It is an open secret that almost every business in the world today is working on some kind of AI project. In fact, every mobile app that we use in our daily lives has some form of AI or ML influence.

Artificial intelligence and Machine Learning have become a cornerstone technology for all companies aiming for digital transformation.

Personalization turns out to be the primary use case that the majority of the businesses are trying to achieve with Machine Learning.

And they are right with that approach.

Machine learning is efficient at finding patterns in data. Patterns lead to insights about customer behavior, which is a precedent to personalization.

Understanding what customers want, what actions they repeatedly perform, what actions they skip can lead to developing experiences that are truly personalized.

There are countless ways how Machine Learning can help us personalize the customer experience.

Let’s take a closer look at how Machine Learning can help personalize the customer experience.

Ecommerce Product Recommendations

Ever wondered how Amazon or for the matter any online store is able to guess your preferred choice of products with such accuracy?

Your previous order history, wish lists, and a vast amount of data from other sources enable online stores to personalize the product recommendation.

And, it is Machine Learning which acts as the brain behind these recommendations. As mentioned earlier, ML sans through customer order data-seeking patterns.

Based on these patterns and predefined datasets, it arrives at a conclusion of products that have a high probability of a purchase.

For example, if you are shopping for running sneakers, athletic socks could be one logical recommendation that a Machine Learning system could make.

The difference is that these recommendations could be made at scale, say hundreds, tens of thousands, or even millions of recommendations to a global customer base.

That is something that cannot be achieved by human capabilities but machine learning can.

Personalized Content Recommendations

YouTube. Netflix. Hulu. Prime. Take any video streaming website or platform.

Have you ever noticed that the video feed that you get and the feed suggestions that your friend could get are totally different?

In fact, the video suggestions tend to change drastically even when accessed from a different device or even location.

This is Machine Learning at work.

Netflix, the video streaming giant has been able to hook users to binge-watching marathons through personalized content recommendations.

Netflix uses Machine Learning and a host of other data analytics tools to observe viewer preferences, watch history, demographics, and even the common traits of similar user persona to make content recommendations.

These personalized content recommendations are highly accurate, relevant, and even engaging for the audience.

The same ML-powered content recommendation engine can be used by online publications and even website owners to serve personalized digital content.

Ensuring Internet Safety

The internet has democratized content creation and publication. Along with it, it has also unleashed a new sleuth of challenges.

Spams. Offensive comments. Fake information. These challenges are a threat to the safe usage of the internet.

Especially for children who are increasingly becoming reliant on online education portals and learning management systems.

Also, even businesses are finding it difficult to combat the menace that fake information is creating.

Sifting through social media, online news, and other content to zero in hatred, offensive comments, etc. Is not a humanly possible thing.

But, it is something that machine Learning can easily do like it is nothing.

In fact, like mentioned twice earlier in this article, Machine Learning is efficient at seeking patterns in large amounts of data.

If it is trained to track and highlight content that contains flagged content, it becomes easy for online publications to make the internet a safer place.

Chatbot-led Customer Service

Websites have become the gateways to customer interactions.

It is your business website that a customer would first head to when they want to find information or even buy products or services from you. However, there is a downside to websites.

It is difficult to assign someone to constantly be online and respond to queries that come in from website visitors through live chat or through emails.

Also, it is a slow process that hampers customer experience.

It is here that Chatbots, which are a product of Machine Learning, come into play. Chatbots are programs that can offer canned responses to users based on their queries.

They can be customized to offer specific responses when users ask frequently asked questions.

In other words, they can become virtual customer support reps that can work round the clock without any recess or holidays.

They are in fact a perfect solution for small and medium businesses that rely on website traffic to drive business growth.

Taking a Machine Learning Approach to Customer Experience

Customer experience has surpassed price and quality as a differentiator. Customers are willing to pay the extra price for better experiences.

When transaction volumes are soaring and businesses do not have enough manpower to manage the rush, technology must step in.

Today, we have Machine Learning to the rescue. Machine Learning can help trace data patterns that can shed light on customer behavior.

Armed with such data, businesses can devise better experiences that will go a long way in impressing customers.

Whether you are selling through an online store or publishing content online, Machine Learning can help take your customer experience to the next level.