6 questions with Neal Richter of Amazon Ads on Amazon DSP and its upgraded capabilities

Amazon Ads is unique in our industry given its deep understanding of our customers. And as a data scientist who interprets large sets of information through computational methods, you want to go to the companies that not only have the most compelling insights, but are also in a position to turn that information into a business.

We started by asking what we want Amazon DSP to become. And our solution was to develop a more comprehensive DSP that leverages our valuable audience signals and measurement capabilities for our customers’ ad campaigns on any inventory on the internet, so beyond just Amazon.com.

Additionally, we have also increased the quantity of information analyzed by our machine learning models, including a broader range of audience signals and outcomes, to continuously enhance campaign performance.

And as advertisers continue to seek ways to improve campaign performance, our latest enhancements have improved delivery accuracy, pacing, and ad performance prediction. These upgrades have resulted in a 12.6% increase in CTR for our customers, providing them with greater confidence that their campaign goals will be met, no matter the audience or supply environment.

When we say “behind the scenes,” we mean Amazon DSP customers will not need to make changes to benefit. We’re essentially taking the information our customers have already given us, and we’re using advanced technology and a wider range of signals to help them reach their performance goals. The best is that they need to do little to nothing, and don’t even have to pay extra. In other words, if you’re running a campaign through Amazon DSP, you should see improvements in areas like performance and addressability.

Our new algorithm upgrades have improved Amazon DSP capabilities to buy anywhere on the internet, where we have direct access to tens of thousands of sites and apps, as well as third-party exchanges using Amazon Audiences, measurement, and signal-based marketing to make it a full-featured, enterprise DSP.

This means a hotel or car rental brand, for example, can reach customers who recently purchased luggage more efficiently through both traditional and emerging channels.

We’ve also enhanced tools our customers are already familiar with to better connect with hard-to-reach audiences. Our key differentiator, however, is that we’re combining those products with all the unique capabilities that Amazon Ads can offer. Customers who used contextual and modeled ways to reach audiences saw an increase in incremental addressability by 20% to 30% on previously unaddressable inventory such as Safari, Firefox, and iOS.

Streaming TV has especially benefited from our latest upgrades. The enhancements we’ve made have bolstered advertisers’ ability to reach audiences in a streaming TV environment, which includes Fire TV and all its streaming apps, as well as third-party streaming inventory.

All of this in turn is helping our customers solve for some of the largest challenges in TV buying, such as addressability, purchasing video inventory more efficiently, while also driving better campaign performance.

We recently released a new generation of our core bidder, a multiyear build that includes upgraded core prediction systems that are powered by deep learning. This includes improvements to pacing and budgeting algorithms, as well as bid price calculation and optimization toward customer objectives. Over the past year, Amazon DSP has also refined the core algorithms to optimize for areas such as CPA, ROAS, reach, and frequency.