Advertising in an AI Era

How Artificial Intelligence Is Transforming Marketing Now

Oct 04, 2019
Marketing

SMITH BRAIN TRUST  Artificial intelligence is transforming and disrupting industries. And advertising is no exception.

Today’s smart marketing professionals are embracing the disruption, using the power of AI to create authentic, customized messages for each consumer.

Disruptor Daily recently examined the role that AI is playing in the industry, reaching out to a number of marketing experts, including Maryland Smith’s P.K. Kannan, for insights.

Here is some of what Kannan, the Dean’s Chair in Marketing Science at the University of Maryland’s Robert H. Smith School of Business, had to say:

What’s the State of AI in Advertising Today?

“The term Artificial Intelligence is rather broad. It encompasses expert systems of the 1980s the neural nets of ’80s and ’90s and machine learning of the 21st century and more recently Deep Learning, Natural Language Processing and Text Analysis.

In today’s advertising industry, AI in the form of machine learning is widely used. In advertising, the major objectives include: (1) identifying the right segment, right group or the right person to advertise to; (2) coming up with the right message (content), at the right time to the right person to communicate to (3) efficiently allocating marketing dollars across the different advertising channels so that the overall campaign is optimized.

Machine learning models are used to identify the right groups across various platforms (across websites online and mobile sites), personalize content communicated to the different groups, and coming up with optimal allocation of budget across various advertising channels. Many consultants provide such services so that firms can automate many of these functions using algorithms.”

Which Trends Are Shaping AI’s Role In Advertising Today?

“Using AI to create advertising content. Basically, you have data on what type of content has been effective in getting customer engagement and using the data to create new content automatically that will appeal to various groups you intend targeting. This takes into account the image data, copy data and other features of the advertising campaign and parceling the effectiveness of each in order to create the best copy ad and/or image/color etc.”

What Challenges Face AI Adoption In Advertising?

“Using AI for targeting purposes, creating personalized ad copy and communication messages and understanding their effectiveness requires analyzing a lot of individual level data that tracks customers across websites, devices and platforms using cookies, pixels and other invasive technologies.

Given the privacy concerns of using such data for targeting and communicating, there is going to be pressure on using less of such data which might dampen the use of such technologies. The challenge in these times is to come up with privacy-preserving analytics to aid advertising targeting. There is work on-going in this area but still such time there will be increased scrutiny of such data usage.”

What benefits does AI bring to advertising?

“Advertising can be made more personalized in terms of content, in terms of the specific site/website/device where the customer is to be targeted, in terms of the frequency with which they are targeted, while making these decisions and implementing them in real-time as data comes in. Without AI, none of these would be possible.”

What’s the future of AI in advertising?

“AI is key to efficient and effective advertising campaigns that can lead to reductions in acquisition costs and an increase in customer lifetime value. More and more, content will be designed and campaigns executed automatically in real-time based on AI algorithms.”

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About the Expert(s)

KannanPK

P. K. Kannan is the Dean's Chair in Marketing Science at the Robert H. Smith School of Business at the University of Maryland. His main research focus is on marketing modeling, applying statistical and econometric methods to marketing data. His current research stream focuses on attribution modeling, media mix modeling, new product/service development and customer relationship management (CRM).

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