In today’s world, shopping has become a very personalized experience. From getting personal perks to recommendations based on preference to recommended products and items that are specially curated for individual shoppers- they’ve got it all covered.
What Are The Algorithms Used In Ecommerce?
This very user-centric approach is made possible by artificial intelligence. eCommerce websites make use of algorithms guided by artificial intelligence that help them understand their customer preference in real-time and make recommendations based on that.
Collaborative Filtering Technique
One of the most popular algorithms used by eCommerce websites to make recommendations to their customers is the Collaborative filtering technique. In this method, the recommendation relies on user-to-user preference. The method works by measuring the customer’s average product rating. The basic idea for this type of algorithm is that customers with similar tastes, purchases, and preferences might want to use the same types of products in the future.
This recommendation algorithm uses two main ways in which gauges the customer’s interest-
- They use the traditional rating method where in a customer rates a purchased product and the product is ranked based on the rating. If it is highly rated then it will not be recommended to them again nor will it be recommended to other customers matching their profiles.
- The website offers options of rating various different products on the website or via mail and the customer would rate them based on their preference- this will automatically place the chosen item over the others. Without a purchase, the eCommerce website is trying to identify the interests of the customers.
This algorithm is a type of content-based recommendation system that tries to match a user’s likes and interests to that of a similar user profile and make recommendations according to that. The algorithm collects data and makes use of them to track similarities, patterns, and surfing behaviors of buyers and potential customers. The algorithm can either use Artificial intelligence, machine learning, or deep learning. Each technique has a way to sense, act, adapt learn and gather data for these eCommerce websites. The algorithm can gradually calculate the likes and dislikes, understand their wants, and recommend products accordingly.
Some of the most popular and effective algorithms that help in Collaborative filtering techniques are-
- Bayesian method
- pageRank Algorithm
- Neural Networks, LSTM
These algorithms significantly improve the footfall of the website traffic thereby making a consistent improvement in their sales as well. These algorithms work to show the website what a potential customer would like, what their personal preferences are, and recommend products based on their liking. The algorithm helps websites and companies to increase their customer base by providing them a very customized and personalized shopping experience. They also help to keep track of the popular products, best sellers, and highest-rated products – all providing a good business insight that go a long way in their growth. Algorithms are one of the greatest contributions of technology and it is a great asset to the eCommerce business world.