Impression Share Metrics for Advertiser Optimization
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Solution Overview
Problem
Advertisers in online advertising networks lack insights into how often their ads are displayed, as they do not receive information on impressions lost due to budget limits or low bids, hindering their ability to optimize their advertising strategies.
Innovation Solution
A system and method to calculate and provide advertisers with impression share metrics, which include the percentage of times their ads are displayed out of total potential impressions, helping them understand budget utilization and ad ranking through detailed data analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If advertisers do not receive information on impressions lost due to budget limits or low bids, then the advertising network system remains simple, but advertisers cannot optimize their advertising strategies
Solution Approach 1:
The patent introduces an intermediary component (impression share calculation system) that mediates between the advertising network's auction/budget system and the advertisers. This intermediary calculates and provides impression share metrics, translating complex internal system operations into actionable insights for advertisers without requiring changes to the core advertising network infrastructure.
Solution Approach 2:
The patent implements a feedback mechanism where impression share data is collected from the advertising system and fed back to advertisers. This feedback loop enables advertisers to understand why their ads were not displayed (budget exhaustion, low bids) and adjust their strategies accordingly, creating a closed-loop optimization system.
2Productivity
If the advertising network tracks and provides detailed impression data to advertisers, then advertisers can optimize their strategies, but the system complexity and data processing requirements increase
Solution Approach 1:
The patent extracts only the essential impression share metrics needed for advertiser optimization from the vast amount of available advertising data. By focusing on key metrics (impressions served, impressions lost to budget, impressions lost to bids) rather than providing all raw data, the system reduces processing complexity while maintaining optimization effectiveness.
Solution Approach 2:
The patent transforms raw impression data into meaningful parameters (impression share percentages, budget utilization rates, bid competitiveness metrics) that are directly actionable for advertisers. This parameter transformation simplifies the data structure and makes it easier for both the system to process and advertisers to interpret.
Data Source
AI summary
An advertisement associated with a bid and a budget for placement of the advertisement is received, and a determination as to whether to present the advertisement is made. A number of times the advertisement is presented is calculated, and the number of times the advertisement is not presented is calculated. An impression share statistic for the advertisement is calculated based on the calculation of the number of times the advertisement is presented and the calculation of the number of times the advertisement is not presented.