How To Improve Bank Cross-Selling *Without Making Up Fake Customer Accounts

In case you missed it, last week there was a bit of a dust up at Wells Fargo. While investigations are still ongoing, current reports allege that Wells Fargo employees illegally used current customer data to open upwards of 1.5 million fake or unauthorized accounts. Thus far, Wells Fargo has agreed to a $100 million fine and $85 million in penalties and restitutions – and the company’s stock and brand has been significantly devalued. Richard Cordray, Director of the Consumer Financial Protection Bureau, says the Wells Fargo investigation puts “the entire banking industry on notice.”

Putting aside the issues of regulatory missteps, legality, and morality, early reports indicate that heavy internal pressure to cross-sell bank products may have been a significant factor contributing to this debacle.

It should go without saying that predatory and fraudulent sales practices are a no-no. However, over the past few years, many banks have raised product sales quotas year over year to maintain growth. After all, cross-selling has been a great place to develop customer relationships and generate revenue from lower cost targets. As the marketplace has become saturated with offers, products, and marketing, sales agents saw limited pipeline and pathways to reach new and existing customers.

Instead of rewarding unrealistic sales quotas or illegal sales tactics, it would make far more sense for banks to embrace the use of big data analytics to target customers more specifically. In fact, by monitoring customer behaviors, needs, and feelings, banks can offer targeted products that actually help customers reach personal goals, endearing customers to brand and product. Rather than carpet bombing the marketing landscape with wide sweeping offers, it is now possible to use data more intelligently to generate revenue.

Cross-Selling and Data

Cross-selling is a core banking sales function. In regards to the aggressive cross selling at Wells Fargo, Matt Levine at Bloomberg commented, “When you get a customer to open a new credit card, and he/she uses that card, you make money. That's how banks work…If Wells Fargo had kept its aggressive culture of cross-selling, but just had a filter to reject new accounts with fake e-mail addresses, it still could have made the tens of billions of dollars, without defrauding any customers.”

While this is somewhat true, pushing a slew of products on a customer base that doesn’t need or understand them only works for so long. Customers may begrudgingly sign up for new products for a short time, but eventually the market will become saturated and customers will shift to products and brands that actually address their needs. But all is not lost for banks, there is a short cut to targeting this type of customer: Big Data.

Big Data and analytics offer an alternative to aggressive “spray and pray” marketing. By using the wealth of existing customer data (collected by both your business and other companies), it is now possible to make inferences, segment, and tailor cross-selling efforts to directly fit customer needs.

Tools and Solutions

Take MX Insights, an analysis tool built to help understand bank customers and competition. Insight contains 100+ pre-loaded interactive visualizations that show data such as interest rates and account types. Why is this kind of insight helpful? It dissects competitors automatically and helps users understand complex data immediately. For example, if you know which users have car loans, mortgages and checking accounts, in addition to the interest rates these products, you can quickly fine-tune marketing campaigns against these specific competitors.

Whether you want to see customers that have accounts at competing organizations, users with direct deposit, external mortgages by interest rate, or users who have credit cards at competing organizations, it is now possible to get extremely granular with segmentation. Products need to keep pace with data analysis however and these products need to match customer needs and expectations. This new world of data requires flexibility of product and deep market/competition knowledge. Without these insights, your sales agents will continually struggle to make their quotas in an over-saturated market.

s