Intelligent advertisement campaign effectiveness and impact evaluation
AssigneeInternational Business Machines Corporation
InventorsJoao H BETTENCOURT-SILVIA, Stefano BRAGHIN, Michalis PACHILAKIS
Life of this patent
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Abstract
Embodiments for implementing intelligent advertisement effectiveness and impact evaluation in a computing environment by a processor. A degree of impact and a degree of distribution of one or more communication campaigns upon a targeted entity may be identified according to a user persona, one or more communication rules, security factors, or a combination thereof.
Claims20
A method, by a processor, for implementing intelligent advertisement effectiveness and impact evaluation in computing environment, comprising:
- monitoring user access patterns as a user accesses various webpages over a selected period of time, wherein the user access patterns are inclusive of advertisements accepted and rejected by the user while accessing the various webpages;
- training a machine learning component according to the user access patterns, wherein the training includes teaching the machine learning component to identify specific types of those of the advertisements accepted and rejected by the user using reinforced feedback learning;
- creating a user persona for the user based on the user access patterns, wherein the user persona includes a persona profile having characteristic and demographic information of the user;
- simulating the user persona by an automated web crawler, using the trained machine learning component, to reproduce the user access patterns of accessing the various webpages while automatically monitoring one or more communication campaigns promoted to the user persona during the accessing;
- and
- identifying a degree of impact and a degree of distribution of the one or more communication campaigns upon a targeted entity according to the user persona, one or more communication rules, security factors, or a combination thereof.
A system for implementing intelligent advertisement effectiveness and impact evaluation in a computing environment, comprising:
- one or more computers with executable instructions that when executed cause the system to:
- monitor user access patterns as a user accesses various webpages over a selected period of time, wherein the user access patterns are inclusive of advertisements accepted and rejected by the user while accessing the various webpages;
- train a machine learning component according to the user access patterns, wherein the training includes teaching the machine learning component to identify specific types of those of the advertisements accepted and rejected by the user using reinforced feedback learning;
- create a user persona for the user based on the user access patterns, wherein the user persona includes a persona profile having characteristic and demographic information of the user;
- simulate the user persona by an automated web crawler, using the trained machine learning component, to reproduce the user access patterns of accessing the various webpages while automatically monitoring one or more communication campaigns promoted to the user persona during the accessing;
- and
- identify a degree of impact and a degree of distribution of the one or more communication campaigns upon a targeted entity according to the user persona, one or more communication rules, security factors, or a combination thereof.
A computer program product for implementing intelligent advertisement effectiveness and impact evaluation in a computing environment by a processor, the computer program product comprising a non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising:
- an executable portion that monitors user access patterns as a user accesses various webpages over a selected period of time, wherein the user access patterns are inclusive of advertisements accepted and rejected by the user while accessing the various webpages;
- an executable portion that trains a machine learning component according to the user access patterns, wherein the training includes teaching the machine learning component to identify specific types of those of the advertisements accepted and rejected by the user using reinforced feedback learning;
- an executable portion that creates a user persona for the user based on the user access patterns, wherein the user persona includes a persona profile having characteristic and demographic information of the user;
- an executable portion that simulates the user persona by an automated web crawler, using the trained machine learning component, to reproduce the user access patterns of accessing the various webpages while automatically monitoring one or more communication campaigns promoted to the user persona during the accessing;
- and
- an executable portion that identifies a degree of impact and a degree of distribution of the one or more communication campaigns upon a targeted entity according to the user persona, one or more communication rules, security factors, or a combination thereof.
Dependencies are inferred from the claim text.