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The Three V’s To Analyze Customer Behavior: A BFSI perspective

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srinivasan-govindanrajulu

Customer experiences when utilized in product and services, can result in customer delight. To understand customer preferences and taste, marketers may leverage from the power of Big Data. An example is the case of a diabetic walking into a pizza store, and being served sugar-free beverages while he orders his coke.

A classic area where big data is heavily used, but information is very nascently available is Indian Banking and Financial sectors. Indian Banks have been employing legacy technologies to manage data analysis, and a very small chunk looking at adopting alternate technologies to monetize the huge volume and variety of data available. On the other hand on an average, a bank uses more than 5 different technologies to analyze data today, which reflects a lack of awareness towards technological cohesion in an enterprise.

In a conversation with CSAT360, Srinivasan Govindanrajulu, Senior Director and Practice Head- Enterprise Information Management, Virtusa Corporation, opines the challenges, the opportunities and the factors that govern the usage of Big Data in BFSI sector.

Here are the excerpts:

CS3: What are the potential large case use scenarios of Big Data solutions in BFSI industry?

Banking companies should identify the processes that most directly interact with customers, followed by strategy to enhance costumer experience at touch points. For Most banking companies, this will mean start with customer analytics that enable better service to customers. Banks could use these insights to generate sales leads, enhance products, take advantage of new channels and technologies, adjust pricing and improve customer satisfaction.

Adding social analytics as an additional source of valuable insight can boost revenue, and help increased ROI. By accurately predicting products that appeal to micro segments, banks can also successfully optimize cross-sell/up-sell. By collecting and analyzing all of the data that banks have available about their customers, they can then group those customers into different segments based on their expectations and banking needs.

CS3: How Can Big Data drive customer behavior?

Big data is being generated from various sources such as social media, sensors, digital photos, videos, stock trading across industries, financial transactions and telephone calls.

The basic challenge that Big Data presents for many organizations is its unstructured nature, high volume, variety of sources and speed at which it is produced. While traditional data sets have some of these characteristics, the complexity and scale of Big Data makes it much harder to process, organize and store in a cohesive manner that makes it easy to analyze. This has all been aptly captured as the three V’s of Big Data (Volume, Velocity and Variety).

CS3: Has the term lost its touch in the over 2 decades of its existence?

Much of the insights needed for understanding customers, markets, products, promotions and sales lies in the correlation and analysis of that data. Historically, a lot of this analysis would happen in the back office and typically be produced as monthly reports for executives to analyze and react to. But the feeling is changing.

With the emergence of Social Media, Cloud and Mobility Big data and its importance to ensuring customer satisfaction is growing. Big Data today is being used effectively for data crunching to gain operational efficiency. Customers are also seeking analysis solutions for social media data to help with their businesses.

Customers these days with the prolific use of social medium and digital media, leave digital footprints that can be captured. This data gives insights on individual activities that can be gathered to generate meaningful insights.

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