographical mapping system.



FIG. 7 is a block diagram of a group buying search engine.



FIG. 8 is a block diagram of a representative host or maven.



FIG. 9 is a block diagram of a system for electronically conducting business.



FIG. 10 illustrates a web page providing options to buyers desiring to conduct business electronically as a member of a buying group.



FIG. 11 is a flow chart diagram for a buyer desiring to conduct business electronically as a member of a buying group.



FIG. 12 illustrates an on-line registration form for a buyer.



FIG. 13 illustrates an exemplary buyer home screen.



FIG. 14 illustrates a group buying offer in accordance with one aspect of the disclosure.



FIG. 15 illustrates a group buying offer including a bar code.



FIG. 16 is a web page for a host to create or modify buying groups.



FIG. 17 is an input screen for managing a buying group.



FIG. 18 is a host's new group offer input screen.



FIG. 19 is a flow chart diagram for a host adding a new group offer.



FIG. 20 is a seller input screen providing options to create or modify offers.



FIG. 21 is a seller's offer information input screen.



FIG. 22 is a schematic block diagram illustrating a suitable operating environment for aspects of the subject innovation.



FIG. 23 is a schematic block diagram of a sample-computing environment.





DETAILED DESCRIPTION

The subject disclosure pertains to demand aggregation between and amongst a plurality of buyers and sellers. More specifically, the disclosure is related to mechanisms that facilitate hosting of electronic deal rooms including price curves that vary as a function of an amount of product ordered/purchased. In accordance with one embodiment, deal rooms can be hosted by third parties or mavens. These mavens can act as intermediaries between buyers and sellers to promote interaction and commercial transactions between the parties. Such third party activity can be encouraged via monetary incentives, among other things. Various systems and methods are described hereinafter with respect to third party deal room hosting as well as relevant tools to aid such functionality.


Various aspects of the subject disclosure are now described with reference to the annexed drawings, wherein like numerals refer to like or corresponding elements throughout. It should be understood, however, that the drawings and detailed description relating thereto are not intended to limit the claimed subject matter to the particular form disclosed. Rather, the intention is to cover all modifications, equivalents and alternatives falling within the spirit and scope of the claimed subject matter.


Referring initially to FIG. 1, an electronic commerce system 100 is illustrated. System 100 includes a deal room component 110 to facilitate a commercial transaction between a buyer and a seller. The commercial transaction can include an offer to sell particular goods and/or services wherein a final price of the goods and/or services is a function of the total number of orders received by the seller. The offer may also comprise a specified time period in which any goods and/or services of a seller may be purchased. At the conclusion of the specified time period, a final discount amount can be determined as a function of the total amount purchased (e.g., quantity of product, total sales, amount of money spent . . . ). In accordance with one embodiment of the subject disclosure, the offer can be a flash offer. A flash offer is a short-lived offer that provides a greater discount or extra benefit. For example, a seller may create a flash offer wherein the buyer has 45 minutes to place an order. The buyer receives the final discount amount and an extra benefit (e.g., an extra 5% discount) for ordering under the flash offer. The deal room component 110 is communicatively coupled to a buying group interface component 120 and a seller interface component 130. The buying group interface component 120 and seller interface component 130 can facilitate interaction between one or more buyers in a buying group and at least one seller.


By way of example, a seller can employ the seller interface component 110 to create and present an offer to the deal room component 110. The seller interface component 130 can also notify a seller of orders received under an offer in the deal room component 110. Likewise, the buying group interface component 120 can facilitate receipt or retrieval of an offer from the deal room component 110 and provisioning of orders from buyers in a buying group with respect to a particular offer.



FIG. 2 depicts an electronic commerce system 200 including a representative deal room component 110. Deal room component 110 includes an offer presentation component 210 that stores an offer of the deal room gathered from the seller via the seller interface component 130 and communicates the offer to buyers in the buying group through the buying group interface component 120. Accordingly, the offer presentation component 210 can maintain deal room offers and provide guidelines for commercial transactions conducted utilizing the deal room component 110. For example, the presentation component 210 can enforce seller terms and conditions or restrictions on buyers that can access the deal room and/or offers provided therein.


The deal room component 110 also includes an ordering component 220. The ordering component 220 provides a mechanism to initiate and complete an order for goods and/or services under the offer of the deal room. Buyers, via the buying group interface component 120, can elect to purchase goods and/or services presented by the offer presentation component 210. Ordering component 220 is operable to accept orders and communicate the orders to the seller interface component 130 so that it may be provided to the seller for further processing. The ordering component 220 can also notifies buyers that the order was accepted and forwarded to the seller. Additionally, the ordering component 220 is communicatively coupled to a purchase tracking component 240 and the details of the order are provided thereto.


While the ordering component 220 and purchase tracking component 240 are depicted as contained in deal room 110, it is to be appreciated that these components may be distinct from deal room 110. For example, in one embodiment, ordering component 220 can be a checkout register in a store location of the seller. A special coupon code or bar code corresponding to the offer and the buying group is utilized when making a purchase at the store location. The special coupon code or bar code enables the purchase tracking component 240 to link the in-store purchase to the buying group and other purchases made in the deal room and elsewhere. In yet another embodiment, a buyer in the buying group utilizes a credit card when making a purchase at a store location in accordance with the offer. The buyer, when joining the buying group, can supply a credit card number that can be utilized for group buying purchases. When charging a purchase under the offer to a credit card, the seller and the credit card number are matched to the buying group and the offer available to the buying group. Accordingly, the purchase tracking component 240 receives notice of the credit card charge and records the purchase as part of the buying group's group buy under the offer. Thus, while the deal room 110 provides a consolidated means to facilitate purchases and to track purchases, it is to be appreciated that purchases of the buying group can be tracked by any option capable of linking a purchase to the buying group and offer.


The aggregation component 230 receives notifications from the purchase tracking component 240 whenever buyers place orders in the deal room. The aggregation component 230 records the orders of all buyers in the buying group in order to determine a final price or a final discount amount depending on the offer. In one instance, the offer is for specific goods and/or services will include a price curve for the goods and/or services. The price curve is, among other things, a function of a price of a good and/or service based on the total quantity ordered. For example, if the total quantity ordered is 100 units, the unit price may be $10/unit and if the total quantity ordered is 200 units, the unit price may be $8/unit. In another instance, the offer is for any good and/or service of a seller. A discount curve is provided with the offer and is a function of a discount amount based on the total amount purchased. For example, if the buying group purchases goods and/or service totaling $1000, the buying group may receive a 2% discount off the total. If the buying group purchases a total amount of $2000, the group may receive a 4% discount.


The aggregation component 230 populates the recorded orders on a price curve or a discount curve and utilizes such a curve to determine the current price or discount based upon the orders tracked thus far. At the end of the offer period, the aggregation component 230 provides the final price or final discount given to the buying group. It is to be appreciated that movement on the price curve or discount curve can occur in both directions. For example, movement in the forward direction (i.e., towards a lower price and/or greater discount) occurs as the total purchase amount of the buying group increases. However, movement can occur in the reverse direction (i.e., towards a higher price and/or lesser discount) when a purchase product is returned to the seller. Thus, if the purchased product is returned for a refund, the return and refund is reflected by a reduction in the total purchase amount of the buying group and, subsequently, by a change in the final price and/or discount.


Turning now to FIG. 3, a hosted electronic commerce system 300 is illustrated. System 300 includes a host or maven 310 that hosts and controls the deal room component 110 via a maven interface component 320. In one embodiment, the maven 310 is a third-party intermediary. For example, the maven 310 can be an individual, an organization, a corporation, a school, a church or any other non-profit or for-profit entity. It is also to be appreciated that the maven 310 need not be a third-party to the underlying transaction facilitating by the deal room component 110. For example, a buyer or a seller can assume the role of maven 310 and host the deal room.


The maven 310 establishes an opportunity for commerce between a buying group and a seller. In one instance, the maven 310 can discovers an offer from a seller and/or encourage a seller to join the deal room. Additionally or alternatively, the maven 310 can create and/or manage a buying group. By way of example, the maven 310 can invite potential buyers to join a buying group and benefit from demand aggregation with respect to offers gathered by the maven 310 and established in deal room component 110.


The maven 310 can be incentivized for facilitating interactions between buyers and sellers. For example, a price or discount curve provided with an offer from a seller, for instance, can be modified by maven 310 to include a sales commission to maven 310 as compensation for hosting the deal room component 110. Additionally or alternatively, maven 310 may take a 1% sales commission on all purchases through the deal room component 110. The sales commission can be taken from the discount curve. In other words, a seller may offer a 4% discount if the purchase total is $2000 but the buying group will receive a 3% discount on such a purchase total thus reflecting the sales commission taken by the maven 310.


In one embodiment of the subject disclosure, system 300 includes an auditing component 330 that monitors activity in the deal room 110. Activity in the deal room 110 is monitored so the auditing component 330 can ensure sellers are adhering to discounts detailed in the offers. Thus, sellers can be held accountable for failing to provide the agreed discount to the buying group. While auditing component 330 is depicted as a distinct object, it should be appreciated that the auditing component 330 can be contained in the maven 310, the maven interface component 320 or distributed across both. Alternatively, according to another embodiment, the auditing component 330 can be included in a third-party service distinct from the maven 310, buyers and sellers.


Referring now to FIG. 4, a representative maven interface component 320 is depicted. The maven interface component 320 includes an offer discovery component 410. The offer discovery component 410 facilitates selecting an offer to provide to a buying group. The offer discovery component 410 can include or be embodied as a search engine, for example, that retrieves available offers based upon supplied criteria. The offer discovery component 410 can also provide a list of sellers available to the maven. A maven 310 can subsequently select one or more sellers and view offers available through the one or more sellers. The maven 310 can then select an available offer to provide to the buying group in a deal room. It is also to be appreciated that a seller can contact a maven 310 with an offer it would like the maven 310 to manage for example via the discovery component 410 or alternative mechanism. In this manner, the discovery component 410 can not only search out offers but also simply receive them.


According to one aspect of the subject disclosure, the discovery component 410 can receive a flash offer from a seller available to the maven 310 or otherwise already providing a typical offer to the maven's buying group. As flash offers are only active for a short period of time, the discovery component 410, communicatively coupled to a notification component 430, can immediately inform the buying group of the flash offer.


A deal room for a selected offer can be established by the deal room establishment component 420 (also referred to simply as establishment component 420). The maven utilizing the deal room establishment component 420 creates the terms and conditions of the deal room. A sales commission, if taken, can also be set via the establishment component 420. Once the establishment component 420 launches a deal room, the notification component 430 communicates to the seller and/or a buying group that a new offer is available and in a deal room. The notification component 430 may notify the buyers of the buying group and the seller via a directed communication method such as e-mail, text message, telephone or the like. The notification component 430 may also advertise the new deal room by a posting on a web site or electronic forum. After the creation of the deal room by the deal room establishment component 420, buyers and sellers may interact via the deal room as described supra with reference to FIGS. 1 and 2.


Turning to FIG. 5, a management system 500 is illustrated employable by a maven and/or included within the maven interface component 320 of FIG. 4. System 500 includes a buying group management component 510. Group management component 510 enables a maven to control the status of a buying group 520 and/or membership therein. For example, terms and conditions can be established that must be accepted before a buyer may join the buying group 520. While this can regulate member action, it can also be used by a maven to control to whom offers are presented and/or particular price curves provided thereto. For example, a maven may limit offers to a particular group of individuals, as a function of group membership (e.g., friends, family, school members, employees . . . ), credit score or any other discriminating factor. Similarly, different price curves can be provided to different groups of users in one or more deal rooms, wherein aggregation can occur by price curve or deal room or across multiple price curves or deal rooms.


It is also to be appreciated that the group management component 510 can facilitate filtering out users of a larger group based on some additional criteria. For example, the group management component 510 can enable a maven to rank buyers in a buying group 520 based upon purchasing histories of individual buyers. In this way, the most active buyers can be determined. A buyer can also be removed from the buying group 520 by the buying group management component 510 if, for example, the buyer violates the terms and conditions of the buying group 520.


System 500 also includes a seller management component 530 that can be employed by a maven to control sellers 540 available thereto. A new seller can be added to the sellers 540 available to the maven. Further, an existing seller may be removed from the sellers 540 for violating terms and conditions or any other reason. The seller management component 530 enables a seller linked to an existing deal room to be switch out with another seller from the available sellers 540 if a more attractive but similar competing offer is discovered in the short term. The seller management component 530 provides statistical measurements such as which sellers 540 are producing the largest sales volumes or which sellers are generating the greatest commission for the maven. The maven can also retrieve histories of sellers 540 that include previous offers, order volumes, discount totals and the like via the seller management component 530.



FIG. 6 depicts a geographical mapping system 600 including a mapping component 610 that can be employed by a maven or included within maven interface component 320 of FIG. 4. Geographical mapping system 600 provides the maven with another manner in which to introduce new sellers and items to the buying group and otherwise expand the product selection available to the buying group members. While offer discovery component 410 in FIG. 4 enables the maven to retrieve new offers from sellers participating in demand aggregation, geographical mapping system 600 provides a different modality to locate and review those sellers. Additionally, system 600 enables the maven to locate sellers not currently participating in demand aggregation but may, nonetheless, be interested in offering specials to the maven's buying group.


Mapping component 610 determines geographical relationships among buyers in a buying group that can be utilized to, among other things, locate sellers that may be interested in providing an offer to the buying group. A buyer may complete a buyer registration form including an address when the buyer joins a buying group. The information from the buyer registration form can be stored in buyer profiles 630 of the buyers in the buying group. The mapping component 610 can utilize the stored buyer profiles 630 and make a graph of the buyer locations. The mapping component 610 can integrate with other mapping tools (e.g. MapQuest, Google Maps, Windows Live . . . ) to depict buyer locations on a street map. The mapping component 610 enables a maven to efficiently discern the geographical distribution of buyers in a buying group. The mapping component 610 is communicatively coupled to a seller locator component 620 to facilitate discovery of new sellers, offers, products and services.


