The CMO Who's Broking Big with Data

We are seeing a 400 percent growth year on year in our mobile traffic, says Gagan Singla, CMO, Angel Broking

Being one of the oldest stock brokerage firms in India can be both a boon and a bane.


A boon for having acquired the loyalty and trust that most online brands can’t. But that’s also a bane if you haven’t transformed with changing time.


Not Angel Broking. The firm has an offline and online presence. It has offices in over 900 Indian cities, 8500 plus sub broker networks, and manages over one million clients. To stay ahead of competition, the company deployed a mobile app few years ago and now investing in a machine learning based engine for its customers. We spoke to Gagan Singla, CMO and Chief Data Scientist at Angel Broking, to understand his data and digital vision for the brokerage firm.


Considering you're one of the oldest stock brokerage firms in India, how do you think technology has transformed the brokerage business in India? Can you explain with an example?


The technology transformation has seen a rather diverse growth path in different industries. In the brokerage business, this transformation has been recent. The last three years has seen the adoption of mobile grow significantly. Today our customers want to see a lot of data before they take a call on what they sell or buy. The times are such that our new customers prefer opening an account online rather than meet in person. We haven’t necessarily pushed our customers to use the mobile app, but they are increasingly using it to keep themselves on top of every market movement. In fact, we are seeing a 400 percent growth year on year in our mobile traffic.


What are your most critical responsibilities as the CMO of Angel Broking?


I’m lucky to wear two hats; one of a chief data scientist and the other of a chief marketing officer at Angel Broking.  I’m also in charge of driving internal digital adoption. Our company has a 29-year old legacy and therefore, our focus is to entirely overhaul our business process and functions with an unrelenting customer focus.

However, there are four key aspects of my role at Angel Broking.  They are data, marketing, product and technology. My job is to make sure that our products and marketing remain tightly coupled. We leverage data and technology in whatever we do. Our entire approach has to be entrepreneurial in nature.


So can we call you the in-house marketing and data specialist?


(chuckles) There’s no doubt that data has become increasingly important to the role of marketers. It can be used in conjunction with a series of digital channels to create personalized surveys, generate recommendations in order to give consistent results in business for the benefit of our customers.  Therefore, collating high-quality accurate data is an imperative for us.  


Data is one of the most important elements in supporting the entire trading ecosystem. What are the three most critical things data is helping you achieve today in brokerage business?


We have a very entrepreneurial approach to data. Whether its customer data, trade data or even the data traffic on our website, the world has come to a point where there are multiple versions of truth and we look at each version in the context of what we are looking for. Therefore, I believe there can be multiple owners of data. However, each one of them must know how to read this data and use it for to make business decisions and drive growth.


How according to you are the two roles (data and digital) connected to each other especially at Angel Broking? 


Angel Broking has heavily invested in digital transformation in last two years. We have also built an internal team of technology experts which consists of data scientists, programmers, developers and talent from e-commerce start-ups.  In my opinion, digital is all-pervasive kind of an ecosystem. It is a feeling and a way of working. While I maybe the facilitator, everyone in the firm has to adopt digital. The CEO has to lead the digital initiative in an organization. As far as connecting the two is concerned, in August this year, we successfully built and launched ARQ, a machine learning based, intelligent and predictive investment engine in order to provide personalized investment advice to retail investors, insights on mutual funds and stocks. We built the entire engine in house with the help of a team comprising 200 techies including data scientists, developers, programmers and e-commerce specialists. ARQ processes a massive amount of data to recommend investment strategy out of billions of possible combinations. 

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