WO2001054024A1

WO2001054024A1 - Bidding process assistant

Info

Publication number: WO2001054024A1
Application number: PCT/US2001/001607
Authority: WO
Inventors: Jett Price
Original assignee: Popdynamics, Inc.
Priority date: 2000-01-18
Filing date: 2001-01-18
Publication date: 2001-07-26
Also published as: AU2001229578A1

Abstract

A bidding process (30) is described. The bidding process (30) includes a first phase (44) where a listing of values offered by a vendor (59a, 59b) or a plurality of vendors is based upon algorithms that vendor marketing initiatives. The bidding process (30) includes a second phase (100) where the listing of values can change based on process that polls the customer for additional information based algorithm (84) (fig. 5) and a third phase (120) to enable vendors to intervene to override (98) (fig. 5A) the prices that are determined by the profile based algorithms (84) and the electronic arbitration algorithm (100).

Description

BIDDING PROCESS ASSISTANT BACKGROUND This invention relates to processes to buy goods and services over a networ such as the Internet. The advent of the Internet has fostered the development of automated processes to buy and sell products and services. For example, auction processes over the Internet are known.

SUMMARY According to an aspect of the present invention, a method includes gathering information from a first customer for purchasing of good and/or service, comparing the gather information to information gathered from a second customer that seeks to purchase the goods or services and evaluating the information from the first customer and the information from the second customer to determine if it is possible to get a better offer for the second customer.

According to an additional aspect of the present invention, a method of encouraging a customer to accept a bid for services or goods from one or more vendors includes determining unknown factors of a first customer that is not in a subset of factors determined for a second customer and polling the second customer about unknown factors and, if those factors are applicable, passing that information to the vendors for bidding, wherein the factors are the second customer's interest in promotional perks.

According to an additional aspect of the present invention, a computer program product residing on a computer readable medium for negotiating a deal for a product or service between at least one customer and at least one vendor, includes instructions to cause a computer to gather information from a first customer for purchasing of good and/or service, compare the gathered information to information gathered from the at least one customer that seeks to purchase the goods or services and evaluate the information from the first customer and the information from the at least one customer to determine if it is possible to get a better offer for the second customer.

BRIEF DESCRIPTION OF THE DRAWING FIG. 1 is a block diagram of a system employing a bidding process.

FIG. 2 is a high level block diagram showing major functions of a server bidding process in the system of FIG. 1. FIG. 3 is a diagram showing major components of the bidding process. FIG. 4 is a flow chart of a client process to interface to the system of FIG 1.

FIGS. 4A-4D are exemplary web pages hosted by the server process for a client process in the bidding system.

FIG. 5 is a flow chart of the server bidding process. FIG. 5A is a web page hosted by the server process.

FIG. 6 is a diagram that depicts an aspect of the bidding process.

FIG. 7 is a flow chart that depicts an electronic arbitration process. FIG. 8 is a flow chart that depicts an intervention process.

FIGS. 9A-9B are flow charts that depict alternative cases for use of the bidding system.

DETAILED DESCRIPTION Referring to FIG. 1, clients 12a-12b are shown connected to a bidding system 16 through a first network, e.g., the Internet 14. The clients 12a-12b run browser programs and are systems that can be used by prospective purchasers of goods/services offered by vendors at vendor systems 20 through the bidding system 16. The bidding system 16 includes a server computer 17 including a web server 18. In some embodiments, the bidding system 16 also includes a switch 19 coupled to the first network to provide selective public access to an intranet of an organization. Such a switch 19 is often called an extranet switch. In other embodiments, the system 10 can use an Internet connection, a secure Internet connection or a proprietary network, e.g., LAN, a WAN, or a combination thereof.

Prospective purchasers can be identified or can use the system anonymously. That is, profile data (to be described below) can include the actual identity of the individual. Alternatively, a pseudonym can be used for identity of the profile information when sent to a vendor. The extranet switch 19, secure connection, etc. couples vendors on a plurality of vendor systems, e.g., vendor systems 20a-20c into the bidding system 16.

