There are currently no items in your cart
How AI-driven Product Recommendations Are Driving Ecommerce In 2021
Not using machine learning to create hyper-personalised product recommendations? You’re missing out. Adobe explains how to get started.
Did you know Amazon’s personalised recommendations account for 35 percent of their revenues?
But Amazon isn’t the only one: modern e-commerce stores offer some form of a personalised experience. In fact, the one-to-one strategy of delivering personalised content and recommendations is driving today’s intelligent commerce.
If your e-commerce store still isn’t using AI-powered product recommendation engines, you may be losing out on sales.
Read on to learn how machine learning can help you speed up the buying process and how to get started today.
What Are AI-Powered Product Recommendations?
Visit Amazon, and you’ll see a list of highly-rated recommendations or “also bought” recommendations. Amazon is using machine learning to provide you with products you might like based on your browsing activity and customer details.
But they’re not the only ones. Take Netflix or Spotify, for instance—they use similar tactics to make the customer experience more rewarding. (Let’s blame machine learning for the reason you’re binge watching Netflix or listening to Taylor Swift on an endless loop.)
To create a customised shopping experience, brands need to use machine learning and artificial intelligence to determine what products their customers want. This allows the customer to shop without having to spend time browsing endlessly.
Recommendations also tend to be hyper-targeted, which means that the audience can be a single individual or a small cluster of like-minded customers.
You can try to do this manually, but if you’re dealing with a massive product catalogue, you may find that your recommendations can quickly become imprecise and irrelevant. And if you have over a thousand SKUs in your system, it will be impractical and almost impossible to keep up.
For this reason, many companies have turned to AI-powered product recommendation engines to help increase their sales and reduce cart abandonment rates.
3 Benefits You Can Get from Product Recommendation Engines
Product recommendations result in a lot of benefits for your business. These benefits, however, go beyond sales and revenue.
- Shoppers who engage with a recommended product online have a 70% higher conversion rate, which means they are more likely to buy a particular recommended product during that specific session.
- Though some shoppers click on a recommended product but decide against buying it, they are 20% more likely to return to your site another time.
- Overall, product recommendations account for about 31% of total e-commerce revenues.
Online shopping is changing today’s landscape. In fact, researchers estimate that there will be over two billion people shopping online by the end of 2021. Whilst not every visit will turn into a sale, product recommendations are one of the many strategies that can give you that competitive edge.
How To Get Started With Product Recommendations
Product recommendation engines will help you to create a conversion-focused strategy for your e-commerce store. And with the right AI engine provider, the investment will pay for itself.
In today’s world, it’s not enough to just have a website—you need to give shoppers a personalised experience. With more and more companies embracing AI and machine learning for recommendation engines, don’t let your company fall behind.
Learn how recommendation engines work, what to look for in a product recommendation engine, and how to tell if it’s working for your business by downloading our FREE ebook The Rise of Intelligent Commerce.
You’ll get a quick snapshot of the different technologies involved and figure out if it is right for you and your business.