Pre-bid Client-side Viewability Detection for Ad Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Advertisers face challenges in determining the viewability of their web advertisements, as they may be paying for impressions that are not actually seen by users due to ad-blocking software or hidden placements, and current bid optimization methods rely on stale historical data for viewability predictions.
Innovation Solution
The use of pre-bid client-side detection to access runtime viewability data, combined with historical performance data, to determine an impression level performance value for advertising spaces, allowing for more accurate autonomous bid-decisioning and optimized viewability rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If advertisers use cost-per-impression methodology to purchase web advertisement space, then they can automatically bid on ad impressions through programmatic instantaneous auctioning, but they cannot determine whether their advertisements are actually being viewed or visible to end-users
Solution Approach 1:
The system performs pre-bid viewability detection before the actual ad impression is served. Client-side detection code is executed in advance to determine if the ad placement will be viewable, allowing advertisers to make informed bidding decisions before committing to the impression purchase.
Solution Approach 2:
A viewability detection intermediary system is introduced between the ad exchange and the advertiser's bid decisioning process. This intermediary provides real-time viewability data that bridges the gap between automated bidding and actual viewability verification, enabling informed bid adjustments.
2Extent of automation
If advertisers rely on historical performance data to optimize bid amounts based on calculated probability of viewability, then they can automate bid adjustments, but the optimization logic is limited by stale data that cannot ensure high probability of viewability at the time of impression serving
Solution Approach 1:
The system executes viewability detection code in advance of the ad impression, obtaining real-time data about the ad placement environment. This preliminary detection occurs before the bid is finalized, allowing automation to use current rather than historical data for decision-making.
Solution Approach 2:
The bid optimization system transitions from static historical data to dynamic real-time viewability data. The detection system continuously monitors current page state, ad placement position, and potential obstructions, providing live feedback that adapts to changing conditions at the moment of impression serving.
3Productivity
If advertisements are fetched and loaded on web pages, then advertisers pay for impressions, but the advertisements may be filtered by ad-blocking software, maliciously hidden within web pages, or hidden under multiple web-browser tabs
Solution Approach 1:
The system takes preliminary protective action by detecting potential viewability issues before the ad impression is purchased. Client-side code checks for ad-blockers, hidden placements, and other obstructions in advance, allowing the system to avoid bidding on impressions that would be blocked or hidden, thus preventing wasted spend.
Solution Approach 2:
Real-time viewability detection feedback is integrated into the bid decisioning process. The system continuously monitors whether ads are actually viewable and uses this feedback to adjust bidding behavior, creating a closed-loop system that learns from actual viewability outcomes and improves future bid decisions.
Data Source
AI summary
In various embodiments, methods and systems for optimizing viewability rates by utilizing pre-bid client-side detection in autonomous bid-decisioning for advertising campaigns is provided. When provided with a unitary demand-side platform and sell-side platform system, advertisers may employ aspects of the present disclosure to pose a significant advantage in optimizing viewability rates for exchange sites purchased on the open digital advertising market. An advertiser, by way of the unitary demand-side and sell-side platform, can determine that runtime pre-bid viewability data corresponding to an exchange site is available. Based on the runtime pre-bid viewability data and historical performance data corresponding to the exchange site, an optimized calculation can be made to infer a substantially high likelihood of viewability if the exchange site is ultimately purchased by the advertiser. This optimized autonomous bid-decisioning can provide a significant advantage to advertisers in meeting their advertising campaign goals.