Seller locator component 620 utilizes geographical relationships determined by the mapping component 610 to reveal sellers in a geographical area that may be interested in offering specials to the maven's buying group. Seller locator component 620 may search amongst sellers participating in hosted demand aggregation systems hosted by other mavens. Sellers discovered by the seller locator component 620 can be managed by the seller management component 530 described with respect to FIG. 5. Further, the seller locator component 620 may also integrate with other mapping tools similar to the mapping component 610. For example, the seller locator component 620 may utilize features of other mappings tools to locate businesses in a particular geographical area offering certain products and/or services. The maven can contact these businesses and encourage them to offer specials and participate in volume pricing.


In accordance with one embodiment, mapping system 600 operates on an individual buyer level. If a buyer in a buying group subscribes to a membership in the buying group, the mapping component 610 periodically receives data relating to the buyer's location. The mapping component 610 can utilize the seller locator component 620 to find sellers and/or offers base upon and near the buyer's location. The mapping component 610 can ping the buyer's mobile device (e.g., cell phone, PDA, blackberry . . . ) to notify the buyer of the nearby sellers and/or offers. The notification can be a text message, a voicemail message, an e-mail message or the like. Accordingly, the buyer can continuously receive special offers while moving around to different locations.


Referring next to FIG. 7, a group buying search engine system 700 is illustrated. A buyer input component 720 submits a query to a search engine 710 to generate search results 730. The query from the buyer input component 620 includes criteria supplied by a potential buyer. The query may include a product and/or service or a class of products and/or services. For example, the query may be for “teddy bears” or “children's toys.” The search results 730 returned by the search engine 710 include buying groups containing offers for the product and/or service or class of products and/or services included in the query. The potential buyer reviews search results 730 and selects one or more buying groups to join in order to participate in a group buy as described with respect to FIGS. 1 and 2.


Search engine 710 includes a query component 712 that is communicatively coupled to the buyer input component 720. Query component 712 receives the query and accesses a database 714 to retrieve matching buying groups and/or offers. Information retrieved from database 714 is conveyed to a presentation component 716. Presentation component 716 processes the information and generates the final search results 730. The presentation component 716 can rank buying groups and/or offers from the query component 712 based upon various criteria. For example, the matching buying groups may be sorted according to current lowest price, lowest potential price, number of members, number of active buyers, or the like. Presentation component 716 may also utilize geographical data to provide a potential buyer with relevant buying groups based upon the potential buyer's location. For example, the potential buyer may desire participating sellers within a particular geographic area. The presentation component 716 will include buying groups with offers from those sellers in the search results 730. Results can also be filtered by the presentation component 716 as a function of a stored profile or other ascertainable information about a potential buyer (e.g., age, ethnicity, marital status, political affiliation, credit score, group memberships . . . ) and/or any other contextual information (e.g., time, date, holiday, event . . . ). In this manner, potential buyers can be married with the most relevant buying groups including, for example, only those in which it would satisfy membership requirements.


Referring to FIG. 8, a graphical representation of a host or maven 310 is illustrated to facilitate clarity and understanding. As shown, maven 310 can host more than one buying group. For example, maven 310 hosts buying group 820 and buying group 830. Each buying group 820 and 830 can be provided more than one offer from one or more sellers. For example, maven 310 hosts two offers, one from seller 822 and one for seller 824, and facilitates transactions between sellers 822 and 824 and buying group 820 under the offers. Likewise, maven 310 facilitates transactions between sellers 832 and 834 and buying group 830 under offers provided to buying group 830.


Maven 310 can establish a variety of relationships among the buying groups and/or sellers. For example, the maven 310 can establish a cross-selling offer between buying groups. Thus, the maven 310 can facilitate commercial transactions not only among sellers and buying groups, but among several buying groups as well. Cross selling transactions amongst buying groups are tracked and recorded similar to buyer/seller transaction described in relation to FIG. 2.


According to another aspect of the subject disclosure, buying groups can be combined, split and/or linked. For example, buying groups 820 and 830 can be merged into a single buying group. All the sellers and offers available to either buying group 820 or 830 become available to the merged buying group. A new buying group may be created by splitting or spinning off from an existing buying group. Maven 310 may allow a buyer in a buying group to create a spin-off buying group linked to the parent. For example, buying group 820 can be created and sponsored by maven 310. A buyer in buying group 820 may desire to create a new buying group. Maven 310 can sponsor the buyer and create buying group 830 as a spin-off of buying group 820. The purchase volume from buying groups 820 and 830 are combined or linked to increase overall purchase volume. Sales commissions derived from the buying group purchases can be split between maven 310 and sponsored buyer based upon terms and conditions established prior to spinning off. If allowed by the terms and conditions, buying group 830 can later by unlinked from buying group 820 to become a distinct buying group separate from maven 310.


Referring initially to FIG. 9, a hosted demand aggregation system 900 is shown in which multiple mavens 310, buyers 930 and sellers 940 are electronically linked via a central server 910. As discussed in more detail below, the central server 910 is configured to provide the mavens 310 a place to host a convenient forum in which the buyers 930 and sellers 940 utilize to buy and sell goods and/or services. The forum may be an Internet web page, for example, established by mavens 310 where mavens 310 can post select product information from sellers 940 and the buyers 930 can order products.


The multiple criteria buying scheme calls for a seller 940 to provide a number of deals for a given product, which vary according to different offering criteria defining the limits of a number of selling criteria, such as, for example, price, volume, quality and delivery time. The buyers 930 can enter a range of criteria that the buyer would require for a deal to be made. A list of sellers and prospective deals offered by sellers 940 is generated for the buyers 930 to review. The buyers 930 can then review the list of deals and choose a deal based on the buyers' 930 particular needs. In this manner, the buyers 930 can be certain that particular thresholds have been met.


It is to be appreciated that the present invention has wide applicability to the purchasing and/or selling of a variety of different products and/or services. For example, the present invention may be applied within the context of purchasing and/or selling airline tickets wherein buyers' criteria may include, for example: (1) reputation of airline; (2) reliability; (3) timeliness; (4) price; (5) number of alternative flights; (6) comfort; (7) quality of service; and (8) quality of foods. The sellers' criteria may include, for example: (1) volume of tickets; (2) buyer's versatility in time schedule; (3) buyer's method of payment, etc.


The subject innovation may also be applied in the context of purchasing and/or selling an automobile wherein buyer's criteria may include, for example: (1) reputation of automobile manufacturer; (2) reputation of dealer; (3) price of automobile; (4) delivery options; (5) automobile availability; (6) safety; and (7) financing terms; etc. While, the seller's criteria may include, for example: (1) buyer's creditworthiness; (2) desired finance terms; (3) delivery requests of buyer; (4) delivery dates; etc.


Thus, the subject aspects of the claimed innovation allow buyers and/or sellers of products and/or services to pre-select a plurality of criteria prior to negotiating a deal for the product and/or service. Of course, the pre-selected criteria will vary depending on the particular product and/or service. The scope of the subject invention as defined in the hereto appended claims intends to include any product and/or service (and plurality of pre-selected criteria associated therewith) suitable for deal-making in accordance with the described aspects of the innovation.


Each of the mavens 310, buyers 930 and sellers 940 may access the central server 910 in any of a variety of ways. For example, in the subject embodiment each maven 310, buyer 930 and seller 940 is shown to be part of separate establishments, which include one or more respective computer systems 922 and local servers 926. The computer systems 922 may, for example, be a desktop or laptop computer with a local area network (LAN) interface for communicating over a network backbone 924 to the local server 926. The local servers 926, in turn, interface with the central server 910 via a network cable 950 or the like. It will be appreciated that while the present aspect depicts the computer system 922 communicating with the central server 910 via hardwired network connections. In an alternative aspect, the computer system 922 may interface with the central server 910 using a modem, wireless local area and/or wide area networks, etc. Further, it will be appreciated, that while the mavens 310, buyers 930 and sellers 940 are shown to communicate with the central server 910 via different computer systems 922, it will be appreciated that the mavens 310, buyers 930 and/or sellers 940 may access the central server 910 from the same computer system 922.


The aforementioned systems, architectures, environments and the like have been described with respect to interaction between several components. It should be appreciated that such systems and components can include those components or sub-components specified therein, some of the specified components or sub-components, and/or additional components. Sub-components could also be implemented as components communicatively coupled to other components rather than included within parent components. Further yet, one or more components and/or sub-components may be combined into a single component to provide aggregate functionality. Communication between systems, components and/or sub-components can be accomplished in accordance with either a push and/or pull model. The components may also interact with one or more other components not specifically described herein for the sake of brevity, but known by those of skill in the art.


Furthermore, as will be appreciated, various portions of the disclosed systems and methods may include or consist of artificial intelligence, machine learning, or knowledge or rule based components, sub-components, processes, means, methodologies, or mechanisms (e.g., support vector machines, neural networks, expert systems, Bayesian belief networks, fuzzy logic, data fusion engines, classifiers . . . ). Such components, inter alia, can automate certain mechanisms or processes performed thereby to make portions of the systems and methods more adaptive as well as efficient and intelligent. By way of example and not limitation, the offer discovery component 410 can employ such mechanisms to intelligently locate relevant offers. Likewise, the group management component 510 can employ similar mechanism to identify/filter group buy members, for example by mining user profile data.


In view of the exemplary systems described supra, methodologies and means that may be implemented in accordance with the disclosed subject matter will be better appreciated with reference to FIGS. 10-20 including a plurality of exemplary screenshots/webpages and methodologies. These figures and related text are provided solely to facilitate clarity and understanding and are not intended to limit the scope of the appended claims. In accordance therewith, the screenshots are illustrative of only one of many manners of which graphics and text can be combine. Furthermore, it is to be noted that for purposes of simplicity of explanation, methodologies are shown and described as a series of blocks, it is to be understood and appreciated that the claimed subject matter is not limited by the order of the blocks, as some blocks may occur in different orders and/or concurrently with other blocks from what is depicted and described herein. Moreover, not all illustrated blocks may be required to implement the methodologies and means described hereinafter.


Turning now to FIG. 10, an exemplary web page 1000 is illustrated that can be generated and/or otherwise utilized by a maven to attract buyers. A maven may create and post web page 1000 to advertise hosted buying groups and/or particular group buying events to potential buyers. The web page 1000 provides potential buyers options to view group buy offers and join the corresponding buying group. For example, web page 1000 depicts information panels 1010 and 1030 providing the details of group buy events. Hyperlinks 1020 and 1040 are provided so that potential buyers may elect to join a buying group and participate in the group buy events displayed in panels 1010 and 1030.


In accordance with embodiment, web page 1000 can be generated and/or utilized by an affiliate distinct from the maven. The affiliate advertises the maven's buying groups and/or group buy events on behalf of the maven. If potential buyers utilizing links 1020 and 1040 on the affliate's website ultimately become members of buying groups, the affliate's website is recorded as a referring website as part of a member profile. The affiliate receives a commission or other compensation based upon the number of referrals or other such metric. For example, the maven pays a flat rate for each new member that joined via the affliate's website. In another embodiment, the affiliate receives a percentage of the maven's commission on the purchases made by members referred by the affiliate.


Referring now to FIG. 11, the general actions taken by a potential buyer desiring to join a buying group through web page 1000 is shown via flow chart diagram 1100. More particularly, at reference numeral 1102 it is initially determined whether a potential buyer is already a registered member of the buying group. If the potential buyer is not registered, terms and conditions of membership in the buying group are displayed at 1104. The potential buyer is presented with a choice at 1106 whether or not to accept the terms and conditions. If the potential buyer does not accept the terms and conditions at 1106, the potential buyer is informed at 1112 that membership in the buying group is denied. If the terms and conditions are accepted, the potential buyer fills out a registration form. For example, the potential buyer fills out a registration form 1200 such as that shown in FIG. 12. In this example, registration form 1200 requests that the buyer enter the following information: buyer name; address; telephone; fax; e-mail; preferred contact method; preferred user name; and preferred password. With respect to the user name and password, if the selected user name and password combination are unavailable, the potential buyer is prompted to enter a new user name and password until an available combination is supplied.


If at 1102, a potential buyer has already registered, the buyer may login as a registered user by entering a user name and pass code when prompted at 1114. Upon entry of such information, the user name and password is verified at 1116 with the information in the database at 1110. If the user name and pass code entered by the buyer does not match any entry in the database, the buyer returns to 1114 for re-entry of a user name and pass code. If, however, at 1116, a valid user name and pass code are entered, group offers available to the buying group are displayed at 1118.


Referring now to FIG. 13, an exemplary buyer home screen 1300 is illustrated. Home screen 1300 can be displayed at reference numeral 1118 of FIG. 11. Home screen 1300 displays a list of buying groups in which the buyer is a member and a list of offers currently available to one or more of those buying groups. Home screen 1300 also includes various hyperlinks 1310, 1320, 1330 and 1340 employable to access aspects of the system. For example, hyperlink 1310 enables a buyer to utilize a group buying search engine as described with reference to FIG. 7. The buyer employs the search engine to find new buying groups to join. Hyperlink 1330 enables the buyer to change elements of the buyer profile. A form similar to form 1200 of FIG. 12 is displayed to accept profile changes.


