How Rise Leverages Artificial Intelligence and Magnite for Programmatic Success

Magnite Team

September 25, 2024 | 4 min read

Artificial intelligence (AI) and machine learning (ML) have become integral parts of the programmatic advertising ecosystem's development, from driving auction efficiencies to enabling campaign success. We recently spoke to Noa Keydar, VP of Data Science at Rise, to find out more about the role they see AI playing in the ecosystem going forward and how they're combining reliable and unique demand sources with tech to fuel success.

Who is Rise? How do you work with Magnite?

Rise is a programmatic advertising technology company that leverages the power of AI to revolutionize digital advertising by enhancing auction logic with real-time bidding (RTB) efficiency. Our core technological engine, SAM (Smart Auction Management), utilizes deep learning algorithms to optimize auction processes and maximize efficiency in an RTB environment. SAM empowers partners to leverage every publisher bid request or opportunity in the most effective and efficient way in real time.

Fostering a close partnership with Magnite, we ensure that publishers receive ads that are relevant and suitable for their audiences. We do this while being cost-efficient, reducing latency, and delivering valuable impressions for brands.

What role does Artificial Intelligence play in Rise's technology?

AI is taking an increasingly bigger role in every aspect of the programmatic landscape, from creative AI to generative AI, and as an overall tech enhancer. Its rapid growth poses both challenges and opportunities to publishers and the industry at large. However, when used correctly, AI can increase performance, ensure better ad quality, and create a more coherent user experience. With user ad fatigue on the rise, this will be critical for sustaining demand quality moving forward.

This stance on AI was reinforced at a recent Rise panel held with HUMAN in Cannes, featuring representatives from Prebid, Omnicom Media Group, and Beeler.tech. During the session, panelists debunked the notion of AI as just a buzzword, suggesting it as a transformative force recognized as a crucial tool for making efficient decisions in ad tech.

At Rise, AI is also at the heart of our programmatic technology, allowing us to enhance optimizations and efficiency. Using ML algorithms, we dynamically adjust bidding strategies by various parameters. This enables us to place ads in real time, optimizing campaign performance, reducing cost, and maximizing ROI.

How has machine learning impacted Rise's programmatic tech?

ML plays a pivotal role in our day-to-day operations, allowing us to optimize various aspects of our processes and minimize carbon emissions. For instance, traffic shaping helps publishers streamline and optimize their supply chain removing irrelevant bids in real-time from auctions. We then use intricate statistics to evaluate which bids have the highest probability of winning and converting to an impression. With the same volume of requests, publishers yield more impressions, leading to an enhanced user and, ultimately, advertiser experience.

Additionally, Dynamic Floor Price Optimization (FPO) ensures that each ad is matched with the most relevant inventory by prioritizing the real value and price of every user. Incorrectly matching campaigns with inventory can lead to bid inflation and excess requests. Therefore, FPO helps build trust along the supply chain, leading to increased traffic, scale, and campaign budgets.

What industry challenges and opportunities are Rise most focused on?

The current industry ecosystem presents several challenges, but within these challenges lie opportunities. For instance, the deprecation of third-party cookies has been postponed yet again, and the ascent of new and improved identity solutions is well underway. As an industry, we have a collective responsibility to learn what prospects they bring. At Rise, we take a holistic approach to ensure comprehensive coverage and flexibility. Simultaneously, our publisher partners are proactively conducting their own thorough research, discerning the offerings of various stakeholders and identifying sources of value, prioritizing long-term strategies over short-term gains.

One of those long-term solutions we emphasize is improving contextual capabilities. This will be crucial to ensure accurate and effective advertising in a cookie-less future.

Promoting more cost-efficient auctions is another key strategy in which supply-path optimization (SPO) has played-and will continue to play-an essential role. By enhancing efficiency, boosting sustainability efforts, and optimizing performance, we can collectively shape a future where advertising is not only more effective but also more environmentally friendly.

What kind of formats and environments does Rise operate in? Do you see any particular growth opportunities?

We are very well established in mobile and desktop web and made serious in-roads for mobile in-app, which, along with CTV is our big focus moving forward as we are striving to be completely omnichannel. Specifically in the in-app sector, we've seen notable growth opportunities in utilizing brand budgets in otherwise underused and less competitive ad sessions. This aligns with our strategy of catering to branding objectives, ensuring brands and advertisers receive more viewability and accessibility.

Tags: Artificial Intelligence, Machine Learning, Programmatic