This is a guest post by Derek Miller, a digital marketing expert with a background in content, SEO, PR, email and social media marketing, who works for CopyPress.
Data analysis is one of the most important things an e-commerce company can use to boost its sales.
Most marketing companies use various types of data to determine things like how many products your store can expect to sell next month, whether a certain customer will return, and why some visitors leave your site without buying any products or services.
These are still crucial aspects of optimizing e-commerce stores, but the right type of machine learning could improve site performance on the fly.
Machine learning works especially well at recommending products to customers.
If customer A buys one item that customer B bought, then it makes sense for the website to ask customer A if he or she would like to buy the other products that customer B got.
Product recommendation doesn’t stay that simple for long. The more information it has about shopping habits and customer interests, the more accurately it can predict items that a specific person will want to buy. Obviously, this has enormous potential for growing your e-commerce site’s sales.
Machine learning is a relative newcomer to the behavior analysis game. Learn more about other behavior analysis tools by visiting this infographic made by CopyPress.
No matter the size of your marketing budget, one of the options mentioned in the infographic will help improve your site’s performance without forcing you to spend too much money.