In one embodiment, hyperlink 1320 is provided to allow buyer access to a community forum. The community forum enables buyers, mavens and sellers to interact amongst one another. These interactions can take the form of blogs, e-mails, bulletin boards and the like. To facilitate interaction, each buyer has a buyer card 1350. Buyer card 1350 includes an avatar, a user name and a buyer status identifier. The avatar is a symbol or graphical representation of the buyer. The avatar facilitates interactions in the community forum by providing a visual representation of buyers. The user name is the user name supplied during registration as described with reference to FIG. 11. The buyer status identifier categorizes the buyer according to the buyer's purchase volume. For example, once a buyer reaches a purchase volume threshold, the buyer is tagged with a status such as “kingpin buyer” in the case of a high volume buyer. Accordingly, mavens, sellers and other buyers can recognize high volume active buyers by the buyer card associated with a particular buyer.


Turning now to FIG. 14, an exemplary group offer 1400 is illustrated. Group offer 1400 may be displayed by a buyer through utilization of hyperlink 1340 of FIG. 13. Group offer 1400 includes the name of the seller, the date and/or time period of the offer, the group code and the price or discount curve. Group 1400 also includes a hyperlink 1410 that a buyer may utilize to make a purchase in accordance with the offer. In the example group offer 1400, the seller is offering a discount on the total purchase volume of any goods and/or service provided by that seller. In one instance, hyperlink 1410 may send the buyer directly to the seller. The buyer enters the group code displayed in the group offer 1400 when making a purchase in order for the buyer's purchase to be recorded by the purchase tracking component 240 (FIG. 2). Hyperlink 1410 may also redirect the buyer to an electronic forum or deal room on central server 910 (FIG. 9) wherein the buyer may complete the purchase.



FIG. 15 depicts another exemplary group offer 1500 in accordance with an aspect of the subject disclosure. Group offer 1500 includes offer details similar to group offer 1400 in FIG. 14. Instead of an alphanumeric group code, group offer 1500 includes a graphical bar code 1510. A buyer may print bar code 1510 and utilize the bar code when making a purchase at a seller's location. Alternatively, a buyer may present the bar code for scanning via a mobile device (e.g., personal digital assistant (PDA), phone, music/video player . . . ) at a seller's location.


Turning now to FIG. 16, an exemplary maven web page 1600 is illustrated. Web page 1600 displays a list of buying groups currently hosted by the maven, a list of sellers currently available to the maven, and a list of offers currently provided to the buying groups. The web page 1600 also includes various hyperlinks 1610, 1620, 1630 and 1640 to enable the maven to access various aspects of the system. Hyperlink 1610 enables the maven to create a new buying group. Hyperlink 1620 enables the maven to find new sellers to add to the list of available sellers. The maven employs hyperlink 1630 to add a new offer available to one or more hosted buying groups. The maven can review the details of a buying group, a seller, or an offer utilizing hyperlinks 1640.


Referring to FIG. 17, an exemplary maven input screen 1700 is depicted. The input screen 1700 displays the details of a particular buying group hosted by the maven. Input screen 1700 includes a list of buyer who are members of the group, a list of sellers providing specials to the buying group, and a list of offers currently available to the buying group. Input screen 1700 enables a maven to remove buyers from the buying group. The maven may also add and/or remove sellers and offers from the buying group by employing input screen 1700.


Input screen 1700 also displays the total amount purchased to date by members of the buying group. In addition, the total amount received in discounts under a price or discount curve is also displayed. The maven may utilize the input screen 1700 to view the best selling products, the top buyers making the most purchases or top sellers with the largest sales volume.


Turning now to FIG. 18, a maven input screen 1800 for adding a new offer to a buying group is illustrated. Input screen 1800 include of list of available sellers 1810. List 1810 includes all sellers that the maven may interact with and include in group-buying events. If the maven selects a seller from the list of sellers 1810, a list of offers 1820 from the seller is displayed. The maven selects an offer and can review the details of the offer. The details include a description of the offer, an offer period, an offer code and a price curve. Input screen 1800 enables the maven to enter a sales commission to be taken from the price curve before providing the offer to the buying group.


Referring now to FIG. 19, a method for adding a new offer 1900 is provided. At reference numeral 1902, offers are displayed for review. At 1904, a desirable offer is selected to be added to a buying group. At 1906, the terms and conditions established for the seller providing the selected offer are displayed for review. At numeral 1908, a determination is made as to whether the seller's terms and conditions are accepted. If no, method 1900 cycles back to numeral 1902 where the available offers are displayed for selection. If yes, method 1900 proceeds to 1910, where a sales commission amount is entered in accordance with the terms and conditions of the seller. If the terms and conditions of the seller disallow a sales commission, this option will not be presented. Further, if the terms and conditions dictate a sales commission amount, the specified commission will be entered at 1910. At 1912, the buying group is notified that a new offer is available. Each member of the buying group will be notified according to the preferred contact method supplied in registration form 1200 (FIG. 12). Additionally, the new offer will be available for displayed after buyer login, for example, at 1118 of FIG. 11.


Referring now to FIG. 20, a seller input screen 2000 is illustrated. The seller input screen 2000 includes a list of offers 2010 currently provided by the seller. An option 2020 on the input screen 2000 is provided to enable the seller to create a new offer that can be made available to a buying group via a maven. The seller can also utilize an option 2030 to view details of an existing offer.


Turning now to FIG. 21, a seller input screen 2100 for establishing a new offer is provided. The seller inputs a description of the offer, a start date and time of the offer, an end date and time of the offer and a desired price or discount schedule. The seller may desire to provide the offer to only a select group of mavens. Accordingly, input screen 2100 includes an option to enter mavens to which the offer will be made available for inclusion in a buying group. For example, only those mavens listed by the seller on input screen 2100 will see the seller and offer in the list of sellers 1810 and list of offers 1820 on the maven input screen 1800 in FIG. 18. The seller may also specify a particular price incentive offered to mavens. The price incentive establishes the sales commission the maven receives on purchases by the buying group under the offer.


For purposes of brevity and clarity, discussion of additional aspects of deal rooms and demand aggregation (e.g., setup, interaction . . . ) has not been explicitly reproduced herein. For additional detail, regarding such subject matter see the additional patent applications incorporated herein by reference.


As used herein, the terms “component,” “system” and the like are intended to refer to a computer-related entity, either hardware, a combination of hardware and software, software, or software in execution. For example, a component may be, but is not limited to being, a process running on a processor, a processor, an object, an instance, an executable, a thread of execution, a program and/or a computer. By way of illustration, both an application running on a computer and the computer can be a component. One or more components may reside within a process and/or thread of execution and a component may be localized on one computer and/or distributed between two or more computers.


The word “exemplary” is used herein to mean serving as an example, instance or illustration. Any aspect or design described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other aspects or designs. Furthermore, examples are provided solely for purposes of clarity and understanding and are not meant to limit the subject innovation or relevant portion thereof in any manner. It is to be appreciated that a myriad of additional or alternate examples could have been presented, but have been omitted for purposes of brevity.


Furthermore, all or portions of the subject innovation may be implemented as a method, apparatus or article of manufacture using standard programming and/or engineering techniques to produce software, firmware, hardware, or any combination thereof to control a computer to implement the disclosed innovation. The term “article of manufacture” as used herein is intended to encompass a computer program accessible from any computer-readable device or media. For example, computer readable media can include but are not limited to magnetic storage devices (e.g., hard disk, floppy disk, magnetic strips . . . ), optical disks (e.g., compact disk (CD), digital versatile disk (DVD) . . . ), smart cards, and flash memory devices (e.g., card, stick, key drive . . . ). Additionally it should be appreciated that a carrier wave can be employed to carry computer-readable electronic data such as those used in transmitting and receiving electronic mail or in accessing a network such as the Internet or a local area network (LAN). Of course, those skilled in the art will recognize many modifications may be made to this configuration without departing from the scope or spirit of the claimed subject matter.


In order to provide a context for the various aspects of the disclosed subject matter, FIGS. 22 and 23 as well as the following discussion are intended to provide a brief, general description of a suitable environment in which the various aspects of the disclosed subject matter may be implemented. While the subject matter has been described above in the general context of computer-executable instructions of a program that runs on one or more computers, those skilled in the art will recognize that the subject innovation also may be implemented in combination with other program modules. Generally, program modules include routines, programs, components, data structures, etc. that perform particular tasks and/or implement particular abstract data types. Moreover, those skilled in the art will appreciate that the systems/methods may be practiced with other computer system configurations, including single-processor, multiprocessor or multi-core processor computer systems, mini-computing devices, mainframe computers, as well as personal computers, hand-held computing devices (e.g., personal digital assistant (PDA), phone, watch . . . ), microprocessor-based or programmable consumer or industrial electronics, and the like. The illustrated aspects may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. However, some, if not all aspects of the claimed subject matter can be practiced on stand-alone computers. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.


With reference to FIG. 22, an exemplary environment 2210 for implementing various aspects disclosed herein includes a computer 2212 (e.g., desktop, laptop, server, set-top box, hand held, programmable consumer or industrial electronics . . . ). The computer 2212 includes a processing unit 2214, a system memory 2216 and a system bus 2218. The system bus 2218 couples system components including, but not limited to, the system memory 2216 to the processing unit 2214. The processing unit 2214 can be any of various available microprocessors. It is to be appreciated that dual microprocessors, multi-core and other multiprocessor architectures can be employed as the processing unit 2214.


The system memory 2216 includes volatile and nonvolatile memory. The basic input/output system (BIOS), including the basic routines to transfer information between elements within the computer 2212, such as during start-up, is stored in nonvolatile memory. By way of illustration, and not limitation, nonvolatile memory can include read only memory (ROM). Volatile memory includes random access memory (RAM), which can act as external cache memory to facilitate processing.


Computer 2212 also includes removable/non-removable, volatile/nonvolatile computer storage media. FIG. 22 illustrates, for example, mass storage 2224. Mass storage 2224 includes, but is not limited to, devices like a magnetic or optical disk drive, floppy disk drive, flash memory or memory stick. In addition, mass storage 2224 can include storage media separately or in combination with other storage media.



FIG. 22 provides software application(s) 2228 that act as an intermediary between users and/or other computers and the basic computer resources described in suitable operating environment 2210. Such software application(s) 2228 include one or both of system and application software. System software can include an operating system, which can be stored on mass storage 2224, that acts to control and allocate resources of the computer system 2212. Application software takes advantage of the management of resources by system software through program modules and data stored on either or both of system memory 2216 and mass storage 2224.


The computer 2212 also includes one or more interface components 2226 that are communicatively coupled to the bus 2218 and facilitate interaction with the computer 2212. By way of example, the interface component 2226 can be a port (e.g., serial, parallel, PCMCIA, USB, FireWire . . . ) or an interface card (e.g., sound, video, network . . . ) or the like. The interface component 2226 can receive input and provide output (wired or wirelessly). For instance, input can be received from devices including but not limited to, a pointing device such as a mouse, trackball, stylus, touch pad, keyboard, microphone, joystick, game pad, satellite dish, scanner, camera, other computer and the like. Output can also be supplied by the computer 2212 to output device(s) via interface component 2226. Output devices can include displays (e.g., CRT, LCD, plasma . . . ), speakers, printers and other computers, among other things.



FIG. 23 is a schematic block diagram of a sample-computing environment 2300 with which the subject innovation can interact. The system 2300 includes one or more client(s) 2310. The client(s) 2310 can be hardware and/or software (e.g., threads, processes, computing devices). The system 2300 also includes one or more server(s) 2330. Thus, system 2300 can correspond to a two-tier client server model or a multi-tier model (e.g., client, middle tier server, data server), amongst other models. The server(s) 2330 can also be hardware and/or software (e.g., threads, processes, computing devices). The servers 2330 can house threads to perform transformations by employing the aspects of the subject innovation, for example. One possible communication between a client 2310 and a server 2330 may be in the form of a data packet transmitted between two or more computer processes.


The system 2300 includes a communication framework 2350 that can be employed to facilitate communications between the client(s) 2310 and the server(s) 2330. Here, the client(s) can correspond to buyer and/or maven computing devices and the server(s) can provide the functionality with respect to maintaining deal rooms and demand aggregation, as previously described. The client(s) 2310 are operatively connected to one or more client data store(s) 2360 that can be employed to store information local to the client(s) 2310. Similarly, the server(s) 2330 are operatively connected to one or more server data store(s) 2340 that can be employed to store information local to the servers 2330. By way of example, a user (e.g., buyer, seller, maven . . . ) can login to one or more servers 2330 via a client 2310 to facilitate interaction with deal room/demand aggregation data persisted to data store(s) 2340.


What has been described above includes examples of aspects of the claimed subject matter. It is, of course, not possible to describe every conceivable combination of components or methodologies for purposes of describing the claimed subject matter, but one of ordinary skill in the art may recognize that many further combinations and permutations of the disclosed subject matter are possible. Accordingly, the disclosed subject matter is intended to embrace all such alterations, modifications and variations that fall within the spirit and scope of the appended claims. Furthermore, to the extent that the terms “includes,” “has” or “having” or variations in form thereof are used in either the detailed description or the claims, such terms are intended to be inclusive in a manner similar to the term “comprising” as “comprising” is interpreted when employed as a transitional word in a claim.

