An Effective Cross-Sell Strategy: Both High-Tech and High-Touch

Two bankers looking at data analytics on a computer monitor.

Short of developing clairvoyant abilities, is it possible to determine the best product or service to offer a customer?

It is when you use next-best, or predictive, modeling — the piece of data analytics that helps banks model and make predictions. In fact, any cross-sell program worth its salt should include this component.

Like the name says, next-best modeling can help determine what products customers might purchase next based on specific attributes, demographics, transactional data, and so forth. Data analysis, for example, can identify customers with a propensity to accept a debit card offer or open a home equity line of credit.

But that’s only one part of the equation. We all know analytics can’t predict when a customer will get married, have children, move or change jobs. These needs can only be identified by communicating with your customers and having them share this information.

By learning what your customers want and need you can provide appropriate and timely offers to them. The more insight you have with respect to your customers’ needs, the more products they’ll buy and the longer they’ll stay.

Since we know customers are continuously experiencing lifestyle changes, the big question is: How can you identify these lifestyle changes so your bank can send timely relevant offers to meet those specific needs?

Enter the personal needs assessment.

A personal needs assessment asks customers if and when they plan on experiencing specific life events in a period of time — such as graduating from college, becoming a parent, getting married, or buying or selling a home. The response information allows banks to make relevant offers at the specific time the customer has expressed a need for a bank’s product or service.

Keep in mind the assessment can, but doesn’t have to be, a mailed/emailed survey. You can identify a customer’s needs through a call center or an in-person conversation. However, while the latter yields the most direct, and sometimes the best, results, it’s not always practical.

That’s mainly because not all banks have personnel with the skills necessary to have these types of conversations with customers. As a result, these same banks — maybe yours is one of them — struggle with a low cross-sell ratio. Make an investment in nurturing customer relationships and you’ll show you’re committed to your employees and your customers.

When you do invest in learning about your customers’ needs, the results can be golden. Developing a dialogue with customers helps your bank make targeted offers instead of having to rely on random offers, at random times, through random channels. It’s so much easier to get the customer to accept your product offering when they’ve actually told you what and when they might have a need for one of your products or services.

Analytics should play a role in any good cross-sell program — especially for banks that don’t do a good job of creating a dialogue and eliciting customer feedback. To be successful, however, you need to develop a cross-sell program that combines the use of predictive analytics with ongoing communication that encourages customers to share their upcoming needs with your bank. The combination of the two is the best way to identify and meet all the needs of your customers and improve your cross-sell ratio.