Marketing in the age of emerging technologies is entirely different and new. In the past, ad systems relied on basic heuristics, which can be effective for making immediate judgments, but often result in inaccurate conclusions. Machine learning platforms can optimize results and do everything from predicting conversion likelihood to determining the best price to bid for an individual ad request. This interesting topic came to our attention from AIThority in their article, “How Machine Learning and First-party Data Work in Harmony for Performance Marketers.”

Another important aspect of machine learning is it puts a priority on privacy-safe options in ad targeting, which is critical in today’s cybersecurity environment.

Even though this is an exciting and innovative time for the industry, most organizations have little knowledge on how artificial intelligence (AI) systems make the decisions they do, and as a result, how the results are being applied. Explainable AI allows users to comprehend and trust the results and output created by machine learning algorithms. Explainable AI is used to describe an AI model, its expected impact and potential biases.

Melody K. Smith

Data Harmony is an award-winning semantic suite that
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