EP-4740164-A1 - INTELLIGENT SYSTEMS AND METHODS FOR CLICK PRICE GENERATION

Abstract

Systems and methods for intelligent click price generation may include solving for a plurality of coefficients of a plurality of respective factors, wherein each coefficient is an exponent in an equation; determining a factor value for each factor, wherein the factor value for each factor is between 0 and 1; setting a respective factor exponent for each factor value for each factor to 0 or 1 based on a truth determination of a factor whether to include each factor; solving for a plurality of respective factor solutions based on each factor value for each factor set to a power of each respective factor exponent; determining a probability of a conversion associated with an imminent click for an individual i based on a multiplication of the plurality of respective factor solutions; and generating a click price based on at least the probability and a target acquisition cost of an entity.

Inventors

• WINN, REX

Assignees

• Allstate Insurance Company

Dates

Publication Date

20260513

Application Date

20240705

Claims (1)

1. Docket No. - ALT0309WO CLAIMS 1. A system comprising: a processor; and a memory storing computer-executable instructions that, when executed by the processor, cause the system to: solve for a plurality of coefficients of a plurality of respective factors, wherein each coefficient is an exponent in an equation; determine a factor value for each factor, wherein the factor value for each factor is between 0 and 1; set a respective factor exponent for each factor value for each factor to 0 or 1 based on a truth determination of a factor whether to include each factor, wherein the respective factor exponent set to 0 is indicative of the truth determination of the factor being false; solve for a plurality of respective factor solutions based on each factor value for each factor set to a power of each respective factor exponent; determine a probability of a conversion associated with an imminent click for an individual i based on a multiplication of the plurality of respective factor solutions; and generate a click price based on at least the probability of the conversion associated with the imminent click for the individual i and a target acquisition cost of an entity. 2. The system of claim 1, wherein the factor value ^ ^^ ^^ ^^ ^^ ^^ ^^ ^ ^ for each factor (k) is based on a following factor value equation: ್ ^^ ^^ ^^ ^^ ^^ ^^ ^ ೖ ^ ൌ ^ା^್ೖ 3. The system of claim 1, wherein the probability of the conversion associated with the imminent click for the individual i ( ^^ ^ ) based on the multiplication of the plurality of respective factor solutions is based on a following probability equation: 4. The system of claim 1, wherein the computer-executable instructions, when executed by the processor, further cause the system to: generate a loss function (ℒ ^ ) for the individual i based on the probability; and Docket No. - ALT0309WO apply a gradient descent (→ ∇ ^ ) based on a time series ( ^^ ^ ) and the loss function (ℒ ^ ) to minimize the loss function (ℒ ^ ) and optimize the probability. 5. The system of claim 4, wherein the computer-executable instructions, when executed by the processor, further cause the system to: generate the loss function (ℒ ^ ) for the individual i based on the probability and a regularization variable as a penalty bias of a coefficient for the individual i to prevent overfitting based on the coefficient for the individual i. 6. The system of claim 5, wherein the computer-executable instructions, when executed by the processor, further cause the system to train, via an artificial intelligence model, the regularization variable on one or more validation training data sets comprising data of a plurality of individuals. 7. The system of claim 4, wherein the computer-executable instructions, when executed by the processor, further cause the system to train, via an artificial intelligence model, the time series on one or more validation training data sets comprising data of a plurality of individuals, wherein the time series is based on at least a parameter of click weighting over time of the plurality of individuals. 8. The system of claim 7, wherein the time series comprises a weightage for a training click of the one or more validation training sets that diminishes with time. 9. The system of claim 5, wherein the loss function (ℒ ^ ) for the an individual i is based on a following loss equation: ℒ ^ ൌ ^^ ^ log^ ^^ ^ ^ ^ ^1 െ ^^ ^ ^ log^1 െ ^^ ^ ^ ^ ^^ ൈ | ^^ ^ െ ^^ ^^^௧ | 10. The system of claim 5, wherein the gradient descent (→ ∇ ^ ) based on a time series ( ^^ ^ ) and the loss function (ℒ ^ ) is based on a following gradient descent equation: Docket No. - ALT0309WO 11. The system of claim 1, wherein the entity is an advertiser, and the target acquisition cost is a predetermined value provided by the advertiser and is indicative of desired spend for a product associated with the click price. 