Introduction
An impressive branch of Artificial Intelligence, Machine Learning is advancing moreover simplifying the complex operations of the eCommerce world.
As we all know Machine Learning (ML) has brought a very innovative turn to fourfold the revenue of the e-commerce industry.
Moreover, the prime purpose of machine learning technology is to build algorithms that can get input data and set statistical analysis to predict the adequate output value.
So, in this article, we will discuss ML Applications and how machine learning is helping in creating better technology to power today’s business plans. Therefore, ML is a transformation that ultimately benefits both sides of the marketplace.
How machine learning can benefit to eCommerce business?
Makes Data Actionable
Data is the prime source in the fast forward eCommerce industry to stay and shine. Smart and appropriate utilization of data is turning online retailers into a stable industrialist. The machine learning approach is making the data actionable for the specified purpose.
Predicts Customers Behavior
Machine learning facilitates the merchants to reach target buyers, analyze their activities and interactions to predict what shoppers will need and do next in order to optimize offers. Henceforth, machine learning observes and predicts the prospect’s future requirements.
Develops Brand Engagement
ML approach facilitates the online merchants to execute the right action at the right time, on the right channel. The more data the better the analysis of machine learning technology to engage shoppers in more meaningful ways.
Agility and balance are essential to engage with customers whenever, wherever they are and it is not possible with human efforts. Enroll machine learning technologies, that can act on data with swiftness and accuracy.
Machine Learning Boosts Sales
Machine learning algorithms can handle key pricing variables, such as seasonality, supply, and demand. This feature benefits the eCommerce merchant to boost sales with the ability to offer the right price at the right time.
Even it accommodates the merchant to track with specific targets, such as maximum profit or revenue optimization. Machine learning technology additionally excludes the usually deleterious impact of human mistake or bias.
Through effective pricing standards implicated by huge data sets, merchants can more correctly set amounts that fulfill all their purposes in a fast and expeditious way with accuracy as well.
Personalized Product Recommendations
The most complex process for store owners is to serve products and services to the customer based on their tastes, preferences, and choices. It’s a difficult task and extreme touch for the merchants with a huge customer base.
That’s why the Personalised Recommendation System is in trend for store customers observed using machine learning technology. Personalization enables to increase customer retention through more appropriate and tailored experiences.
Machine learning algorithms can generate personalized suggestions for best-suited items, instead of promoting outcast items.
Top 7 machine learning extensions helpful for eCommerce merchants
Machine Learning (ML) is reforming the e-commerce trade, improving industries use Big Data to automate operations moreover flatter the customer experience to the next level.
Thus, check below drafted Webkul’s Award-Winning Innovative tools and mobile apps that use complex Machine Learning algorithms and AI (Artificial Intelligence) technologies:
Enhanced Web Store Search Engine
Elasticsearch is a highly scalable open-source full-text search and analytics engine. So, advance the eCommerce store with the Magento 2 Elasticsearch engine.
Additionally, it allows you to store, search, and analyze big volumes of data quickly and in near real-time. Henceforth, it is generally used as the underlying engine/technology that powers applications that have complex search features and requirements.
Amazon Personalize Service
The extension integrates Amazon Personalize service into Magento online store to provide real-time personalization and machine learning recommendation.
With this, every customer will have a unique experience on the web store and will view products based on personalized data.
Virtual Try On
Provide your customers to try products in a virtual environment. On the frontend, the customer just needs to upload an image using a camera or can browse it from files.
Facebook Chatbot
Add message template for salutation, not found, greeting, product search, and provide instant replies to customers using Facebook Chatbot.
Facebook Chatbot is a program developed for the Facebook Messenger platform. It allows businesses to do automated communication with their customers.
The chatbot can send and receive messages from the users. Consequently, with the help of this extension, you can set up Facebook Chatbot for your customers.
Image Recognition Based Products Tags
Image Recognition Based Products Tags for Magento 2 module allows the admin to generate the related tags for the products by analyzing the product image.
Thus module uses the AWS Rekognition APIs to analyze the nature of the image. The tags are clickable and visible to the customer in category pages and product pages.
Product Search Via Image
Save the time of your customers by allowing them to search the products by an image of your store. Through machine learning, this module recognizes the image uploaded by the customer.
Furthermore displays keywords related to the image by clicking on which the related search results get displayed.
Voice Recognition Alexa Integration
Allow the eCommerce store customers to use Amazon’s Alexa voice assistant AI technology to do online shopping, order, and listen to order details. Also, the admin can create the JSON module for the skills and deploy them to the Alexa console.
In case of any clarification or query regarding the machine learning application, kindly email us at support@webkul.com or create your ticket at Webkul UV Desk.