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There is not even a single point of doubt that artificial intelligence (AI) is going to change the world over the next few years. It has already become an integral part of the status quo. AI is graced by almost every industry and sector globally including e-commerce.

Below are some of the examples that explain how we are going to live in the virtue of AI applications to advance our e-commerce business:

Predicting Sales

Machine learning is the supervised form of AI in which the sample data is given which helps to train it and process the data in the future. With more than 200 million products being traded, machine learning algorithms help us to forecast the sales volume based on the historical data of products to a higher degree of accuracy.

Targeting Right Groups

Traditionally, people make use of unsupervised learning algorithms which are segmenting the customer groups for the marketing campaigns. Marketers have defined the segment in such a way that makes sense to them via gender, age, and income. But AI is more on demonstrating that these are not the most efficient approaches rather it is based on more accurate predictor of tastes or interests.

Analyzing Rating and Reviews

Understanding the user reviews and ratings play an important role, but it is also a time-consuming work. By using and applying the structural algorithms of machine learning, a method which is most commonly used in the study of the formation of words(morphology), can efficiently collect and analyze the product reviews with text that is both negative and positive. Apart from this, structural machine learning can also help in mining the valuable information from the reviews and page explanation.

Classifying Products and Categories

Categorizing the products under each classification is a very arduous task. To solve and overcome this problem, a semi-supervised artificial learning algorithm can be used, which resamples the data until the algorithms learn how to process it in the best efficient way.

Improved Customer Experience

With the help of ‘reinforcement’ algorithms, now we are able to process data based on the user reaction with respect to the products they are shown. For example, let’s say, whether the user has clicked on the product when it was shown to them in the search result option or in recommendations. Reinforcement algorithms check how much ‘reward’ (positive response) is obtained when different types of products are displayed in response to different circumstances. With the combination of user’s past reactions at a certain point in time, this algorithm helps to know about the most efficient course of action to take when those circumstances occur again. And, with each reaction and response, this algorithm keeps on refining smartly.

Image Recognition

On the platform of the customer to customer interaction, deep learning techniques can be efficiently and effectively used for image recognition. Inspired by the functions and structure of the deep learning algorithms, one can develop the ability to see and recognize objects in a snap and categorize them automatically, which makes it easier for the users to post the products for sale.

E-commerce may or may not be the first thing which comes to the mind of the people while hearing the words “artificial intelligence” or “machine learning” but there is no denying in it, that it is already on the way we buy and sell online.

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