Technology is becoming more advanced than ever these days, especially when it comes to artificial intelligence. The most advanced systems are now capable of doing things that were previously only possible for humans to perform, and they are supporting organizations to make more reliable business choices than ever before.

One type of AI called machine learning, in which machines can improve and adjust their processes without being explicitly programmed by a human, has become particularly important for people who do online business.

If you manage an eCommerce business, there is a range of ways that you can dig into the potential of machine learning to provide you with an improved user interface, become more efficient and open up revenue opportunities that might previously have been impossible.

Different ways to use machine learning in your eCommerce business

To determine patterns and trends

Wouldn’t it be amazing if you could get into your typical customers’ brain, understanding what make them happy, what they want, and what they think about your goods or services?

Machine learning will carry the Holy Grail closer than ever before by detecting trends and finding patterns based on historical data.

Efficient, reliable, and automated, it’s simple to see why so many eCommerce businesses are transitioning to machine learning from human analysis.

To optimize search results

Search is important for any eCommerce company to succeed. If your services do not turn up before potential clients, how would they ever know that you exist?

Machine learning algorithms will greatly improve the search results for eCommerce products, helping to increase those click rates, user reviews, and conversions.

Machine learning allows users to get so much more out of the experience of searching and can precisely identify the products or services they are looking for.

With machine learning involved in the search process strategically, search results are more accurate and focused on what the customers want rather than what they just tapped into the search bar. Also, based on these variables, search results will reveal exactly what consumers are searching for, and recommend related products.

For product recommendations

One of the most effective forms of marketing is the product recommendations. Commonly, existing product recommendation technologies analyze a product’s importance to determine when and how to make a recommendation.

On the other hand, machine learning can dig into more reliable and specific data such as the particular shopping preferences of the customers, the colors or looks they like, and the sort of budget with which they may have to operate. A machine-learning approach will prioritize product suggestions, which are likely to produce the most revenue or incremental sales, by moving one step further.

For content feed customization

The main objective behind customization with AI in eCommerce is user engagement that results in positive customer experience, with more sales, of course.

Marketplaces want users to spend more time on their platforms and end up buying their products or services. To make that work, they reshape other features of the website to fit the requirements of the individual in question.

With the help of machine learning algorithms, the customization process can be easily handled.

Service customization results in a better user experience that prevents potential distractions, cart abandonment, and unnecessary products while highlighting the products or services that are of interest.

For dynamic price adjustment

Price adjustment is the area where you can feel the scope of the benefits of machine learning. In the eCommerce industry, the competition is fierce and you have to stay on top, that’s why you need to get as many benefits as possible to attract and keep the clients.

One of the most successful ways of doing this is by providing more reasonable prices for the products of interest.

On example is Amazon that uses price adjustment based on market trends and product demand, as well as internal user data. This way, they can subtly make the prices more attractive to the customers interested in them.

To implement visual search

Imagine you are on the bus, and you see the person near you wearing a coat you never knew you wanted. You turn to your phone to see if you can find it online, but what to type? How to describe this coat? Black with blue stripes? Blue with black stripes? Mid-to-short length? So many questions and so many ambiguous search terms come to mind when trying to determine the exact search terms to find this coat.

Enter the visual search!

Visual search is the capacity to search for similar or related visual assets using an image. (Pinterest is a great example of visual search).

Visual search would not be possible without machine learning.

How this works:

  • There is an algorithm for image recognition. This is used to identify an image and to describe the features of its surface.
  • The process typically involves a convolutional neural network (CNNs- a category of Neural Networks that have proven very effective in areas such as image recognition and classification.) that recognizes an image and a recurrent neural network to further define an image.
  • Then the interpretation of the image is associated with the information regarding the product.
  • As the search engine handles the input of an image- it matches the descriptions of the image and goes to the relevant product details.

For fraud detection

Fraud is one of the most significant banes in eCommerce. The eCommerce industry had lost more than billions on multiple fraudulent activities just last year. It’s one of the things that never really go away- you can find a way to remove the current risks, and then it’ll adjust and come back with the new technique pack.

Implementing custom software for your eCommerce business can help you avoid fraudulent activities, but also with the implementation of specialized machine learning algorithms, you will be able to detect suspicious activity and preventing it from causing damage.

You can read more about this topic in our article: eCommerce Website Security – Protect your Online Store Against Cyber Threats

Is machine learning right for your business?

Machine learning it’s an amazing tool with plenty of opportunities.

In the era of technology, machine learning is expected to become a massive benefit for eCommerce companies trying to simplify many of their most resource-intensive and expensive manual processes to obtain valuable feedback from their customers and, most importantly, to produce clicks, sales, repeat purchases, and positive reviews. It tests and adapts, using various scenarios and data to determine slowly the best way to reach the customers.

Machine learning is one possible catalyst that will drive some e-commerce companies into the technology arena further than they initially expected, while also improving their profitability.

Making your potential a reality will ultimately come down to selecting the right technology and the right partner or team. And it’s clear that machine learning will significantly improve your business.

The aim of artificial intelligence in eCommerce is to make the users have a more enjoyable and more effective experience with multiple machine learning algorithms.

eCommerce is an area where machine learning technologies lead directly to the success of the user experience and business growth.

Are you ready to implement machine learning in your online business and to stay ahead of the competition? Let’s get in touch!

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