6 Ways Machine Learning Impacts Millennial Marketing

machine learning impact millennial marketing

Advancements in artificial intelligence skyrocketed in 2018, putting Baby Boomers on edge as Gen X’ers came nowhere closer, therefore, staying at the rear end of technological science. Millennials, however, are at the brink of technological science, creating a wave of idealism and multicultural vision that will push through all ends and stigmas. While machine learning is concerned to be highly difficult to grasp for the average 90s layman, this technological barrier, therefore, might create a breakthrough in automation, in more ways than one. 

Machine learning is at times, confused with artificial intelligence, despite being an avid branch of the broader, umbrella term. From upping your Wi-Fi router to driving a new wave of experiments in marketing for digital marketers, machine learning aims to deliver aspects unlikely to any prior technological experience. 

6 Ways How Machine Learning Impacts Millennial Marketing 

Speaking of marketing, machine learning helps to automate, manage, integrate, and analyze comprehensive data for functioning models. Its main aim is to identify and build patterns that can operate without the need of humans. 

With every passing day, millennials are succumbing to the screens of their smart devices, where every chore, activity, and experience is virtualized yet on-the-go. With machine learning hoping to bridge barriers in business, marketing, and science with its incredibly self-relying and self-transitioning model, millennials, in fact, might as well enjoy and make use of this technology without feeling threatened by it. 

In order to assess the benefits that Machine Learning has in store for Marketing to Millennials, consider the following six ways to garner a thorough impact. 


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1) Helps To Rank Customer Behavior 

To denote a brand’s success online, it is important that the company’s bread and butter, that is, its consumers are not only satisfied with its products and services, but also with their overall user experience (UX). To garner a positive user experience, brands have to pay attention not only to their inventory, but the way their website is marketed for lead generation. From assessing navigation features of a website to a brand’s e-mail marketing techniques for increasing click-through rates, all of these help to analyze whether the UX of a consumer is positive or negative. 

Machine Learning can help millennials analyze customer behavior not only with confidence but with proof of analytics that can help them improve their performance. For instance, machine learning not only tells you about the number of clicks you achieved via your opened e-mails, or the times a consumer visited your website and downloaded, saved, or simply hung around your content. It also gives you an insight regarding their social media, which in today’s current is inhabited by 90.4% of millennials alone. 

Their social media will help you to acknowledge the type of websites, content, and ads they engage with; the type of industrial influencers they consider worthy of following on social media; and most importantly, their browsing history for making buying personas relevant to their purchase intent. 

Therefore, you can assess and calculate a lead’s score by putting in data regarding the aforementioned aspects. By making buyer personas and lead profiles according to your consumers, you can market exactly what they want you to achieve from your brand. Therefore, enabling you to improve your brand campaigns, ecommerce funnel, user experience, and brand performance. 

2) Predicts Customer Turnover 

Customer turnover, or more commonly known as customer churn in SaaS business terms, helps to depict the percentage of people or consumers who abandon the services of a brand due to a number of reasons during a verified or specific period of time. Customer churn, therefore, helps a brand to predict the position of its business in the industry. It also helps a brand to understand the reasons why customers consider leaving its business, therefore, enabling it to seek improvements through applicable customer behavior models. 

With machine learning, you can create a model based on customer data integration throughout a consumer’s history. You can assess when a consumer started visiting your profile to the time when they narrowed down their visits to once or twice a month. The data collected will help you to up your marketing campaigns so that you can reach your pre-existing customers through promotional offers, loyalty programs, and referrals, to name a few, to lure them back towards your brand. 

Customer turnover will also help you to analyze the ratio between the number of people leaving to the number entering and embracing your website. 

3) Customer Personalization 

Approximately 78% of consumers require a user-friendly, customized and highly- relevant customer experience to maintain their interest in a brand’s products or services and purchase intent. One of the biggest breakthroughs of machine learning is to help marketers personalize their data for targeting and retargeting consumers towards their brand and website. Machine learning helps you to personalize data by collecting and integrating it for highly-customized marketing towards different target audiences. 

Its algorithms are highly intelligent, and therefore, can assess the body language, tone, and format to the type of content highly preferable by each customer on the website. Moreover, machine learning makes use of buyer personas by allowing you to create profiles that are highly personalized and enriched with user-based information for targeting, presenting product recommendations, and offering personalized e-mails to the established leads. 

4) Tracks Media For Product Recognition 

Apart from giving marketers and brands an edge for spying on their competition with the help of machine learning, this technology also helps you to recognize your products by scanning shared content on different types of media on the Internet. Machine learning was therefore, highly helpful in scanning content such as videos or images that showed no relevance to targeted keywords or tags, or didn’t use them at all in the first place. 

Machine Learning, however, can help marketers collect data that has been shared over millions of websites for assessing motives of promotion and publicity, or copyright infringements. 

5) Chatbots 

One can never talk about the impact of machine learning on millennials and miss mentioning its biggest breakthrough of all times, i.e. the chatbot. Chatbots are revamping customer service in such a way that they are not only providing humans with time to respond to unique, real-time based queries, but also to those questions that warrant inexplicably long periods of time. 

Today, millennials require live chat features to automated concepts with a 92% positive customer satisfaction experience. Machine learning, however, helps you to implement comprehensive and robust live chat features so that you can improve customer experience at a better rate than before. Moreover, implementing machine learning via chatbots will also help marketers collect relevant data regarding their purchase intent and preferences from their consumers. 

Consumers also tend to prefer live chat options mainly because they achieve answers to their queries at higher response rates with information that they didn’t ask for but helped them anyway as a bonus. 

6) Improved Product Recommendations 

With a boost in customer personalization techniques, improving product recommendations for consumers has been a breeze. Machine learning, however, doesn’t only let you know about a consumer’s purchase intent. It helps to create comprehensive and highly-integrated buyer personas that challenge the norms with their exhaustive customer data management. Machine learning shows that it can too, care about your experiences and preferences just like humans do. For marketers, the ultimate goal is to prove that their products are of use and utmost importance, which they can achieve if they pay more attention to creating customer-tailored product recommendations. 

For instance, take a look at Netflix, where it has separate categories for bringing tailored content towards you to pique your interest. The ‘who’s watching’, ‘trending now’, ‘familiar favorites’, and ‘because you’ve watched…’ are tailored with options to bring you content that’s not only trending and viral, but also relevant to your previous choices. 


machine learning impact millennial marketing campaigns

The Final Verdict 

Approximately, 79% of millennials recognize the necessity, purpose, and reason behind using sponsored ads for a brand’s publicity. Since almost 94% of millennials are armed with a smartphone, every experience starts, and would indefinitely, with the help of a screen, a robust Wi-Fi or 4G/5G connection, and click. 

Machine learning can solve problems and answer queries in an instant, which not only makes it an adaptable invention, but more of a new-generation kind. Market better to Millennials with machine learning!

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