Claims
  • 1. A non-transitory computer readable storage medium having embodied thereon computer executable instructions, the instructions being executable by a processor to perform a method for: tracking a current purchasing volume associated with a live offer for a product or service provided by a first merchant;tracking an offer price;tracking a time associated with a purchase;receiving updated information related to a live offer for a similar product or service from a second merchant, wherein the updated information triggers an automatic price adjustment to the offer provided by the first merchant and wherein the updated information includes a quantity purchased over a set period of time;verifying resource availability data associated with the first merchant, wherein the resource availability data indicates at least one of a real time spare capacity or inventory of a product or service provided by the first merchant that is expressed numerically, and a time period associated with the spare capacity or available inventory;determining at least one suitable recipient of the offer for the product or service based upon information associated with a set of buyer profiles; andproviding the offer to the at least one suitable recipient by way of a mobile device associated with the at least one suitable recipient.
  • 2. The non-transitory computer readable storage medium of claim 1, wherein the price adjustment is an increase in the price.
  • 3. The non-transitory computer readable storage medium of claim 1, wherein the price adjustment is a discounted price.
  • 4. The non-transitory computer readable storage medium of claim 3, wherein the discounted price is contingent upon acceptance of the offer for the product or service with spare capacity by a predetermined number of suitable recipients or by an aggregate volume received within a displayed time period.
  • 5. The non-transitory computer readable storage medium of claim 3, wherein the updated information includes real-time information associated with the live offer for a similar product or service from the second merchant.
  • 6. The non-transitory computer readable storage medium of claim 3, wherein the trigger is set by the second merchant.
  • 7. The non-transitory computer readable storage medium of claim 1, wherein the trigger is set by a seller of the good or service and is influenced by purchases over time of at least one product or service recipient.
  • 8. The non-transitory computer readable storage medium of claim 1, wherein the determination of the suitable recipient includes a consideration of a transaction history in the buyer profile.
  • 9. The non-transitory computer readable storage medium of claim 1, wherein the buyer profile information includes demographics data in the buyer profile and a stored preference associated with a buyer.
  • 10. The non-transitory computer readable storage medium of claim 1, wherein the buyer profile information includes location information included in the buyer profile updated by way of a mobile device associated with a buyer.
  • 11. The non-transitory computer readable storage medium of claim 1, wherein the buyer profile information includes a search related to a product or service category of interest as indicated by a buyer.
  • 12. The non-transitory computer readable storage medium of claim 1, wherein the buyer profile includes an updated location associated with a mobile device of a buyer and a visual representation of at least one interested party.
  • 13. The non-transitory computer readable storage medium of claim 1, wherein the at least one suitable recipient may accept the offer and provide payment information through a registered account.
  • 14. The non-transitory computer readable storage medium of claim 1, wherein the offer is transmitted to a third-party account associated with the suitable recipient.
  • 15. The non-transitory computer readable storage medium of claim 1, wherein the updated information related to a live offer includes information related to a purchase volume.
  • 16. The non-transitory computer readable storage medium of claim 1, wherein the updated information related to a live offer includes information related to updated purchases.
  • 17. The non-transitory computer readable storage medium of claim 1, wherein the mobile device associated with the at least one suitable recipient is a wearable device.
  • 18. The non-transitory computer readable storage medium of claim 17, wherein the wearable device is a watch.
  • 19. A computer-implemented method, the method comprising: executing computer readable instructions stored in a non-transitory computer readable storage medium to: track a current purchasing volume associated with a live offer for a product or service provided by a first merchant, tracking an offer price;track a time associated with a purchase;receive updated information related to a live offer for a similar product or service from a second merchant, wherein the updated information triggers an automatic price adjustment to the offer provided by the first merchant and wherein the updated information includes a quantity purchased over a set period of time, the instructions executed by use of a processing device;executing computer readable instructions stored in a non-transitory computer readable storage medium to: verify resource availability data associated with the first merchant, wherein the resource availability data indicates at least one of a real time spare capacity or inventory of a product or service provided by the first merchant that is expressed numerically, anda time period associated with the spare capacity or available inventory;executing computer readable instructions stored in a non-transitory computer readable storage medium to examine a set of buyer profiles for identifying at least one suitable recipient of the offer for the product or service based upon information associated with a set of buyer profiles, the instructions executed by use of a processing device;executing computer readable instructions stored in a non-transitory computer readable storage medium to provide the offer to the at least one suitable recipient by way of a mobile device associated with the at least one suitable recipient, the instructions executed by use of a processing device.
  • 20. The computer-implemented method of claim 19, wherein the offer includes a price for the product or service that differs from a market price for the product or service offered by the merchant.
  • 21. The computer-implemented method of claim 19, wherein a price included in the offer for the product or service varies depending on a status of the at least one suitable recipient from amongst a group of suitable recipients.
  • 22. The computer-implemented method of claim 19, wherein a price included in the offer for the product or service varies depending on a behavior of the at least one suitable recipient from amongst a group of suitable recipients.
  • 23. The computer-implemented method of claim 19, wherein a price included in the offer for the product or service is contingent upon a predetermined number of suitable recipients accepting the offer for the product or service or by an aggregate volume.
  • 24. The computer-implemented method of claim 19, wherein a price included in the offer for the product or service is contingent upon the at least one suitable recipient accepting the offer for the product or service within a predetermined time specified in the offer.
  • 25. The computer-implemented method of claim 19, wherein a price included in the offer for the product or service is contingent upon the at least one suitable recipient accepting the offer for the product or service during a time in which a spare capacity condition exists for the merchant.
  • 26. The computer-implemented method of claim 19, further comprising determining the at least one suitable recipient based upon a transaction stored in the buyer profile.
  • 27. The computer-implemented method of claim 19, further comprising determining the at least one suitable recipient based upon demographic data stored in the buyer profile.
  • 28. The computer-implemented method of claim 19, further comprising determining the at least one suitable recipient based upon a location of the suitable recipient stored in the buyer profile.
  • 29. The computer-implemented method of claim 19, further comprising determining the at least one suitable recipient based upon activity associated with the suitable recipient.
  • 30. The computer-implemented method of claim 19, further comprising determining the at least one suitable recipient based upon a set of contacts associated with the suitable recipient.
  • 31. The computer-implemented method of claim 19, further comprising determining the at least one suitable recipient based upon activity associated with a contact included in a set of contacts of the at least one suitable recipient.
  • 32. A non-transitory computer readable storage medium having embodied thereon computer executable instructions, the instructions being executable by a processor to perform a method for: tracking a current purchasing volume associated with a live offer for a product or service provided by a first merchant;tracking an offer price;tracking a time associated with a purchase;receiving updated information related to a live offer for a similar product or service from a second merchant, wherein the updated information triggers an automatic price adjustment to the offer provided by the first merchant and the updated information includes a quantity purchased over a set period of time;verifying resource availability data associated with the first merchant, wherein the resource availability data: indicates at least one of a real time spare capacity or inventory of a product or service provided by the first merchant that is expressed numerically, and a time period associated with the spare capacity or available inventory,indicates current excess capacity or inventory of a product or service offered by the first merchant;examining a set of buyer profiles;determining at least one eligible recipient of the offer for the product or service with current excess capacity based upon the examined set of buyer profiles; anddelivering an offer based upon the resource availability data, the offer provided to the at least one eligible recipient by way of a mobile device associated with the at least one suitable recipient.
  • 33. A non-transitory computer readable storage medium having embodied thereon computer executable instructions, the instructions being executable by a processor to perform a method for: tracking a current purchasing volume associated with a live offer for a product or service provided by a first merchant;tracking an offer price;tracking a time associated with a purchase;receiving updated information related to a live offer for a similar product or service from a second merchant, wherein the updated information triggers an automatic price adjustment to the offer provided by the first merchant and wherein the updated information includes information related to a purchase volume;verifying resource availability data associated with the first merchant, wherein the resource availability data indicates at least one of a real time spare capacity or inventory of a product or service provided by the first merchant that is expressed numerically, and a time period associated with the spare capacity or available inventory;determining at least one suitable recipient of the offer for the product or service based upon information associated with a set of buyer profiles; andproviding the offer to the at least one suitable recipient by way of a mobile device associated with the at least one suitable recipient.
  • 34. The non-transitory computer readable storage medium of claim 33, wherein the price adjustment is an increase in the price.
  • 35. The non-transitory computer readable storage medium of claim 33, wherein the price adjustment is a discounted price.
  • 36. The non-transitory computer readable storage medium of claim 35, wherein the discounted price is contingent upon acceptance of the offer for the product or service with spare capacity by a predetermined number of suitable recipients or by an aggregate volume received within a displayed time period.
  • 37. The non-transitory computer readable storage medium of claim 35, wherein the updated information includes real-time information associated with the live offer for a similar product or service from the second merchant.
  • 38. The non-transitory computer readable storage medium of claim 35, wherein the trigger is set by the second merchant.
  • 39. The non-transitory computer readable storage medium of claim 33, wherein the trigger is set by a seller of the good or service and is influenced by purchases over time of at least one product or service recipient.
  • 40. The non-transitory computer readable storage medium of claim 33, wherein the determination of the suitable recipient includes a consideration of a transaction history in the buyer profile.
  • 41. The non-transitory computer readable storage medium of claim 33, wherein the buyer profile information includes demographics data in the buyer profile and a stored preference associated with a buyer.
  • 42. The non-transitory computer readable storage medium of claim 33, wherein the buyer profile information includes location information included in the buyer profile updated by way of a mobile device associated with a buyer.
  • 43. The non-transitory computer readable storage medium of claim 33, wherein the buyer profile information includes a search related to a product or service category of interest as indicated by a buyer.
  • 44. The non-transitory computer readable storage medium of claim 33, wherein the buyer profile includes an updated location associated with a mobile device of a buyer and a visual representation of at least one interested party.
  • 45. The non-transitory computer readable storage medium of claim 33, wherein the updated information includes a quantity purchased over a set period of time.
  • 46. The non-transitory computer readable storage medium of claim 45, wherein the at least one suitable recipient may accept the offer and provide payment information through a registered account.
  • 47. The non-transitory computer readable storage medium of claim 33, wherein the offer is transmitted to a third-party account associated with the suitable recipient.
  • 48. The non-transitory computer readable storage medium of claim 33, wherein the updated information related to a live offer includes information related to updated purchases.
  • 49. The non-transitory computer readable storage medium of claim 33, wherein the mobile device associated with the at least one suitable recipient is a wearable device.
  • 50. The non-transitory computer readable storage medium of claim 49, wherein the wearable device is a watch.
CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No. 11/618,412, filed Dec. 29, 2006 and entitled HOSTED DEMAND AGGREGATION, which: (1) is a continuation-in-part of U.S. Pat. No. 7,689,469, filed Aug. 14, 2006 and entitled E-COMMERCE VOLUME PRICING, which is a continuation of U.S. Pat. No. 7,124,099, filed on Feb. 20, 2003 and entitled E-COMMERCE VOLUME PRICING, which is a continuation of U.S. patent application Ser. No. 09/324,391, filed Jun. 3, 1999 and entitled E-COMMERCE VOLUME PRICING, now abandoned, which claims the benefit of U.S. Provisional Patent Application Ser. No. 60/133,769, filed May 12, 1999 and entitled E-COMMERCE VOLUME PRICING; (2) is a continuation-in-part of U.S. Pat. No. 7,747,473, filed Nov. 3, 2006 and entitled DEMAND AGGREGATION SYSTEM, which is a continuation of U.S. Pat. No. 7,181,419, filed on Sep. 13, 2002 and entitled DEMAND AGGREGATION SYSTEM, which claims the benefit of U.S. Provisional Application Ser. No. 60/318,789 filed on Sep. 13, 2001; (3) is a continuation-in-part of U.S. patent application Ser. No. 09/922,884, entitled E-COMMERCE VOLUME PRICING filed on Aug. 6, 2001, which: (A) is a continuation-in-part of U.S. patent application Ser. No. 09/324,391, entitled E-COMMERCE VOLUME PRICING filed on Jun. 3, 1999, which claims priority to U.S. Patent Application Ser. No. 60/133,769, filed May 12, 1999, and entitled E-COMMERCE VOLUME PRICING; (B) is a continuation-in-part of U.S. Pat. No. 7,818,212, filed Oct. 22, 1999 and entitled MULTIPLE CRITERIA BUYING AND SELLING MODEL; (C) is a continuation-in-part of P.C.T. Patent Application Serial No. PCT/US00/11989, filed May 3, 2000, and entitled MULTIPLE CRITERIA BUYING AND SELLING MODEL, AND SYSTEM FOR MANAGING OPEN OFFER SHEETS, which claims priority to: U.S. Patent Application Ser. No. 60/137,583, filed Jun. 4, 1999, and entitled E-COMMERCE AUTOMATED SELLER SELECTION SYSTEM; U.S. Patent Application Ser. No. 60/138,209, filed Jun. 9, 1999, and entitled SECURITIZATION OF ACCOUNTS RECEIVABLE; U.S. Patent Application Ser. No. 60/139,338, filed Jun. 16, 1999, and entitled REAL-TIME OPTIMIZED BUYING BLOCK; U.S. Patent Application Ser. No. 60/139,518, filed Jun. 16, 1999, and entitled REAL-TIME MARKET PURCHASING; U.S. Patent Application Ser. No. 60/139,519, filed Jun. 16, 1999, and entitled E-COMMERCE PURCHASING CARD; U.S. patent application Ser. No. 09/342,345, filed Jun. 29, 1999, and entitled CREDIT BASED TRANSACTION SYSTEM AND METHODOLOGY; U.S. Patent Application Ser. No. 60/142,371, filed Jul. 6, 1999, and entitled TIME VALUE OF MONEY BASED CREDIT CARD FOR MERCHANT; U.S. Patent Application Ser. No. 60/160,510, filed Oct. 20, 1999, and entitled MULTIPLE CRITERIA BUYING AND SELLING MODEL, AND SYSTEM FOR MANAGING OPEN OFFER SHEETS; U.S. patent application Ser. No. 09/426,063, filed Oct. 22, 1999, and entitled MULTIPLE CRITERIA BUYING AND SELLING MODEL; U.S. Patent Application Ser. No. 60/162,182, filed Oct. 28, 1999, and entitled MULTIPLE CRITERIA BUYING AND SELLING MODEL, AND SYSTEM FOR MANAGING OPEN OFFER SHEETS; and U.S. Patent Application Ser. No. 60/173,409, filed Dec. 28, 1999, and entitled MULTIPLE CRITERIA BUYING AND SELLING MODEL, AND SYSTEM FOR MANAGING OPEN OFFER SHEETS; and (D) claims priority to U.S. Patent Application Ser. No. 60/237,474, filed Oct. 2, 2000, and entitled MULTIPLE CRITERIA BUYING AND SELLING MODEL, AND SYSTEM FOR MANAGING OPEN OFFER SHEETS. The entireties of all prior-filed applications listed herein are hereby incorporated herein by reference.