Web server 18 hosts web pages that are used in a bidding process 30. Part of the bidding process 30 includes executing proprietary algorithms of the vendors 19a-19c. Those algorithms can be in the server 16 or could reside on vendors systems that are accessed by the bidding process 30. The algorithms take factors about an individual, e.g., components of a customer's profile, and determine from those factors a unique price for products or services to be offered by each of the vendors through vendor systems 20a-20c. In some embodiments, the algorithms with the permission of the owner, can be modified by the server 16 such as for use in the electronic arbitrator (discussed below) .

Many companies use proprietary algorithms to price their services or products for an individual. An example is a credit card company. Arguably, credit card companies may use an individual's factors such as age, income and past credit history to price a service, e.g, a card's interest rate or other special offers or bonuses. In addition, other examples include terms of a life insurance policy, a home mortgage, long distance or cellular phone service, terms from mortgage companies and consumer loans. Each of these purveyors of services can offer specialized pricing depending on an individual's factors. The system 10 is particularly useful for vendors that offer a service priced specifically for someone with particular profile characteristics. Other examples could be a commodity where a vendor customizes the price or other terms of purchasing that- commodity based on characteristics of the purchaser.

Referring to FIG. 2, the bidding process 30 that is executed on the server 16 is shown. The bidding process 30 includes a bid process 31 that conducts bidding or negotiation between one or more customers and one or more vendors, as described below. The bid process 31 uses the information from the processes below to have vendors bid to acquire a customer or groups of customers. The bidding process 30 includes a web server process 32 that interfaces users, e.g., client systems 12 to the server 16. The bidding process 30 also includes a profile access process 34 to access a database 35 that stores profiles about customers using the client systems. Exemplary profile information includes name, age, willingness to commit to acquiring the offered service, credit rating, psychological factors, household size, household income, degree of brand loyalty, hobbies, and so forth. The bidding process 30 also includes an algorithm access process 36 that can be used to price goods/services, an offerings access process 38 to access a basket of offerings, e.g., goods and/or services offered by vendors with any special inducements, and so forth, and an vendor access process 40 to provide vendor access to the system 16. The database 35 that stores the algorithms and baskets of offerings can reside in the system 16 or can be made accessible to the system from vendor systems (not shown) . Referring to FIG. 3, the bidding process 30 includes three main functional stages that can assess or cause the bidding process 30 to access or request access to the stored algorithms and basket of goods. These main functional processes include a profile-based bidding process 44 (FIG. 5), an electronic arbitration process 100 (FIG. 7) that automatically or at the request of a customer is invoked, and a vendor intervention process 120.

An example of an offering is a credit card. The basket of goods could be the card itself, the interest rate, airline miles from a partner airline, and so forth. That is, the basket of offerings in addition to an underlying product could include a set of perks that a vendor may want to offer to produce more loyal customers.

Referring to FIG. 4, a client process 44 that is executed through a web browser or equivalent is shown. After log in and verification or authentication of credentials 44a, the customer selects 44b a service offering, e.g., long distance telephone service, credit card, etc. The customer can enter 44c its profile information relative to the selected service. The information is collected in a web page hosted by the server 18 and is sent back to the server 18. Alternatively, other sources of profile information can be accessed including existing profiles, etc. The information is parsed from the received web page and stored into the database 35 (FIG. 2) . The collection of profile information is an ongoing process. The profile information could be modified during a bidding process discussed below, and over time as a customer makes subsequent purchases. The profile information can accumulate to obtain a clearer picture of the customer. At some point, e.g., after the system has collected profile information or after the customer has selected a product or service, the customer initiates or resumes 44d a bidding process.

Referring now to FIG. 4A, an initial web page 50a that a customer would see after log on is shown. The web page 50a can include a welcome (not shown) , instructions about the system and how the bidding process works (not shown) , a listing 52 of the services offered, long distance, insurance, credit card, etc. The listing 52 can include controls or a hyperlink 52a for a user to indicate a particular product or service and a different control (not shown) to initiate the bidding process. The web page 50a can include a search engine (not shown) where the customer can type in the type of service they are looking for, a feedback/help mechanism where the customer can request an additional type of service, and so forth.

