# US 10,482,485 B2 · System, method and computer program for varying affiliate position displayed by intermediary > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,482,485 B2 - Document ID: US10482485B2 - Status: Granted - Kind: B2 - Application number: 14/604,014 - Filed: 2015-01-23 - Published: 2015-05-14 - Granted: 2019-11-19 - Earliest claimed: 2012-05-11 - Assignees: TrueCar, Inc. - Applicants: TrueCar, Inc. - Inventors: Michael D. Swinson; Jason McBride; Isaac Lemon Laughlin; Thomas J. Sullivan - Web page: https://patentgrep.com/patent/US10482485B2 ## CPC - G06Q 30/0206: {Price or cost determination based on market factors} - G06Q 30/0277: {Online advertisement} - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR ## Abstract Endogenous and exogenous variables associated with an item for sale by an affiliate may be displayed to a user of an affiliate decision-making tool. In response to the user selecting one of the endogenous variables, the affiliate decision-making tool may compute a number of introductions, a number of leads, and a number of sales for each of a plurality of possible values of the endogenous variable. The computation may be done utilizing a display position algorithm. A visualization of effects of setting the endogenous variable at different levels may be presented. The user may interact with the display position algorithm to vary one or more of the plurality of possible values of the endogenous variable such that the affiliate is eligible or disqualified to be displayed by an intermediary in response to a search for the item by a visitor of a network site owned and operated by the intermediary. ## Claims ### Claim 1 A method for dealer pricing, comprising: determining, by a dealer pricing system embodied on one or more server machines: a per-unit revenue realized by a dealer when an item is sold; a per-unit cost to the dealer for the item; a number of leads for the item in a geographic unit; an amount of inventory of the item the dealer is able to sell; a probability of the dealer closing a sale on the item to a customer from the geographic unit utilizing a regression model expressed relative to a set of exogenous features not controlled by the dealer and a set of endogenous features over which the dealer has control, wherein the probability of the dealer closing the sale is a function of a weighted sum of values corresponding to the set of exogenous features and the set of endogenous features; an expected number of sales as a function of the amount of inventory of the item the dealer is able to sell, times the number of leads for the item in the geographic unit and the probability of the dealer closing the sale on the item to the customer from the geographic unit; and a total amount of gross margin for the dealer as a function of the expected number of sales times the difference between the per-unit revenue realized by the dealer when the item is sold and the per-unit cost to the dealer for the item; and providing, by the dealer pricing system, a visualization function through a user interface on a client device associated with the dealer, the visualization function provided by the dealer pricing system configured for visualizing effects of a plurality of metrics, the plurality of metrics including at least two of a display rank, the number of leads for the item in the geographic unit, the expected number of sales, or the total amount of gross margin for the dealer, the visualization function providing the dealer with an ability to select any endogenous feature over which the dealer has control and determine, through the effects visualized by the visualization function in a data structure or graph on the client device associated with the dealer, how varying a value of a selected endogenous feature changes the plurality of metrics. ### Claim 2 (depends on 1) The method according to claim 1, wherein the dealer pricing system is further operable to determine an expected revenue for an intermediary based on a per-unit revenue paid by the dealer to the intermediary and the probability of the dealer closing the sale on the item to the customer from the geographic unit. ### Claim 3 (depends on 2) The method according to claim 2, wherein the dealer pricing system is further operable to determine, based at least in part on the expected revenue for the intermediary, whether the dealer is eligible for display on a website where the item is presented to visitors of the website. ### Claim 4 (depends on 2) The method according to claim 2, wherein the dealer pricing system is further operable to determine, based at least in part on the expected revenue for the intermediary, a display position of the dealer relative to other dealers affiliated with the intermediary. ### Claim 5 (depends on 1) The method according to claim 1, wherein the set of endogenous features includes a close rate for the dealer and wherein the close rate is determined by the dealer pricing system based on a number of sales by the dealer relative to a number of leads provided to the dealer by the intermediary in a preceding time period. ### Claim 6 (depends on 1) The method according to claim 1, wherein the item represents a vehicle having a specific vehicle configuration. ### Claim 7 (depends on 1) The method according to claim 1, wherein the geographic unit represents a zip code, a city, a county, a state, or any spatial entity for which an online search at a website is restricted. ### Claim 8 A computer program product comprising at least one non-transitory computer readable medium storing instructions, the instructions when translated by at least one processor causing a dealer pricing system to perform: determining: a per-unit revenue realized by a dealer when an item is sold; a per-unit cost to the dealer for the item; a number of leads for the item in a geographic unit; an amount of inventory of the item the dealer is able to sell; a probability of the dealer closing a sale on the item to a customer from the geographic unit utilizing a regression model expressed relative to a set of exogenous features not controlled by the dealer and a set of endogenous features over which the dealer has control, wherein the probability of the dealer closing the sale is a function of a weighted sum of values corresponding to the set of exogenous features and the set of endogenous features; an expected number of sales as a function of the amount of inventory of the item the dealer is able to sell, times the number of leads for the item in the geographic unit and the probability of the dealer closing the sale on the item to the customer from the geographic unit; and a total amount of gross margin for the dealer as a function of the expected number of sales times the difference