A growing number of professionals are hailing machine learning as the future of digital marketing. This branch of artificial intelligence has generated a tremendous amount of buzz among digital marketers in recent months. Many businesses are already using this technology to create a more impactful digital marketing strategy. In 2020, 84% of marketers reported using artificial intelligence in some capacity, a significant jump from 29% in 2018. As more businesses begin to realize the advantages of machine learning, it will become near impossible for digital marketers to ignore this technology.
In this article, we’ll explore the undeniable benefits machine learning offers to digital marketers and some specific applications of this AI technology for your digital marketing strategy.
What Are The Benefits Of Using Machine Learning In Digital Marketing?
While there are numerous advantages to incorporating machine learning into digital marketing, its biggest draw for most businesses is the ability to understand consumers better. Despite the ingenuity and creativity of the most experienced digital marketers, they simply lack the time to sift through endless amounts of consumer data. Machine learning, on the other hand, can process and analyze vast data sets almost instantaneously.
Using the valuable insights from data offered by machine learning, digital marketers can tailor their strategies to achieve higher conversion rates and greater levels of engagement. In addition to gaining access to insights into customer behaviors, digital marketers can take advantage of machine learning’s predictive analytics.
Predictive analytics allow marketers to identify trends with the most potential and highly profitable channels. Supervised machine learning is even capable of accurately forecasting demand based on factors such as regional availability. This ability to predict consumer trends empowers digital marketers who embrace machine learning as a tool to stay ahead of their competitors.
“Since customer experience is one of the strongest determinants of success and growth as a business, machine learning offers companies an accelerated path towards massive revenues and growth,” explains Thomas Cook, a tech blogger at Academicbrits.com.
Ways To Apply Machine Learning To Your Digital Marketing Strategy
If you fear falling behind your competitors and want to leverage machine learning in your digital marketing strategy, here are a few ways some of the largest companies are applying machine learning.
Plenty of businesses are taking advantage of chatbots to provide 24/7 service to their customers. While most chatbots fetch their answers from a database of answers, machine learning allows businesses to improve consumer interaction with these chatbots.
Using machine learning, chatbots will be able to understand the customer’s queries better and actually converse with them. Leveraging machine learning in chatbots allows digital marketers to promote certain products in response to customer behaviour as well. This can drive engagement and increase conversion rates.
Moreover, digital marketers can use machine learning’s analytics to understand customer concerns better through chatbots.
Create Targeted Content
Greater insights into their target audience enables marketers to create content that is specifically designed for them. With machine learning, digital markets have the advantage of understanding the types of content that perform best among their customers. This insight gives their content the best chance of success and consumer engagement.
Disney’s new streaming platform, Disney Plus, relies on machine learning to determine the ideal mix of content to offer their subscribers. Their research team uses machine learning algorithms to understand their viewers better, predict the optimal content for each individual, and personalize each subscriber’s viewing experience.
Personalize Customer Experience
Disney Plus is far from the only streaming service to take advantage of machine learning capabilities. In fact, every single streaming service relies on some form of machine learning to offer its subscribers personalized viewing recommendations. Netflix, for example, reportedly saved $1 billion thanks to the personal recommendations generated by machine learning.
Similarly, other businesses capitalize on machine learning’s ability to generate individually customized recommendations. Based on an individual’s purchase or browsing history, machine learning is able to identify the products they are most likely to enjoy. This enables digital marketers to drastically increase sales and engagement.
The coffee giant, Starbucks, depends on machine learning to create a highly personalized experience for each of their customers. Their mobile app not only recommends drink and food orders based on the customer’s past orders, but their reward system uses machine learning to influence consumer purchases.
Reduce Wait Times
Machine learning’s ability to streamline various processes can significantly reduce wait times for customers. Since machine learning is constantly improving, it is impressively efficient. This means faster service and faster delivery for consumers. This allows digital marketers to use reduced wait times to appeal to more consumers.
Using machine learning, the ecommerce giant, Amazon, reduced the time between a customer selecting click to ship to items being shipped out by a whopping 225%. From the moment a customer places a quick order, their Amazon package will be shipped in as little as 15 minutes. Machine learning allows Amazon to fulfill shipping expectations from their customers that would otherwise be impossible.
Machine learning and other branches of artificial intelligence are predicted to generate as much as $2.6 trillion globally in marketing and sales. Businesses and digital marketers who have yet to capitalize on machine learning should seriously consider incorporating this technology into their strategy as soon as possible. Your competitiveness in any industry depends on your ability to embrace the future which, in digital marketing’s case, is machine learning.