With the fluctuation in the finance industry, the lending environment is rapidly changing for banks, credit unions, and other lending institutions. Historically, banks have been relying on demographic data, including age, education level, gender, race, and geographic location to segment customers. However, the rising younger workforce has rapidly changed this traditional dataset used by banks, pushing them into a new era of customer behavior.

Banks that have adapted to using customer behavior to determine the borrowing habits of their consumers have found new ways to segment customers based on their consumption habits, needs, and preferences. The changing preferences of the young generation, coupled with technological innovations, are paving the way for banks to adopt a strategic approach towards consumer segmentation. Significant drivers are facilitating the transformation of analyzing behavioral data, thus helping lending institutions understand their consumer habits and abilities. These drivers can be categorized into the following areas:

Machine Learning

The rapid adoption of machine learning models enables banks to use predictive analytics to detect patterns within big data. This modern approach gives banks the ability to look at their customer’s historical activities to identify which trends would be of most importance to them as compared to relying on demographic data to predict consumption patterns.

Big data has redefined the banking sector to the point where loan opportunities are identifiable through data analytics. Big data and analytics are helping banks locate and target the right people for financial products by analyzing signals based on life events, behavior, and passive information.

Behavior-based signals are some of the concrete actions that consumers take to indicate that they are ready to purchase new financial products. For instance, transactional data can send signals to the bank that there is a potential customer for a mortgage or a loan to purchase an asset. A consumer’s data builds a profile of predictive signals that banks can utilize to provide different financial products.

Digital Services

The explosion of digital services and products that consumers use daily creates an opportunity for banks to acquire data sources to get a better understanding of their customers’ consumption behaviors. This technique is not new in the US, where companies were reported to have spent $20.2 billion acquiring third-party audience data and activation solutions to support their marketing activities. The banking sector will follow a similar approach to segment customers in ways that yield deeper insights, leading to more effective customer service strategies.

Changing Customer Base

Traditionally, banks and other lending institutions succeeded in demographic segmentation due to the customer classification that existed before the eruption of technology. Generation Z and millennials joining the workforce have transformed the banking sector by being socially aware of the technological advancements, which they use for most of their daily functions, including shopping. It is estimated that 61 million of the millennials will join the workforce by 2022, which is an excellent opportunity for banks to take advantage of the tech-savvy customers to sell their products. Given that the younger lot has little patience for brands that do not demonstrate an understanding of their desires and needs, banks will need to do an in-depth analysis of their consumption patterns to appeal to these consumers based on refined and personalized marketing strategies.

How Banks Can Leverage Buyer Persona

1 – Get A Clear Picture Of The Customer

By understanding customer behavior based on their needs, tastes, and preferences, product managers can utilize this information to acquire a higher customer base for specific products. Understanding website behavior, product interest, social media engagement, and email preferences combined with offline activities such as phone calls can help banks leverage digital technology to create products that appeal to their customer base.

2 – Prioritize Personalization

Today’s consumers demand that brands treat them as individuals through personalized marketing. IT executives in financial institutions can help in classifying data based on customer behavior as a way of helping product managers to develop products for a specific consumer niche. Personalizing each product and consumer can be daunting; hence, with the help of Risk Management Executives, the process can be split into categories to be accomplished in bits.

3 – Create A Seamless Customer Journey

Once personalization is complete, the next step is to tie the customer experience together across channels and devices. Banks must leverage in-house transactional data to help in building a continuous journey with customers. The secret is for the entire banking team to keep learning and looking for new ways to apply analytics for fun and profit.

Looking Into The Future

For the future of financial institutions, data will be the greatest asset that these institutions can utilize to build products for their markets. Banks that can combine internal and external data sources to create value will find themselves well adapted to the digital market that will make up for future generations.

For financial institutions, knowing their customers’ actual financial situation is more critical now than ever. Contact our team at IFM to learn more about how we have emerged as the leader in large scale transactional/behavioral analysis for generating detailed knowledge to better understand your customer.

Rob Reale

Rob Reale is an Associate Partner and National Sales Manager responsible for business development and sales at Insight Financial Marketing. Rob began working in the Mortgage Banking industry in 1990 and currently helps the financial service industry leverage unique and innovative solutions.

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