between the per-unit revenue realized by the dealer when the item is sold and the per-unit cost to the dealer for the item; and providing a visualization function through a user interface on a client device associated with the dealer, the visualization function provided by the dealer pricing system configured for visualizing effects of a plurality of metrics, the plurality of metrics including at least two of a display rank, the number of leads for the item in the geographic unit, the expected number of sales, or the total amount of gross margin for the dealer, the visualization function providing the dealer with an ability to select any endogenous feature over which the dealer has control and determine, through the effects visualized by the visualization function in a data structure or graph on the client device associated with the dealer, how varying a value of a selected endogenous feature changes the plurality of metrics. ### Claim 9 (depends on 8) The computer program product of claim 8, wherein the instructions when translated by the at least one processor further cause the dealer pricing system to determine an expected revenue for an intermediary based on a per-unit revenue paid by the dealer to the intermediary and the probability of the dealer closing the sale on the item to the customer from the geographic unit. ### Claim 10 (depends on 9) The computer program product of claim 9, wherein the instructions when translated by the at least one processor further cause the dealer pricing system to determine, based at least in part on the expected revenue for the intermediary, whether the dealer is eligible for display on a website where the item is presented to visitors of the website. ### Claim 11 (depends on 9) The computer program product of claim 9, wherein the instructions when translated by the at least one processor further cause the dealer pricing system to determine, based at least in part on the expected revenue for the intermediary, a display position of the dealer relative to other dealers affiliated with the intermediary. ### Claim 12 (depends on 8) The computer program product of claim 8, wherein the set of endogenous features includes a close rate for the dealer and wherein the close rate is determined by the dealer pricing system based on a number of sales by the dealer relative to a number of leads provided to the dealer by the intermediary in a preceding time period. ### Claim 13 (depends on 8) The computer program product of claim 8, wherein the item represents a vehicle having a specific vehicle configuration. ### Claim 14 (depends on 8) The computer program product of claim 8, wherein the geographic unit represents a zip code, a city, a county, a state, or any spatial entity for which an online search at a website is restricted. ### Claim 15 A dealer pricing system, comprising: at least one processor; at least one non-transitory computer readable medium; and instructions embodied on the at least one non-transitory computer readable medium, the instructions when translated by the at least one processor causing the dealer pricing system to perform: determining: a per-unit revenue realized by a dealer when an item is sold; a per-unit cost to the dealer for the item; a number of leads for the item in a geographic unit; an amount of inventory of the item the dealer is able to sell; a probability of the dealer closing a sale on the item to a customer from the geographic unit utilizing a regression model expressed relative to a set of exogenous features not controlled by the dealer and a set of endogenous features over which the dealer has control, wherein the probability of the dealer closing the sale is a function of a weighted sum of values corresponding to the set of exogenous features and the set of endogenous features; an expected number of sales as a function of the amount of inventory of the item the dealer is able to sell, times the number of leads for the item in the geographic unit and the probability of the dealer closing the sale on the item to the customer from the geographic unit; and a total amount of gross margin for the dealer as a function of the expected number of sales times the difference between the per-unit revenue realized by the dealer when the item is sold and the per-unit cost to the dealer for the item; and providing a visualization function through a user interface on a client device associated with the dealer, the visualization function provided by the dealer pricing system configured for visualizing effects of a plurality of metrics, the plurality of metrics including at least two of a display rank, the number of leads for the item in the geographic unit, the expected number of sales, or the total amount of gross margin for the dealer, the visualization function providing the dealer with an ability to select any endogenous feature over which the dealer has control and determine, through the effects visualized by the visualization function in a data structure or graph on the client device associated with the dealer, how varying a value of a selected endogenous feature changes the plurality of metrics. ### Claim 16 (depends on 15) The dealer pricing system of claim 15, wherein the instructions when translated by the at least one processor further cause the dealer pricing system to determine an expected revenue for an intermediary based on a per-unit revenue paid by the dealer to the intermediary and the probability of the dealer closing the sale on the item to the customer from the geographic unit. ### Claim 17 (depends on 16) The dealer pricing system of claim 16, wherein the instructions when translated by the at least one processor further cause the dealer pricing system to determine, based at least in part on the expected revenue for the intermediary, whether the dealer is eligible for display on a website where the item is presented to visitors of the website. ### Claim 18 (depends on 16) The dealer pricing system of claim 16, wherein the instructions when translated by the at least one processor further cause the dealer pricing system to determine, based at least in part on the expected revenue for the intermediary, a display position of the dealer relative to other dealers affiliated with the intermediary. ### Claim 19 (depends on 15) The dealer pricing system of claim 15, wherein the set of endogenous features includes a close rate for the dealer and wherein the close rate is determined by the dealer pricing system based on a number of sales by the dealer relative to a number of leads provided to the dealer by the intermediary in a preceding time period. ### Claim 20 (depends on 15) The dealer pricing system of claim 15, wherein the item represents a vehicle having a specific vehicle configuration.