The world of online advertising is constantly evolving, and Amazon Ads is at the forefront of this change. The company has recently announced the introduction of new machine learning models and optimized campaign control systems for its Demand Side Platform (DSP). These advancements are set to enhance bidding and pacing decisions, boost campaign performance, and help advertisers reach previously unaddressable audiences. In this article, we will dive into the details of these new models, their potential impact on the advertising industry, and how they compare to similar offerings from other tech giants.
The Need for Advanced Machine Learning Models
With the advertising industry shifting away from third-party cookies, it has become increasingly important to model available signals to reach desired audiences and drive sales. Traditional ad identifiers are becoming less reliable, making it essential for advertisers to find new ways to target and engage with their audience. Amazon Ads has identified this need and responded by developing advanced machine learning models that analyze a range of signals to help advertisers predict and reach highly relevant audience segments with optimal cost-efficiency.
A Focus on Performance and Cost-efficiency
Neal Richter, director of Amazon DSP Technology, emphasizes the importance of constant improvement in advertising performance. He believes that “every percentage point of improvement counts to advertisers,” and that the new upgrades introduced by Amazon Ads will help increase engagement and return on ad spend. The company’s focus on advanced science and technology ensures that their DSP continually explores ways to boost performance and increase cost-efficiency for advertisers.
Boosting Campaign Performance with New Budget Distribution Models
The new machine learning models introduced by Amazon Ads are designed to optimize budget distribution, ensuring that brands reach their desired audiences at the optimal price for every ad placed throughout a campaign’s duration. By better predicting the likelihood of a bid request converting, these models enable algorithmic changes that improve pacing-to-goal while optimizing for performance.
Impressive Performance Improvements
The introduction of these models has led to significant performance improvements for advertisers using Amazon DSP. Early tests have shown 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. These impressive results demonstrate the potential of these new models to revolutionize the way advertisers approach their campaigns.
Reaching Previously Unaddressable Audiences with Expanded Amazon Audiences and Contextual Targeting
Amazon Ads has also expanded its Amazon audiences and contextual targeting capabilities to help reduce reliance on traditional ad identifiers. The company’s model-based audience inference methodology leverages available event and contextual signals to match the right message to the appropriate audience and increase sales. Advertisers using these expanded audiences and contextual targeting have seen 20%-30% incremental addressability on inventory that was previously unaddressable.
Behind-the-scenes Algorithmic Improvements
These algorithmic improvements deliver more cost-efficient ad placements without the need for advertisers to adjust their existing campaigns. The enhancements are designed to work seamlessly with advertisers’ current strategies, allowing them to reap the benefits of these advancements without any additional effort on their part.
Amazon Ads Continues to Innovate for Sellers
Amazon Ads is committed to inventing new ways for brands to solve marketing challenges. Their advertising technology helps brands uncover new insights, maximize marketing performance, lower costs, and discover the impact of cross-media investments both on and off Amazon. With the introduction of these new machine learning models and optimized campaign control systems, Amazon Ads is once again demonstrating its dedication to staying at the cutting edge of the advertising industry.
Comparing Amazon’s Machine Learning Models with Google and Meta
Amazon’s new machine learning models aren’t the only advanced advertising technology on the market. Both Google and Meta (formerly Facebook) have introduced their own AI-driven advertising products, Performance Max and Advantage+ Shopping Campaigns, respectively. However, there are some key differences between these offerings and Amazon’s new DSP models.
Transparency and Control
While Google’s Performance Max and Meta’s Advantage+ Shopping Campaigns offer powerful machine learning-based advertising solutions, they have been criticized for “withdrawing control and transparency” from advertisers. In contrast, Amazon’s machine learning upgrade is a core function of their DSP for all advertisers, meaning that the product enhancements do not sacrifice campaign transparency or analytics reporting.
Direct Connection to Sales Data
One significant advantage that Amazon has over its competitors is its direct connection to sales data. As Neal Richter explains, “The backbone of our performance is how we measure ROAS and CPA, in real terms, on the store. We have a direct connection with the cash register, so to speak.” This direct connection allows Amazon to more accurately measure the success of campaigns and make better-informed decisions about ad placements and targeting.
Amazon’s Impressive Growth in the Advertising Industry
Amazon’s advancements in advertising technology have contributed to impressive growth in the company’s advertising services division. In Q1 2023, the division reported revenue of 7.87 billion the previous year. Furthermore, Amazon’s worldwide ecommerce sales are forecast to grow nearly 9% to $685.39 billion by the end of 2023, giving the company an 11.6% share of the global ecommerce market. Amazon’s U.S. advertising business is also expected to grow more than 17% this year, reaching $33.96 billion and giving the company a 12.9% share of the U.S. digital ad market.
Future Developments and Innovations
Amazon Ads is not resting on its laurels. Neal Richter has indicated that there will be more announcements related to machine learning and advertising technology in the near future, stating, “I think of this as just the starting gun.” With Amazon’s track record of innovation, advertisers can expect even more exciting advancements in the world of online advertising.
The introduction of new machine learning models and optimized campaign control systems for Amazon DSP marks a significant step forward in the evolution of online advertising. These advancements offer advertisers improved performance, cost-efficiency, and the ability to reach previously unaddressable audiences. As the advertising industry continues to change and adapt, it’s clear that companies like Amazon Ads will play a crucial role in shaping the future of digital marketing.