Referring now to FIG. 4B, a subsequent web page 50b that is sent to the client is shown. For example, assume that a credit card is selected. The subsequent web page 50b could include a questionnaire 55 that is used to gather profile information relative to that offering, as described above. Multiple ways of capturing the information could be used such as yes/no controls, slide bars, multiple choice controls, typed responses (not shown) and so forth. The page can include a help/feedback utility (not shown) .

Referring now to FIGS. 4C and 4D, other web pages 50c and 50d that can be sent to the client by the server after start of bidding are shown. The web page 50c dynamically shows results of bidding preferably in real time. The results of the bidding process dynamically change throughout the bidding process, as described below. The web page 50c includes a results table 57 that here shows two vendors "First USA Visa" in column 57a and "Citibank" in column 57b. In each column is displayed a current vendor offering 59a_!, 59b_: by the particular vendor. A current vendor offering can be displayed for each phase of the bidding process as shown in FIG. 4D for web page 50d. The vendor offering can be a value, as shown, e.g., an interest rate on a credit card or a per minute charge for long distance phone service or a perk, e.g., frequent flyer miles, etc. The offering can be related to particular phases 58 of the bidding process, as indicated by 58a-58c in FIG. 4D. Thus, after phase 58a (e.g., after initial submission of a request for bid by the potential customer, vendor 1 and vendor 2 can respond with values 59a_x and 59b_: respectively. The result screen can also include controls 57a to allow a purchaser to indicate acceptance of the bid from the vendors at any stage of the process.

Referring to FIG. 5, an embodiment of the bidding process 30 is shown. The bidding process 30 commences by receiving 82 a bid request from a client system. The process 80 examines the basket of offerings and executes the algorithms using the collected profile information. The system matches 84 items from the basket of offering with vendors and sends that information to the client where it is displayed in the web page 50c. The process can call 90 the electronic arbitration algorithm 100. The process can 92 also call a vendor intervention algorithm 120 to permit vendors either directly or through proxies to override values calculated in the algorithms.

The display 88 of bidding information, electronic arbitration 100, and intervention 120 can be iterative processes. At some point the bidding settles where, the consumer does not want to enter any more information about their profile; and/or the vendor is not interested in changing their bids. Thus, after some period of time elapses the customer is faced with a decision to select 93 one of the vendors (which might be a bundle of providers) 94 and the bid from the selected vendor (s) is processed.

The system 17 sends the web page 50d that displays 66 different phases of the bidding process to the client. The web page 50c is updated each time a profile characteristic is evaluated by the process 80. In essence, this may loop several times to fetch or alter different profile information depending upon the algorithms and desires of the consumer. A purchaser could also elect to change a profile characteristic and the new information could be evaluated and possibly produce different results. For example, a purchaser of a service who had committed to keep the service for six months during a profile examination could decide to commit to three months in the middle of the bidding process. The corresponding prices from each of the vendors would possibly change depending on how the algorithms considered the commitment profile in calculating a value/price for the service.

Generally in phase 1, the listing of the prices is based upon the algorithms executing elements of that person' s profile and the company's marketing initiatives. Phase 2 is based on changes in the profile resulting from an electronic algorithm discussed in detail below. Suffice to say that, the electronic arbitration algorithm polls the consumer for additional information based upon analytical algorithms in the electronic arbitration algorithm. The third phase of the bidding process can have vendors intervene to override the prices that are determined by the algorithms.

Referring now to FIG. 5A, a web page 95 that is sent to the vendors over the extranet, secure Internet, LAN or other network connection is shown. The web page 95 has one portion, e.g., on the left hand side 95a, where is listed relevant, unique profile information, e.g., age, income, and so forth, about the customer who wants the service from the vendor. The right hand side 95b of the web page 95 depicts current bids from vendors in the bidding process. The right side of the web page 95 is "transparent" meaning that any selected provider of the selected service, e.g., vendor 1 with bids 97a_!-97a₃, can see bidding (vendor names could be included) from other selected vendors, e.g., vendor 2 with bids 97b_!- 7 ₃ and use this information and the information about the client to determine whether or not to override the values determined by their proprietary algorithms. This web page 95 can depict information on a per phase basis, as shown and can enable vendor intervention and manual override, e.g., via controls 98 if a vendor decides to buy a customer in the marketplace.

