Can Machine Learning Help Capture the Attention of Generation Z?

Generation Z is the most connected age group, being the biggest and most active segment of smartphone owners.

Most of these people don’t even know what the image on the “save button” in MS Office stands for. To them, it’s like floppy disks never existed. These young, highly engaged and incredibly web-savvy users generate vast amounts of data while they browse the internet, use location-based services, or do other activities online. Their online personas are highly interconnected with their real lives.

All this data is being used “against” them; that’s why targeted ads, promotions, and other types of engagement tactics have mostly become ineffective through overexposure. To put it bluntly – Gen Z is tired of the advertising practices that they’re exposed to, and that’s why ad-blockers have become a standard feature for browsers.

But it doesn’t have to be this way. Based on our experience at Iflexion, machine-learning-based tools can actually help businesses overcome these obstacles. Let’s take a closer look at how machine learning modeling has already transformed marketing and improved marketing performance for businesses that target Gen Z.

Robots Are Taking Over!

Gen Z has started to resemble cyborgs: they spend a lot of time with their smartphones and are practically merging with their devices. This continuous use of handheld devices and the fact that they’re not quite suitable for proper input, allows personal assistants to steadily gain ground within the smartphone ecosystem. It’s a lot easier to say something than to keep tapping your screen.

This unique phenomenon has paved the way for a shift in marketing that may affect a lot of search results and SEO practices. Voice search optimization deals with issues that arise when people search online using their AI-based assistants. Voice search is different, as it deals with spoken language, which is more fluid. People don’t say “t-shirt…red…Levi’s.” They say, “Siri, find me the nearest Levi’s store.” This is just one example, but it illustrates just how advanced machine learning has become, and how it directly affects consumers and online businesses.

Customer Behavior Models

Another great application for machine learning right now is customer behavior modeling. Although each of us is unique, we still share a ton of common traits as consumers. This is why people buy into discounts, sales, and other marketing promotions.

It’s also why predictive analytics is a perfect tool to use in marketing towards Gen Z – it allows businesses to analyze tons of user data through their cookies, site search history, purchasing history, responsiveness towards promotions, and then come up with a more or less accurate prediction of their future behavior as a customer. Soon, user online behavior will be analyzed like a loan application, with lead scoring metrics in place to know with high probability whether certain promotions will influence them.

Recommendations

Apart from predicting behavior, we can predict the product that the client will want to purchase. There are tons of companies that can do this for you, including Google. Again, all of this fits perfectly into the daily online routines of Gen Z and the massive amounts of data that they generate.

Customer Care for a Better User Experience

It’s common knowledge that customer care plays an important role in marketing: it improves user experience and builds rapport, especially when there’s a human connection. But it’s hard to keep up with the ever-increasing numbers of people trying to get help online, especially with Gen Z being the most demanding group of customers.

So, while machine learning and its natural language processing components aren’t yet ready to fully substitute real customer care reps, there is a niche, which ML can really excel at. Prioritizing, labeling, and automating certain types of responses are the things that machine learning can take over. This helps your actual customer care reps to efficiently deal with clients and make them happy.

Social Media Evolved with Machine Learning

Another incredibly concentrated place machine learning can find data to process is social media. Chatbots rule this space, armed with NLP. However, not everything is dandy, in fact, machine learning can’t keep up with the fluidity of language on social media and how quickly it evolves.

Conclusion

Machine learning is the perfect marketing tool for Gen Z. They spend the most time online, they generate big amounts of data, and so AI-based predictive and analytical tools can easily use all of this information to create marketing predictions. Various marketing niches already use machine learning to refine their efficiency: from customer care to pricing and product recommendations.

If companies want to achieve anything that’s beyond subpar industry standards for their specific marketing KPIs, then machine learning is the way to go. This tech allows any business to circumvent standard marketing practices and augment their marketing efforts with powerful predictive tools.

Information about the author

Yaroslav Kuflinski is an AI/ML Observer at Iflexion. He has profound experience in IT and keeps up to date on the latest AI/ML research. Yaroslav focuses on AI and ML as tools to solve complex business problems and maximize operations.

Image Credits: Machine Learning from gstockstudio/Shutterstock

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