US Referenced Citations (467)
Number Name Date Kind
4789928 Fujisaki Dec 1988 A
4799156 Shavit et al. Jan 1989 A
4887207 Natarajan Dec 1989 A
4947028 Gorog Aug 1990 A
4992940 Dworkin Feb 1991 A
5053956 Donald et al. Oct 1991 A
5053957 Suzuki Oct 1991 A
5063506 Brockwell et al. Nov 1991 A
5402336 Spiegelhoff et al. Mar 1995 A
5414838 Kolton et al. May 1995 A
5444630 Dlugos Aug 1995 A
5564115 Clarkson Oct 1996 A
5592375 Salmon et al. Jan 1997 A
5615109 Eder Mar 1997 A
5623660 Josephson Apr 1997 A
5664115 Fraser Sep 1997 A
5689652 Lupien et al. Nov 1997 A
5710887 Chelliah et al. Jan 1998 A
5717989 Tozzoli et al. Feb 1998 A
5732400 Mandler et al. Mar 1998 A
5734890 Case et al. Mar 1998 A
5794207 Walker et al. Aug 1998 A
5797127 Walker et al. Aug 1998 A
5799285 Klingman Aug 1998 A
5822736 Hartman et al. Oct 1998 A
5826244 Huberman Oct 1998 A
5835896 Fisher et al. Nov 1998 A
5837071 Andersson et al. Nov 1998 A
5842178 Giovannoli Nov 1998 A
5845265 Woolston Dec 1998 A
5850442 Muftic Dec 1998 A
5855008 Goldhaber et al. Dec 1998 A
5870721 Norris Feb 1999 A
5878400 Carter, III Mar 1999 A
5884271 Pitroda Mar 1999 A
5890138 Godin et al. Mar 1999 A
5897620 Walker et al. Apr 1999 A
5903830 Joao et al. May 1999 A
5923741 Wright et al. Jul 1999 A
5933817 Hucal Aug 1999 A
5940807 Purcell Aug 1999 A
5945653 Walker et al. Aug 1999 A
5950172 Klingman Sep 1999 A
5960411 Hartman et al. Sep 1999 A
5966697 Fergerson et al. Oct 1999 A
5970478 Walker et al. Oct 1999 A
5974396 Anderson et al. Oct 1999 A
5974406 Bisdikian et al. Oct 1999 A
5987434 Libman Nov 1999 A
5995943 Bull et al. Nov 1999 A
5999915 Nahan et al. Dec 1999 A
6014638 Burge et al. Jan 2000 A
6016484 Williams et al. Jan 2000 A
6026383 Ausubel Feb 2000 A
6032136 Brake et al. Feb 2000 A
6035289 Chou et al. Mar 2000 A
6052670 Johnson Apr 2000 A
6055519 Kennedy et al. Apr 2000 A
6055573 Gardenswartz et al. Apr 2000 A
6064981 Barni et al. May 2000 A
6078906 Huberman Jun 2000 A
6101484 Halbert et al. Aug 2000 A
6108632 Reeder et al. Aug 2000 A
6108639 Walker et al. Aug 2000 A
6112185 Walker et al. Aug 2000 A
6112189 Rickard et al. Aug 2000 A
6131087 Luke et al. Oct 2000 A
6141653 Conklin et al. Oct 2000 A
6151588 Tozzoli et al. Nov 2000 A
6154738 Call Nov 2000 A
6167383 Henson Dec 2000 A
6195646 Grosh et al. Feb 2001 B1
6219653 O'Neill et al. Apr 2001 B1
6233566 Levine et al. May 2001 B1
6236972 Shkedy May 2001 B1
6236977 Verba et al. May 2001 B1
6236978 Tuzhilin May 2001 B1
6249772 Walker et al. Jun 2001 B1
6253189 Feezell et al. Jun 2001 B1
6260019 Courts Jul 2001 B1
6260024 Shkedy Jul 2001 B1
6266651 Woolston Jul 2001 B1
6269343 Pallakoff Jul 2001 B1
6289348 Richard et al. Sep 2001 B1
6323894 Katz Nov 2001 B1
6327574 Kramer et al. Dec 2001 B1
6332127 Bandera et al. Dec 2001 B1
6332135 Conklin et al. Dec 2001 B1
6336105 Conklin et al. Jan 2002 B1
6338050 Conklin et al. Jan 2002 B1
6360205 Iyengar et al. Mar 2002 B1
6397208 Lee May 2002 B1
6415270 Rackson et al. Jul 2002 B1
6418415 Walker et al. Jul 2002 B1
6418441 Call Jul 2002 B1
6449601 Friedland et al. Sep 2002 B1
6450407 Freeman et al. Sep 2002 B1
6456986 Boardman et al. Sep 2002 B1
6466919 Walker et al. Oct 2002 B1
6496568 Nelson Dec 2002 B1
6505046 Baker Jan 2003 B1
6507279 Loof Jan 2003 B2
6510434 Anderson et al. Jan 2003 B1
6519571 Guheen et al. Feb 2003 B1
6535856 Tal Mar 2003 B1
6553346 Walker et al. Apr 2003 B1
6553350 Carter Apr 2003 B2
6560501 Walser et al. May 2003 B1
6578014 Murcko, Jr. Jun 2003 B1
6584451 Shoham et al. Jun 2003 B1
6587835 Treyz et al. Jul 2003 B1
6598026 Ojha et al. Jul 2003 B1
6601043 Purcell Jul 2003 B1
6604089 Van Horn et al. Aug 2003 B1
6606603 Joseph et al. Aug 2003 B1
6606607 Martin et al. Aug 2003 B1
6607136 Atsmon et al. Aug 2003 B1
6631356 Van Horn et al. Oct 2003 B1
6647257 Owensby Nov 2003 B2
6647373 Carlton-Foss Nov 2003 B1
6658093 Langseth et al. Dec 2003 B1
6662194 Joao et al. Dec 2003 B1
6705520 Pitroda et al. Mar 2004 B1
6716101 Meadows et al. Apr 2004 B1
6754636 Walker et al. Jun 2004 B1
6769607 Pitroda et al. Aug 2004 B1
6778968 Gulati Aug 2004 B1
6782370 Stack Aug 2004 B1
6785661 Mandler et al. Aug 2004 B1
6839690 Foth et al. Jan 2005 B1
6847938 Moore Jan 2005 B1
6847965 Walker et al. Jan 2005 B2
6850907 Lutnick et al. Feb 2005 B2
6868392 Ogasawara Mar 2005 B1
6871140 Florance et al. Mar 2005 B1
6871190 Seymour et al. Mar 2005 B1
6876974 Marsh et al. Apr 2005 B1
6876977 Marks Apr 2005 B1
6876982 Lancaster Apr 2005 B1
6876983 Goddard Apr 2005 B1
6877655 Robertson et al. Apr 2005 B1
6877665 Challa et al. Apr 2005 B2
6915275 Banerjee et al. Jul 2005 B2
6922674 Nelson Jul 2005 B1
6925446 Watanabe Aug 2005 B2
6928416 Bertash Aug 2005 B1
6934690 Van Horn et al. Aug 2005 B1
6952219 Lee Oct 2005 B2
6954734 Kuelbs et al. Oct 2005 B1
6985879 Walker et al. Jan 2006 B2
6990467 Kwan Jan 2006 B1
6992794 Keane et al. Jan 2006 B2
7013285 Rebane Mar 2006 B1
7013286 Aggarwal et al. Mar 2006 B1
7016865 Weber et al. Mar 2006 B1
7035820 Goodwin et al. Apr 2006 B2
7039603 Walker et al. May 2006 B2
7047206 Schultze May 2006 B1
7062452 Lotvin et al. Jun 2006 B1
7065494 Evans Jun 2006 B1
7069228 Rose et al. Jun 2006 B1
7072849 Filepp et al. Jul 2006 B1
7072853 Shkedi Jul 2006 B2
7076447 Peyser et al. Jul 2006 B1
7080030 Eglen et al. Jul 2006 B2
7082408 Baumann et al. Jul 2006 B1
7103565 Vaid Sep 2006 B1
7103567 Smukowski Sep 2006 B2
7107225 McClung, III Sep 2006 B1
7107226 Cassidy et al. Sep 2006 B1
7120592 Lewis Oct 2006 B1
7124099 Mesaros Oct 2006 B2
7124107 Pishevar et al. Oct 2006 B1
7133835 Fusz et al. Nov 2006 B1
7143057 Kuelbs et al. Nov 2006 B2
7146330 Alon et al. Dec 2006 B1
7165045 Kim-E Jan 2007 B1
7181419 Mesaros Feb 2007 B1
7194427 Van Horn et al. Mar 2007 B1
7194442 Flanagan et al. Mar 2007 B1
7213754 Eglen et al. May 2007 B2
7236575 Kim et al. Jun 2007 B2
7240021 Walker et al. Jul 2007 B1
7243082 Forlai Jul 2007 B1
7254833 Cornelius et al. Aug 2007 B1
7263498 Van Horn et al. Aug 2007 B1
7263505 Forlai Aug 2007 B1
7296001 Ephrati et al. Nov 2007 B1
7330826 Porat et al. Feb 2008 B1
7343317 Jokinen et al. Mar 2008 B2
7349890 Pathak et al. Mar 2008 B1
7363246 Van Horn et al. Apr 2008 B1
7364086 Mesaros Apr 2008 B2
7376613 Cofino et al. May 2008 B1
7379899 Junger May 2008 B1
7415428 Garwood Aug 2008 B2
7415617 Ginter et al. Aug 2008 B2
7433832 Bezos et al. Oct 2008 B1
7464051 Heggem Dec 2008 B1
7467103 Murray et al. Dec 2008 B1
7475024 Phan Jan 2009 B1
7480627 Van Horn et al. Jan 2009 B1
7496543 Bamford et al. Feb 2009 B1
7516089 Walker et al. Apr 2009 B1
7523045 Walker et al. Apr 2009 B1
7539742 Spector May 2009 B2
7542927 Mukai Jun 2009 B2
7552069 Kepecs Jun 2009 B2
7577582 Ojha et al. Aug 2009 B1
7584146 Duhon Sep 2009 B1
7593871 Mesaros Sep 2009 B1
7596509 Bryson Sep 2009 B1
7599857 Bishop et al. Oct 2009 B2
7606731 McClung, III Oct 2009 B2
7624044 Wren Nov 2009 B2
7630919 Obrecht Dec 2009 B1
7636672 Angles et al. Dec 2009 B2
7672870 Haines et al. Mar 2010 B2
7680696 Murray Mar 2010 B1
7689463 Mesaros Mar 2010 B1
7689468 Walker et al. Mar 2010 B2
7689469 Mesaros Mar 2010 B1
7693748 Mesaros Apr 2010 B1
7698173 Burge et al. Apr 2010 B1
7698208 Hirani et al. Apr 2010 B2
7698240 Chatterjee et al. Apr 2010 B1
7706838 Atsmon et al. Apr 2010 B2
7725350 Schlee May 2010 B2
7729977 Xiao et al. Jun 2010 B2
7747473 Mesaros Jun 2010 B1
7792699 Kwei Sep 2010 B2
7801803 Forlai Sep 2010 B2
7813955 Ariff et al. Oct 2010 B2
7814106 Guido et al. Oct 2010 B2
7814114 Mi et al. Oct 2010 B2
7815114 Mesaros Oct 2010 B2
7818212 Mesaros Oct 2010 B1
7860776 Chin et al. Dec 2010 B1
7890373 Junger Feb 2011 B2
7899707 Mesaros Mar 2011 B1
7912761 Vaid Mar 2011 B2
7917386 Christensen Mar 2011 B2
7917416 Quinn et al. Mar 2011 B2
7937288 Blaser et al. May 2011 B2
7942316 Bennett et al. May 2011 B2
7953730 Bleckner et al. May 2011 B1
7958007 Urbanski et al. Jun 2011 B2
8005747 Forlai Aug 2011 B2
8015583 Bates et al. Sep 2011 B2
8024226 Fusz et al. Sep 2011 B2
8032409 Mikurak Oct 2011 B1
8032422 Pickard et al. Oct 2011 B2
8036941 Bennett et al. Oct 2011 B2
8073762 Sheth et al. Dec 2011 B2
8104682 Junger Jan 2012 B2
8140402 Mesaros Mar 2012 B1
8140405 Mesaros Mar 2012 B2
8140442 Heyer Mar 2012 B2
8140615 Miller et al. Mar 2012 B2
8150735 Walker et al. Apr 2012 B2
8160931 Mesaros Apr 2012 B2
8171561 Moskowitz et al. May 2012 B2
8196811 Mesaros Jun 2012 B2
8209226 Cheney et al. Jun 2012 B2
8219460 Mesaros Jul 2012 B1
8249942 Mesaros Aug 2012 B2
8271327 Walker et al. Sep 2012 B2
8271332 Mesaros Sep 2012 B2
8285598 Mesaros Oct 2012 B2
8285600 Mesaros Oct 2012 B2
8290824 Mesaros Oct 2012 B1
8306870 Mesaros Nov 2012 B2
8311896 Mesaros Nov 2012 B2
8341033 Porat et al. Dec 2012 B2
8341035 Mesaros Dec 2012 B2
8401918 Mesaros Mar 2013 B2
8438075 Mesaros May 2013 B2
8473353 Matsuda et al. Jun 2013 B2
8489466 Van Horn et al. Jul 2013 B1
8494914 Mesaros Jul 2013 B2
8494915 Mesaros Jul 2013 B2
8533002 Mesaros Sep 2013 B2
8567672 Mesaros Oct 2013 B2
8573492 Mesaros Nov 2013 B2
8584940 Mesaros Nov 2013 B2
8589247 Mesaros Nov 2013 B2
8590785 Mesaros Nov 2013 B1
8616449 Mesaros Dec 2013 B2
8620765 Mesaros Dec 2013 B2
8626605 Mesaros Jan 2014 B2
8635108 Mesaros Jan 2014 B2
20010011247 O'Flaherty et al. Aug 2001 A1
20010011264 Kawasaki Aug 2001 A1
20010014868 Herz et al. Aug 2001 A1
20010018660 Sehr Aug 2001 A1
20010039514 Barenbaum et al. Nov 2001 A1
20010044751 Pugliese, III et al. Nov 2001 A1
20010047296 Wyker Nov 2001 A1
20010047311 Singh Nov 2001 A1
20020004765 Han et al. Jan 2002 A1
20020007324 Centner et al. Jan 2002 A1
20020026351 Coleman Feb 2002 A1
20020032573 Williams et al. Mar 2002 A1
20020035536 Gellman Mar 2002 A1
20020040352 McCormick Apr 2002 A1
20020046105 Gardenswartz et al. Apr 2002 A1
20020046147 Livesay et al. Apr 2002 A1
20020052782 Landesmann May 2002 A1
20020065762 Lee et al. May 2002 A1
20020065769 Irribarren et al. May 2002 A1