Referring to FIG. 6, the process 84 that accesses the proprietary algorithms and service offerings from potential vendors is shown. The proprietary algorithms and service offerings from potential vendors are retrieved 84a, and evaluated 84b based upon the profile information that was stored about that customer. For example, a customer could have selected a credit card with a low interest rate and frequent flyer miles. The process 84 retrieves 84c vendors that offer credit cards and matches the item or items, e.g., low interest rate and frequent flyer miles from the basket of goods of the vendors to the requests of the customer. That is, the process searches for vendors offering credit cards that offer those features. The matches are displayed 84d to the customer from at least one and preferably two vendors for an initial phase of the bidding process .

Referring to FIG. 7, a customer at client system 12b enters the system 10 to purchase long distance service and enters profile information. With client 12b, the system can gather information that can help provide a better service offering to client 12a through an intervention or "electronic arbitration algorithm." The information from client 12b can be used to impact the offering given to client 12a. FIG. 7 shows an embodiment of the electronic arbitration algorithm 100. In this case it should be noted that the information from client 12b is evaluated because the electronic arbitration algorithm 100 determines that client 12b received a better bid or set of bids from selected vendors than did client 12a or because the customer at client 12a makes a request for the electronic arbitration algorithm 100 to determine if it is possible to get a better offer.

The electronic arbitration process 100 can receive profile information from the customer at client 12a. The electronic arbitration algorithm 100 examines existing profiles, e.g., the profile of the customer at client 12b to extract a plurality of common factors that exist from profiles of individuals. The customer at client 12b might have a subset, i.e., 10 of those elements, whereas the customer at client 12a has a smaller subset of the set, i.e., 8 of the 10 elements of customer 12b. The system can determine 104 that there is a high correlation between the 8 elements that the customer at client 12a possesses and the 10 elements that the customer at client 12b. With the a high correlation, the electronic arbitration process 100 can conclude that the two unknowns of client 12a may likely exist. The electronic arbitration algorithm 100 makes an assumption that the likelihood that the two factors that client 12b has and client 12a does not have are likely present, but they were never disclosed or discovered. The electronic arbitration algorithm 100 under that hypothesis polls 108 client 12a about the two unknown factors and, if those factors are applicable,

(the client can respond yes or no if they are applicable) , that information is stored in the profile for the customer and passed 110 to the vendors for proxy intervention or manual intervention. The process 30 processes the vendor intervention or result of algorithms and updates the web page 50c.

There may be another feature that the vendors have in their basket of offering that can be passed back to the customer. For example, one of the unknown elements of customer A may have been an interest in frequent flyer miles. While this interest was never revealed in client 12a' s profile, it was revealed in client 12b' s. Client 12a was queried about frequency flyer miles and responded positively. This information is handed back to the vendors through the Extranet switch connection, Internet connection, secure Internet, LAN or other network system. The electronic arbitration algorithm 100 can thus modify the vendor's basket of goods offered to the customer in order to secure the customer. That is, the vendor can offer e.g., frequent flyer miles to entice the purchaser to select. In this manner, the electronic arbitration algorithm 100 tailors a deal to the customer from the complete set of offerings that the vendor or vendors might have. This electronic arbitrator algorithm 100 ca access information about a customer and other similar customers. The electronic arbitrator algorithm 100 also has information concerning the offerings and inter-vendor relationships.

The electronic arbitration algorithm 100 functions as a real world arbitrator giving up pieces (but not all) information of each side until a negotiated settlement agreeable to both parties is reached. Vendors bid for the right to have an individual as a customer. To collect bids from vendors, customers give up some portion of their profile information. The information is kept confidential. The vendors are given access to a portion of the information but generally not all of the customer's information during the bidding process. The vendors bid on critical pieces of information they need to tailor the bid based on the desires of the customer. Also the second customer referred to above could be an actual profile that is retrieved from the database of an actual customer. Alternatively, the second customer could be a virtual customer, i.e., a customer having a composite profile of multiple existing customers in the database or a customer that has an idealized profile based on desires of vendors. Other arrangements are possible.

