Data distribution method and system

• US 7,966,210 B2
• Filed: 10/02/2008
• Issued: 06/21/2011
• Est. Priority Date: 05/31/2001
• Status: Expired due to Term

• Current Assignee: Landmark NV-S Ventures Group Incorporated
• Original Assignee: Landmark NV-S Ventures Group Incorporated
• Inventors: Hall, Stephen A., Moore, Robert B., Javdan, David G.
• Primary Examiner(s): Choi; Peter
• Application Number:
  US12/244,522
• Publication Number:
  US 20090083130A1
• Time in Patent Office: 992 Days
• Field of Search: 705/10
• US Class Current: 705/7.29
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/06375 Prediction of business process outcome or impact based on a proposed change
• CPC Class Codes: G06Q 10/0875 Itemisation or classification of parts, supplies or services, e.g. bill of materials
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/0204 Market segmentation
• CPC Class Codes: G06Q 30/0275 Auctions
• CPC Class Codes: G06Q 30/0611 Request for offers or quotes
• CPC Class Codes: G06Q 30/08 Auctions
• CPC Class Codes: G06Q 40/03 Credit; Loans; Processing thereof
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
• CPC Class Codes: G06Q 50/16 Real estate

Abstract

A method for distributing data among automotive dealers, including selecting the data from the dealers, processing the data, and providing the processed data to the dealers while maintaining confidentiality of individual data of each dealer. The selecting of the data further includes collecting data indicating which vehicles are in demand. The data includes at least one of a number of a vehicle'"'"'s make a dealer has in stock, a vehicle identification number, a vehicle'"'"'s year, a vehicle'"'"'s make, a vehicle'"'"'s model, a vehicle'"'"'s body style, a vehicle'"'"'s exterior color, a vehicle'"'"'s interior color, a vehicle'"'"'s mileage, a vehicle'"'"'s retail asking price, a vehicle'"'"'s transactions cost, a vehicle'"'"'s reconditioning cost, a vehicle'"'"'s age, a vehicle'"'"'s selling price, a vehicle'"'"'s gross profit, an acquisition need of a vehicle, a selling need of a vehicle, a vehicle'"'"'s image, a vehicle'"'"'s turnover rate, or an aggregate of any of the above-listed data. The distributed data may provide optimization on return on investments to the dealers.

Claims

1. A method of scoring potential purchasing dealers within a network of competitive dealers, the method comprising:

(a) obtaining, by a computer, sales history data for each of the purchasing dealers in the network, the sales history data corresponding to vehicles comparable to a vehicle for sale and including a plurality of sales indicators corresponding to prior sales made by the respective purchasing dealers, the plurality of sales indicators including at least two of i) number of bids made, ii) quantity of vehicles sold, iii) quantity of vehicles purchased, iv) frequency of bidding by the potential purchasing dealer, and v) return on investment for the vehicles comparable to the vehicle for sale;

(b) assigning, by the computer, a score and a weight to each of the sales indicators for each of the potential purchasing dealers based on the sales history data, wherein the weight assigned to each of the sales indicators is based at least in part on the combination of sales indicators in the sales history data;

(c) generating prior to receiving bids for the vehicle for sale, by the computer, a smart score for each potential purchasing dealer by aggregating the weighted assigned scores for the sales indicators, wherein the smart score indicates the likelihood that each purchasing dealer will bid on the vehicle for sale; and

(d) ranking the potential purchasing dealers in the network based at least in part on the generated smart scores.

2. The method of claim 1, wherein the scores assigned to the sales indicators are assigned according to a normalized scale.

3. The method of claim, 1 wherein the scores assigned to the sales indicators for one of the potential purchasing dealers are relative to the sales history of the other purchasing dealers in the network.

4. The method of claim 1, wherein the sales history data of each individual purchasing dealer is confidential to the other purchasing dealers.

5. The method of claim 1, wherein the identity of each potential purchasing dealer is confidential to the other purchasing dealers.

6. The method of claim 1, wherein the scores assigned to the sales indicators for each potential purchasing dealer are confidential to the other purchasing dealers.

7. The method of claim 1, wherein the smart score for each potential purchasing dealer is confidential to the other purchasing dealers.

8. The method of claim 1, wherein the number of bids made is based on the number of bids a potential purchasing dealer made in the last predetermined number of days.

9. The method of claim 1, wherein the quantity of vehicles sold is based on the number of the same make and model the potential purchasing dealer sold over a predetermined number of days.

10. The method of claim 1, wherein the return on investment is based on the potential purchasing dealer'"'"'s return on investment for the make and model vehicle purchased over a predetermined number of days, for the vehicle for sale.

11. The method of claim 1, wherein a potential purchasing dealer with a higher smart score is recommended to a selling dealer over a potential purchasing dealer with a lower smart score.

12. The method of claim 1, wherein a selling dealer selects at least one of the sales indicators used to generate the smart score for a potential purchasing dealer.