How machine learning can enhance the customer experience in your eCommerce business
You don’t really have to be into tech to have heard the phrase Machine Learning. It isn’t new either - conceptualized in 1952 by Arthur Samuel, it waited for the future where the available technology would have sufficient computing power to run such calculations. This future is now and ML is being used to perform an ever-increasing number of tasks. In this article, we would like to talk about the ways Machine Learning can enhance the customer experience in eCommerce environments. Both eCommerce and Machine Learning are rapidly developing fields that utilize the potential of the latest technological advances. But what happens if we merge them together?
To get properly started, we need to define Machine Learning briefly. We’ve asked Bartłomiej Kwiatkowski, Qanuk.ai’s COO for a short explanation:
“Personally, I define Machine Learning as a process that uses real-world data to create a virtual model of this world. This model is based on algorithms that are then translated to software. In the case of Qanuk.ai, we’re talking about a tiny sliver of the world - a collection of product photographs or a log of user behaviors in an online store. Machine Learning allows us to create a logical way to interpret enormous amounts of data. Because of the sheer number of possible combinations of parameters, writing an old-school type of function in code for them manually would be impossible. Machine Learning is, of course, a type of AI that is used in a narrow way, that is, to perform a single, precisely defined task.”
What does ‘customer experience’ entail?
Customer experience is the overall impression customers have of your brand. It consists of three major components: Customer journey - Every journey begins with the first step. For the customer, it’s the the moment they realize they need something. It might be prompted by an ad, word-of-mouth, or an actual necessity. With so many different online stores to pick from, what is the factor that will make them choose you over the competition? The journey then follows the customer through their entire shopping experience, from picking the product and buying it, all the way to receiving it and formulating their opinion on it, as well as the brand they bought it from. Branding - Branding is the all-encompassing message you send to customers and visitors about who you are, what values do you believe in and how you can make people’s lives better. It includes every element of your website, from the graphics and the text, through your social media presence, all the way to the font and the color scheme you’ve chosen. An essential part of it is also communication. Branding gives potential customers to get to know your company, which often has a decisive impact on whether or not they’ll decide to stay on their consumer journey. UX - Is navigating your website an easy process? Are all the instructions understandable and the pages loading smoothly? Can people easily find what they’re looking for? Are the buttons and text boxes placed intuitively? All of these factors have a huge impact on customer experience.
Securing a good customer experience gives you an instant competitive advantage, as visitors will simply have fewer reasons to leave and more reasons to stay. Machine Learning can help you elevate that even further.
Enhancing customer experience with Machine Learning
Machine Learning touches most of the aspects of customer experience, from recognition of unique needs, through personalized communication, to personalization of pages. The algorithm taught with Machine Learning takes into account all the data on the behaviors of customers on your pages. Because of that, it can create personalized models of behavior. That, in turn, allows for tracking the behavior of visitors in real-time, predicting what type of action they may undertake, and nudging them in the right direction. How is it done in practice, though? At Qanuk.ai, we train Machine Learning models to create personalized recommendations, either visual or behavioral. It means the visitor will be recommended products they are most likely to be interested in. That doesn’t just mean they might spend more money at the store. It also means they are more likely to stay on the website and continue with their customer journey.
Personalization of customer experience while you’re busy High-volume online stores need entire teams in order to process all of the customer queries, requests and complaints they receive. Sometimes it takes a while to get back to everyone and employees can frequently experience traffic overload, especially around the times of increased spending, such as Christmas or Black Friday. Not all customer queries are the same, but that doesn’t mean that there are no patterns. Machine Learning is an effective tool for automating repetitive and mundane processes with structured data. Such processes include photo tagging or evaluating and segmenting incoming messages from customers. It’s a widely used functionality of ML, as it provides a personalized way to deal with customer requests, while simultaneously giving you more time to focus on actual pressure points.
Machine Learning can be a lot of things, but…
...it’s not an all-around cure for all the ailments your company has. It can certainly elevate the experience of the customers at your online store, but you need to put in the effort as well. Machine Learning simply won’t work without your input and data collection activities. It also takes a while to get it up and running, because, as the name suggests, it needs to learn. That means it has to process the data and make sense of it by calculating all the possible combinations. Finally, as a developing field, you can expect to have to update it regularly.
With all this effort and bother, is it still worth it? Yes! The benefits of ML implementation far outweigh the work companies have to put in. Moreover, the fact that the field is still developing is actually a huge advantage. Who knows what types of new ways to interact with customers will be created with Machine Learning in years to come! Given that implementing and launching ML-based campaigns on your website takes time, it’s best to start as soon as possible. In this way, you’ll not only have a well-trained algorithm, but you’ll also give your team more chances to gain valuable knowledge and experience. In the long run, it will make future implementations much easier and more naturally intertwined with your company’s usual operations. Companies that already use Machine Learning are experiencing a sizable ROI. Asos noted a 300% increase in revenue after launching AI-backed sizing assistance. Uniqlo, a global apparel brand originating from Japan has managed to increase client satisfaction by creating a system of personalized style recommendations for its users, along with stores where recommended products are available for purchase.
The data backing use of ML is out there - find out for yourself and join in!