Deprecated: Function get_magic_quotes_gpc() is deprecated in /customers/9/1/4/finex.solutions/httpd.www/wp-includes/load.php on line 651 Notice: Trying to access array offset on value of type bool in /customers/9/1/4/finex.solutions/httpd.www/wp-includes/theme.php on line 2241 Deprecated: Function get_magic_quotes_gpc() is deprecated in /customers/9/1/4/finex.solutions/httpd.www/wp-includes/formatting.php on line 4382 Deprecated: Function get_magic_quotes_gpc() is deprecated in /customers/9/1/4/finex.solutions/httpd.www/wp-includes/formatting.php on line 4382
In most countries, we see the same trend at retail banks — fewer trips to the bank branch and more online visits. Customers are not just logging in to their online or mobile banking applications to check balances, but also to buy banking products and services. According to Mckinsey, at leading banks more than 40 percent of sales nowadays is made through digital channels.
Millennials are especially open to purchasing products online and receiving recommendations from their bank about products and services that would be relevant to them, with 58 percent stating that they welcome such proactive recommendations.
However, in order for product sales via digital channels to be successful, banks have to deliver highly relevant and personalized product recommendations to their customers and provide sufficient information to the customer to be confident of conducting the purchase.
Advertisers spend enormous amounts of time and money attempting to tailor their advertising campaigns to the needs of different customers, by analyzing data like the demographical background of the customers. However, even within a given demographic category, there are many individual differences, such as personality, which shapes consumer behavior.
Nowadays banks have access to an extraordinary amount of customer data through digital devices. By combining this data with predictive analytics and psychometrics – the science of measuring personality traits – banks can predict their customer’s personality traits by analyzing their digital interaction patterns. For example, FINEX Solutions, a FinTech company specializing in innovative digital banking solutions, utilizes the customer’s physical movement patterns collected via mobile banking to calculate the user’s personality.
Banks can use this data to tailor their product recommendations and marketing to match the customer’s personality traits, values and subconscious beliefs. This can enable delivering highly relevant and personalized recommendations to customers.
A good example is Hilton Worldwide, which collaborated with researchers from Cambridge University’s Psychometrics Centre to study the effectiveness of marketing campaigns tailored based on personality traits. The research team prepared 10 different variations for a Hilton ad optimized to different personality types, e.g. a dedicated ad version was created with content and images optimized to appeal to people who are highly extroverted. The research team utilized the Facebook profile and interactions of people who “liked” Hilton pages to measure their personality traits and to deliver the tailored advertisements.
The research team found that clickthrough rates (CTR) for personality-matched ads were at least as twice as high as the travel industry benchmark — the lowest performing segment had an average CTR of .17 compared to the travel industry benchmark for Facebook advertising, .08%. Personality-matched ads were also shared on Facebook more than three times as often — 34.32% compared to a 9.22% benchmark.
The same way as Hilton, banks can significantly increase their marketing efficiency by tailoring their online and mobile banking advertisements to their customer’s personalities in the following areas:
1. Tailoring the ad message, content and images to match the customer’s subconscious beliefs and values: e.g. a highly extroverted person is more likely to positively respond to an advertisement centered around people and friends, compared to an introverted person.
2. Tailoring product recommendations based on personality traits: e.g. a highly conscientious person is more likely to be interested in and positively respond to insurance products compared to a more easy going person.
3. Tailoring the call to action: e.g. for highly analytical personalities a “Learn more” option should be more prevalent, while for people who make spur of the moment decisions, “Buy now” option should be prominent.
This approach can enable banks to deliver highly relevant product recommendations to their customers, with content that will capture the customer’s attention on a subconscious level.
Digital technologies are evolving at an increasing speed, and nowadays banks have access to an extraordinary amount of customer data through digital devices. By combining this data with sophisticated data analytics and behavioral science, banks can successfully turn digital banking into a revenue generating channel. Those banks that will manage to fully utilize the data available on their hands —and do it soon—will excel in the coming years.
To find out more on this topic, you can download our brochure or request a live demo.