Ai in Programmatic Advertising Fraud Detection to Deliver Performance and Sustainability
The rise of programmatic advertising has shifted the focus towards accuracy and automation. It surged from $9.75 billion in 2023 to $12.46 billion in 2024, an annual growth rate of 27.8% and is expected to continue expanding, reaching $28.12 billion by 2028 at a compound annual growth rate (CAGR) of 22.6%. However, with AI coming into the picture, performance programmatic platforms are prone to ad fraud even more. The need for optimization of programmatic media buying with comprehensive ad fraud solution across the advertising funnel is the necessity to yield results.
Why Programmatic Ad fraud prevention?
Protect your brand with programmatic ad fraud prevention. Ensuring the invalid traffic is blocked from malicious sources not only safeguards advertising budget but also protect brand reputation.
Here’s how mFilterIt guides with trust and transparency in programmatic advertising:
Impression fraud
Impression Fraud analysis is better at the post-bid stage than pre-bid, measuring performance beyond viewability metrics. In pre-bid analysis, i.e. before the ad is served, fraud can be identified based on only two parameters, IP and User Agents. Also, the time for analysis is limited to 10 milliseconds. This results in a meager 2% fraud identification.
This is where a post-bid analysis trumps a pre-bid impression validation. Now that we have several more parameters fraud detection is done on deterministic and heuristic measures as well. This results in the detection of higher invalid impressions of 15–20%. This results in improved ROI on Ad spending. Post-bid impression analysis is a more beneficial method for detecting ad fraud.
Programmatic Advertising Fraud in USA, UAE, India, Saudi Arabia.
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