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Five Terms Marketers Should Know To Succeed In An AI Future - Junction AI
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5 Terms for AI Success in Marketing

Five Terms Marketers Should Know To Succeed In An AI Future

Marketers everywhere are adopting AI based tools to better harness data to drive value and benefits for their brands and their clients. Everyday I encounter marketers eager and ready to learn more about using this powerful technology to advance their impact, and their careers.

Understanding the lingo is a great first step to building a strong foundation. You don’t need to be a data engineer or data scientist to get a handle on the basics needed to engage productively and benefit.

Success in an AI Future

AI machine learning is becoming more common and embedded into the marketing tech stack. Many of our commonly used tools already rely on AI capability. This will only grow and accelerate as early adopters demonstrates the advantages.

To get started, and to succeed, digital marketers need a terminology upgrade. It’s important to understand some of the key terms to better understand and act upon the opportunities AI predictions and insights offer.

My latest Forbes.com article focuses on some of the key terms to help engage AI enhanced marketing tools. Familiarity with just a few terms will equip marketers to better understand the techno0logy and data, how to apply the results and interpret the predictions and insights.

The Junction AI solution for predicting ad creative effectiveness and providing insights to improve and optimize ad creative is a perfect examnple. You have access to a mountian of data on your Google or Facebook ad account. Every day you use that data to report performance, track results and inform campaign decision-making.

But have you ever wondered how good the data is for decision-making?

We lift the cover and pull back the curtains on your data with a data health check.

Our data health check delivers marketers an assessment of their audience model built from their data. Utilizing the data health check marketers can see critical information about their audience model, its confidence and precision, the data variance and other metrics. Knowing the quality of the data and resulting model is critically important to knowing how and what to do to boost ad results.

Our data health check is just one feature, and just one example, of some of the new emerging skills a successful digital marketer needs.

Check out my latest Forbes.com article for five key terms to get started. Better yet, it’s in plain english, you don’t need to be a data engineer or a data scientist!

Read on here: Five Terms Marketers Should Know To Succeed In An AI Future

 

 

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