How it works
Upon loading, Browsi analyzes and maps the page structure in real-time to detect content composition, images, text length, paragraph structure, existing ad units, monetization partners and more. Its findings, along with user metrics and behavioral data, are sent back to the engine for ad layout and viewability prediction.
2Ad placement creation
Using machine learning, the highest viewable ad layout is suggested. Viewability prediction per placement is then ready to be used.
3Connection with the publisher’s ad server
Requesting publisher demand, per viewability
Each Browsi placement sends in real-time its predicted viewability per impression. The publisher’s ad server can then pair it with the right advertiser for increased revenue and reduced ad waste.
Embedding the impressions
Browsi’s engine will embed successful impressions exclusively, leaving no blank spaces on the page.
Tracking placement viewability
Impressions (yes, all 100% of impressions) are tracked for viewability and used to fine-tune the prediction model.
4User engagement benchmarking
User behavior metrics like scroll depth and velocity, article bounce rate, time on page and more are benchmarked to guarantee user experience is not compromised.
5Ongoing page optimization
As traffic to page increases, the AI learns and improves its ad layout and viewability prediction. Publishers can also easily deploy any custom viewability campaign or ad layout strategy they need.