20020069079 Vega Jun 2002 A1
20020080950 Koko et al. Jun 2002 A1
20020082881 Price et al. Jun 2002 A1
20020091580 Wang Jul 2002 A1
20020099643 Abeshouse et al. Jul 2002 A1
20020103741 Boies et al. Aug 2002 A1
20020107773 Abdou Aug 2002 A1
20020116282 Martin et al. Aug 2002 A1
20020143692 Heimermann et al. Oct 2002 A1
20020147670 Lange Oct 2002 A1
20020165771 Walker et al. Nov 2002 A1
20020165821 Tree Nov 2002 A1
20020169703 Lutnick et al. Nov 2002 A1
20020169759 Kraft et al. Nov 2002 A1
20020174000 Katz et al. Nov 2002 A1
20020174051 Wise Nov 2002 A1
20020178077 Katz et al. Nov 2002 A1
20020188508 Lee et al. Dec 2002 A1
20030004802 Callegari Jan 2003 A1
20030004808 Elhaoussine et al. Jan 2003 A1
20030004823 Sagy Jan 2003 A1
20030028473 Eso et al. Feb 2003 A1
20030041002 Hao et al. Feb 2003 A1
20030055774 Ginsberg Mar 2003 A1
20030088494 Lee May 2003 A1
20030093355 Issa May 2003 A1
20030109949 Ikeda Jun 2003 A1
20030111531 Williams et al. Jun 2003 A1
20030115100 Teicher Jun 2003 A1
20030126040 Mesaros Jul 2003 A1
20030126250 Jhanji Jul 2003 A1
20030149619 Stanley et al. Aug 2003 A1
20030167222 Mehrotra et al. Sep 2003 A1
20030195832 Cao et al. Oct 2003 A1
20030200150 Westcott et al. Oct 2003 A1
20030208412 Hillestad et al. Nov 2003 A1
20030216960 Postrel Nov 2003 A1
20030233276 Pearlman et al. Dec 2003 A1
20030233557 Zimmerman Dec 2003 A1
20040015415 Cofino et al. Jan 2004 A1
20040019494 Ridgeway et al. Jan 2004 A1
20040019646 Zweben et al. Jan 2004 A1
20040039661 Fuzell-Casey et al. Feb 2004 A1
20040039677 Mura et al. Feb 2004 A1
20040093276 Nishio May 2004 A1
20040128197 Bam et al. Jul 2004 A1
20040153431 Bhogal et al. Aug 2004 A1
20040172372 Wells et al. Sep 2004 A1
20040215467 Coffman et al. Oct 2004 A1
20040215500 Monahan Oct 2004 A1
20050021400 Postrel Jan 2005 A1
20050021401 Postrel Jan 2005 A1
20050038713 Pickard et al. Feb 2005 A1
20050149458 Eglen et al. Jul 2005 A1
20050171918 Eden et al. Aug 2005 A1
20050197857 Avery Sep 2005 A1
20050216337 Roberts et al. Sep 2005 A1
20050272442 Miller et al. Dec 2005 A1
20050273415 Mathews et al. Dec 2005 A1
20050288954 McCarthy et al. Dec 2005 A1
20060036491 Leung et al. Feb 2006 A1
20060059062 Wood et al. Mar 2006 A1
20060069619 Walker et al. Mar 2006 A1
20060095327 Vaughn et al. May 2006 A1
20060095366 Sheth et al. May 2006 A1
20060106678 Walker et al. May 2006 A1
20060129454 Moon et al. Jun 2006 A1
20060143080 Garg et al. Jun 2006 A1
20060155598 Spurr et al. Jul 2006 A1
20060178918 Mikurak Aug 2006 A1
20060190379 Maas et al. Aug 2006 A1
20060259421 Maass Nov 2006 A1
20070150349 Handel et al. Jun 2007 A1
20070206584 Fulling et al. Sep 2007 A1
20070212938 Shin Sep 2007 A1
20070220169 Silver et al. Sep 2007 A1
20080015711 Charland et al. Jan 2008 A1
20080052189 Walker et al. Feb 2008 A1
20080052750 Grunnet-Jepsen et al. Feb 2008 A1
20080071634 Rampell et al. Mar 2008 A1
20080082418 Fordyce et al. Apr 2008 A1
20080126201 Ullah May 2008 A1
20080146204 Gu et al. Jun 2008 A1
20080147534 Ephrati et al. Jun 2008 A1
20080249846 Yonemoto et al. Oct 2008 A1
20080255886 Unkefer et al. Oct 2008 A1
20090055328 Bamford et al. Feb 2009 A1
20090059856 Kermoal et al. Mar 2009 A1
20090083136 Blackwood Mar 2009 A1
20090089177 Dayton et al. Apr 2009 A1
20090150218 Brunner et al. Jun 2009 A1
20090187455 Fernandes et al. Jul 2009 A1
20090198622 Temte et al. Aug 2009 A1
20090276305 Clopp Nov 2009 A1
20090307073 MirrokniBanadaki et al. Dec 2009 A1
20090319359 Soza et al. Dec 2009 A1
20090327034 Petersen Dec 2009 A1
20090327038 Petersen Dec 2009 A1
20090327101 Sayed Dec 2009 A1
20090327140 Kuo Dec 2009 A1
20100088174 Cohagan et al. Apr 2010 A1
20100125525 Inamdar May 2010 A1
20100169161 Sacco Jul 2010 A1
20110004515 Mesaros Jan 2011 A1
20110016010 Mesaros Jan 2011 A1
20110040624 Jhanji Feb 2011 A1
20110125592 Mesaros May 2011 A1
20110213648 Mesaros Sep 2011 A1
20110213649 Mesaros Sep 2011 A1
20110213650 Mesaros Sep 2011 A1
20110238476 Carr et al. Sep 2011 A1
20110246271 Mesaros Oct 2011 A1
20110246274 Mesaros Oct 2011 A1
20110264499 Abendroth et al. Oct 2011 A1
20110270699 Mesaros Nov 2011 A1
20110270700 Mesaros Nov 2011 A1
20120022970 Mesaros Jan 2012 A1
20120029993 Mesaros Feb 2012 A1
20120029995 Mesaros Feb 2012 A1
20120035999 Mesaros Feb 2012 A1
20120036000 Mesaros Feb 2012 A1
20120036031 Mesaros Feb 2012 A1
20120041811 Mesaros Feb 2012 A1
20120054012 Mesaros Mar 2012 A1
20120158475 Mesaros Jun 2012 A1
20120158479 Raisch Jun 2012 A1
20120179526 Mesaros Jul 2012 A1
20120179530 Mesaros Jul 2012 A1
20120197705 Mesaros Aug 2012 A1
20120197722 Mesaros Aug 2012 A1
20120203603 Mesaros Aug 2012 A1
20120203611 Mesaros Aug 2012 A1
20120203615 Mesaros Aug 2012 A1
20120209683 Mesaros Aug 2012 A1
20120209737 Mesaros Aug 2012 A1
20120209738 Mesaros Aug 2012 A1
20120209739 Mesaros Aug 2012 A1
20120209740 Mesaros Aug 2012 A1
20120209743 Mesaros Aug 2012 A1
20120226541 Mesaros Sep 2012 A1
20120245993 Mesaros Sep 2012 A1
20120253912 Mesaros Oct 2012 A1
20120253977 Mesaros Oct 2012 A1
20120265590 Mesaros Oct 2012 A1
20120265600 Mesaros Oct 2012 A1
20120278157 Mesaros Nov 2012 A1
20120284110 Mesaros Nov 2012 A1
20120290395 Mesaros Nov 2012 A1
20120310738 Mesaros Dec 2012 A1
20130006741 Mesaros Jan 2013 A1
20130013385 Mesaros Jan 2013 A1
20130013388 Mesaros Jan 2013 A1
20130080282 Mesaros Mar 2013 A1
20130117086 Mesaros May 2013 A1
20130246122 Mesaros Sep 2013 A1
20130246223 Mesaros Sep 2013 A1
20130275253 Mesaros Oct 2013 A1
Foreign Referenced Citations (5)
Number Date Country
11-184910 Jul 1999 JP
WO 9821713 May 1998 WO
WO-0050970 Aug 2000 WO
WO 0070424 Nov 2000 WO
WO 2008083371 Jul 2008 WO
Non-Patent Literature Citations (231)
Entry
Garner, K., “Culture Vulture: up from under—Germaine Greer,” Off Our Backs, Jun. 24, 1971, vol. 1, Iss. 23, p. 14.
Groupon, Inc.'s Motion for Summary Judgment of Non-Infringment dated Oct. 17, 2011.
Groupon, Inc.'s Opening Claim Construction Brief dated Jul. 5, 2011.
U.S. Appl. No. 13/517,528 Office Action mailed Dec. 6, 2012.
U.S. Appl. No. 13/794,721 Office Action Sep. 10, 2013.
“Excite@Home Standardizes on Siebel eBusiness; Leading Broadband Media Company Relies on Siebel Systems to Manage Customer Relationships Across Its Entire Family of Services,” Business Wire, Jan. 19, 2000.
“Global Real Estate Markets Spell Opportunity, Experts Tell Realtors,” PR Newswire, Nov. 21, 1991.
“Lucent Launches On-Line Catalog” M2 Presswire, Jan. 22, 1999.
“Screen Savers,” Lawyer, Feb. 19, 2001.
“The Oil and Gas Asset Clearinghouse, a Pertoleum Place Company, to Host It's Second Exclusively Online Auction of Oil and Gas Properties on Aug. 14-16, 2000.” PR Newswire, p. 5591, Aug. 3, 2000, 2 pages.
Amazon.com, “Help/Shipping”, Archived on Feb. 2, 2003 by www.archive.org. Last accessed Mar. 19, 2008, 9 pages.
Ashton Technology Group, Inc. Announces NASDAQ National Market System Listing; Enters into Clearing Arrangements with 8 National Brokerage Firms, Business Wire, Jan. 3, 2000. http://www.findarticles.com/p/articles/mi—mOEIN/is—2000—Jan—3/ai—58429780/print. Last accessed Apr. 8, 2009, 3 pages.
Beaty. Mass Customisation. Manufacturing Engineer, vol. 75, issue 5, Oct. 1996, pp. 217-220.
Blyth, et al. Merchandising System Collecting Data. Derwent Information Ltd. Last accessed Jan. 20, 2009, 2 pages.
Breyer. “Bargains in Cyberspace,” National Home Center News, vol. 26, No. 21, p. 21, Nov. 20, 2000.
Business Editors and High Tech Writers, “eWinWin Announces the Release of DAS 3.0, the Next Generation of B2B Demand Aggregation Solutions” Dec. 28, 2000, Businee wire, p. 1 (4 pages).
Business Editors. “Weatherchem Announces Major eCommerce Success with eWinWin”, Aug. 9, 2001, Business Wire, (p. 1) 2 pages.
CBOT, “Trading in Futures Can Provide Considerable Financial Rewards”, Last accessed Mar. 19, 2008, 41 pages.
Chicago Board of Trade, “Knowledge Center,” as archived by Archive.org, on Feb. 13, 2003.
China—Welcome to the Machine: New Machinery, Electronics B-to-B Website Launched. China Online, Jul. 24, 2000, 1 page.
Computer Geeks Discount Outlet, “Order Status,” Mar. 1, 2002.
Deierlein. “Smart Fuel Buying,” Fleet Equipment, vol. 24, No. 8, pp. 42-44, Aug. 1998.
Dibiase. The Inventory Simulator: A Micro Computer Based Inventory Model. Modeling and Simulation on Microcomputers, Paul F. Hogan, ed., Society for Computer Simulation (SCS), La Jolla, pp. 104-106, Jan. 1987.
DomainTradeLlVE! Launched by solutionhome.com. Business Wire, Oct. 20, 1999, 1 page.
Easley, et al. Time and the Process of Security Price Adjustment, Journal of Finance, vol. 47, No. 2, Jun. 1992. http://ideas.repec.org/a/bla/jfinan/v47y1992i2p576-605.html. Last accessed Sep. 10, 2009, 30 pages.
Edwards. “Increase Your Bottom Line : Automated Customer Service and Marketing,” E-Business Advisor, vol. 17, No. 7, p. 30, Jul. 1999.
Enos. Vying to be the Top Dog. Upside vol. 12, No. 3, pp. 160-165, Mar. 2000.
eWinWin, “eCommerce Redefined : The Positive Impact of eWinWin's Demand Aggregation System on the Manufacturing Supply Chain”, Oct. 2000. Last accessed Mar. 19, 2008, 11 pages.
Gaonkar, et al. Strategic Sourcing and Collaborative Planning in Internet Enabled Supply Chain Networks Producing Multigeneration Products. IEEE Transactions on Automation Science and Engineering, vol. 2, issue 1, Jan. 2005, pp. 54-66.
Gurley. Creating a Great E-Commerce Business. Fortune, Mar. 16, 1998.
International Search Report for PCT Application No. PCT/US 07/89195, mailed May 12, 2008, 8 pages.
Jonsson, et al. Impact of Processing and Queueing Times on Order Quantities. Mater. Flow, vol. 2, No. 4, pp. 221-230, Aug. 1985. [in related U.S. Appl. No. 09/922,884 on May 7, 2004].
Kantrow, American Express Sets a Three-Tier Pricing on Optima, Dialog: File 148 #05812190 (The Gale Group), American Banker, v157, n25, p1(2), Feb. 6, 1992.
