Almost every consumer can attest to receiving irrelevant offers from bank or credit union employees, call center representatives or directly via direct mail, email or other channels. A bank or credit union offers a travel reward credit card when a consumer clearly no longer travels, sends offers for hundreds of dollars to open a new checking account when one is already owned at the same institution, or randomly suggests a consumer take advantage of the latest equity credit “loan sale” when a home isn’t owned. In many cases, the financial institution completely misses the target.
This is an existential crisis for the banking industry. An organization’s inability to suggest solutions that are relevant and timely to a consumer represents the beginning of the financial institution’s irrelevance to the consumer. Even worse, it may be the beginning of the shopping process for a new financial institution partner.
This crisis is born out of a technology problem. It’s long since been the goal of analytics to provide the right solution, at the right time, using the right channel for the customer. So why, after decades of work, have we still not achieved this goal?
A Flawed Idea
Part of the problem is that the underlying goal of cross-selling is flawed. To be effective at cross-selling in the digital age, banks and credit unions need the ability to present each customer with a relevant solution – something that will encourage the customer to begin a discussion with the organization to refine the offer and find the exact right solution. That means, in order to cross-sell effectively, organizations need to be prepared to refine and customize the offer with the consumer.
The idea that, “if we just get the analytics right, the offer will be a perfect match,” is flawed. Many institutions operate as if cross-sell offers are a “take it or leave it” proposition. Based on that flawed approach, a technology backbone is built and cross selling infrastructures are established that are destined to fail.
Old, Irrelevant Data and Analytics
It is also too common to find banks and credit unions building cross-sell models using data about their customers and members from 9 months, even 12 months ago. In the digital age, acting on data this old can only spell doom. We need to look at how a customer is researching service in real time, where they are visiting on the institution’s website, and what questions they are asking. The window to sell directly to a potential customer is very small.
In one large bank in the United States, the outbound team responded to online leads based on last-in, first-out queuing approach (versus first-in, first-out). That allowed them to jump on the new information fastest, even if that meant some leads fell by the wayside. They found that customer activities in the most recent 30 days leading up to a purchase, that are important. They also discovered that online leads age rapidly – anything more than a few days old is no longer relevant.
Worse yet, many banks still operate in channel silos. Data collected about the customer in the online channel are not shared with branch employees. Even if the bank or credit union does not have time to create a new model from that information, simply exposing it to the branch advisor gives them so much more information than they had before.
- 7 Common Sense Ways to Increase Bank Cross-Selling
- Banking’s One-to-One Future is Finally Possible
- Digital Consumers Ripe With Cross-Selling Opportunities
- 8 Steps to Improved Bank and Credit Union Cross-Selling
- The Power of Location-Based Offers
Another big challenge for financial institutions is that classic cross-selling practices rely on market segmentation based on demographics. These old school segments (many times based only on age and income) are becoming less useful. We have learned from other industries – like retail – that while some demographic data can be relevant, the real measurement of readiness-to-buy is determined by the individual customer’s real time behavior. If banks are not capturing behavioral and transaction insight and using it to guide cross-selling decisions, then they are leaving the most predictive data out of the equation.
Making It Personal
In order to be effective in making relevant offers that meet the evolving needs and desires of its customers, a financial institution needs to start solving their customers’ and members financial needs 1:1. But what is the customer’s need? If an organization does not know enough about the customer to know the financial need they are trying to find a solution for, how can the organization possibly be of value to the customer?
We need a cross-sell framework that allows us to adapt the offer in real-time with the customer to find something that will meet the need they have today.
Most banks feel cross selling is a one step process – make the “perfect” offer, sit back and watch the orders roll in. Meanwhile, the modern day banking consumer expects more.
Cross selling is a two-step process (at least). First, we use data and analytics to put a highly relevant offer in front of the consumer in order to earn the right to continue the discussion. But then, we also need to have technology in place that allows the consumer to refine that offer in a way that really meets their needs.
For example, say your bank offers a travel rewards credit card to the customer. Does the customer think that the offer is a “take it or leave it?” What if they don’t travel anymore and would prefer a cash-back rewards card to take advantage of their purchases? Will your organization be able to adapt that offer in real-time? Or does the customer simply walk away thinking, “they don’t know me at all?”
Cross-Selling in the Digital Era
To be effective at cross selling in the digital age, banks and credit unions need to be able to make personalized offers and initiate interactions based on a clear, up-to-date understanding of their customers and members.
We need a technology infrastructure that can break down channel silos, collect information, and centralize the data to create an offer repository where we know what is offered, rejected and accepted. We need to get a 360-degree view of the customer: their transaction history, their interactions with the bank – both live and virtual, as well as collecting relevant customer data from outside the bank.
This “financial graph” of data must be visible and accessible across all channels, so that everyone is on the same page. Finally, we need to be adaptable. We need a technology infrastructure that knows what is important to a consumer, can capture additional consumer needs, and suggest in real-time the appropriate solution based on those data points.
What we have today are bank marketing campaigns that fall short of a win-win relationship – for the bank as well as for the consumer. When a bank is doing something that isn’t in the best interest of the consumer, it is not in the bank’s best interest either. This includes focusing on simply meeting volume goals and new account metrics thinking they are a substitute for delivering real value to the consumer.
Effective cross-selling starts with knowing what is important to each consumer, and then following up a relevant offer supported by the ability to refine that offer in real-time. To do this banks and credit unions need access to crucial data on consumer behaviors, understanding when to engage with the consumer, and how to make offers aligned with both the consumer and the financial institution’s goals. But beyond analytics, banks and credit unions need the technology platform to transform their “take it or leave it”, irrelevant offers into value-added sales conversations.