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10 Benefits of Machine Learning in E-Commerce

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No matter what types of products you sell, staying competitive in e-commerce requires constant attention across multiple departments. Sales teams need to know product details, marketing teams must be mindful of popular search terms, product teams must stay on top of trends, and IT teams are responsible for making sure the site is always functional and fast. All of this will always require a certain degree of time and skill, but some tasks, especially the most repetitive ones, can be better handled with machine learning. 

Machine learning is a tool you can use to handle the mundane and repetitive tasks that are essential for e-commerce success. One of the many benefits of machine learning is that it allows you to maintain the necessary attention to detail without the intensive labor.

The Problems Machine Learning Can Help You Solve

Machine learning can be used to help you streamline a variety of e-commerce tasks, especially those that include managing unstructured data such as images, videos, and product descriptions. 

Product categorization

Manual categorization can be time-consuming, especially for e-commerce businesses with large product portfolios. Machine learning can be used to automatically categorize new products without having to spend time manually tagging them all individually. It does this by picking up keywords from the product description and categorizing them accordingly. It can also categorize products by identifying attributes in images, so even if you don’t have text yet, your new products can be accurately sorted. 

If you decide to add new categories to your product portfolio, just tell the machine what keywords to look for and it already knows how to find the products that match. This makes it easier to build out your e-commerce site as new product types are introduced. 

Image tagging

Manually tagging thousands of images is taxing work, but it is essential for customers and search engines to find the products you sell. Human errors can also result in confusing experiences for customers and abandoned pages when they don’t see what they expected. Machine learning can be used to tag images with keywords and descriptions, significantly speeding up the process. While scanning the images, the system can also verify image quality, saving yet another step.

Product recommendation

Customers browsing certain products may be interested in others that are either similar or complementary. Product recommendations are a common feature on modern e-commerce sites, and if you don’t have them, you could be missing out on larger revenue per sale. As with image tagging and categorization, the manual process to link products to each other takes a lot of time, but not necessarily a lot of brainpower. Machine learning can do it much faster by associating products with keywords and connecting them to other products. 

Review moderation

Consumers use product reviews to make purchasing decisions, so it’s critical to have quality information on your site. Machine learning can be used to weed out reviews that are offensive and prioritize positive reviews so that they are prominently displayed on the site. Doing this automatically helps ensure that your site is geared toward making sales without compromising the user experience.

Related: Download the checklist that lays out everything you should consider  before implementing a machine learning project or workflow →

The Benefits of Machine Learning for E-Commerce

Machine learning can help you do all of these essential tasks with many positive impacts to your company, such as: 

1. Higher productivity levels and more time available for higher-level tasks

Free up your team’s time with machine learning. Take away the mundane, repetitive tasks that consume a lot of hours and focus on the work that truly requires a human brain. Your team will be more productive—and probably more satisfied with their work.

2. Fewer human errors such as misspelled words and miscategorization

Even the smartest people make mistakes, especially when they’re doing a task that isn’t engaging. Unfortunately, those small errors can have a big impact on your e-commerce site and impact the customer experience. 

3. More accurate image tagging and categorization

Machine learning uses the rules you teach it to tag images and categorize products with a high degree of accuracy. Whether it’s using information from the product description or making decisions based on product photos, you can count on a properly trained machine to deliver accurate results. 

4. Better-quality user-generated content displayed on your site

If your e-commerce site relies on user-generated content such as product reviews or recommendations, you want the highest-quality content to be displayed first. Train the machine to identify content with a minimum word count, a certain number of stars, or other criteria so your customers see the information that is most helpful to them. 

5. More products in shopping carts 

You’re in the e-commerce business to generate revenue, and the more products each individual puts in their cart, the more revenue you can bring in. Displaying complementary or similar items exposes your customers to products they didn’t even know you offered, increasing the chance that they will add them to their carts. 

6. Higher revenue per sale

More products in carts typically means more revenue per sale, which means a bigger bottom line. Acquiring new customers is expensive, and getting repeat sales also requires an investment in marketing resources. While you have customers’ attention and a commitment to purchase, machine learning helps you get the most out of each sale.     

7. Better customer conversion rates 

Attention spans are short these days, and if consumers don’t quickly find what they want on an e-commerce site, they quickly move on. Having accurate image tagging and categorization through machine learning helps keep customers on your site and browsing the products they came to find.   

8. More customers returning to shop again

The modern consumer values convenience. Providing an exceptional shopping experience that includes personalized recommendations and high-quality content will keep your customers coming back whenever they need something your e-commerce site offers. 

9. Fewer product returns

Displaying similar products helps ensure that your customers see all of the options that might be of interest to them so they can choose right the first time. This helps reduce product returns, which saves you time and money. 

10. Greater customer loyalty

Using machine learning to create an exceptional customer experience leads to greater customer loyalty. Consumers like to return to sites that are easy to navigate and consistently produce the results they expect. Devoted customers also like to refer their friends, so the more you can do to boost loyalty, the more you’ll get from your investment. 

Try Machine Learning on Your E-Commerce Site

The most successful e-commerce teams are able to gain additional revenue while keeping employee costs low. Incorporating machine learning into your business strategy is one way to eliminate busywork and repetitive tasks so your team can focus their efforts on other important work. Skyl.ai can help you get all the benefits of machine learning without a major up-front investment, minimal investment in DevOps resources, and with no specialized skills required in-house. If you’re curious and would like to learn more, watch our webinar about how to improve the online shopping experience with machine learning. 

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