In Marketing 101 we learned that it takes more money to acquire a new customer than it does to retain an existing one. I don't think that has changed, but we have gotten much more sophisticated in understanding which customers we want to retain and how to determine if they are about to leave us. Banks have an opportunity to use just a portion of the enormous amount of data they have to improve their customer retention in financial services efforts. After having seen the effectiveness (and ineffectiveness) of a variety of different retention strategies, I have identified five common mistakes and suggestions for how to avoid them:
Waiting too long to save an account. Banks maintain a rich repository of transactional, personal, and contact channel information, so they are armed with the tools to identify "at-risk" customers well before actual attrition occurs. By using financial services analytics to segment the customer base and track the history of account transactions and events, banks can build statistical models that predict the likelihood of customer attrition. These predictive statistical models can then be embedded in business rules engines that continuously monitor account transactions and events. In real time, an engine can identify customers with a high likelihood of attrition, so that action can be taken immediately. For example, a bank could pull at-risk customers from the interactive voice response queue and send them directly to a highly trained retention specialist to re-engage them by offering online bill pay, upgrades, bundled accounts or valuable rewards programs. This re-engagement will create a more loyal customer with opportunities for future revenue growth.
Assuming an at-risk account that stays open is a good "save." Just because the customer initially agrees to keep the account open does not mean he or she will continue to keep it open. To avoid reattrition, banks must not only save the account, but also re-engage the customer. Offering rewards programs, direct deposit or special promotions can help to ensure that the customer will remain loyal. Again, financial services segmentation and analysis of historical patterns can be used to determine which re-engagement offer is appropriate for each customer. Banks also need to develop incentives for agents based not only on "saves," but also on increased account activity once the account is retained. Often agents are paid to save accounts, but the customer never re-engages, so the bank incurs the cost of saving and servicing a dormant account until the customer calls to close once again.
Trying to save every account. Businesses find it difficult to openly say that they do not want to keep every customer; however, just as it doesn't make economic sense to approve every loan, it also doesn't make economic sense to save every account. Customer lifetime value varies significantly, and often banks spend more to save an account than they can ever recoup. Banks need to consider the entire banking relationship, not just individual accounts. A business rules engine can easily and unobtrusively integrate with numerous back-office systems to offer a complete picture of customer lifetime value, so educated decisions can be made about salvaging accounts.
Assuming every agent is good at retention. Often, we assume that just because an agent is good at service, he or she will be equally good at retention. Normally, this is simply not the case. Retaining a customer's account requires a consultative selling approach that even sales people find challenging. Having a specially trained group handle these contacts will definitely yield better results. Some banks try to minimize the load on their retention specialists, and allow front-line agents to make part of the retention offer or do "a reselling of the account benefits." This approach presents several real dangers: it becomes even harder for the retention specialist to save the account; the customer can become frustrated by talking to two people; and, the account will likely attrite again if the customer never speaks with the specialist to become re-engaged.
Not using the customer's channel preference. Some companies focus retention efforts heavily on one channel, such as the contact center. Creating a retention strategy that matches the customer's channel preference can dramatically improve results. For instance, if a customer typically banks online and the predictive statistical model indicates that the customer is likely to attrite, the bank can reach out and chat with the customer to make re-engagement offerings. Developing the right preemptive retention strategy for each channel can really pay off when customers feel that the bank has personalized communication for them.
As you evaluate your retention strategy, try to avoid these common, but costly, mistakes.
