Have you ever wondered how Facebook shows us ads that are in line with our recent likes or searches? How does YouTube display ads related to our recent internet searches? In this era, we already know that marketing trends are such that, ads and promotions are customized to the needs and preferences of the end customers. Industries have become highly customer centric and are devising strategies to make their products to be in sync with their customers’ life style and interests.
Machine Learning is the most trending topic after predictive analytics and big data. What is machine learning? ‘Machine learning is a type of AI that provides computers with the ability to learn without being explicitly programmed.’ Actually, ML goes hand in hand with big data analytics. IDC (International Data Corporation) had already estimated that “banks will spend US$17 billion in big data and business analytics solutions in 2016.”
From massive data, ML actually studies and makes patterns that are meaningful. With this, it learns and understands the trends from past data and gives us relevant results. For instance, when we type in a Google search term, we see the prompters and auto fills for the search keywords. How is this even possible? With millions of searches every day, how does Google know what we are looking for with just a few search terms that are typed in? Many times, when we mistype a search term, Google cross references this with similar ‘typos’ in the past and gives us the correct search terms.
All of these are because of ML and big data analytics. Search engines like Google and other big streaming services like Netflix have their own analytics engines that study millions of users’ behaviour and engagement information to know what items are most viewed or what image is most searched and provides results based on that. Amazon is another example of how it tries to sell products that are based on the customers’ past searches and purchases. Facebook claims that – “it processes 2.5 billion pieces of content and over 500 terabytes of data every day. In addition, it collects an average of 2.7 billion “Likes” and 300 million photos a day. Every hour, Facebook scans more than 200 terabytes of data.” This is just one company we are talking about.
ML is a huge enhancement to big data analytics. ‘Smart machines will become an integral part of business and daily life creating insight from data in ways that, humans on their own could never do’ – Machine Learning: The real business intelligence. ML is starting to simplify user interaction with machines to the extent that there is a virtual person that has the ability to think, solve problems and give apt solutions based on historic data.
Experts of various financial institutions (FI) are developing solutions that have the ability to interact with potential customers and suggest various products and services based on buyer personas (like their income, financial goals, spending patterns and life style). For instance, a wealth management app can have an analytics engine that could track and study the patterns of the past investments of a customer and suggest various portfolio options for the user. This is just the tip of the iceberg.
At Market Simplified, we are already in this journey of designing our solutions with all of these product embellishments. When solutions are designed with such enhancements, customers would surely be delighted. Millennial customers want minimal physical interaction with their FIs. They needn’t go to the FI in person or painstakingly call a customer service help line number only to hear an automated message and wait till the ‘end of time’ before an actual executive tends to them. ML would enable FIs to run the entire financial operations with least human intervention. It is just a matter of time!References: Tim Cole’s – Big Data is Dead: Long Live Predictive Analysis; Kai Goerlich – Machine Learning: The Real Business Intelligence; Fintech Innovation – Banks lead big data analytics spend through 2020; Market Simplified – How important is it to know your customers. About Market Simplified: Market Simplified is a thought leader in revolutionizing and digitizing products for financial institutions by continuously innovating and simplifying finance. We empower our customers with cutting edge digital experience that is highly personalized and enhanced for the end users with our ‘Experience Engineering’ platform driven by Analytics, AI, Machine Learning and Blockchain technologies. Our clientele includes industry leaders like OptionsXpress (Charles Schwab), Currenex (State Street), MB Trading, Maybank Kim Eng, Kotak Mahindra Bank, National Stock Exchange of India and many others across the globe. About the author: Venkat Rangan is the Founder and CEO of Market Simplified Inc. He is a technology enthusiast. Venkat also has great interest in aviation and loves to read and learn about airplanes. Whenever he gets time, he likes to fly the Cessna Sky Hawk 172. His dream is to fly the Gulf Stream G650. Sometimes it makes us wonder – why he isn’t a pilot or running an airline business…