How Machine Learning is taking over Advertising

How Machine Learning is taking over Advertising

The ad industry has been slow to embrace artificial intelligence, but the technology could be a game-changer for marketers and consumers. 

In 2016, Google announced that it was working with Facebook on an effort called “Project Dragonfly,” which would use AI to help advertisers target ads more effectively in real time. It wasn’t long before other tech giants joined in. Amazon bought DoubleClick, while Microsoft acquired Nest. And last month, Apple purchased AI-focused startup Spotfire, as well as its parent company, iAd. 

But what does this mean for advertisers? What will these companies do about it? Will they adopt new techniques or simply adapt their existing ones — like using data from social media sites such as Twitter and Facebook? Or perhaps they’ll just keep doing what they’ve always done, right? 

To find out, I spoke with three experts who have studied how digital technologies are changing advertising. They all agreed that, at least initially, there won’t be much of a change in terms of strategy. Instead, it’s going to come down to adapting old tactics to fit the needs of today’s customers. 

“The big thing that’s happening now is, ‘Hey, we can get better results by having fewer people involved in our ads,’” says David Karp, CEO of Karp Research Group, a marketing research firm based out of New York. “But if you look back historically, most businesses were not very good at that. You had one person running your business, and then you’d hire another person. That didn’t work well.” 

For example, he says, many newspapers used to employ dozens of reporters covering local news events. Today, those stories often run only once every few weeks. That’s because there’s so little money left after paying salaries and benefits to reporters, editors, photographers, etc. So instead of hiring hundreds of people, publishers might try to cut costs by cutting staff. 

“It’s really hard to make changes when you’re losing money,” Karp says. “You need to think outside the box and innovate differently.” 

One way to do that? Use algorithms to analyze customer behavior across different channels and determine where customers spend most. This way, you’ll know exactly what’s driving traffic to specific websites and ads, rather than relying solely on traditional sales numbers. 

Another strategy involves creating content specifically tailored to each customer. Instead of writing articles about products they’re interested in, some brands create videos featuring celebrities talking about their favorite products. These videos, known as branded content, tend to attract higher engagement rates compared to standard content. 

Finally, don’t forget to consider the impact of online video ads. According to Nielsen, YouTube alone generates $4.5 billion per year in revenue for marketers. If consumers watch less video, however, that number drops significantly. 

 “If you want to reach consumers, you’ve got to understand them better,” Karp says. “That’s why we’re building tools that let us learn things about people’s preferences and behaviors.”

This Content was developed as a part of our ongoing research for Content Automation through Growth Engine’s Content Engine. As a result, there may be some grammatical and contextual errors.

Growth Engine is a Branding and Marketing Agency focused on developing solutions and strategies for Businesses of all sizes and industries.

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