Koenig, et al. Quantitative Industrial Ecology. IEEE Transactions on Systems, Man and Cybernetics, Part C, Issue 1, Feb. 1998, pp. 16-28.
Lamparter. “Natural Selection.” American Printer, vol. 217, No. 3, pp. 54-64, Jun. 1996.
Magna Cash Cybersource Partner to Expand Online Payment Options. PR Newswire, New York, Jan. 15.
Market Engineering Research for Structural Impacts of e-Business in the European Chemicals Industry (Ch. 3), Structural Impact of e-Business on the Chemicals Industry, Frost & Sullivan, Market Research Report, Jun. 2001.
Maxwell, Pricing education in the United States of America: responding to the needs of business, The Journal of Product & Brand Management, Santa Barbara, Aug. 1998, vol. 7, Issue 4, p. 336-341.
Medrano, et al. Strategic Behaviour and Price Discovery, RAND Journal of Economics, vo1. 32, No. 2, Jun. 21, 2001. https://editorialexpress.com/cgi-bin/rje—online.cgi?action=view&year=2001&issue=sum&page=221&&tid=83197&sc=uogfbloa. Last accessed Sep. 3, 2009, 29 pages.
Meriam Webster's Collegiate Dictionary, Tenth Edition, 1997, p. 732.
Meridex Introduces Advanced Features to its B2B Network, PR Newswire, May 25, 2000. Available online: http://www.canadait.com/cfm/index.cfm?It=106&Id=3421&Se=355&Sv=Company&Lo=441. Last accessed Apr. 30, 2009, 3 pages.
Mesaros. Innovation in Difficult Times : How US Manufacturers are Using Demand Aggregation to Increase Sales and Lower Costs. Jul. 26, 2001. Last accessed Mar. 19, 2008, 4 pages.
MobShop Launches New Rev of Selling App, Online Reporter, May 28, 2001. http://findarticles.com/p/articles/mi—hb5932/is—200105/ai—n23884526/. Last accessed Apr. 30, 2009, 2 pages.
MobShop Selected by WHN(TM) (WhatsHotNow.com (R), Inc.) to Power Demand Aggregation Within Its Licensed Merchandise Marketplace; Demand Aggregation Technology Enables Marketplaces to Improve Liquidity by Generating Volume Transactions, PR Newswire, San Francisco, Jan. 16, 2001. Alternative—http://www.allbusiness.com/retail-trade/4291613-1.html.
Moody. From E-Commerce to We-Commerce. Computer Weekly, 42, Jun. 3, 1999. Last accessed Apr. 9, 2009, 2 pages.
Mullich. Altrade Serves as a Natural Resource—A Head Start and Big Trading Volume Give the Natural Gas Marketplace a Competitive Edge. Can it Last? Information Week, 152, Jun. 12, 2000, 3 pages.
Myers. “E-Solutions for Surplus Inventory,” Dsn Retailing Today, vol. 39, No. 21, p. 13, Nov. 6, 2000.
Nellore, et al. Factors Influencing Success in Integrated Product Development (IPD) Projects. IEEE Transactions on Engineering Management, vol. 48, issue 2, May 2001, pp. 164-174.
OA dated Feb. 23, 2010 for U.S. Appl. No. 09/426,063, 11 pages.
OA dated Mar. 19, 2008 for U.S. Appl. No. 11/152,462, 26 pages.
OA dated Apr. 29, 2009 for U.S. Appl. No. 10/464,585, 19 pages.
OA dated Jul. 2, 2009 for U.S. Appl. No. 09/426,063, 24 pages.
OA dated Sep. 9, 2009 for U.S. Appl. No. 11/556,604, 60 pages.
OA dated Oct. 6, 2009 for U.S. Appl. No. 12/042,051, 53 pages.
OA dated Oct. 28, 2009 for U.S. Appl. No. 10/464,585, 37 pages.
OA dated Nov. 27, 2009 for U.S. Appl. No. 11/680,431, 43 pages.
OA dated Apr. 16, 2010 for U.S. Appl. No. 12/042,051, 32 pages.
OA dated Apr. 29, 2010 for U.S. Appl. No. 10/464,585, 16 pages.
OA Dated Apr. 10, 2009 for U.S. Appl. No. 10/351,069, 27 pages.
OA Dated Apr. 6, 2009 for U.S. Appl. No. 11/680,431, 33 pages.
OA Dated Feb. 6, 2009 for U.S. Appl. No. 09/626,296, 11 pages.
OA Dated Mar. 25, 2009 for U.S. Appl. No. 11/556,604, 59 pages.
OA Dated Nov. 3, 2008 for U.S. Appl. No. 11/150,920, 161 pages.
OA Dated Oct. 20, 2008 for U.S. Appl. No. 10/464,585, 11 pages.
OA Dated Oct. 27, 2008 for U.S. Appl. No. 11/464,376, 13 pages.
OA Dated Oct. 29, 2008 for U.S. Appl. No. 11/152,462, 27 pages.
O'Gorman, et al. Considerations for Connecting Renewable Generation into Bulk Supply Networks. Sixth International Conference on Advances in Power System Control, Operation and Management, ASDCOM 2003, vol. 2, Nov. 11-14, pp. 674-680. Last accessed Sep. 10, 2009, 7 pages.
Rahim, et al. Optimal Decision Rules for Determining the Length of Production Run, (Abstract Only), Computers and Industrial Engineering, vol. 9, No. 2, pp. 195-202, 1985.
Rahim, et al. “Optimal Production Run for a Process with Random Linear Drift,” (Abstract only), Omega, vol. 16, No. 4, pp. 347-351, 1988.
Scott. Chains of Trust, Supply Chain Management, Manufacturing Engineer, vol. 75, issue 4, Aug. 1996, pp. 172-174.
Scott. Supply Partnerships in the Aerospace Industry. Transforming Your Material Flow: A Practical Insight Into World Class Logistics and Supply Chain Management IEE Colloquium on, Oct. 24, 1996, pp. 3/1-3/3.
Scott. Supply Partnerships and the Effective Management of Low Cost Components. Transforming Your Material Flow: A Practical Insight Into World Class Logistics and Supply Chain Management IEE Colloquium on, Mar. 19, 1996, pp. 2/1-2/4.
Sivakumar, et al. Price Match Guarantees: Rationale, Implementation, and Consumer Response. Pricing Strategy and Practice, Bradford, 1996, vol. 4, issue 4, 11 pgs. Recovered from ProQuest Database Aug. 25, 2006.
Sjostrom. Price Discrimination by Shipping Conferences. Logistics and Transportation Review, Jun. 1992, [from Dialog® File 15, acc. No. 00727777 93-76998].
Stacklin. “Bridgestone Printing Unit Teams with ewinwin”, Mar. 25, 2002, Crain's Cleveland Business, vol. 23, issue 12, 3 pages.
Tanaka. “As Other Companies Crumble, Ecount Carves Out Niche in Online-Payment Services.” Knight Rider Tribune News Service, Washington, Feb. 27, 2002. (Recovered from ProQuest Database Dec. 4, 2006.).
Thomas, et al. JIT: Strategies for Distant Suppliers (Abstract). Business, vol. 40, No. 4, pp. 36-39, Dec. 1990.
Watson. The Effects of Demand Forecast Fluctuations on Customer Service and Inventory Cost When Demand is Lumpy. Journal of the Operational Research Society, vol. 38, No. 1, pp. 75-82, Jan. 1987. http://www.palgrave-journals.com/jors/journal/v38/n1/abs/jors19879a.html. Last accessed Sep. 10, 2009, 8 pages.
Wayback Machine. “Searched for http://www.ewinwin.com/corp/ewinwinwhitepaper.pdf”, Oct. 2, 2008, Archive.org.
Yeh, et al. “Optimal Production Run Length for Products Sold with Warranty,” (Abstract only), European Journal of Operational Research, vol. 120, No. 3, pp. 575-582, Feb. 1, 2000.
“Supplier pricing and lot sizing when demand is price sensitive”. Abad, P.L. Fac. of Bus., McMaster Univ., Hamilton, Ont., Canada. European Journal of Operational Research , vol. 78, No. 3, p. 334-54. Date: Nov. 10, 1994 [recovered from Dialog on Oct. 20, 2009]. 1 page.
Efficient bid pricing based on costing methods for Internet bid systems Sung Eun Park; Yong Kyu Lee. Dept. of Comput. Eng., Dongguk Univ., South Korea. Book Title: Web Information Systems-WISE 2006. 7th International Conference on Web Information Systems Engineering. Proceedings (Lecture Notes in Computer Science vol. 42) [recovered from Dialog on ]. 1 page.
Advisory Action Dated Apr. 29, 2010 for U.S. Appl. No. 11/680,431.
OA dated Sep. 17, 2010 for U.S. Appl. No. 11/618,412, 97 pages.
Mack, Going Local. © 2006 ProQuest Info&Learning. Last accessed Sep. 17, 2010, 2 pages.
De Gheest, Computer Implemented Electronic Bidding for Electronic Sales Application. Derwent Acc No. 2001-006585, © 2010 Derwent Information Ltd. Last accessed Sep. 17, 2010, 2 pages.
Swartz, Wireless Ads: Loved/Loathed. Wireless Review. © 2006 The Gale Group. Last accessed Sep. 17, 2010, 3 pages.
OA dated Sep. 30, 2010 for U.S. Appl. No. 11/618,418, 125 pages.
OA dated Aug. 4, 2010 for U.S. Appl. No. 11/680,415, 65 pages.
OA dated Oct. 21, 2010 for U.S. Appl. No. 12/788,513, 62 pages.
OA mailed Mar. 21, 2011 for U.S. Appl. No. 12/887,778, 38 pages.
OA mailed Feb. 18, 2011 for U.S. Appl. No. 11/680,431, 33 pages.
OA mailed Jan. 24, 2011 for U.S. Appl. No. 11/680,415, 24 pages.
OA mailed Feb. 23, 2011 for U.S. Appl. No. 11/618,412, 27 pages.
OA mailed Mar. 28, 2011 for U.S. Appl. No. 11/618,418, 22 pages.
OA mailed Jan. 21, 2011 for U.S. Appl. No. 12/881,923, 48 pages.
OA dated Apr. 6, 2011 for U.S. Appl. No. 12/788,513, 38 pages.
OA dated Aug. 18, 2011 for U.S. Appl. No. 12/881,923, 32 pages.
OA dated Aug. 2, 2011 for U.S. Appl. No. 11/680,415, 27 pages.
OA dated Jul. 28, 2011 for U.S. Appl. No. 12/704,280, 55 pages.
OA dated Sep. 12, 2011 for U.S. Appl. No. 09/922,884, 31 pages.
OA dated Sep. 2, 2011 for U.S. Appl. No. 11/680,431, 24 pages.
OA dated Sep. 21, 2011 for U.S. Appl. No. 13/106,622, 52 pages.
U.S. Appl. No. 13/271,464 Office Action mailed May 10, 2012.
U.S. Appl. No. 09/922,884 Office Action mailed May 1, 2012.
U.S. Appl. No. 13/104,723 Final Office Action mailed Jun. 8, 2012.
U.S. Appl. No. 13/270,133 Final Office Action mailed Jun. 12, 2012.
U.S. Appl. No. 13/292,971 Office Action mailed Jun. 14, 2012.
U.S. Appl. No. 13/272,144 Office Action mailed May 16, 2012.
U.S. Appl. No. 11/680,415 Final Office Action mailed May 2, 2012.
Amazon.com, “Earths Biggest Selection,” Jun. 30, 2001, archived by Archive.org: http://web.archive.org/web/20010630130618/http://www.amazon.com/exec/obidos/subst/home/home.html.
Anon., “ELCOM: Virgin Trains Cuts Procurement Costs with elcom.com; New Electronic Ordering System Offers Personalised Pricing,” M2 Presswire, Jul. 18, 2000.
Anon., “Open Market Introduces New Software for Dynamic Web-Based Commerce” PR Newswire, Oct. 1, 1996.
Boroshok, Jon, “Wireless, Location-Based, Shopping Portal being Tested in New York City and San Francisco by GeePS.com, Inc.,” published Apr. 3, 2000, New York, NY and San Francisco, CA; as downloaded from http://www.techmarcom.com/geeps.html on Jan. 6, 2012.
Business/High Tech Editors “Mercata Launches Compelling Alternative to Online Auctions,” Business Wire, Nov. 15, 2000.