Referring to FIG. 8, the vendor can receive notification of a bidding process in several ways. One way is through a proxy, e.g., the algorithms bidding on behalf of the vendor. A vendor can at some stage in the bidding process determine to override its offerings by a vendor intervention process 120. An example of vendor intervention process 120 can have a telemarketing individual or some representative from the vendor observe 124 a bidding process and decide 126 to override the price that is given to the customer by their algorithm in order to price gouge, to buy that customer, or to have a loss leader. The override intervention can be sent 128 at anytime in the bidding process 30 or could be configured to become available at a specific stage of the process, e.g., after invocation of the electronic arbitrator 100. The process 30 works with various aggregations of customers and vendors. Four different cases can be considered. A first one of the cases, one-to-one, was discussed above. Other cases include many-to-one, one-to-many and many-to-many discussed below. Referring to FIG. 9A, in the many-to-one case 150, the system 10 retrieves 152 multiple profiles of customers, i.e., 1000 customers all interested in a given service, e.g., long distance service. The system bundles 154 these customers into a portfolio, that is, some of the weaker performers will be bundled with some of the stronger performers. The system calculates 156 group statistics for the portfolio e.g., average statistics. The average statistics are calculated for the customers in the portfolio, and the portfolio is revealed 158 to likely interested vendors. The process can initiate 160 a bidding process with these vendors on behalf of the customer group.

With bundling of profiles, the system provides to a vendor a group of customers, i.e., 1000, that have a certain average profile. This group should be more valuable than a group of 1,000 people picked at random because profile information of the group is known. For example, a group of 1,000 people to a credit card company is more valuable if the company knows that bundling of 1,000 creates a certain group profile rather than 1,000 people at random. Because it's more valuable, part of that value can be passed to the company operating the bidding process, or it can be passed on to consumers in the group through the company. Use of the profile gives higher value added services to the consumer, e.g., the consumer can get a lower rate than before and provides a more loyal customer and more pleasant buying process. The vendor benefits by acquiring just the right customer base and group profiles for their business goals. Additionally, the vendor benefits through lower customer acquisition costs.

Referring to FIG. 9B, another version is one-to-many, that is, one customer to many vendors. In this case, the system retrieves 172 profile information about one customer and based upon the profile bundles 174 together several different vendors to produce a unique package. That is, the system bundles a long distance service and a credit card service and offers 176 one or both of the services at a special rate, etc. in exchange for taking the other service. The system bundles 174 offerings from the baskets of goods from multiple vendors. The profile information is used to bundle services from service providers that care about a person's profile and is not necessarily concerned with the quantity of prospects.

The bidding process 30, in conjunction with profiling, allows vendors to tailor their response to a customer based upon the customer's profile. Not only can the vendors tailor an offering, the vendors can bid against one another and through the transparency of the bidding process, they can see what their competitors are bidding. It makes for a more efficient marketplace.

The bidding process 30 can collect a complete set of profile information about a customer, only a subset of which is provided to the vendors, often in exchange for the vendor giving something up. The system also has, or has access to, a complete set of information about the vendors and their basket of offerings, only a subset of which is provided to the consumer. The electronic arbitration algorithm can access information about the vendors and the clients but only divulges what is needed to suggest a better profile for the customer. The process gives customers the ability in an electronic manner to negotiate with large vendors on a one-to-one basis. While the vendor gets unique access to information that specifies what a customer really wants.

Another case is many to many where many vendors offering a package of goods/services from multiple vendors, possible with multiple sets of such vendors competing for a group of multiple customers with aggregated or average profile characteristics .

Other Embodiments It is to be understood that while the invention has been described in conjunction with the detailed description thereof, the foregoing description is intended to illustrate and not limit the scope of the invention, which is defined by the scope of the appended claims. Other aspects, advantages, and modifications are within the scope of the following claims.

