The Diminishing Returns of Rational Ignorance

by Alan See

"Rational ignorance" is the deliberate decision to remain uninformed about something because the perceived cost of the additional intelligence, in terms of both effort and expense, is greater than the expected return on the knowledge gained. In life, rational ignorance is the natural default when we believe we have reached the point of diminishing returns as it relates to the value of acquiring additional insight.

The exact moment that the law of diminishing returns kicks in can be difficult to determine since it varies, based on several factors. However, in general, when the relationship between input and output – like an ROI measurement – starts to deteriorate noticeably, you know the law is in play. In a business environment, rational customer ignorance is often the marketing department's default decision, because siloed customer information sources inevitably stifle attempts to construct comprehensive customer intelligence that reflects the total customer relationship. The consequence of this ignorance? Customer relationship strategies and marketing campaigns that are based solely on conventional wisdom, assumptions, hopes and prayers. The concept of rational ignorance, while popping up on a daily basis for most of us, is detrimental to the banking industry, especially as it relates to the impact of cross-selling activity on customer profitability.

Not all business is profitable business

Today, many marketers are faced with customer and product data that is scattered throughout multiple systems, departments and platforms, leaving them little choice but to launch cross-sell campaigns that fail to take entire, enterprisewide customer relationship into account. Without complete customer intelligence, organizations focus on product wins, pitching offers under the assumption that customer profitability will automatically increase with each new product purchased.

Under this "volume is king" assumption, marketers use their precious budgets to create campaigns that target the entire customer base, hoping to sell some new product to anyone who will respond. In the process, many inconsistent sales pitches will be delivered, increasing the cost of the campaign and the frustrations of the customers who find the offers irrelevant. In truth, at various points in the customer life cycle, not all business is profitable business. Research indicates that 75 percent of current banking cross-sell activities actually destroy value – they diminish returns! Such is the case when customers merely transfer funds from higher-margin products to lower-margin products, thus compressing margins and driving overall profitability down. In other words, rational customer ignorance leads to diminishing returns, because overall individual customer profitability often decreases if the new product, as offered, is accepted. The remedy is customer intelligence that allows marketers to project customer value accurately to improve the likelihood that each incremental sale is profitable.

Customer Intelligence: A true competitive advantage

So, how can marketing migrate to a level of customer intelligence that doesn't just expand sales, but also ensures that any new business that's generated is profitable? Well, first of all, marketing needs to understand the past drivers as well as the possible future drivers of profitability at the customer level. Leading factors that create or influence current and future profitability for retail banking customers include the products currently owned by the customer and the balances maintained; the probability that the customer will migrate funds from higher-margin products to buy the product offered; and the probability that the customer will actually use the new product profitably. In addition, there are day-to-day indicators of customer profitability, such as channel usage (teller, ATM, online, phone, etc.), transaction frequency and type (paper versus electronic), and risk (delinquency).

To fully understand these factors, banks must compile customer information from every corner of the enterprise. Most banks still struggle with the technology issues that produce this single view of the customer. Customer data collected from all contact channels and stored in front-office and back-office systems, as well as third-party data, must be integrated and made available to the user community in a consistent and easy-to-use format. In addition, the customer data collected from those systems must be linked with financial information so that individual customer profitability calculations reflect the total revenue generated minus the total cost of providing the consumed products and services across the entire relationship.

When banks go beyond historical queries and reporting, embracing predictive analytics for targeted (profitable) cross-selling, then true customer intelligence and competitive differentiation are achieved. Predictive analytics provide proactive firepower to help marketers explore and understand complex customer relationships and behavior. Product offerings and marketing campaigns that are based on the customers' likelihood to buy, behavioral data from transactions and channel usage, and overall profitability can be designed to increase customer value and improve customer satisfaction.

A formidable competitive advantage emerges when customer interactions based on customer value, loyalty and preferences are put into practice. Every customer deserves respect and should receive the basics of good service. When sufficiently armed with customer intelligence, a bank has the golden opportunity to "raise the relationship bar" and guide customers toward a profitability that is based on mutual value and respect.