Ad Management Engine Personalizing Content via User Input Options
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Solution Overview
Problem
Users experience frustration with repetitive and irrelevant advertisements on third-party websites, leading to reduced user engagement and potential sales for merchants, as conventional techniques lack effective user control over advertisement content.
Innovation Solution
An advertisement management engine that provides user input options based on user browsing and purchase history, allowing users to indicate preferences and disinterests, thereby tailoring subsequent advertisements to their interests and excluding irrelevant content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional advertisement techniques are used to maximize ad exposure, then advertisement visibility is improved, but user frustration increases and user experience deteriorates
Solution Approach 1:
The system performs preliminary actions by collecting user browsing and purchase history data before generating advertisements. This advance preparation enables the system to pre-segment users based on their demonstrated interests, ensuring that advertisements are tailored to user preferences before they are even presented, thereby reducing user frustration while maintaining exposure.
Solution Approach 2:
The system segments the user base into distinct groups based on browsing history and purchase behavior. By dividing users into segments with similar interests, the system can present targeted advertisements to each segment, maximizing relevance and reducing the harmful effect of repetitive irrelevant ads on user experience.
2Productivity
If repetitive advertisements are displayed to maximize merchant sales opportunities, then potential sales are improved, but user engagement decreases
Solution Approach 1:
The advertisement system dynamically adapts to user preferences by continuously analyzing browsing and purchase history. Rather than displaying static repetitive advertisements, the system adjusts ad content in real-time based on user behavior, maintaining sales opportunities while improving user engagement through personalized, non-repetitive advertisement delivery.
Solution Approach 2:
The system implements feedback mechanisms by monitoring user interactions with advertisements and using this information to refine future ad selections. This feedback loop ensures that advertisements align with user interests, maintaining productivity for merchants while enhancing user engagement through continuously optimized content delivery.
3Device complexity
If conventional advertisement selection is used to fill ad space, then advertisement delivery is simplified, but advertisement relevance to user interests deteriorates
Solution Approach 1:
The system performs preliminary analysis of user browsing and purchase history to extract interest information before ad selection. This advance processing of user data captures valuable interest information that would otherwise be lost, enabling relevant ad matching while keeping the delivery mechanism itself relatively simple.
Solution Approach 2:
The system introduces an intermediary layer between ad space filling and user interest matching. This intermediary component processes user history data and translates it into relevant ad selections, preserving user interest information while maintaining simplified advertisement delivery infrastructure through the use of a dedicated matching layer.
Data Source
AI summary
An advertisement request identifying a user may be received by a computing device of an electronic marketplace provider. User information for the user may be determined based on the advertising request. An advertisement featuring an item offered on an electronic marketplace may be selected. The advertisement may be provided for placement within content of a third-party network page provider. A first plurality of user input options configured to elicit a level of interest of the user with respect to the first advertisement may also be provided within the content of the third-party network page provider. User interaction information indicating the level of interest of the user with respect to the advertisement may be received. A second plurality of user input options may be determined based on the item of the advertisement and the first plurality of user input options. The second plurality of user input options may be provided to the content.