How to Increase eCommerce Conversion Rate with Machine Learning

Are you interrupting your online visitors - or are you leaving them hanging?  Most industries working with large amounts of data have already recognized the value of AI and machine learning technology. 

Optimising ecommerce conversion rate

By using machine learning algorithms to build models that uncover connections and identify important insights in data, companies can make better decisions without human intervention. This means that companies can work more efficiently and gain an advantage over competitors.

Machine learning is used also with AI chatbots to provide a more personalised chatbot experience and provide better service.

Ecommerce websites can also use real-time analytics and machine learning to recommend visitors items they might like based on their buying history – and to promote other items they could be interested in.


And, this ability to utilize the data collected to provide even more personalized shopping experiences (or implement targeted marketing campaigns), is the future of retail. Visit any major eCommerce sites and you may notice that this future is already becoming a reality. 

From a business point of view, real-time analytics and machine learning tools can help you increase your eCommerce conversion rates by allowing you to target your sales efforts better. 

The most important thing to start with is identifying those indecisive visitors who may require some additional information or assistance to build up the confidence to complete their purchase. Thus, when offered the right incentive, they are the ones most likely to convert.



You don't really want to interrupt the buying process of someone who is already giving you money and there's no reason to spend extra effort to those who are not going to convert anyway.

With real-time analytics you can identify those indecisive visitors and show them the right incentive (i.e. action) they need to build up the courage to buy. 

By using machine learning tools and the data collected from your site as well as from your extensive network, you can predict the buying probability of each and every online store visitor, and reduce shopping cart abandonment. 

This information can then be used to categorize visitors in real-time and to decide which kind of actions you want to use to convert these visitors into buyers. An action can be e.g. a discount coupon code, a proactive sales chat, a reminder of an existing trait (e.g. free shipping) or any other action you want to add to your toolbox. Sounds convenient, right?

Want to learn more about how to improve your eCommerce conversion rate? Check out our free guide with 12 tips for your eCommerce strategy. 

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AI , eCommerce