Cross-Publisher Ad Frequency Caps Using Causal Conversions
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional advertising frequency caps are inefficient as they are set per publisher and do not account for individual user responses, leading to wasted advertising budgets and missed opportunities to target other customers.
Innovation Solution
Implementing a campaign frequency cap based on causal conversions, which involves determining the probability of advertisement viewability and user response, identifying converting users, and adjusting the frequency cap based on probabilistic distributions of campaign conversions to optimize ad presentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If traditional per-publisher frequency caps are used, then each publisher can control ad delivery to individual users, but the same user can be targeted multiple times by different publishers leading to wasted advertising budget
Solution Approach 1:
The patent merges frequency cap control from individual publisher level to campaign level across multiple publishers. The system consolidates ad delivery data from multiple publishers and implements a unified frequency cap that tracks total impressions across all publishers for each user, preventing the same user from being over-targeted by different publishers while maintaining individual publisher autonomy.
Solution Approach 2:
The system implements feedback mechanisms where ad delivery data is collected from multiple publishers, processed to determine cumulative impression counts per user, and used to dynamically adjust frequency cap decisions. The system continuously monitors and responds to user exposure patterns across the publisher network, adjusting cap enforcement based on real-time data.
2Productivity
If traditional per-publisher frequency caps are used, then publishers have control over their own ad delivery, but advertising budget is wasted on users who have already been sufficiently targeted
Solution Approach 1:
The system collects and processes user response data from ad deliveries across multiple publishers, using this feedback to optimize frequency cap settings. By analyzing user responses (such as conversions, clicks, or engagement metrics), the system determines the optimal number of impressions needed and adjusts frequency caps accordingly, preventing waste on users who have already responded or been sufficiently exposed.
Solution Approach 2:
The frequency cap system transitions from static, predetermined limits to dynamic, adaptive caps that adjust based on user behavior and campaign performance. The system continuously learns from user responses and modifies frequency cap parameters in real-time, optimizing the balance between user exposure and campaign effectiveness rather than applying fixed rules.
3Quantity of substance
If higher frequency caps are set to reach more users, then more users can be targeted, but the same users are targeted too many times leading to diminishing returns
Solution Approach 1:
The system implements dynamic frequency caps that adapt to individual user characteristics and campaign performance. Rather than applying a uniform cap to all users, the system adjusts caps based on user response patterns, allowing higher caps for users who haven't responded and lower caps for users showing signs of saturation, thereby maximizing the number of effective impressions while minimizing waste.
Solution Approach 2:
The system applies differentiated frequency cap strategies to different user segments based on their response characteristics. Instead of a one-size-fits-all approach, the system tailors cap levels to local user conditions, providing higher exposure limits to users who need more impressions to convert and lower limits to users who respond quickly or show diminishing returns, optimizing both reach and efficiency.
Data Source
AI summary
In accordance with some embodiments of the disclosed subject matter, methods, systems, and media for setting and using an advertisement frequency cap based on causal conversions or impact of advertisements are provided.