Today, Amazon Ads announced that Amazon DSP is now using new, more advanced machine learning models and optimized campaign control systems to enhance bidding and pacing decisions and help advertisers reach previously unaddressable audiences. With the advertising industry moving away from third-party cookies, modeling available signals to reach desired audiences is critical. The new machine learning models analyze a range of signals to help advertisers predict and reach highly relevant audience segments with optimal cost-efficiency.
With these enhancements, advertisers have experienced1:
12.6% increase in click-through rate
34.1% increase in return on ad spend
24.7% decrease in cost per click
20%-30% incremental addressability on inventory that was previously unaddressable
“Advanced science and technology are at the heart of Amazon DSP. We continually explore ways to boost performance and increase cost-efficiency for advertisers,” said Neal Richter, director of Amazon DSP Technology. “We know that every percentage point of improvement counts to advertisers, and these new upgrades have helped increase engagement and return on ad spend. We’re excited to introduce these enhancements at a time when brands are especially focused on improving cost-efficiency and delivering results.”
Boost campaign performance and deliver ads more cost-efficiently
The new budget distribution machine learning models help ensure brands reach their desired audiences at the optimal price for every ad placed throughout a campaign’s duration. These models better predict the likelihood of a bid request converting, enabling algorithmic changes that improve pacing-to-goal while optimizing for performance. Performance improvements include a 12.6% increase in click-through rate, a 34.1% increase in return on ad spend, and a 24.7% decrease in cost per impression.
Reach previously unaddressable audiences
Announced at Amazon Ads unBoxed 2022, Amazon DSP expanded Amazon audiences and contextual targeting to help reduce reliance on traditional ad identifiers. Amazon’s model-based audience inference methodology matches the right message to the appropriate audience by leveraging available event and contextual signals. Advertisers using expanded Amazon audiences and contextual targeting saw 20%-30% incremental addressability on inventory that was previously unaddressable.
These behind-the-scenes algorithmic improvements deliver more cost-efficient ad placements with no need for advertisers to adjust their existing campaigns.
Amazon Ads will continue to invent for customers and develop new ways for brands to solve marketing challenges. Amazon’s advertising technology helps brands uncover new insights, maximize marketing performance, lower costs, and discover the impact of cross-media investments wherever they spend time.