12. The system of claim 11, wherein the probability of the conversion associated with the imminent click for the individual i is further based on a pre-determined publisher parameter associated with one or more types of click traffic. 13. The system of claim 1, wherein the plurality of factors includes a homeowner status, an insured status, a credit status, or any combination thereof. 14. The system of claim 1, wherein for a factor of the plurality of factors: the respective factor exponent set to 0 is indicative of the truth determination of the factor being false or unknown; and the respective factor exponent set to 1 is indicative of the truth determination of the factor being true. 15. A system comprising: a processor; and a memory storing computer-executable instructions that, when executed by the processor, cause the system to: solve for a plurality of coefficients of a plurality of respective factors, wherein each coefficient is an exponent in an equation; determine a factor value for each factor, wherein the factor value for each factor is between 0 and 1; set a respective factor exponent for each factor value for each factor to 0 or 1 based on a truth determination of a factor whether to include each factor, wherein the respective factor exponent set to 0 is indicative of the truth determination of the factor being false; solve for a plurality of respective factor solutions based on each factor value for each factor set to a power of each respective factor exponent; Docket No. - ALT0309WO determine a probability of a conversion associated with an imminent click for an individual i based on a multiplication of the plurality of respective factor solutions; and generate a click price based on at least the probability of the conversion associated with the imminent click for the individual i and a target acquisition cost of an advertiser, wherein the target acquisition cost is a predetermined value provided by the advertiser and is indicative of desired spend for a product associated with the click price, and the plurality of factors includes a homeowner status, an insured status, a credit status, or any combination thereof. 16. The system of claim 15, wherein the computer-executable instructions, when executed by the processor, further cause the system to: generate a loss function (ℒ ^ ) for the individual i based on the probability and a regularization variable as a penalty bias of a coefficient for the individual i to prevent overfitting based on the coefficient for the individual i; and apply a gradient descent (→ ∇ ) based on a time series ( ^^ ^ ) and the loss function (ℒ ^ ^ ) to minimize the loss function (ℒ ^ ) and optimize the probability. 17. The system of claim 16, wherein the computer-executable instructions, when executed by the processor, further cause the system to train, via an artificial intelligence model, the time series and the regularization variable on one or more validation training data sets comprising data of a plurality of individuals, wherein the time series is based on at least a parameter of click weighting over time of the plurality of individuals, and wherein the time series comprises a weightage for a training click of the one or more validation training sets that diminishes with time. 18. The system of claim 15, wherein the probability of the conversion associated with the imminent click for the individual i is further based on a pre-determined publisher parameter associated with one or more types of click traffic. 19. The system of claim 15, wherein for a factor of the plurality of factors: Docket No. - ALT0309WO the respective factor exponent set to 0 is indicative of the truth determination of the factor being false or unknown; and the respective factor exponent set to 1 is indicative of the truth determination of the factor being true. 20. A method comprising: solving, by a processor, for a plurality of coefficients of a plurality of respective factors, wherein each coefficient is an exponent in an equation; determining, by the processor, a factor value for each factor, wherein the factor value for each factor is between 0 and 1; setting a respective factor exponent for each factor value for each factor to 0 or 1 based on a truth determination of a factor whether to include each factor, wherein the respective factor exponent set to 0 is indicative of the truth determination of the factor being false; solving, by the processor, for a plurality of respective factor solutions based on each factor value for each factor set to a power of each respective factor exponent; determining a probability of a conversion associated with an imminent click for an individual i based on a multiplication of the plurality of respective factor solutions; and generating, by the processor, a click price based on at least the probability of the conversion associated with the imminent click for the individual i and a target acquisition cost of an entity.

