How Machine Learning is changing the way we live?

Machine Learning (ML) is the technology that gives computer systems the ability to learn without being programmed. Machine learning works by using algorithms that can access data and use it to identify patterns in order to make predictions based on what they already know. The algorithms in machine learning are designed to automatically improve with experience, after exposure to new data. Much inefficiency of traditional business models will be replaced by successful applications of ML technologies. At present, there are vast opportunities for businesses to leverage these technologies but only a handful have successfully created intelligent infrastructures which could result in disruptive strategies across various industries.

Big Data

The application of powerful analytics tools like machine learning is an increasingly important part of any organization’s competitive advantage. And these applications rely on having access to data – lots of it. The volume, variety, and velocity of data are perhaps the defining characteristics of big data. Data that are too big to process with traditional databases or tools is generally referred to as “big.” Big data technologies can help you capture this unstructured information.

Big Data Technologies helps us understand the massive amounts of data being created every day by connected people and things, so we can derive insights more quickly than ever before. A new approach to analytics called “Fast Data” has emerged which accelerates our ability to extract value from massive volumes of disparate sources by up to 100x compared with prior approaches based on market-predictive analytics – previously considered state-of-the-art.

Machine learning algorithms have been an integral part of this sea change in data processing because they are capable of modeling almost any system without being explicitly programmed where to look or what to look for – which is why machine learning is sometimes referred to as “unsupervised” learning.

Digital Analytics

The ability for businesses to derive insights from big data generated by customers can bring enormous competitive advantage. Machine learning combined with digital analytics tools helps companies uncover novel customer insights, at scale, and act on them dynamically according to business goals. It enables professionals across industries to transform the way they engage with customers, enhance customer experience and increase revenue through intuitive decision-making based on a deep understanding of each individual consumer’s behavior. Certain areas in eCommerce that can be revolutionized using machine learning are as follows:

Recommendation Engines: 

Customers expect to find the products they want, when they want them, wherever they are – online or physical store. Using machine learning-based recommendation engines allows companies to provide personalized product recommendations based on customers’ purchase history and other behavioral data.

Personalization across channels   

Email Marketing Automation Campaign Management Customer Service Chatbots & Virtual Assistants Social Media Optimization SEO Tools Other areas where Machine Learning can help the eCommerce industry are Intelligent Search Personalized Product Recommendations Inventory Prediction Fraud Detection Price Optimization Abandoned Cart Prevention Content Curation Display Advertising Creative Testing And many more…               

Only a handful of businesses have successfully created intelligent infrastructures that could result in disruptive strategies across various industries. According to Gartner’s research, by the end of 2018, only about 10% of CIOs will manage ML and DL projects that deliver business value. The risks may be high but so are the benefits – especially in emerging markets where AI-led automation is expected to contribute up to USD 9.1 trillion to the economies by 2025.

Conclusion:

Machine learning is a subset of artificial intelligence that has been in existence for about 4 decades. It can be considered as an element of AI that focuses on the discovery of patterns and relationships from large sets of data. In this article, we gave an overview of what machine learning are, its applications across several industries and the future scope in eCommerce.

This portal provides step-by-step tutorials for machine learning algorithm implementations using the Python programming language. It covers topics like linear regression, logistic regression, recommendation engine, and several other courses related to artificial intelligence concepts.          

Machine Learning is a powerful tool that can be applied to various eCommerce activities such as recommendation engines, product search and personalization based on purchase history. It will not only enhance customer experience but also help in internet fraud detection and price optimization which results in more revenue. As the future is trending towards automation and digitization of every industry, Machine Learning seems like a logical step in this direction, especially with its cost-effectiveness when compared with human labor. Organizations need to evolve with time by adopting new technology trends thereby creating a sustainable competitive advantage in their chosen markets.