ebay.com “eBay Services: The Feedback Forum,” Aug. 1, 2001, archived by archive.org: “http://web.archive.org/web/20010801145144/http://pages.ebay.com/services/forum/feedback.html”.
Ha, Sung Ho et al., “Matching Buyers and Suppliers: An Intelligent Dynamic-Exchange Model,” IEEE Intelligent Systems, 2001.
Hinze, Annika et al., “Location- and Time-Based Information Delivery in Tourism,” as downloaded Apr. 20, 2012 from http://page.mi.fu-berlin.de/voisard/Papers/sstd03.pdf.
IEEE Xplore Search Results, Aug. 12, 2007.
Kauffman et al., “Bid Together Buy Together, On the Efficacy of Group-Buying Business models in Internet-based Selling,” May 16, 2001.
Mercata.com “How to Ship an Order” Oct. 22, 2000, archived by archive.org: http://web.archive.org/web/20001022035135/http://www.mercata.com/cgi-bin/mercata/mercata/v1/pages/editorial.jsp?name=Ship+an+Order.
Mercata.com, archived by archive.org on or before Jun. 19, 2000.
Millman, H., “Legacy Data Links Shrinks Costs,” InfoWorld, vol. 20, No. 1, pp. 51, 56, Jan. 5, 1998.
Rajaraman, Rajesh et al., “The Effect of Demand Elasticity on Security Prices for the Poolco and Multi-Lateral Contract Models,” IEEE Transactions on Power Systems, vol. 12, No. 3, Aug. 1997.
Rozic, Jeff “Who's Watching While You Surf?” Inside Business 3, 5, 64, May 2001.
Tippr http://www.tipper.com/ Internet Archive (Feb. 29, 2008)—http://web.archive.org/web/20080229121727/http://tippr.com/.
WHN Selects MobShop to Power Aggregated Buying for WHN Exchange. Jan. 23, 2001. http://www.allbusiness.com/retail-trade/4291613-1.html. Last accessed Sep. 11, 2009, 2 pages.
U.S. Appl. No. 09/922,884 Final Office Action mailed Jan. 4, 2012.
U.S. Appl. No. 13/104,723 Office Action mailed Mar. 22, 2012.
U.S. Appl. No. 13/106,622 Final Office Action mailed Jan. 3, 2012.
U.S. Appl. No. 13/270,133 Office Action mailed Jan. 3, 2012.
U.S. Appl. No. 12/710,095 Office Action mailed Apr. 6, 2012.
U.S. Appl. No. 13/161,192 Office Action mailed Apr. 5, 2012.
U.S. Appl. No. 13/251,668 Office Action mailed Feb. 9, 2012.
U.S. Appl. No. 13/251,668 Final Office Action mailed Apr. 17, 2012.
U.S. Appl. No. 13/160,128 Final Office Action mailed Feb. 22, 2012.
U.S. Appl. No. 13/272,147 Office Action mailed Jan. 10, 2012.
Adam et al. “Strategic Directions in Electronic Commerce and Digital Libraries: Towards a Digital Agora”. ACM Computing Surveys [Online] 1996, vol. 28, Issue 4, pp. 818-835.
U.S. Appl. No. 13/269,360 Final Office Action mailed Jul. 6, 2012.
U.S. Appl. No. 12/710,095 Final Office Action mailed Jun. 28, 2012.
U.S. Appl. No. 12/881,923 Office Action mailed Jun. 29, 2012.
U.S. Appl. No. 13/345,681 Office Action mailed Jun. 20, 2012.
U.S. Appl. No. 11/618,412 Final Office Action mailed May 1, 2012.
eWinWin, Inc. v. Groupon, Inc. Appeal Per Curiam Decision dated Oct. 9, 2012.
eWinWin, Inc. v. Groupon, Inc. Reply Brief of Appellant dated Jun. 4, 2012.
eWinWin, Inc. v. Groupon, Inc. Brief of Appellee dated May 17, 2012.
eWinWin, Inc. v. Groupon, Inc. Brief of Appellant dated Apr. 2, 2012.
Order re Motion for Summary Judgment dated Nov. 23, 2011.
eWinWin, Inc.'s Opposition to Groupon, Inc.'s Motion for Summary Judgment of Non-Infringement dated Nov. 8, 2011.
Order re eWinWin, Inc. Motion for Reconsideration dated Oct. 3, 2011.
Order re Claim Construction dated Sep. 5, 2011.
eWinWin, Inc. Supplemental Brief in Support of Claim Construction dated Aug. 24, 2011.
Groupon, Inc.'s Supplemental Claim Construction Brief dated Aug. 24, 2011.
eWinWin, Inc.'s Reply Brief in Support of Claim Construction dated Aug. 5, 2011.
Groupon, Inc.'s Responsive Claim Construction Brief dated Aug. 5, 2011.
Opening Claim Construction Brief of eWinWin, Inc.dated Jul. 5, 2011.
U.S. Appl. No. 13/275,054 Final Office Action mailed Nov. 5, 2012.
U.S. Appl. No. 13/292,971 Office Action mailed Dec. 4, 2012.
U.S. Appl. No. 13/292,971 Office Action mailed Sep. 14, 2012.
U.S. Appl. No. 13/449,275 Office Action mailed Oct. 4, 2012.
U.S. Appl. No. 13/449,276 Office Action mailed Sep. 26, 2012.
U.S. Appl. No. 13/449,658 Office Action mailed Oct. 30, 2012.
U.S. Appl. No. 13/452,647 Office Action mailed Dec. 7, 2012.
U.S. Appl. No. 13/460,512 Office Action mailed Dec. 10, 2012.
U.S. Appl. No. 13/523,820 Office Action mailed Nov. 8, 2012.
U.S. Appl. No. 13/525,040 Office Action mailed Nov. 23, 2012.
U.S. Appl. No. 13/407,622 Office Action mailed Dec. 3, 2012.
U.S. Appl. No. 13/407,622 Office Action mailed Sep. 12, 2012.
U.S. Appl. No. 12/881,923 Final Office Action mailed Oct. 5, 2012.
U.S. Appl. No. 13/251,668 Office Action mailed Sep. 14, 2012.
U.S. Appl. No. 13/345,681 Final Office Action mailed Sep. 20, 2012.
U.S. Appl. No. 13/621,158 Office Action mailed Dec. 5, 2012.
U.S. Appl. No. 13/274,213 Final Office Action mailed Aug. 1, 2012.
U.S. Appl. No. 13/538,302 Office Action mailed Oct. 25, 2012.
U.S. Appl. No. 11/618,418 Final Office Action mailed Jul. 26, 2012.
U.S. Appl. No. 11/680,415 Office Action mailed Aug. 31, 2012.
Mercata.com, “Our Privacy Policy”, Archived by Archive.org on or before May 26, 2000.
Mercata.com, “Special Offers”, Archived by Archive.org on or before Jun. 19, 2000.
Mercata.com, “Terms of Use”, Published by Mercata.com, Nov. 6, 2000.
We-Commerce.com, “The We-Commerce™ Network Mission”, Archived by Archive.org on or before Oct. 23, 2000.
U.S. Appl. No. 13/104,723 Office Action mailed Feb. 22, 2013.
U.S. Appl. No. 13/269,360 Final Office Action mailed Apr. 17, 2013.
U.S. Appl. No. 13/270,133 Final Office Action mailed Feb. 1, 2013.
U.S. Appl. No. 13/275,054 Final Office Action mailed Feb. 21, 2013.
U.S. Appl. No. 13/292,971 Final Office Action mailed Apr. 18, 2003.
U.S. Appl. No. 13/449,275 Final Office Action mailed Feb. 22, 2013.
U.S. Appl. No. 13/449,276 Final Office Action mailed Feb. 25, 2013.
U.S. Appl. No. 13/452,647 Final Office Action mailed May 2, 2013.
U.S. Appl. No. 13/460,478 Final Office Action mailed Apr. 29, 2013.
U.S. Appl. No. 13/460,478 Office Action mailed Dec. 20, 2012.
U.S. Appl. No. 13/460,512 Final Office Action mailed May 2, 2013.
U.S. Appl. No. 13/523,820 Office Action mailed Feb. 26, 2013.
U.S. Appl. No. 13/491,449 Final Office Action mailed May 2, 2013.
U.S. Appl. No. 13/491,449 Office Action mailed Dec. 19, 2012.
U.S. Appl. No. 13/525,040 Final Office Action mailed Apr. 18, 2013.
U.S. Appl. No. 13/407,622 Final Office Action mailed Apr. 17, 2013.
U.S. Appl. No. 13/251,668 Office Action mailed May 10, 2013.
U.S. Appl. No. 13/251,668 Final Office Action mailed Dec. 24, 2012.
U.S. Appl. No. 13/609,250 Office Action mailed Jan. 3, 2013.
U.S. Appl. No. 13/621,158 Final Office Action mailed Mar. 27, 2013.
U.S. Appl. No. 13/274,213 Office Action mailed Apr. 23, 2013.
U.S. Appl. No. 13/274,213 Final Office Action mailed Jan. 9, 2013.
U.S. Appl. No. 11/152,462 Office Action mailed Feb. 6, 2013.
U.S. Appl. No. 13/160,128 Office Action mailed May 23, 2013.
U.S. Appl. No. 13/538,302 Final Office Action mailed Mar. 26, 2013.
U.S. Appl. No. 11/680,431 Office Action mailed Mar. 11, 2013.
U.S. Appl. No. 13/517/528 Office Action mailed May 8, 2013.
U.S. Appl. No. 13/584,809 Office Action mailed Feb. 14, 2013.
U.S. Appl. No. 13/681,403 Office Action mailed Aug. 21, 2013.
U.S. Appl. No. 13/270,133 Office Action mailed Jun. 21, 2013.
U.S. Appl. No. 13/523,820 Final Office Action mailed Jun. 28, 2013.
U.S. Appl. No. 13/891,154 Office Action mailed Aug. 28, 2013.
U.S. Appl. No. 12/881,923 Office Action mailed Sep. 20, 2013.
U.S. Appl. No. 13/621,158 Office Action mailed Oct. 11, 2013.
U.S. Appl. No. 13/105,441 Office Action mailed May 31, 2013.
U.S. Appl. No. 11/152,462 Final Office Action mailed Aug. 22, 2013.
U.S. Appl. No. 12/704,151 Office Action mailed Jul. 30, 2013.
U.S. Appl. No. 11/680,415 Office Action mailed Sep. 16, 2013.
U.S. Appl. No. 11/680,431 Final Office Action mailed Jun. 27, 2013.
U.S. Appl. No. 13/584,809 Office Action mailed Jul. 24, 2013.
U.S. Appl. No. 12/710,095,Gregory J. Mesaros, Multiple Criteria Buying and Selling Model, filed Feb. 22, 2010.
U.S. Appl. No. 14/077,969, Gregory J. Mesaros, Presenting Offers to Users of Wireless Devices, filed Nov. 12, 2013.
U.S. Appl. No. 14/154,632, Gregory J. Mesaros, Presenting Offers to Users of Mobile Devices, filed Jan. 14, 2014.
U.S. Appl. No. 11/152,462, Gregory J. Mesaros, Flexible Ship Schedules and Dynamic Discounts, filed Jun. 14, 2005.
U.S. Appl. No. 11/618,412, Gregory J. Mesaros, Hosted Demand Aggregation, filed Dec. 29, 2006.
U.S. Appl. No. 13/198,964, Gregory J. Mesaros, Volume Pricing Search, filed Aug. 5, 2011.
U.S. Appl. No. 14/065,037, Gregory J. Mesaros, Discounts in a Mobile Device, filed Oct. 28, 2013.
U.S. Appl. No. 14/075,316, Gregory J. Mesaros, Promoting Offers Through Social Network Influencers, filed Nov. 8, 2013.
U.S. Appl. No. 13/104,723 Office Action mailed Nov. 25, 2013.
U.S. Appl. No. 13/269,360 Final Office Action mailed Dec. 6, 2013.
U.S. Appl. No. 14/077,969 Office Action mailed Jan. 3, 2014.
Related Publications (1)
Number Date Country
20110213653 A1 Sep 2011 US
Provisional Applications (12)
Number Date Country
60133769 May 1999 US
60318789 Sep 2001 US
60137583 Jun 1999 US
60138209 Jun 1999 US
60139338 Jun 1999 US
60139518 Jun 1999 US
60139519 Jun 1999 US
60142371 Jul 1999 US
60160510 Oct 1999 US
60162182 Oct 1999 US
60173409 Dec 1999 US
60237474 Oct 2000 US
Continuations (4)
Number Date Country
Parent 11618412 Dec 2006 US
Child 13105387 US
Parent 10370237 Feb 2003 US
Child 11464376 US
Parent 09324391 Jun 1999 US
Child 10370237 US
Parent 10243456 Sep 2002 US
Child 11556604 US
Continuation in Parts (6)
Number Date Country
Parent 11464376 Aug 2006 US
Child 11618412 US
Parent 11556604 Nov 2006 US
Child 11618412 US
Parent 09922884 Aug 2001 US
Child 11618412 US
Parent 09324391 Jun 1999 US
Child 09922884 US
Parent 09426063 Oct 1999 US
Child 09324391 US
Parent PCT/US00/11989 May 2000 US
Child 09426063 US