How does Machine Learning Affect User Experience?

by | Jun 27, 2017 | Insights |

This series discusses the affect that machine learning, artificial intelligence, virtual reality and augmented reality have on user and customer experience.  I am very passionate about the impact that these innovative technologies can have on creating unique experiences across the board and felt that I would share this with you.

What Is Machine Learning?

 

Machine Learning can be described as “A computer program that learns from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E.” This is the formal definition by Tom M. Mitchell.

It seems rather crazy but basically, Machine Learning is a set of Algorithms that identify patterns in data to deliver and increase the chances of better predictions and decision making.

Machine Learning is already incorporated in so many of the technologies we use. The best example of this would be Netflix. As you continue to watch and rate a particular series or movie, Netflix begins to make recommendations based on this. Remember the heading “because you like this” or “you may enjoy this”?

These are generated via ML to give you the best possible experience based on your data and viewing history.

 

 

 

 

How does ML impact Customer Experiences?

 

ML is deeply integrated into the recommendations programs, like Netflix, give you. This creates a unique, to the point experience that keeps you interested. Helping you to find content that you would want to consume.

However, Machine learning goes beyond just being used in consumer-facing programs like Netflix or YouTube or Facebook. As businesses, we are constantly looking at using new techniques to drive more sales and improve experiences. This is where Machine Learning becomes extremely powerful and the more it’s used the stronger it gets.

These are some examples of how ML can help enhance customer experience;

ChatBots

The first case is called the Call Center Chat Bot idea. As customers, we have all experienced the call center or chat bot before. This experience very rarely creates customer satisfaction.

Enter ML. When you start chatting to a Bot online it can determine by the word choices, sentiment, and statistical data to assess at which point you may need to be transferred to a human to solve your query.

I find this extremely useful and time-saving. We may see more and more queries being solved via the bot and if not fewer queries going to an actual center. Here the customer experience will be enhanced tremendously. The more it’s used the better the Bot will get at understanding a person and their questions and ultimately become a faster more useful tool to solving customer issues.

Personalised Experiences

The next case would be personalization. Yes, a lot of professionals are talking about tailoring their efforts to become more and more personal but how do you get there? Manually creating data sets and segmenting people into groups? The problem here is that it isn’t entirely accurate and the people in Group A might not actually be the people for Group A.

This is where machine learning can take your data and combine it with the habits of your customers. It then segments them into the most relevant groups to make the most tailored experience based on learnings.

A prime example of this is an online store. With ML as the basis for recommendations, a user’s behavior and demographic information will be used to create a list of recommendations best suited to them.

Taking this a step further, ML would allow you to create entire experiences of your online store to become completely unique to each user. You could have 1 store that would become a thousand different stores, personalized to a thousand different customers.

Does ML really help?

 

ML is a tool that creates customer experiences catered to their exact needs. This is super crucial to delivering the best customer experience.

But, this isn’t just the best part. If you think about the examples mentioned above, we can use these cases to enhance UX design. UX is all about creating a design for personas. Allowing machine learning to help with this we should have amazing UX on a site tailored to the individual persona.

However, machine learning only really helps if used in the correct context and when it’s allowed to spread its proverbial wings. In essence, ML is there to serve the role of seeing, thinking and acting. It alleviates pressure and delivers experiences for us.

Gus is a digital marketing strategist obsessed with data backed strategies and arguments. He is driven to constantly innovate and potentially change lives through online experiences.
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