A Look At An Ecommerce Recommendation Engine And How It Functions

What Is An Ecommerce Recommendation Engine And How Exactly Does It Work?


You may have heard of the term ecommerce recommendation engine before, but are probably not sure what it means and how it functions. Major online retailers such as Amazon and eBay use eCommerce recommendation engines on their websites. It is also likely that you have seen ecommerce recommendation engines at work while browsing online retail sites without even noticing it or knowing about it.


Ecommerce recommendation engines work in two primary ways. The first way is through what is called collaborative filtering. This is when you will be given suggestions of products to buy on a site based on the purchasing habits of another customer that has a similar profile to you. For example, maybe that customer is a similar age, gender, income level, location etc. The recommendation engine will show products that the other “similar” customer has bought in a suggestion box often found at the bottom or side of the shopping page.


The other way that ecommerce recommendation engines function is through what is called content filtering. This is when the engine suggests products you may like based on previous products you purchased or have looked at. So, for example, if you bought Levy jeans in the past, you will be shown additional Levy brand items based on your past purchase and browser history.


The Benefits Of Ecommerce Recommendation Engines To Businesses


There are many benefits to ecommerce recommendation engines, especially to online retailers to whom this technology is targeted at. It offers online retailers the opportunity to cross sell other related or similar products. For example, the engine can suggest a skirt to compliment a shirt that a woman has bought. This provides an excellent way to boost sales through cross selling.


Ecommerce recommendation engines have been found to increase sales significantly. This is because recommendation engines have a high rate of being able to show products that a customer would be interested in buying. Thanks to advances in machine learning and deep learning, ecommerce recommendation engines are becoming more powerful and accurate. They can be made to function based on individual user shopping history instead of an aggregated base of information or a similar customer.


The recommendation engine is a great tool for ecommerce businesses and online retailers to use to increase sales and conversions. A different form of recommendation engines exists on other online platforms such as Facebook and YouTube. The people you may know suggestion and videos you may like are recommendation engines at work in the social media sphere. It is also expected that recommendation engines will continue to be used more often by more businesses and online platforms in the future.