Marketers can use deep learning and AI tools to assess each media buy separately and target ads in real-time market conditions.
While self-serving programmatic ad buying platforms offer more direct control over campaign spend and provide transparency on pricing and placements, the process in itself is tedious. Deep learning and AI algorithms provided by integrations like dynamic private marketplaces let marketers optimise media buys and boost performance cost-effectively.
The demand for increased transparency in programmatic is growing, as platforms like Yahoo and The Trade Desk have become popular self-serve platforms in 2021, as per Advertiser Perceptions. However, given that self-service systems demand traders to analyse enormous amounts of data like market conditions, consumer preferences, and more under deadlines, consistently optimising performance at scale and across many clients becomes challenging.
Advertisers can use machine learning tools like deep learning to efficiently optimise ad performance while also saving time to concentrate on all campaigns equally. Brands can use AI algorithms to prevent displaying ads to those who are unlikely to buy, as well as automate real-time predictions to gather audience response data for ads.
[4 minute read]