Description

Docket No. - ALT0309WO INTELLIGENT SYSTEMS AND METHODS FOR CLICK PRICE GENERATION CROSS-REFERENCE TO RELATED APPLICATIONS [0001] The present application claims priority to U.S. Provisional Application No. 63/512,427, filed July 7, 2023, and entitled “AUTOMATED ADVERTISING PRICING SYSTEMS AND METHODS,” the entirety of which is incorporated herein. TECHNICAL FIELD [0002] The present disclosure relates to systems and methods for intelligent systems and methods and, in particular, artificial intelligence (AI) based systems and methods for predicting a probability of a conversion associated with an imminent click and generating a click price based at least thereon. BACKGROUND [0003] Publishers can price clicks associated with clicks on advertisements via search platforms, social platforms, or the like for an advertiser and attempt to price a click at a highest end of the advertiser’s performance constraint. However, consequences of overpricing clicks may result in the advertiser’s withdrawal due to excessing costs. Accordingly, a need exists for efficient method of accurately pricing advertisement clicks by a publisher for an advertiser. BRIEF SUMMARY [0004] According to the subject matter of the present disclosure, a system may include a processor; and a memory storing computer-executable instructions that, when executed by the processor, cause the system to: solve for a plurality of coefficients of a plurality of respective factors, wherein each coefficient is an exponent in an equation, and determine a factor value for each factor, wherein the factor value for each factor is between 0 and 1. The computer-executable instructions, when executed by the processor, may further cause the system to: set a respective factor exponent for each factor value for each factor to 0 or 1 based on a truth determination of a factor whether to include each factor, wherein the respective factor exponent set to 0 is indicative of the truth determination of the factor being false, solve for a plurality of respective factor solutions based on each factor value for each factor set to a power of each respective factor exponent, determine a probability of a conversion associated with an imminent click for an individual i based on a multiplication of the plurality of respective factor solutions, and generate Docket No. - ALT0309WO a click price based on at least the probability of the conversion associated with the imminent click for the individual i and a target acquisition cost of an entity. [0005] According to another embodiment of the present disclosure, a system may include a processor; and a memory storing computer-executable instructions that, when executed by the processor, cause the system to: solve for a plurality of coefficients of a plurality of respective factors, wherein each coefficient is an exponent in an equation, determine a factor value for each factor, wherein the factor value for each factor is between 0 and 1, and set a respective factor exponent for each factor value for each factor to 0 or 1 based on a truth determination of a factor whether to include each factor, wherein the respective factor exponent set to 0 is indicative of the truth determination of the factor being false. The computer-executable instructions, when executed by the processor, may further cause the system to: solve for a plurality of respective factor solutions based on each factor value for each factor set to a power of each respective factor exponent, determine a probability of a conversion associated with an imminent click for an individual i based on a multiplication of the plurality of respective factor solutions, and generate a click price based on at least the probability of the conversion associated with the imminent click for the individual i and a target acquisition cost of an advertiser, wherein the target acquisition cost is a predetermined value provided by the advertiser and is indicative of desired spend for a product associated with the click price. The plurality of factors may include a homeowner status, an insured status, a credit status, or any combination thereof. [0006] According to yet another embodiment of the present disclosure, a method may include solving, by a processor, for a plurality of coefficients of a plurality of respective factors, wherein each coefficient is an exponent in an equation, and determining, by the processor, a factor value for each factor, wherein the factor value for each factor is between 0 and 1. The method may further include setting a respective factor exponent for each factor value for each factor to 0 or 1 based on a truth determination of a factor whether to include each factor, wherein the respective factor exponent set to 0 is indicative of the truth determination of the factor being false, solving, by the processor, for a plurality of respective factor solutions based on each factor value for each factor set to a power of each respective factor exponent, determining a probability