AI Articles and Analysis about Marketing and advertising

Episode summary:  In this episode of AI in Industry we speak with Abhi Yadav, the CEO of ZyloTech, a Boston-based customer analytics platform for omni-channel marketing operations. Abhi talks about what's possible now with AI for marketing personalization, and what will be possible in the next 5 years.

Episode Summary: Natural Language Processing (NLP) can be applied to tasks such as customer service handling or in chatbots to answer fact based questions. Another emerging application for NLP is in content marketing and content production.

After a presentation at the Shop!Association’s national conference late last year, I had plenty of time to chat with retail business people about their own ideas about AI’s uses, and the trends that matter most. This prompted me to gather my thoughts and combine the ideas of retailers with the AI-in-retail research we’ve done, and put together a piece to help retail vendors make sense of the next 2-3 years of AI’s influence in retail.

Introduction: In this episode of AI in Industry, we explore how artificial intelligence can be use to manipulate human behavior - in gaming and in business. We explore how game designers use psychology and machine learning to drive their own desired outcomes, leaving users to "feel" in control.

The entertainment and media (E&M) industry is a diverse sector composed of multiple segments including film, television and media streamed online. By 2021, the U.S. E&M industry is projected to reach $759 billion in revenue,  increasing at a compound annual growth rate (CAGR) of 3.6 percent.

Episode Summary: How can machine learning help us advertise through social media? In this episode, Thomas Jelonek, CEO of Envision.ai, talks to us about how in the next five years, machine learning might automate the laborious guess-and-check process of finding visual content with which users can engage. Right now, finding images and videos that will best generate engagement is a task reserved for a human. He or she shifts through images and video clips that may work for an audience based on anecdotal evidence and perception of past post success. Learn how, according to Thomas, machine learning could help you save time and money, generate you a better ROI, and build you a larger list with more accurate targeting on social media.

Facial recognition technology has been traditionally associated with the security sector but today there is active expansion into other industries including retail, marketing and health. By 2022, the global facial recognition technology market is projected to generate an estimated $9.6 billion in revenue with a compound annual growth rate (CAGR) of 21.3 percent*.

When managers and leaders think about machine learning in retail, they often imagine helpful in-store robots, automated processes like checkout or stocking shelves, or conversational agents that suggest products and answer questions for customers. While these applications should be considered as disruptive factors for retail’s future, it’s unlikely that these factors will be the first wave of AI’s impact on the sector.