Digital Marketing Trends for 2022

Digital Marketing Trends for 2022

The advent of digital tools has turned age-old marketing and advertising processes upside down. Digital marketing technology is now a requirement for identifying, acquiring and retaining customers in an omnichannel world.

A new e-book from MIT’s Digital Economy Initiative highlights learnings from the MIT Chief Marketing Officer Summit 2022, held this spring. Top message to marketing leaders: Add data, analytics and algorithms to better reach socially connected modern consumers.

Here are MIT Sloan researchers’ top digital marketing trends for 2022:

Social consumers in broad digital and social networks

Today’s consumers make branding decisions based on a very wide range of digitally connected networks, from Facebook to WhatsApp, and the mix is ​​constantly changing.

Because social consumers are influenced by what their peers on social media think about different products and services (a trend dubbed “social proof”), marketers need to conduct granular analysis to truly understand the role of social media in marketing , according to the IDE director

Aral examined 71 different products in 25 categories purchased by 30 million people on WeChat and found significant positive effects from including social proof in an ad, although effectiveness varied. For example, Heineken saw a 271% increase in click-through rate, while Disney engagements increased by 21%. According to Aral, there are no brands where social proof reduces the effectiveness of the ads.

Video analysis on TikTok, YouTube and other social media

TikTok influencers are big, especially among Gen Z. The issue is whether or not these viral influencer videos are actually converting beyond attention into sales.

Research shows that engagement and product appearance aren’t the deciding factor—it’s more about whether the product complements or syncs well with the video ad. And the effect is more pronounced with “product purchases, which tend to be more impulsive, hedonic, and affordable,” according to a study conducted by Harvard Business School assistant professor Jeremy Yang while he was a graduate student at MIT.

Measuring consumer engagement with machine learning

Call it the “chip and dip” challenge: Marketers have long grappled with bundling goods and finding the right consumer goods to buy together from a vast assortment. With billions of options, this research is challenging and extensive, and data analysis can be daunting.

Researcher Madhav Kumar, a graduate student at MIT Sloan, developed a machine learning-based framework that iterates through thousands of field scenarios to identify successful and less-successful product pairs.

“The streamlined bundling policy is expected to increase revenue by 35%,” he said.

Using machine learning to predict outcomes

Most marketers are concerned about retention and revenue, but without good forecasting, decisions about effective marketing efforts can be arbitrary, he said Head of the research group for social and digital experiments at the IDE. Instead, upgrade customer targeting by using AI and machine learning to predict results faster and more accurately.

In collaboration with Boston Globe, IDE researchers used a statistical machine learning approach to analyze the results of a discount offer on customer behavior after the first 90 days. The short-term replacement prediction was as accurate as an 18-month prediction.

“There is great value in applying statistical machine learning to predict long-term outcomes that are difficult to measure,” Eckles said.

Adding “good friction” to reduce AI bias

Digital marketers often talk about reducing customer “friction points” by using AI and automation to simplify the customer experience. But many marketers don’t understand that bias is a very real factor in AI, he said Head of the Human/AI Interface Research Group at IDE. Instead of getting caught up in “frictionless fever,” marketers need to think about when and where friction can actually play a positive role.

“Use friction to disrupt the automatic and potentially non-critical use of algorithms,” Gosline said. “The human-centric and non-exploitative use of AI will be a real strategic advantage for marketing.”

Read the MIT CMO Summit Report 2022

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