Claims

What is claimed is:

1. A method comprises gathering information from a first customer for purchasing of good and/or service; comparing the gather information to information gathered from a second customer that seeks to purchase the goods or services; and evaluating the information from the first customer and the information from the second customer to determine if it is possible to get a better offer for the second customer.

2. The method of claim 1 further comprising: determining that the first client received a better bid or set of bids from selected vendors than did the second customer.

3. The method of claim 1 wherein the customer makes a request for the electronic arbitration algorithm.

4. The method of claim 1 wherein an intervention by a electronic arbitration algorithm is used to impact the offering given to second customer.

5. The method of claim 1 wherein an electronic arbitration algorithm determines that the first customer received a better bid or set of bids from selected vendors than did the second customer.

6. The method of claim 5 wherein the first customer at a client workstation makes a request for the electronic arbitratio algorithm to determine if it is possible to get a better offer.

7. The method of claim 1 wherein determining comprises: receiving profile information from the second customer; examining existing profile information of the first customer; and extracting a plurality of common factors that exist from both profiles.

8. The method of claim 1 wherein if the second customer has a subset of the factors that the first customer has, determining unknown factors of the first customer that are not in the subset of factors of the second customer; and polling the second customer about unknown factors and, if those factors are applicable, passing that information to the vendors for bidding.

9. The method of claim 1 determining features that vendors have in their basket of offering that can be passed back to the second customer.

10. The method of claim 1 wherein the profile of the first customer can be a profile of an actual individual, a composite profile of actual individuals, or a profile of an model individual.

11. A method of encouraging a customer to accept a bid for services or goods from one or more vendors comprises: determining unknown factors of a first customer that is not in a subset of factors determined for a second customer; and polling the second customer about unknown factors and, if those factors are applicable, passing that information to the vendors for bidding, wherein the factors are the second customer's interest in promotional perks.

12. The method of claim 11 further comprising: receiving profile information from the first customer and the second customer; and wherein interest in the perks was revealed in the first client's profile but not the second client's profile.

13. The method of claim 11 wherein the interest in the perks by the second customer is sent back to the vendors to modify the vendor's basket of goods offered to the customer.

14. The method of claim 11 the method tailors a deal to the customer from a complete set of offerings that the vendor or vendors might have.

15. The method of claim 11 wherein the process gives up portions of information of each side until a negotiated settlement agreeable to both parties is reached.

16. A computer program product residing on a computer readable medium for negotiating a deal for a product or service between at least one customer and at least one vendor, comprises instructions to cause a computer to: gather information from a first customer for purchasing of good and/or service; compare the gathered information to information gathered from the at least one customer that seeks to purchase the goods or services; and evaluate the information from the first customer and the information from the at least one customer to determine if it is possible to get a better offer for the second customer.

17. The computer program product of claim 16 further comprising instructions to: determine that the first client received a better bid or set of bids from selected vendors than did the at least one customer.

18. The computer program product of claim 16 wherein the at least one customer makes a request for the electronic arbitration algorithm.

19. The computer program product of claim 16 wherein an intervention by a electronic arbitration algorithm is used to impact the offering given to the at least one customer.

20. The computer program product of claim 16 wherein the electronic arbitration algorithm determines that the first client received a better bid or set of bids from selected vendors than did the at least one customer.

21. The computer program product of claim 20 wherein the at least one customer at a client workstation makes a request for the electronic arbitration algorithm to determine if it is possible to get a better offer.

22. The computer program product of claim 16 wherein determining comprises: receiving profile information from the at least one customer; examining profile information of the existing first customer; and extracting a plurality of common factors that exist from both profiles.

23. The computer program product of claim 16 wherein if the at least one customer has a subset of the factors that the first customer has, determining unknown factors of the first customer that is not in the subset of factors of the at least one customer; and polling the at least one customer about unknown factors and, if those factors are applicable, passing that information to the vendors for bidding.

24. The computer program product of claim 16 further comprising instructions to: determine features that vendors have in their basket of offering that can be passed back to the second customer.