# US 2024/0205485 A1 · Systems and methods for addressable targeting of electronic content > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2024/0205485 A1 - Document ID: US20240205485A1 - Status: Published application - Kind: A1 - Application number: 18/590,508 - Filed: 2024-02-28 - Published: 2024-06-20 - Earliest claimed: 2014-08-04 - Assignees: ADAP.TV, Inc. - Applicants: ADAP.TV, Inc. - Inventors: Brendan KITTS; Dyng AU; Sih Huseyin ULGER - Web page: https://patentgrep.com/patent/US20240205485A1 ## CPC - H04N 21/2668: Creating a channel for a dedicated end-user group, e.g. insertion of targeted commercials based on end-user profiles {(information retrieval from the Internet by querying with filtering and personalisation G06F16/9535; arrangements for replacing or switching information during the broadcast H04H20/10; push services over packet-switching network H04L12/1859; adaptation of message content in packet-switching networks H04L51/063)} - H04N 21/252: {Processing of multiple end-users' preferences to derive collaborative data} - H04N 21/25883: {being end-user demographical data, e.g. age, family status or address (arrangements for identifying locations of users in broadcast systems H04H60/52)} - H04N 21/44224: {Monitoring of user activity on external systems, e.g. Internet browsing} - H04N 21/812: {involving advertisement data (advertising per se G06Q30/02)} - H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION ## Abstract A method of targeting of advertising content for a consumer product is disclosed. The method comprises obtaining consumer demographic data from a first server over a network, the consumer demographic data including a plurality of demographic attributes for each person among a plurality of persons; obtaining product purchaser data for a plurality of product purchasers of the consumer product from a second server over the network, each product purchaser among the plurality of product purchasers being among the plurality of persons; and enriching the purchaser data with the consumer demographic data. The method further comprises enriching viewing data with consumer demographic data; and selecting viewed media among the aggregated viewed media having the highest similarity to the product purchasers as target media for the advertising content. ## Claims ### Claim at position 1 1-20. (canceled) ### Claim 21 A computer-implemented method of targeting electronic media content using an analytics platform, the method comprising: associating, by one or more processors of the analytics platform, a rank with each unique viewer of a plurality of viewers based on a determined match score of each unique viewer of the plurality of viewers; generating, by the one or more processors, one or more packages of unique viewers according to the rank associated with each unique viewer of the plurality of viewers; selecting, by the one or more processors, a first package of unique viewers of the one or more packages of unique viewers; determining, by the one or more processors, an expected lift value of the first package of unique viewers; and transmitting, by the one or more processors and to a user interface, a graphical representation of the first package of unique viewers based on the expected lift value. ### Claim 22 (depends on 1) The computer-implemented method of claim 1, further comprising: receiving, by the one or more processors, a plurality of set top box data, the plurality of set top box data including a set of viewing behavior data of a unique user device associated with the unique viewer of the plurality of viewers; and determining, by the one or more processors, the match score based on a similarity factor between a set of product purchase data of a plurality of product purchasers and the set of viewing behavior data. ### Claim 23 (depends on 2) The computer-implemented method of claim 2, further comprising: determining, by the one or more processors, the expected lift based on a comparison of the set of product purchase data to the first package of unique viewers. ### Claim 24 (depends on 2) The computer-implemented method of claim 2, further comprising: receiving, by the one or more processors, a plurality of demographic data of the unique viewer; and determining, by the one or more processors, the match score based on a similarity factor between the set of product purchase data of the plurality of product purchasers, the set of viewing behavior data, and the plurality of demographic data of the unique viewer. ### Claim 25 (depends on 1) The computer-implemented method of claim 1, further comprising: initiating, by the one or more processors and in response to a user interaction with the user interface, an electronic transaction associated with the first package of unique viewers. ### Claim 26 (depends on 1) The computer-implemented method of claim 1, further comprising: selecting, by the one or more processors, a second package of unique viewers of the one or more packages of unique viewers; determining, by the one or more processors, a second expected lift value of the second package of unique viewers; and transmitting, by the one or more processors and to the user interface, a second graphical representation of the second package of unique viewers based on the second expected lift value. ### Claim 27 (depends on 6) The computer-implemented method of claim 6, further comprising: initiating, by the one or more processors and in response to a user interaction with the user interface, an electronic transaction associated with the second package of unique viewers. ### Claim 28 A system for targeting electronic media content using an analytics platform, the system comprising: a data storage device storing instructions for targeting the electronic media content using the analytics platform; and one or more processors configured to execute the instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: associating, by the one or more processors, a rank with each unique viewer of a plurality of viewers based on a determined match score of each unique viewer of the plurality of