comscore Machine Learning is changing the face of businesses today

Machine Learning is changing the face of businesses today

Here's how machine learning is having a positive impact on businesses.


It was not long ago when tablets were the craze, and technology was taken less seriously by businesses. Back then it was a perfect mix between people, technology, and process. Today, we are in an era when technology is improving, and people and process are gradually replaced by it. Also Read - Netflix Streamfest: How to watch all Netflix shows for free this weekend

Although that may not be entirely true. It is actually a paradox since more often than not we introspect how technology has made our lives easier both from an individual and industrial point of view. One of those aspects which has helped build economies and various sectorial businesses is Machine Learning (ML). From automation to analysis of data, the technology has the power to learn without having to be explicitly programmed. Also Read - Free Netflix subscription in India: Here's how to get it for two days

Today, a lot of functions are carried out by computers that directly affect the sales of the businesses. In precise terms, they are led by Machine Learning. For example, a business model like Netflix is based on subscriptions rather than on advertising. In its case, when we are being recommended a set of movies or genres, it is the work of machine learning monitoring our history, tastes and preferences. But how does Machine Learning affect businesses? It is due to ML that Netflix is able to acquire more users and achieve user retention thanks to the personalization of content. This directly affects the user experience, and thereby that of the service which accrues to the customer experience. Also Read - Netflix will be free for everyone in India from Dec 5 - 6: Details here

5-10 years back, the subject of big data was in its infancy. Today, that big data has expanded to an extent where we now have multiple touch points of our data. This is where Machine Learning kicks in, and has its most appropriate use. Now it is safe to assume that a lot of businesses have adopted the technology in terms of automating various functions, and personalizing customer behavior based on algorithms and preferences of customers.

Sure, technology is evolving, but is it growing by itself? The fact is that each segment of technology is symbiotic to its neighboring segments. For example, thanks to the facilities that modern cloud computing offer, machine learning as a technology is able to analyse large heaps of data from the cloud and output a function which the Artificial Intelligence is programmed to perform through a set of principles or algorithms. Back in 1990 when big data was creating a buzz, a commercial cloud service was not available for companies to upload their data, and instead they would be forced to take a trip to a data center to procure servers.

Machine learning is probably going to be the next big thing for investors to bet on. Earlier it was social media and previously the internet shortly after the dot com bubble when the internet blew up, and investors took special interest in companies such as Google, Yahoo, MSN, and the likes. Not to say that the other technologies are irrelevant or not as great, but as I had mentioned earlier, they are symbiotic in nature and the increase in one segment is correlative to the others.

Today, consumers are already consuming space on the cloud at commercial costs. They are utilizing other facilities too such as analytics services in social media, and various financial trading applications. Further, machine learning is also finding its sheen in Healthcare and Automobiles with smart cars and understanding patterns in diseases with the use of data that has been stored in the cloud network.

The most important part of machine learning is that it improves customer experience as it is continuously learning. In retail, it incentivises customer loyalty in understanding the preferable options for consumers and providing personalized alternatives to reinforce sales. This is widely used in marketing and advertising, and has also opened many facets of creative marketing in the industry. This in turn helps retailers understand the buying habits of the customers, and thereby formulate better marketing strategies and predict demand based on these patterns.

Our vision is that a system should exist wherein real-time data is fed to an algorithm that can analyze this data with proper integration of mathematical, and machine learning models so that various scenarios are tested to give insight into various behavioral patterns in businesses and consumers alike. This methodical approach brings a high regard toward the data that customers are providing and the technology that companies are creating.

Further, not only are we looking forward to making a breakthrough with the use of machine learning in the face of business but we are also working toward building a stronger ecosystem for enterprises to interact with the environment through the use of technology. The trajectory on which the world is moving with respect to the evolutionary pace of man and machine, should be magnified and recognized far and wide to pursue the futuristic endeavor.

ML is a concept we must not take for granted, especially in business. Although it may sound scary when we say that jobs are being taken by machines, the reality is that, every department’s goal is to attain efficiency. In Machine Learning, the benefits outweigh the challenges. So we are not talking about a loss in number of jobs. Instead of replacing human resources, ML is putting human talents to better use. Support the futuristic endeavor. Businesses must begin reimagining business processes, and restructuring their operations around these efficiencies to take full advantage of the technology.

The article is written by Anupam Kulkarni, co-Founder of iauro Systems.

For the latest tech news across the world, latest PC and Mobile games, tips & tricks, top-notch gadget reviews of most exciting releases follow BGR India’s Facebook, Twitter, subscribe our YouTube Channel.
  • Published Date: August 3, 2018 1:49 PM IST

Best Sellers