Lately, targeted ads have got more accurate than ever before, thanks to easy availability of data from our search preferences, visited websites and public information available via social media and other channels. Banks and financial institutions are not too far behind and are using customer data to be one step ahead.
To cite a recent example, a friend who was interested to buy a car filled in a form (on paper in one of the company’s showroom) for a test drive. The friend mentions that she did not google any car information or lookup related websites; neither did she post anything relevant about it anywhere. However, just minutes after she had a call from the car company to confirm the time and date for the test drive, she got a call from her bank asking if she was interested in a car loan. The timing and the speed with which her information was out took her by surprise.
Enterprises today mine customer data to ensure maximum success by targeting their products and solutions to the right audience. Let us have a look at how Big Data and Customer Analytics are helping businesses use their customer data for maximum benefits.
How does Big Data fit into customer analytics?
Big Data is a cluster of extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions[1]. What the definition clearly mentions is that Big Data is not just related to storage and security of large data, it also includes the managing, handling, and analyzing these large data sets to gain valuable insights.
Today, organizations have tons of customer data which needs to be properly mined to help give their business an edge over its competitors. However, without the proper tools to accurately make sense of this data, organizations are lost and can make the wrong choices. This is where Big Data comes into the picture. To help businesses make key decisions based on the data from customer behavior, customer analytics is being implemented in almost all departments.
Big Data can not only handle large amounts of data, but with the power of Big Data Analytics, enterprises gain the ability to convert raw data into visual representations that can help to make it easier to trace patterns, understand trends and make associations in a concise and precise manner. Thus, Big Data gives businesses an edge in storage, analytics, mining and security of data.
Why do banks analyze customer data?
According to IBM’s Global Industry Leader in Banking and Financial Markets Likhit Wagle, “Although 80% of CEOs believe they offer customers superior services, only 8% of their customers agree.”[2] This statement just goes on to showcase how much more banks and financial institutions need to be doing to keep their customers happy.
Banks are dealing with huge amounts of data that surge in through disparate sources and which are stored in different formats. Analysis of this data is important in AML detection, but the same process can also help banks understand their customer’s needs to help give better services. Using Big Data to analyze a customer’s spending habits, banks can give fraud alerts to its customer using phone calls from credit card issuers about an unusual purchase. Banks can also use the same data to target particular privileges and added features that a card provides to the customer after understanding how and where the customer spends.
Banks can use customer data for[3]:
- Target Marketing: Identify potential clients for their products and services using data from various channels.
- Customer Services: Improve services to current customers by segregating them based on geographical locations, technology, transaction analysis, etc.
- Decision Making: Customer data is taken into consideration to help banks create suitable services, loan options, products, insurance options, etc. to cater to the needs and requirements of its customers.
The nation’s four large universal banks (JP Morgan Chase, Bank of America, Citigroup, and Wells Fargo & Co.) are using Big Data to harness the power of customer analytics and are using it in various other domains to extract insights that can help give them a competitive edge[4]. Even Cleveland-based KeyBank has moved to making data driven decisions using Big Data[5]. Banks and financial institutions are understanding the advantages of using Big Data technology and have started or have in place plans to implement Big Data and Analytics based solutions to get to know their customers better. According to IDC, the banking sector in the US spent $1.8 billion in 2014 on Big Data[6].
Why Hexanika?
HEXANIKA is a FinTech big data software company which has developed an end-to-end solution for financial institutions to address data sourcing and reporting challenges for regulatory compliance. Hexanika’s solution improves data quality, keeps regulatory reporting in harmony with the dynamic regulatory requirements and keeps pace with the new developments and latest regulatory updates.
To know about Hexanika’s Big Data Analytics benefits, see: https://hexanika.com/big-data-analytics/
Contributor: Vedvrat Shikarpur
Image: geralt
[1] Google Search: What is Big Data?
[2] Forbes: How Big Data Helps Banks Personalize Customer Service
[3] Nerdwallet: Banks Mine Big Data to Get to Know You Better, and Better
[4] The Wall Street Journal: Banks Using Big Data to Discover ‘New Silk Roads’
[5] Forbes: KeyBank Moves To Data Driven Decision Making
[6] CIO: IDC says big data spending to hit $48.6 billion in 2019
1 Comment. Leave new
I didn’t realize that customer analytics were so important. It’s cool that they can be implemented into any and every department. Owning a business can be such a big deal, and it can be hard to stay organized. My husband has wanted to start his own business for the longest time. Customer analytics is definitely something we need to learn more about before he does that!