Machine learning is turbocharging the capabilities of e-commerce apps. In this article, we explore five apps powered by machine learning that can help you get the edge you need to thrive.

Artificial intelligence (AI) used to be the stuff of dreams and sci-fi movies. Now, it’s real life — and it’s taking e-commerce stores to new heights. 

Machine learning (ML) is an application of AI that’s fully disrupting the e-commerce industry. A self-learning system that learns about the customer and the fundamentals that make them who they are, it looks beyond mere generalizations and characteristics. It delves deeper, helping you create more detailed buyer personas that allow you to make the shopping experience more unique to each individual. 

Machine learning is already helping e-commerce companies take their business to the next level. In fact, Servion predicts that by 2025 AI will power 95% of all customer interactions. Customers will get to see more of what they want and less of what they don’t want in their digital experiences, which means increased conversions and customer loyalty. 

In this article we’ll dive into some of the many ways machine learning can unleash your brand’s full earning potential — and some of the third-party apps on the market you can leverage to stay ahead.

1. Retarget to Boost Your Conversion Rates 

Not every user who browses an e-commerce store will follow through with a purchase. Heck, not even every user who adds a product to their basket will follow through and buy. 

So what happens next? Do you just let these customers get away? 

In the past, that’s exactly what would happen. But now, machine learning can swoop in to help brands retarget those users. ML can analyze past data that demonstrates how a merchant previously converted users with similar browsing habits, and use this information to determine what will convert new users. It might suggest a time-bound discount or an Instagram ad, for example.

Which app can help you retarget and convert with ease?

Criteo is a dynamic retargeting app that’s constantly monitoring the habits of 1.4 billion shoppers every month. Using machine learning, it knows a thing or two about what customers want, and what will bring them back into the game. 

It leverages personalized ads to retarget customers who ‘got away’ and recommends both previously browsed products and those they haven’t looked at yet, straight from your catalog. The ultimate aim is to drive more sales via personalized ads delivered at the right location, in the right format and in real-time throughout the customer’s journey. 

2. Deliver Hyper-Personalized Product Recommendations 

A recommendation engine charged with machine learning — it’s pretty damn powerful. This technology can take information from past user behavior analytics and use it as training data to learn the different trends and patterns.

After analyzing the data records, it will have a clearer picture of how a user will browse a website, as well as the products they’ll be interested in. The more accurate and personalized suggestions the recommendation engine is able to serve up, the more successful it will be at driving sales.  

Which app can help you deliver smart product recommendations?

Feature-rich Nosto is powered by machine learning algorithms and statistical techniques, enabling it to predict and automatically deliver the most relevant, personalized product recommendations. Its product recommendation engine predicts and suggests the most relevant shopping experience based on data it has collected and analyzed. 

3. Create and Execute the Right Product Pricing Strategy

Price setting is a continual conundrum for many online merchants. Pricing is crucial in e-commerce — it’s how we stay competitive in our market. In fact, 65% of shoppers look up price comparisons on their mobile device while in a physical store.

Machine learning algorithms can now help you hit the right note with your product pricing, first time. Intelligent systems are able to monitor how markets are currently performing, as well as data from your customers’ behavior, to help you set optimal pricing. After that, using predictive analytics, ML makes it easier for you to adjust your prices accurately. 

Which app can help you get your pricing right?

Prisync allows you to track pricing movements in your market and the prices set by your competitors, so you can adapt your own accordingly. Its machine learning to let you change your prices dynamically according to your target profit margins and costs.  

It’s easy to install and use — you just need to pick the products you want to import to the app, add your rivals’ URLs for each product one by one or in bulk. In seconds, the results will start flooding in and ML takes care of the rest. 

4. Spot Fraudulent Orders Before They Happen

The risk of fraud has escalated now the digital age is in full swing, with people reporting losing $1.48 billion to fraud last year. 

E-commerce brands are particularly vulnerable to fraudulent activities like credit card fraud, refund fraud and phishing and need to take action to protect their shoppers. 

Machine learning comes to the rescue here. ML can analyze repetitive data to detect if an attempted activity is suspicious, or if it’s a characteristic of that particular user. ML can constantly collect and analyze customer data, making it possible to respond to threats in real-time. 

Which app can help you prevent fraud?

Ravelin is a global fraud prevention app that uses sophisticated ML technology to help brands stop potential fraud threats before they happen. Ravelin can give you a clear risk score for every single customer who enters your website. It also allows you to customize your solution to create tailor-made models to better identify fraud patterns that are unique to your business.

5. Optimize On-Site Search for Increased Sales

74% of online shoppers rate product selection as important during the online search process. As such, making sure a customer finds exactly what they’ve come to your store for is essential to providing a quality customer experience and driving conversions. 

If you’ve got a particularly large product catalog, machine learning is your friend. It creates smarter searches by understanding both the customer’s intent, and long search terms. Moreover, it ranks search results based on search history and behaviors and returns a wider range of results to each query. 

Which app can help you implement optimized on-site search?

Klevu’s on-site search helps you provide your customers with more accurate search results so that they find what they’re looking for without any hassle. No more huffing, frustration, or looking elsewhere. 

Klevu leverages machine learning to enable merchants to display personalized, relevant recommendations to the shopper within search. Thanks to ML, search results become increasingly personalized as shoppers spend more time on your store. And by connecting your visitors to the most relevant products, you’ll encourage long-term customer loyalty. 

Don’t Waste Time, Adopt Now 

Apps powered by machine learning technology are redefining retail and sales like never before. But why adopt ML now if your brand has so far succeeded without it? ML makes it possible to analyze and learn about millions of interactions so that you can personalize the shopping experience at every touchpoint in the customer journey. In the past, this was something brands could only dream of. The time to adopt is now. 
To find out more about Klevu’s smart on-site search solution that’s powered by machine learning, schedule a live demo.