Case Study: How publishers can reduced fraud with Optimisation

09/12 By IAS Team

A digital publisher that serves the financial, technology, and healthcare sectors was challenged by a sudden spike in bot traffic to its website. The publisher’s advertisers immediately became concerned that a portion of its inventory consisted of fraudulent traffic. This could easily lead to a breakdown in trust between parties – during the spike, the advertisers’ expectations were not being met. Any ads served to bots had no chance to impact consumers.

In order to prevent value erosion, the publisher needed to address this challenge and provide the highest quality inventory and mitigate the resulting damage to the relationships with its advertisers. The publisher started leveraging post-delivery data, but quickly recognized that such manual optimisation was not sustainable, nor was it scalable or accurate enough. As a result, a seamless, automated solution was needed to improve media quality by filtering out fraudulent impressions.

Download the report to learn how the publisher was able to dramatically reduce fraud