Machine Learning Services for Online Ad Optimization
Improve campaign performance with machine learning in Viant’s DSP.
Boost Ad Optimization with Machine Learning
Combat fraud, increase viewability and maximize budget efficiency with built-in advanced machine learning technology in Viant’s DSP that analyzes millions of impressions and data points every second. With our machine learning-powered solutions, you can strengthen your campaign efforts and build confidence in your programmatic campaign performance.
Combat Fraud
Advertisers are losing billions of dollars of ad spend to fraudulent users and inventory. Staying ahead of scammers as they adopt increasingly sophisticated techniques is a challenge that marketers are facing every day.
Our machine learning technology helps protect our clients’ campaigns by ensuring budgets are spent on high-quality, vetted inventory. By evaluating millions of impressions every second to identify and prevent new forms of fraud, our proprietary algorithms and data analysis have helped our clients save over 10% of their marketing budgets.
Increase Viewable Inventory
Unfortunately, marketers often end up wasting spend on ads that aren’t seen. Leverage machine learning technology to ensure that doesn’t happen. Easily bid only on viewable inventory and increase your viewable inventory by as much as four times — without sacrificing scale.
Maximize Budget Efficiency
Our machine learning technology also helps marketers ensure their budgets are always maximized toward their efficiency goals. Currently, many marketers are unknowingly overspending on inventory. Bid optimization capabilities are powered by machine learning algorithms that predict the ideal bid price needed to maintain daily budgets. Our software automatically optimizes to obtain maximum value by achieving the lowest possible price while ensuring KPIs are reached.
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MACHINE LEARNING FAQ
How does machine learning improve online ad optimization for better campaign performance?
Machine learning can help improve online ad optimization by identifying patterns in campaign data and enabling more informed decisions in real time. By analyzing user behavior, creative performance, and contextual signals, machine learning algorithms can support more effective targeting and delivery strategies. While outcomes vary, advertisers often see improvements in campaign efficiency and engagement over time.
What role does machine learning play in marketing spend optimization and ROI tracking?
Machine learning plays a supporting role in optimizing marketing spend by analyzing which channels, messages, and audiences are contributing to performance. It can surface actionable insights that help marketers adjust budgets more strategically and track ROI more accurately. Although results depend on data quality and campaign structure, machine learning may lead to more efficient resource allocation.
How can machine learning in PPC fraud prevention reduce ad fraud risks in digital campaigns?
Machine learning models are frequently used to detect patterns of fraudulent activity, such as invalid clicks or suspicious traffic sources. By continuously analyzing data signals in real time, these systems can flag anomalies that may indicate fraud. While no solution is foolproof, using machine learning in PPC fraud prevention can help advertisers mitigate risk and better protect their investments.
What are the benefits of using a machine learning-powered DSP for media buying?
A DSP (demand-side platform) that leverages machine learning can help streamline and inform media buying decisions. These platforms are often designed to optimize bids, identify valuable impressions, and refine audience targeting using historical and real-time data. While performance gains are not guaranteed, many advertisers use ML-powered DSPs to enhance buying efficiency and decision-making.