How Artificial Intelligence Ties Into Programmatic Media

In a bid to understand the way in which artificial intelligence (AI) is related to programmatic media, Real-Time Daily spoke to Tomer Sade, CEO and founder of Wise Data Media. The company markets an AI, real-time bid management system that aims to facilitate marketing decisions across all digital channels. The data-driven, cloud marketing software is essentially a prediction management platform that tries to forecast how each new campaign can best be optimized in order to achieve optimal results before bids are made.

Real-Time Daily: We don't typically think of AI when we think of programmatic media. What is the connection between AI and programmatic?

Tomer Sade: Marketing is one of the first industries to have been significantly affected by advances in artificial intelligence. AI is at the heart of the digital advertising industry and is becoming a more integral part of programmatic buying.

Programmatic advertising is the automated process of buying and selling ad inventory through an exchange, connecting advertisers to publishers. This process uses artificial intelligence and real-time bidding for inventory across all channels. AI can analyze the complexity of media buying via programmatic in a way that is not humanly possible or not possible by human media buyers and planners.



RTD: Can you offer some specific examples or potential scenarios of what this relationship looks like?

Sade: Artificial intelligence gives marketers the ability to take control of their data to achieve the results they are looking for. It gives them the power to optimize their digital marketing campaigns pre-bid. They can determine exactly where they should place their bid, how much they should bid, and when they should bid — this is all before they even place the bid. The goal is to help them monetize their campaigns and deliver the best possible return on investment.

The purpose of AI is to take the massive amount of consumer data that’s collected, and analyze the information it contains about consumer demographics, interests, and purchasing preferences. Marketers then use this analysis to determine the right audience for an ad so they can create more focused and targeted ads, which leads to better campaign results. This is especially helpful in video ad campaigns, where the proper placement and timing of the ad is a critical aspect of a campaign’s success.

RTD: How are predictive insights generated by AI, and how specifically might they help improve programmatic media practices?

Sade: AI and predictive modeling techniques boost campaign effectiveness by accelerating the decision-making process in terms of determining what ad should be delivered to which user, what type of format should be used, and the best time to deliver it.

RTD: What companies are using this technology now in their programmatic media processes? 

Sade: Google, Microsoft, IBM, the holding companies of media agencies groups, and any media companies looking to optimize their decision-making processes.

RTD: What are the benefits of AI? What are the challenges?

Sade: In terms of benefits, AI can increase marketers’ knowledge and understanding of consumer behavior in ways that were never possible before, making for more relevant, cost-effective, and optimal advertising. AI can process and analyze the quantity and complexity of big data in a way that hasn’t been possible before. The result is marketing on a scale that’s never been imagined, let alone achieved. AI delivers better ad campaign control because it employs more quantified and automated strategies. These strategies can be used to improve the customer’s shopping experience, to test advertising campaigns, and to make campaign bidding decisions more cost-efficient.

The main challenge with AI is having the technology predict the right action, in context. Algorithms need to work seamlessly to make decisions in real time. Not every organization has the resources to build these capabilities. Getting from the theoretical to reality is a challenge that not all companies are prepared for. It’s also an issue of personnel. The motivation for a company to become fully automated is often questioned by workers who fear what that might mean for their job security.

RTD: How does machine learning play into this, if it all?

Sade: Machine learning algorithms operate 24/7. The learning never stops, enabling greater awareness and knowledge of even the most subtle changes in market behavior, which can be used to make better marketing decisions. It’s a combination of developments, including more powerful computing, big data, and advances in deep learning technology. This combination has made it possible to create and maintain large datasets that deep learning algorithms can analyze for marketing purposes, such as identifying trends and making predictions. For example, with AI, large amounts of data, such as browsing or shopping histories, can be analyzed to tell advertisers where, when, and whom to target. 

RTD: Explain how AI ties into probabilistic and deterministic predictive analytics, and to the evolution of programmatic.

Sade: AI is always learning. The more it’s used, the smarter and more efficient it becomes. So AI learns which users to target and which users not to target, which users are likely to engage, and which users aren’t likely to engage. From this, AI can determine only the most relevant users to target, which means fewer wasted ad impressions and highly defined, targeted ad campaigns.

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