In the present era, shopping is an irrefutable need of people. If you will conduct a study regarding shopping, you will find the maximum percentage of people loves shopping. However, there is drastic change in way people do shopping. In earlier times, vendors knew about the preferences and needs of customer to make recommendation based on past purchases. In this way, vendor wins the brand loyalty which increase their profitability and sales.
With the advent of technology, online shopping replaces the traditional shopping. Now a king’s size of people shop online rather than going in shops, malls etc. Additionally, recommendations are made by smart recommendation system which is based on AI algorithm.
Apart from this, you can also think this an intelligent salesman who knows customer preference, needs, style and taste to make smart decision about recommendation right things to people. Further, right recommendation increases the conversion and sales which leads to huge profit for some brand.
Let’s see what are recommendation system and how does they work?
What are Recommendation Systems?
There is basic definition for recommendation systems is “These are generally information filtering system that filter out the important and relevant information from a enormous amount of dynamically generated information based on user’s past preferences, purchases, interests or behavior”.
Apart from this, it is one of the major concepts of Artificial Intelligence which has made great advancement in technology.
A Recommendation system can also be consider as target marketing tool for online business especially for E-commerce platform. For example, In Facebook, there is an option “People You May Know” used to recommend people base on mutual friends or other things as well. In Google, you can see “Visually Similar Images” and In Amazon which is one of most popular e-commerce store shows recommendation in “Customer who bought this item also bought. There are various Artificial Intelligence based software companies.
How does Recommendation System Works?
Recommendation systems are based on AI algorithm which has the ability to learn and predict most preferred or liked product for user. A typical recommendation system is very intelligent that can work smartly in a dynamic environment. They generally used to past data to see which products are most preferred, purchased or liked by the customers. Artificial Intelligence service offerings various services for machine learning, deep learning technologies.
Data Filtration is the most important phase for recommendation system. Here data is got filtered out for making right recommendation. There are various algorithms used for data filtration or we can say recommending data as well. In this article we will discuss about Content-Based Recommendation System:
Content based Filtering is based on keywords used by user for describing preferences, items etc. Basically, this filters out the items or products that have similar characteristics to what user liked or viewed previously. There are various companies working on artificial intelligence in India.
Content-based filtering is using the technique to analyze a set of documents and descriptions of items previously rated by a user, and then build a profile or model of the users interests based on the features of those rated items. Using the profile, the recommender system can filter out the suggestions that would fit for the user. Let’s elaborate it in a simple way, whenever we try to watch some movies on Netflix, searching clothes online, blogs, watching videos on YouTube, you will get message like this
- Recommended for you
- You will also like this
- Frequently bought item
- Product related to this item.
Thus, there are number of messages that will be shown to you but they all have the same meaning at the end. They are just recommending you to choose an item. And that’s because this convoluted systems have a profile of the users, and they know what kind of items they tend to consume. They just try to come up with items you will more probably like, instead of the most popular, or just a random set of items that might not be of your taste. AI vendors put great efforts to make this system comfortable.
In the nutshell, we can say that a lot of money has been put by the E-commerce’s, such as Amazon or EBay in US in recommendation system. Basically their main aim is to woo users to buy more things. Therefore, they are building great teams to improve the accuracy of their recommender.