Automated Content Variation Service for Web Engagement

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Solution Overview

Problem

Existing content generation and experimentation methods for web-based content are inefficient, as they require manual intervention and lack automated processes for creating and testing variations of website elements, which hampers the ability to optimize user engagement effectively.

Innovation Solution

Implementing a content variation service that uses machine-learning techniques to automatically generate and test permutations of website elements based on user-defined and machine-defined rules, analyzing semantic markup and user feedback to optimize content configuration and user engagement.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual intervention is used for content configuration and experimentation, then content can be created and tested, but the process is inefficient and time-consuming

Engineering Contradiction:

Improvecontent creation and testing efficiencyVSAvoidtime for manual content configuration

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system enables self-service through automated content variation generation and engagement testing. The service automatically generates permutations of content elements, conducts engagement tests without manual intervention, and uses machine learning to analyze results and generate insights, eliminating the need for manual content configuration and experimentation

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

Manual mechanical processes of content configuration and testing are replaced with automated computational systems. The service uses machine learning models and automated testing frameworks to substitute human manual work in generating content variations, conducting experiments, and analyzing engagement metrics

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If automated processes are implemented for content variation and testing, then productivity increases, but system complexity increases

Engineering Contradiction:

Improvecontent experimentation throughputVSAvoidcontent variation service complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The content variation service is designed as a universal platform that handles multiple functions: generating content permutations, conducting engagement tests, analyzing results, and providing machine learning insights. This multi-functional approach consolidates what would otherwise require multiple separate systems into a single integrated service

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The service acts as an intermediary between content creators and engagement testing infrastructure. It provides a standardized interface that simplifies complex operations by handling the intricacies of variation generation, test management, and result analysis internally, exposing only essential controls to users

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS10372782B1Content generation and experimentation using engagement tests

Publication Date: 2019.08.06 AMAZON TECH INC

AI summary

In some examples, a content variation service may identify elements of content and generate variations of the elements of the content programmatically. Content may include a website and the elements of the content may include visual and structural elements that make up the website. The variations of the elements may be provided with the content to a user as part of an engagement test. The engagement test may test how the user interacts with the variations of the elements. Based on results of the engagement test, the elements of the content may be adjusted and other variations may be generated.