Customer Analytics: Time to get Your Feet Wet
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22 May 2014
I had the pleasure of speaking at Fiserv Forum 2014 in Las Vegas last week, discussing “The Payoff of Turning Data into Action.” During the presentation, I offered some suggestions to financial institutions that have not yet made inroads into customer analytics. Why Here, Why Now? Quite a few community bankers have resisted implementing CRM solutions, for example, and lived to tell about it. Like big data, the promise of CRM in its early days was somewhat overblown. But, that was then. Is customer analytics the New CRM? I say “no” for at least four reasons: 1. The “new normal” in retail banking – Banks need to grow top-line revenue, but it is increasingly hard to do. Analytics applied to customer segmentation, marketing and customer experience can play a critical role. 2. The growing imperative for customer centricity – As consumers increasingly interact digitally with financial institutions, the branch channel is losing relevance and impact. In addition to improving branch channel efficiency and effectiveness, banks must learn how to engage customers digitally. Analytics is the way to do so. 3. Technological advancements – Analytics used to be the domain of data analysts and large, expensive implementations, but modern analytics applications are tailored for business users and integrated with business applications. Getting started is no longer expensive. 4. There’s money to be made – As the use cases for customer analytics multiply faster than rabbits, financial institutions are finding a growing number of ways to profit from customer analytics. In a 2013 survey of North American financial services firms, 70 percent of those having at least one year’s experience with one or more big data initiatives met or exceeded their business case. Not a bad batting average, to be sure. If you remain unconvinced, the Celent report, Customer Analytics in Retail Banking: Why Here? Why Now? may persuade. Getting Your Feet Wet How does an organization get its feet wet with customer analytics? Are there best practices for turning data into action? From interviews with a number of those in the 70 percent, as well as banks who struggled initially, I offer these getting started tips. • Begin with the end in mind – Analytics is a means to an end. Successful examples of data analytics share a common element of focused energy to achieve a limited and specific business objective. • Start small, remain focused – Like its sister topic, big data, there is really no end to customer analytics. Unlike CRM projects, one is never through with analytics – its very nature requires continual refreshing of models and their use. Analytics invites a new way of doing things as much as it invites using new technology. Get started with a single, manageable project and prove its value before moving on. • Get help – There is a steep learning curve associated with fully leveraging data analytics. A modest up-front investment in assistance from firms that specialize in analytics may hasten your project deployment and product better results. Fiserv is well positioned to help – and may already be hosting your data. • Change your culture – Benefitting from analytics requires a devotion to cultural, organization and procedural change. That’s why it is important to start small. Cultural change can and will come alongside socializing the value of early successes. Tom Davenport has authored several books that shed light on the power of making analytics more than an IT project: Analytics At Work, and Competing on Analytics. • Manage expectations – Firms like Amazon and Google make analytics look easy. It’s not. Deriving benefit from customer analytics will be more of a journey than a destination and the road will seem long at times. All the more reason to get your feet wet soon.