Mobile Offer Chain Logic for Ad Conversion
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for presenting advertisements on mobile devices lack an effective mechanism to optimize the presentation of multiple related advertising offers, leading to suboptimal user engagement and conversion rates, as they do not adequately account for the value generated by sequential offers.
Innovation Solution
Implementing an offer chain logic that presents primary and secondary offers, where the value of sequential conversions is calculated and used to prioritize and optimize the presentation of primary offers, leveraging interactive video advertisements and surveys to drive user interactions and conversions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple related advertising offers are presented sequentially to mobile device users, then user engagement and conversion value increase, but the complexity of managing and optimizing offer presentations increases
Solution Approach 1:
The advertising system segments offers into primary offers and secondary offers that can be presented in sequence. Each offer is an independent unit that can be managed separately, yet they work together as a chain to achieve higher overall conversion rates. The primary offer initiates user interaction, and the secondary offer capitalizes on the engaged user state.
Solution Approach 2:
The system dynamically selects and sequences offers based on real-time factors such as user behavior, device state, and conversion potential. The offer chain logic adapts the presentation sequence and selection of primary and secondary offers to maximize conversion value while managing complexity through automated decision-making algorithms.
2Productivity
If offer chain logic is implemented to optimize advertisement presentation, then conversion value increases, but the computational resources and processing time required increase
Solution Approach 1:
The system performs preliminary analysis and pre-computes offer chain sequences based on historical data and user profiles before actual advertisement presentation. By pre-processing decision logic and pre-selecting potential offer chains, the system reduces real-time computational burden on mobile devices while maintaining high conversion value optimization.
3Productivity
If sequential offers are presented to maximize end-to-end conversion value, then advertiser revenue increases, but user experience complexity increases
Solution Approach 1:
The system implements offer chains with varying levels of sequencing - sometimes presenting only a primary offer, other times adding secondary offers. This partial application of sequential offering allows the system to capture high-value conversion opportunities when appropriate while avoiding unnecessary complexity in situations where a single offer suffices, thus balancing revenue maximization with user experience simplicity.
Data Source
AI summary
Mobile device advertising chains are described herein. Presenting a primary offer, comprising a first action, is caused on a mobile computing device. The first action is caused on the mobile computing device. An end of the first action is detected. Presenting a purchase offer, comprising a purchase action, is caused on the mobile computing device after the end of the first action. Data indicating that the purchase action was completed in connection with the mobile computing device based on the purchase offer is received. A sum of the value to confer in connection with the device for accepting both the primary offer and the purchase offer is determined. The sum of the values may be used in optimizing subsequent presentations of the primary offer to other mobile devices.