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Can Machine Learning Help Capture the Attention of Millennials?

Millennials are the most connected generation, being the biggest and most active group of smartphone owners and they’re also more likely to spend time online.

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 of 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 – Millennials are 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; machine learning is a great tool that can actually help businesses overcome these obstacles. There are plenty of applications that machine learning can be used for. Let’s take a closer look at how machine learning has already transformed marketing and improved marketing performance for businesses that target Millennials.

Robots Are Taking Over!


Millennials have 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 we all think that each one of us is unique, which is true to a certain extent, 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 Millennials – it allows businesses to analyze tons of user data through their cookies, site search history, purchasing history, responsiveness towards promotions and come up with a more or less accurate prediction of their future behavior as a customer. No-one generates as much information online as Millennials do and that’s why over 80% of B2B marketers already have predictive analytics on their agenda. Soon, your 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 you.



Instead of predicting behavior, we’re dealing with predicting the product that the client will 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 Millennials 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 Millennials being the most demanding group of customers.

So, while machine learning and its NLP 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.


Machine learning is the perfect marketing tool for Millennials, specifically. They spend the most time online, they generate the biggest amount 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.

Adriana Blum

Adriana Blum is a Senior Mobile Developer and Technical Lead at Iflexion with 13+ years of experience in designing and implementing software applications for renowned companies. She specializes in cross-platform development on React Native and Xamarin and has broad experience in native iOS and Android development.

For over 10 years, Adriana has been managing and delivering custom mobile solutions for E-commerce, Social Networking, Retail, and Entertainment. As part of Iflexion’s Mobile team, Adriana has been working on a range of complex projects, including TradeStops Mobile – a native iOS app for stock monitoring, and a cross-platform mobile platform for networking and crowdfunding.

Currently, Adriana is actively researching the capabilities and applications of AR and VR in the mobile industry to create innovative mobile solutions for outstanding user experience. Leveraging the potential of Apple’s ARKit and Core ML, she’s working on the prototypes of AI-based apps for Retail and Entertainment.

Can Machine Learning Help Capture the Attention of Millennials?
Adriana Blum August 14, 2016