viewers; generating, by the one or more processors, one or more packages of unique viewers according to the rank associated with each unique viewer of the plurality of viewers; selecting, by the one or more processors, a first package of unique viewers of the one or more packages of unique viewers; determining, by the one or more processors, an expected lift value of the first package of unique viewers; and transmitting, by the one or more processors and to a user interface, a graphical representation of the first package of unique viewers based on the expected lift value. ### Claim 29 (depends on 8) The system of claim 8, the operations further comprising: receiving, by the one or more processors, a plurality of set top box data, the plurality of set top box data including a set of viewing behavior data of a unique user device associated with the unique viewer of the plurality of viewers; and determining, by the one or more processors, the match score based on a similarity factor between a set of product purchase data of a plurality of product purchasers and the set of viewing behavior data. ### Claim 30 (depends on 9) The system of claim 9, the operations further comprising: determining, by the one or more processors, the expected lift based on a comparison of the set of product purchase data to the first package of unique viewers. ### Claim 31 (depends on 9) The system of claim 9, the operations further comprising: receiving, by the one or more processors, a plurality of demographic data of the unique viewer; and determining, by the one or more processors, the match score based on a similarity factor between the set of product purchase data of the plurality of product purchasers, the set of viewing behavior data, and the plurality of demographic data of the unique viewer. ### Claim 32 (depends on 8) The system of claim 8, the operations further comprising: initiating, by the one or more processors and in response to a user interaction with the user interface, an electronic transaction associated with the first package of unique viewers. ### Claim 33 (depends on 8) The system of claim 8, the operations further comprising: selecting, by the one or more processors, a second package of unique viewers of the one or more packages of unique viewers; determining, by the one or more processors, a second expected lift value of the second package of unique viewers; and transmitting, by the one or more processors and to the user interface, a second graphical representation of the second package of unique viewers based on the second expected lift value. ### Claim 34 (depends on 13) The system of claim 13, the operations further comprising: initiating, by the one or more processors and in response to a user interaction with the user interface, an electronic transaction associated with the second package of unique viewers. ### Claim 35 A non-transitory computer readable medium for targeting electronic media content using an analytics platform, the non-transitory computer readable medium storing instructions that, when executed by one or more processors of a computing system, cause the one or more processors to perform operations comprising: associating, by the one or more processors, a rank with each unique viewer of a plurality of viewers based on a determined match score of each unique viewer of the plurality of viewers; generating, by the one or more processors, one or more packages of unique viewers according to the rank associated with each unique viewer of the plurality of viewers; selecting, by the one or more processors, a first package of unique viewers of the one or more packages of unique viewers; determining, by the one or more processors, an expected lift value of the first package of unique viewers; and transmitting, by the one or more processors and to a user interface, a graphical representation of the first package of unique viewers based on the expected lift value. ### Claim 36 (depends on 15) The non-transitory computer readable medium of claim 15, the operations further comprising: receiving, by the one or more processors, a plurality of set top box data, the plurality of set top box data including a set of viewing behavior data of a unique user device associated with the unique viewer of the plurality of viewers; and determining, by the one or more processors, the match score based on a similarity factor between a set of product purchase data of a plurality of product purchasers and the set of viewing behavior data. ### Claim 37 (depends on 16) The non-transitory computer readable medium of claim 16, the operations further comprising: determining, by the one or more processors, the expected lift based on a comparison of the set of product purchase data to the first package of unique viewers. ### Claim 38 (depends on 16) The non-transitory computer readable medium of claim 16, the operations further comprising: receiving, by the one or more processors, a plurality of demographic data of the unique viewer; and determining, by the one or more processors, the match score based on a similarity factor between the set of product purchase data of the plurality of product purchasers, the set of viewing behavior data, and the plurality of demographic data of the unique viewer. ### Claim 39 (depends on 15) The non-transitory computer readable medium of claim 15, the operations further comprising: initiating, by the one or more processors and in response to a user interaction with the user interface, an electronic transaction associated with the first package of unique viewers. ### Claim 40 (depends on 15) The non-transitory computer readable medium of claim 15, the operations further comprising: selecting, by the one or more processors, a second package of unique viewers of the one or more packages of unique viewers; determining, by the one or more processors, a second expected lift value of the second package of unique viewers; and transmitting, by the one or more processors and to the user interface, a second graphical representation of the second package of unique viewers based on the second expected lift value.